WorldWideScience

Sample records for monitoring network optimization

  1. WiMAX network performance monitoring & optimization

    DEFF Research Database (Denmark)

    Zhang, Qi; Dam, H

    2008-01-01

    frequency reuse, capacity planning, proper network dimensioning, multi-class data services and so on. Furthermore, as a small operator we also want to reduce the demand for sophisticated technicians and man labour hours. To meet these critical demands, we design a generic integrated network performance......In this paper we present our WiMAX (worldwide interoperability for microwave access) network performance monitoring and optimization solution. As a new and small WiMAX network operator, there are many demanding issues that we have to deal with, such as limited available frequency resource, tight...... this integrated network performance monitoring and optimization system in our WiMAX networks. This integrated monitoring and optimization system has such good flexibility and scalability that individual function component can be used by other operators with special needs and more advanced function components can...

  2. Optimizing the spatial pattern of networks for monitoring radioactive releases

    NARCIS (Netherlands)

    Melles, S.J.; Heuvelink, G.B.M.; Twenhofel, C.J.W.; Dijk, van A.; Hiemstra, P.H.; Baume, O.P.; Stohlker, U.

    2011-01-01

    This study presents a method to optimize the sampling design of environmental monitoring networks in a multi-objective setting. We optimize the permanent network of radiation monitoring stations in the Netherlands and parts of Germany as an example. The optimization method proposed combines

  3. Optimizing the spatial pattern of networks for monitoring radioactive releases

    NARCIS (Netherlands)

    Melles, S.J.; Heuvelink, G.B.M.; Twenhofel, C.J.W.; Dijk, van A.; Hiemstra, P.H.; Baume, O.P.; Stohlker, U.

    2011-01-01

    This study presents a method to optimize the sampling design of environmental monitoring networks in a multi-objective setting. We optimize the permanent network of radiation monitoring stations in the Netherlands and parts of Germany as an example. The optimization method proposed combines minimiza

  4. Optimizing Groundwater Monitoring Networks Using Integrated Statistical and Geostatistical Approaches

    Directory of Open Access Journals (Sweden)

    Jay Krishna Thakur

    2015-08-01

    Full Text Available The aim of this work is to investigate new approaches using methods based on statistics and geo-statistics for spatio-temporal optimization of groundwater monitoring networks. The formulated and integrated methods were tested with the groundwater quality data set of Bitterfeld/Wolfen, Germany. Spatially, the monitoring network was optimized using geo-statistical methods. Temporal optimization of the monitoring network was carried out using Sen’s method (1968. For geostatistical network optimization, a geostatistical spatio-temporal algorithm was used to identify redundant wells in 2- and 2.5-D Quaternary and Tertiary aquifers. Influences of interpolation block width, dimension, contaminant association, groundwater flow direction and aquifer homogeneity on statistical and geostatistical methods for monitoring network optimization were analysed. The integrated approach shows 37% and 28% redundancies in the monitoring network in Quaternary aquifer and Tertiary aquifer respectively. The geostatistical method also recommends 41 and 22 new monitoring wells in the Quaternary and Tertiary aquifers respectively. In temporal optimization, an overall optimized sampling interval was recommended in terms of lower quartile (238 days, median quartile (317 days and upper quartile (401 days in the research area of Bitterfeld/Wolfen. Demonstrated methods for improving groundwater monitoring network can be used in real monitoring network optimization with due consideration given to influencing factors.

  5. Optimal estuarine sediment monitoring network design with simulated annealing.

    Science.gov (United States)

    Nunes, L M; Caeiro, S; Cunha, M C; Ribeiro, L

    2006-02-01

    An objective function based on geostatistical variance reduction, constrained to the reproduction of the probability distribution functions of selected physical and chemical sediment variables, is applied to the selection of the best set of compliance monitoring stations in the Sado river estuary in Portugal. These stations were to be selected from a large set of sampling stations from a prior field campaign. Simulated annealing was chosen to solve the optimisation function model. Both the combinatorial problem structure and the resulting candidate sediment monitoring networks are discussed, and the optimal dimension and spatial distribution are proposed. An optimal network of sixty stations was obtained from an original 153-station sampling campaign.

  6. Sensor Networks Hierarchical Optimization Model for Security Monitoring in High-Speed Railway Transport Hub

    Directory of Open Access Journals (Sweden)

    Zhengyu Xie

    2015-01-01

    Full Text Available We consider the sensor networks hierarchical optimization problem in high-speed railway transport hub (HRTH. The sensor networks are optimized from three hierarchies which are key area sensors optimization, passenger line sensors optimization, and whole area sensors optimization. Case study on a specific HRTH in China showed that the hierarchical optimization method is effective to optimize the sensor networks for security monitoring in HRTH.

  7. Designing optimal greenhouse gas monitoring networks for Australia

    Science.gov (United States)

    Ziehn, T.; Law, R. M.; Rayner, P. J.; Roff, G.

    2016-01-01

    Atmospheric transport inversion is commonly used to infer greenhouse gas (GHG) flux estimates from concentration measurements. The optimal location of ground-based observing stations that supply these measurements can be determined by network design. Here, we use a Lagrangian particle dispersion model (LPDM) in reverse mode together with a Bayesian inverse modelling framework to derive optimal GHG observing networks for Australia. This extends the network design for carbon dioxide (CO2) performed by Ziehn et al. (2014) to also minimise the uncertainty on the flux estimates for methane (CH4) and nitrous oxide (N2O), both individually and in a combined network using multiple objectives. Optimal networks are generated by adding up to five new stations to the base network, which is defined as two existing stations, Cape Grim and Gunn Point, in southern and northern Australia respectively. The individual networks for CO2, CH4 and N2O and the combined observing network show large similarities because the flux uncertainties for each GHG are dominated by regions of biologically productive land. There is little penalty, in terms of flux uncertainty reduction, for the combined network compared to individually designed networks. The location of the stations in the combined network is sensitive to variations in the assumed data uncertainty across locations. A simple assessment of economic costs has been included in our network design approach, considering both establishment and maintenance costs. Our results suggest that, while site logistics change the optimal network, there is only a small impact on the flux uncertainty reductions achieved with increasing network size.

  8. Designing optimal greenhouse gas monitoring networks for Australia

    Directory of Open Access Journals (Sweden)

    T. Ziehn

    2015-08-01

    Full Text Available Atmospheric transport inversion is commonly used to infer greenhouse gas (GHG flux estimates from concentration measurements. The optimal location of ground based observing stations that supply these measurements can be determined by network design. Here, we use a Lagrangian particle dispersion model (LPDM in reverse mode together with a Bayesian inverse modelling framework to derive optimal GHG observing networks for Australia. This extends the network design for carbon dioxide (CO2 performed by Ziehn et al. (2014 to also minimize the uncertainty on the flux estimates for methane (CH4 and nitrous oxide (N2O, both individually and in a combined network using multiple objectives. Optimal networks are generated by adding up to 5 new stations to the base network, which is defined as two existing stations, Cape Grim and Gunn Point, in southern and northern Australia respectively. The individual networks for CO2, CH4 and N2O and the combined observing network show large similarities because the flux uncertainties for each GHG are dominated by regions of biologically productive land. There is little penalty, in terms of flux uncertainty reduction, for the combined network compared to individually designed networks. The location of the stations in the combined network is sensitive to variations in the assumed data uncertainty across locations. A simple assessment of economic costs has been included in our network design approach, considering both establishment and maintenance costs. Our results suggest that while site logistics change the optimal network, there is only a small impact on the flux uncertainty reductions achieved with increasing network size.

  9. Optical Performance Monitoring and Signal Optimization in Optical Networks

    DEFF Research Database (Denmark)

    Petersen, Martin Nordal

    2006-01-01

    -optical-electrical regeneration points decreases. This thesis evaluates the impact of signal degrading effects that are becoming of increasing concern in all-optical high-speed networks due to all-optical switching and higher bit-rates. Especially group-velocity-dispersion (GVD) and a number of nonlinear effects will require......The thesis studies performance monitoring for the next generation optical networks. The focus is on all-optical networks with bit-rates of 10 Gb/s or above. Next generation all-optical networks offer large challenges as the optical transmitted distance increases and the occurrence of electrical...... enhanced attention to avoid signal degradations. The requirements for optical performance monitoring features are discussed, and the thesis evaluates the advantages and necessity of increasing the level of performance monitoring parameters in the physical layer. In particular, methods for optical...

  10. Enhanced Multi-Objective Optimization of Groundwater Monitoring Networks

    DEFF Research Database (Denmark)

    Bode, Felix; Binning, Philip John; Nowak, Wolfgang

    Drinking-water well catchments include many sources for potential contaminations like gas stations or agriculture. Finding optimal positions of monitoring wells for such purposes is challenging because there are various parameters (and their uncertainties) that influence the reliability and optim...

  11. Multiobjective Network Optimization for Soil Monitoring of the Loess Hilly Region in China

    Directory of Open Access Journals (Sweden)

    Dianfeng Liu

    2014-01-01

    Full Text Available The soil monitoring network plays an important role in detecting the spatial distribution of soil attributes and facilitates sustainable land-use decision making. Reduced costs, higher speed, greater scope, and a loss of accuracy are necessary to design a regional monitoring network effectively. In this paper, we present a stochastic optimization design method for regional soil carbon and water content monitoring networks with a minimum sample size based on a modified particle swarm optimization algorithm equipped with multiobjective optimization technique. Our effort is to reconcile the conflicts between various objectives, that is, kriging variance, survey budget, spatial accessibility, spatial interval, and the amount of monitoring sites. We applied the method to optimize the soil monitoring networks in a semiarid loess hilly area located in northwest China. The results reveal that the proposed method is both effective and robust and outperforms the standard binary particle swarm optimization and spatial simulated annealing algorithm.

  12. Global optimal design of ground water monitoring network using embedded kriging.

    Science.gov (United States)

    Dhar, Anirban; Datta, Bithin

    2009-01-01

    We present a methodology for global optimal design of ground water quality monitoring networks using a linear mixed-integer formulation. The proposed methodology incorporates ordinary kriging (OK) within the decision model formulation for spatial estimation of contaminant concentration values. Different monitoring network design models incorporating concentration estimation error, variance estimation error, mass estimation error, error in locating plume centroid, and spatial coverage of the designed network are developed. A big-M technique is used for reformulating the monitoring network design model to a linear decision model while incorporating different objectives and OK equations. Global optimality of the solutions obtained for the monitoring network design can be ensured due to the linear mixed-integer programming formulations proposed. Performances of the proposed models are evaluated for both field and hypothetical illustrative systems. Evaluation results indicate that the proposed methodology performs satisfactorily. These performance evaluation results demonstrate the potential applicability of the proposed methodology for optimal ground water contaminant monitoring network design.

  13. Synthesize, optimize, analyze, repeat (SOAR): Application of neural network tools to ECG patient monitoring

    Energy Technology Data Exchange (ETDEWEB)

    Watrous, R.; Towell, G.; Glassman, M.S. [Siemens Corporate Research, Princeton, NJ (United States)

    1995-12-31

    Results are reported from the application of tools for synthesizing, optimizing and analyzing neural networks to an ECG Patient Monitoring task. A neural network was synthesized from a rule-based classifier and optimized over a set of normal and abnormal heartbeats. The classification error rate on a separate and larger test set was reduced by a factor of 2. When the network was analyzed and reduced in size by a factor of 40%, the same level of performance was maintained.

  14. Ant colony optimization and neural networks applied to nuclear power plant monitoring

    Energy Technology Data Exchange (ETDEWEB)

    Santos, Gean Ribeiro dos; Andrade, Delvonei Alves de; Pereira, Iraci Martinez, E-mail: gean@usp.br, E-mail: delvonei@ipen.br, E-mail: martinez@ipen.br [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil)

    2015-07-01

    A recurring challenge in production processes is the development of monitoring and diagnosis systems. Those systems help on detecting unexpected changes and interruptions, preventing losses and mitigating risks. Artificial Neural Networks (ANNs) have been extensively used in creating monitoring systems. Usually the ANNs created to solve this kind of problem are created by taking into account only parameters as the number of inputs, outputs, and hidden layers. The result networks are generally fully connected and have no improvements in its topology. This work intends to use an Ant Colony Optimization (ACO) algorithm to create a tuned neural network. The ACO search algorithm will use Back Error Propagation (BP) to optimize the network topology by suggesting the best neuron connections. The result ANN will be applied to monitoring the IEA-R1 research reactor at IPEN. (author)

  15. Optimizing streamflow monitoring networks using joint permutation entropy

    Science.gov (United States)

    Stosic, Tatijana; Stosic, Borko; Singh, Vijay P.

    2017-09-01

    Using joint permutation entropy we address the issue of minimizing the cost of monitoring, while minimizing redundancy of the information content, of daily streamflow data recorded during the period 1989-2016 at twelve gauging stations on Brazos River, Texas, USA. While the conventional entropy measures take into account only the probability of occurrence of a given set of events, permutation entropy also takes into account local ordering of the sequential values, thus enriching the analysis. We find that the best cost efficiency is achieved by performing weekly measurements, in comparison with which daily measurements exhibit information redundancy, and monthly measurements imply information loss. We also find that the cumulative information redundancy of the twelve considered stations is over 10% for the observed period, and that the number of monitoring stations can be reduced by half bringing the cumulative redundancy level to less than 1%.

  16. Artificial Neural Networks Applications: from Aircraft Design Optimization to Orbiting Spacecraft On-board Environment Monitoring

    Science.gov (United States)

    Jules, Kenol; Lin, Paul P.

    2002-01-01

    This paper reviews some of the recent applications of artificial neural networks taken from various works performed by the authors over the last four years at the NASA Glenn Research Center. This paper focuses mainly on two areas. First, artificial neural networks application in design and optimization of aircraft/engine propulsion systems to shorten the overall design cycle. Out of that specific application, a generic design tool was developed, which can be used for most design optimization process. Second, artificial neural networks application in monitoring the microgravity quality onboard the International Space Station, using on-board accelerometers for data acquisition. These two different applications are reviewed in this paper to show the broad applicability of artificial intelligence in various disciplines. The intent of this paper is not to give in-depth details of these two applications, but to show the need to combine different artificial intelligence techniques or algorithms in order to design an optimized or versatile system.

  17. Site location optimization of regional air quality monitoring network in China: methodology and case study.

    Science.gov (United States)

    Zheng, Junyu; Feng, Xiaoqiong; Liu, Panwei; Zhong, Liuju; Lai, Senchao

    2011-11-01

    Regional air quality monitoring networks (RAQMN) are urgently needed in China due to increasing regional air pollution in city clusters, arising from rapid economic development in recent decades. This paper proposes a methodological framework for site location optimization in designing a RAQMN adapting to air quality management practice in China. The framework utilizes synthetic assessment concentrations developed from simulated data from a regional air quality model in order to simplify the optimal process and to reduce costs. On the basis of analyzing various constraints such as cost and budget, terrain conditions, administrative district, population density and spatial coverage, the framework takes the maximum approximate degree as an optimization objective to achieve site location optimization of a RAQMN. An expert judgment approach was incorporated into the framework to help adjust initial optimization results in order to make the network more practical and representative. A case study was used to demonstrate the application of the framework, indicating that it is feasible to conduct site optimization for a RAQMN design in China. The effects of different combinations of primary and secondary pollutants on site location optimization were investigated. It is suggested that the network design considering both primary and secondary pollutants could better represent regional pollution characteristics and more extensively reflect temporal and spatial variations of regional air quality. The work shown in this study can be used as a reference to guide site location optimization of a RAQMN design in China or other regions of the world.

  18. Model Based Optimal Sensor Network Design for Condition Monitoring in an IGCC Plant

    Energy Technology Data Exchange (ETDEWEB)

    Kumar, Rajeeva; Kumar, Aditya; Dai, Dan; Seenumani, Gayathri; Down, John; Lopez, Rodrigo

    2012-12-31

    This report summarizes the achievements and final results of this program. The objective of this program is to develop a general model-based sensor network design methodology and tools to address key issues in the design of an optimal sensor network configuration: the type, location and number of sensors used in a network, for online condition monitoring. In particular, the focus in this work is to develop software tools for optimal sensor placement (OSP) and use these tools to design optimal sensor network configuration for online condition monitoring of gasifier refractory wear and radiant syngas cooler (RSC) fouling. The methodology developed will be applicable to sensing system design for online condition monitoring for broad range of applications. The overall approach consists of (i) defining condition monitoring requirement in terms of OSP and mapping these requirements in mathematical terms for OSP algorithm, (ii) analyzing trade-off of alternate OSP algorithms, down selecting the most relevant ones and developing them for IGCC applications (iii) enhancing the gasifier and RSC models as required by OSP algorithms, (iv) applying the developed OSP algorithm to design the optimal sensor network required for the condition monitoring of an IGCC gasifier refractory and RSC fouling. Two key requirements for OSP for condition monitoring are desired precision for the monitoring variables (e.g. refractory wear) and reliability of the proposed sensor network in the presence of expected sensor failures. The OSP problem is naturally posed within a Kalman filtering approach as an integer programming problem where the key requirements of precision and reliability are imposed as constraints. The optimization is performed over the overall network cost. Based on extensive literature survey two formulations were identified as being relevant to OSP for condition monitoring; one based on LMI formulation and the other being standard INLP formulation. Various algorithms to solve

  19. Sequential Optimal Monitoring Network Design using Iterative Kriging for Identification of Unknown Groundwater Pollution Sources Location

    Science.gov (United States)

    Prakash, O.; Datta, B.

    2011-12-01

    Identification of unknown groundwater pollution source characteristics, in terms of location, magnitude and activity duration is important for designing an effective pollution remediation strategy. Precise source characterization also becomes very important to ascertain liability, and to recover the cost of remediation from parties responsible for the groundwater pollution. Due to the uncertainties in accurately predicting the aquifer response to source flux injection, generally encountered sparsity of concentration observation data in the field, and the non uniqueness in the aquifer response to the subjected hydraulic and chemical stresses, groundwater pollution source characterization remains a challenging task. A scientifically designed pollutant concentration monitoring network becomes imperative for accurate pollutant source characterization. The efficiency of the unknown source locations identification process is largely determined by locations of monitoring wells where the pollutant concentration is observed. The proposed method combines spatial interpolation of concentration measurements and Simulated Annealing as optimization algorithm to find the optimum locations for monitoring wells. Initially, the observed concentration data at few sparsely and arbitrarily distributed wells are used to interpolate the concentration data for the aquifer study area. The concentration information is passed to the optimization algorithm (decision model) as concentration gradient which in turn finds the optimum locations for implementing the next sequence of monitoring wells. Concentration measurement data from these designed monitoring wells and already implemented monitoring network are iteratively used as feedback information for potential groundwater pollution source locations identification. The potential applicability of the developed methodology is demonstrated for an illustrative study area.

  20. Searchlight Correlation Detectors: Optimal Seismic Monitoring Using Regional and Global Networks

    Science.gov (United States)

    Gibbons, Steven J.; Kværna, Tormod; Näsholm, Sven Peter

    2015-04-01

    The sensitivity of correlation detectors increases greatly when the outputs from multiple seismic traces are considered. For single-array monitoring, a zero-offset stack of individual correlation traces will provide significant noise suppression and enhanced sensitivity for a source region surrounding the hypocenter of the master event. The extent of this region is limited only by the decrease in waveform similarity with increasing hypocenter separation. When a regional or global network of arrays and/or 3-component stations is employed, the zero-offset approach is only optimal when the master and detected events are co-located exactly. In many monitoring situations, including nuclear test sites and geothermal fields, events may be separated by up to many hundreds of meters while still retaining sufficient waveform similarity for correlation detection on single channels. However, the traveltime differences resulting from the hypocenter separation may result in significant beam loss on the zero-offset stack and a deployment of many beams for different hypothetical source locations in geographical space is required. The beam deployment necessary for optimal performance of the correlation detectors is determined by an empirical network response function which is most easily evaluated using the auto-correlation functions of the waveform templates from the master event. The correlation detector beam deployments for providing optimal network sensitivity for the North Korea nuclear test site are demonstrated for both regional and teleseismic monitoring configurations.

  1. Deployment of Wireless Sensor Networks for Oilfield Monitoring by Multiobjective Discrete Binary Particle Swarm Optimization

    Directory of Open Access Journals (Sweden)

    Zhen-Lun Yang

    2016-01-01

    Full Text Available The deployment problem of wireless sensor networks for real time oilfield monitoring is studied. As a characteristic of oilfield monitoring system, all sensor nodes have to be installed on designated spots. For the energy efficiency, some relay nodes and sink nodes are deployed as a delivery subsystem. The major concern of the construction of the monitoring system is the optimum placement of data delivery subsystem to ensure the full connectivity of the sensor nodes while keeping the construction cost as low as possible, with least construction and maintenance complexity. Due to the complicated landform of oilfields, in general, it is rather difficult to satisfy these requirements simultaneously. The deployment problem is formulated as a constrained multiobjective optimization problem and solved through a novel scheme based on multiobjective discrete binary particle swarm optimization to produce optimal solutions from the minimum financial cost to the minimum complexity of construction and maintenance. Simulation results validated that comparing to the three existing state-of-the-art algorithms, that is, NSGA-II, JGGA, and SPEA2, the proposed scheme is superior in locating the Pareto-optimal front and maintaining the diversity of the solutions, thus providing superior candidate solutions for the design of real time monitoring systems in oilfields.

  2. Optimal design of hydrometric monitoring networks with dynamic components based on Information Theory

    Science.gov (United States)

    Alfonso, Leonardo; Chacon, Juan; Solomatine, Dimitri

    2016-04-01

    The EC-FP7 WeSenseIt project proposes the development of a Citizen Observatory of Water, aiming at enhancing environmental monitoring and forecasting with the help of citizens equipped with low-cost sensors and personal devices such as smartphones and smart umbrellas. In this regard, Citizen Observatories may complement the limited data availability in terms of spatial and temporal density, which is of interest, among other areas, to improve hydraulic and hydrological models. At this point, the following question arises: how can citizens, who are part of a citizen observatory, be optimally guided so that the data they collect and send is useful to improve modelling and water management? This research proposes a new methodology to identify the optimal location and timing of potential observations coming from moving sensors of hydrological variables. The methodology is based on Information Theory, which has been widely used in hydrometric monitoring design [1-4]. In particular, the concepts of Joint Entropy, as a measure of the amount of information that is contained in a set of random variables, which, in our case, correspond to the time series of hydrological variables captured at given locations in a catchment. The methodology presented is a step forward in the state of the art because it solves the multiobjective optimisation problem of getting simultaneously the minimum number of informative and non-redundant sensors needed for a given time, so that the best configuration of monitoring sites is found at every particular moment in time. To this end, the existing algorithms have been improved to make them efficient. The method is applied to cases in The Netherlands, UK and Italy and proves to have a great potential to complement the existing in-situ monitoring networks. [1] Alfonso, L., A. Lobbrecht, and R. Price (2010a), Information theory-based approach for location of monitoring water level gauges in polders, Water Resour. Res., 46(3), W03528 [2] Alfonso, L., A

  3. Optimal Fair Scheduling in S-TDMA Sensor Networks for Monitoring River Plumes

    Directory of Open Access Journals (Sweden)

    Miguel-Angel Luque-Nieto

    2016-01-01

    Full Text Available Underwater wireless sensor networks (UWSNs are a promising technology to provide oceanographers with environmental data in real time. Suitable network topologies to monitor estuaries are formed by strings coming together to a sink node. This network may be understood as an oriented graph. A number of MAC techniques can be used in UWSNs, but Spatial-TDMA is preferred for fixed networks. In this paper, a scheduling procedure to obtain the optimal fair frame is presented, under ideal conditions of synchronization and transmission errors. The main objective is to find the theoretical maximum throughput by overlapping the transmissions of the nodes while keeping a balanced received data rate from each sensor, regardless of its location in the network. The procedure searches for all cliques of the compatibility matrix of the network graph and solves a Multiple-Vector Bin Packing (MVBP problem. This work addresses the optimization problem and provides analytical and numerical results for both the minimum frame length and the maximum achievable throughput.

  4. Sampling design optimization of a wireless sensor network for monitoring ecohydrological processes in the Babao River basin, China

    NARCIS (Netherlands)

    Ge, Y.; Wang, J.H.; Heuvelink, G.B.M.; Jin, R.; Li, X.; Wang, J.F.

    2015-01-01

    Optimal selection of observation locations is an essential task in designing an effective ecohydrological process monitoring network, which provides information on ecohydrological variables by capturing their spatial variation and distribution. This article presents a geostatistical method for mu

  5. Assessing and optimizing the performance of infrasound networks to monitor volcanic eruptions

    Science.gov (United States)

    Tailpied, Dorianne; Le Pichon, Alexis; Marchetti, Emanuele; Assink, Jelle; Vergniolle, Sylvie

    2017-01-01

    We propose a numerical modeling technique based on a frequency-dependent attenuation relation to assess, quantify and optimize the performance of any arbitrary infrasound network to monitor explosive sources such as volcanic eruptions. Simulations are further enhanced by including realistic sources and propagation effects. We apply our approach to both hemispheres by considering the Euro-Mediterranean and the Eastern Australian regions. In these regions, we use quasi-permanent infrasound signals from Mt. Etna recorded in Tunisia and from Mt. Yasur recorded in New Caledonia. These well-instrumented volcanoes offer a unique opportunity to validate our attenuation model. In particular, accurate comparisons between near- and far-field recordings demonstrate the potential of the proposed methodology to remotely monitor volcanoes. A good agreement is found between modeled and observed results, especially when incorporating representative 10 m s-1 wind perturbations in the atmospheric specifications according to previous campaign measurements. To optimize the network layout in order to ensure the best monitoring of the volcanoes, we proceed through a grid search to find optimum locations of an additional array. We show that adding one array at an appropriate location in both regions under study could significantly improve detections half of the year. The application of the proposed methodology can provide in near real-time a realistic confidence level of volcanic eruption detections, useful to mitigate the risk of aircrafts encountering volcanic ash.

  6. Objective Functions for Information-Content-Based Optimal Monitoring Network Design

    Science.gov (United States)

    Weijs, S. V.; Huwald, H.; Parlange, M. B.

    2013-12-01

    Information theory has the potential to provide a common language for the quantification of uncertainty and its reduction by choosing optimally informative monitoring network layout. Numerous different objectives based on information measures have been proposed in recent literature, often focusing simultaneously on maximum information and minimum dependence between the chosen locations for data collection. We discuss these objective functions and conclude that a single objective optimization of joint entropy suffices to maximize the collection of information. Minimum dependence is a secondary objective that automatically follows from the first, but has no intrinsic justification. Furthermore it is demonstrated how the curse of dimensionality complicates the determination of information content for time series. In many cases found in the monitoring network literature, discrete multivariate joint distributions are estimated from relatively little data, leading to the occurrence of spurious dependencies in data, which change interpretations of previously published results. Aforementioned numerical challenges stem from inherent difficulties and subjectivity in determining information content. From information-theoretical logic it is clear that the information content of data depends on the state of knowledge prior to obtaining them. Less assumptions in formulating this state of knowledge leads to higher data requirements in formulating it. We further clarify the role of prior information in information content by drawing an analogy with data compression.

  7. Optimization of a Coastal Environmental Monitoring Network Based on the Kriging Method: A Case Study of Quanzhou Bay, China

    Directory of Open Access Journals (Sweden)

    Kai Chen

    2016-01-01

    Full Text Available Environmental monitoring is fundamental in assessing environmental quality and to fulfill protection and management measures with permit conditions. However, coastal environmental monitoring work faces many problems and challenges, including the fact that monitoring information cannot be linked up with evaluation, monitoring data cannot well reflect the current coastal environmental condition, and monitoring activities are limited by cost constraints. For these reasons, protection and management measures cannot be developed and implemented well by policy makers who intend to solve this issue. In this paper, Quanzhou Bay in southeastern China was selected as a case study; and the Kriging method and a geographic information system were employed to evaluate and optimize the existing monitoring network in a semienclosed bay. This study used coastal environmental monitoring data from 15 sites (including COD, DIN, and PO4-P to adequately analyze the water quality from 2009 to 2012 by applying the Trophic State Index. The monitoring network in Quanzhou Bay was evaluated and optimized, with the number of sites increased from 15 to 24, and the monitoring precision improved by 32.9%. The results demonstrated that the proposed advanced monitoring network optimization was appropriate for environmental monitoring in Quanzhou Bay. It might provide technical support for coastal management and pollutant reduction in similar areas.

  8. Sequential optimal monitoring network design and iterative spatial estimation of pollutant concentration for identification of unknown groundwater pollution source locations.

    Science.gov (United States)

    Prakash, Om; Datta, Bithin

    2013-07-01

    One of the difficulties in accurate characterization of unknown groundwater pollution sources is the uncertainty regarding the number and the location of such sources. Only when the number of source locations is estimated with some degree of certainty that the characterization of the sources in terms of location, magnitude, and activity duration can be meaningful. A fairly good knowledge of source locations can substantially decrease the degree of nonuniqueness in the set of possible aquifer responses to subjected geochemical stresses. A methodology is developed to use a sequence of dedicated monitoring network design and implementation and to screen and identify the possible source locations. The proposed methodology utilizes a combination of spatial interpolation of concentration measurements and simulated annealing as optimization algorithm for optimal design of the monitoring network. These monitoring networks are to be designed and implemented sequentially. The sequential design is based on iterative pollutant concentration measurement information from the sequentially designed monitoring networks. The optimal monitoring network design utilizes concentration gradient information from the monitoring network at previous iteration to define the objective function. The capability of the feedback information based iterative methodology is shown to be effective in estimating the source locations when no such information is initially available. This unknown pollution source locations identification methodology should be very useful as a screening model for subsequent accurate estimation of the unknown pollution sources in terms of location, magnitude, and activity duration.

  9. Optimization of a Groundwater Monitoring Network for a Sustainable Development of the Maheshwaram Catchment, India

    Directory of Open Access Journals (Sweden)

    Shakeel Ahmed

    2011-02-01

    Full Text Available Groundwater is one of the most valuable resources for drinking water and irrigation in the Maheshwaram Catchment, Central India, where most of the local population depends on it for agricultural activities. An increasing demand for irrigation and the growing concern about potential water contamination makes imperative the implementation of a systematic groundwater-quality monitoring program in the region. Nonetheless, limited funding and resources emphasize the need to achieve a representative but cost-effective sampling strategy. In this context, field observations were combined with a geostatistical analysis to define an optimized monitoring network able to provide sufficient and non-redundant information on key hydrochemical parameters. A factor analysis was used to evaluate the interrelationship among variables, and permitted to reduce the original dataset into a new configuration of monitoring points still able to capture the spatial variability in the groundwater quality of the basin. The approach is useful to maximize data collection and contributes to better manage the allocation of resources under budget constrains.

  10. A heuristic optimization approach for Air Quality Monitoring Network design with the simultaneous consideration of multiple pollutants.

    Science.gov (United States)

    Elkamel, A; Fatehifar, E; Taheri, M; Al-Rashidi, M S; Lohi, A

    2008-08-01

    An interactive optimization methodology for allocating the number and configuration of an Air Quality Monitoring Network (AQMN) in a vast area to identify the impact of multiple pollutants is described. A mathematical model based on the multiple cell approach (MCA) was used to create monthly spatial distributions for the concentrations of the pollutants emitted from different emission sources. These spatial temporal patterns were subject to a heuristic optimization algorithm to identify the optimal configuration of a monitoring network. The objective of the optimization is to provide maximum information about multi-pollutants (i.e., CO, NO(x) and SO(2)) emitted from each source within a given area. The model was applied to a network of existing refinery stacks and the results indicate that three stations can provide a total coverage of more than 70%. In addition, the effect of the spatial correlation coefficient (R(C)) on total area coverage was analyzed. The modeling results show that as the cutoff correlation coefficient R(C) is increased from 0.75 to 0.95, the number of monitoring stations required for total coverage is increased. A high R(C) based network may not necessarily cover the entire region, but the covered region will be well represented. A low R(C) based network, on the other hand, would offer more coverage of the region, but the covered region may not be satisfactorily represented.

  11. A data fusion-based methodology for optimal redesign of groundwater monitoring networks

    Science.gov (United States)

    Hosseini, Marjan; Kerachian, Reza

    2017-09-01

    In this paper, a new data fusion-based methodology is presented for spatio-temporal (S-T) redesigning of Groundwater Level Monitoring Networks (GLMNs). The kriged maps of three different criteria (i.e. marginal entropy of water table levels, estimation error variances of mean values of water table levels, and estimation values of long-term changes in water level) are combined for determining monitoring sub-areas of high and low priorities in order to consider different spatial patterns for each sub-area. The best spatial sampling scheme is selected by applying a new method, in which a regular hexagonal gridding pattern and the Thiessen polygon approach are respectively utilized in sub-areas of high and low monitoring priorities. An Artificial Neural Network (ANN) and a S-T kriging models are used to simulate water level fluctuations. To improve the accuracy of the predictions, results of the ANN and S-T kriging models are combined using a data fusion technique. The concept of Value of Information (VOI) is utilized to determine two stations with maximum information values in both sub-areas with high and low monitoring priorities. The observed groundwater level data of these two stations are considered for the power of trend detection, estimating periodic fluctuations and mean values of the stationary components, which are used for determining non-uniform sampling frequencies for sub-areas. The proposed methodology is applied to the Dehgolan plain in northwestern Iran. The results show that a new sampling configuration with 35 and 7 monitoring stations and sampling intervals of 20 and 32 days, respectively in sub-areas with high and low monitoring priorities, leads to a more efficient monitoring network than the existing one containing 52 monitoring stations and monthly temporal sampling.

  12. Multi-objective optimization of long-term groundwater monitoring network design using a probabilistic Pareto genetic algorithm under uncertainty

    Science.gov (United States)

    Luo, Qiankun; Wu, Jianfeng; Yang, Yun; Qian, Jiazhong; Wu, Jichun

    2016-03-01

    Optimal design of long term groundwater monitoring (LTGM) network often involves conflicting objectives and substantial uncertainty arising from insufficient hydraulic conductivity (K) data. This study develops a new multi-objective simulation-optimization model involving four objectives: minimizations of (i) the total sampling costs for monitoring contaminant plume, (ii) mass estimation error, (iii) the first moment estimation error, and (iv) the second moment estimation error of the contaminant plume, for LTGM network design problems. Then a new probabilistic Pareto genetic algorithm (PPGA) coupled with the commonly used flow and transport codes, MODFLOW and MT3DMS, is developed to search for the Pareto-optimal solutions to the multi-objective LTGM problems under uncertainty of the K-fields. The PPGA integrates the niched Pareto genetic algorithm with probabilistic Pareto sorting scheme to deal with the uncertainty of objectives caused by the uncertain K-field. Also, the elitist selection strategy, the operation library and the Pareto solution set filter are conducted to improve the diversity and reliability of Pareto-optimal solutions by the PPGA. Furthermore, the sampling strategy of noisy genetic algorithm is adopted to cope with the uncertainty of the K-fields and improve the computational efficiency of the PPGA. In particular, Monte Carlo (MC) analysis is employed to evaluate the effectiveness of the proposed methodology in finding Pareto-optimal sampling network designs of LTGM systems through a two-dimensional hypothetical example and a three-dimensional field application in Indiana (USA). Comprehensive analysis demonstrates that the proposed PPGA can find Pareto optimal solutions with low variability and high reliability and is a promising tool for optimizing multi-objective LTGM network designs under uncertainty.

  13. Optimization of a Large-scale Microseismic Monitoring Network in Northern Switzerland

    Science.gov (United States)

    Kraft, T.; Husen, S.; Mignan, A.; Bethmann, F.

    2011-12-01

    We have performed a computer aided network optimization for a regional scale microseismic network in northeastern Switzerland. The goal of the optimization was to find the geometry and size of the network that assures a location precision of 0.5 km in the epicenter and 2.0 km in focal depth for earthquakes of magnitude ML>= 1.0, by taking into account 67 existing stations in Switzerland, Germany and Austria, and the expected detectability of Ml 1 earthquakes in the study area. The optimization was based on the simulated annealing approach by Hardt and Scherbaum (1993), that aims to minimize the volume of the error ellipsoid of the linearized earthquake location problem (D-criterion). We have extended their algorithm: to calculate traveltimes of seismic body waves using a finite differences raytracer and the three-dimensional velocity model of Switzerland, to calculate seismic body waves amplitudes at arbitrary stations assuming Brune source model and using scaling relations recently derived for Switzerland, and to estimate the noise level at arbitrary locations within Switzerland using a first order ambient seismic noise model based on 14 land-use classes defined by the EU-project CORINE and open GIS data. Considering 67 existing stations in Switzerland, Germany and Austria, optimizations for networks of 10 to 35 new stations were calculated with respect to 2240 synthetic earthquakes of magnitudes between ML=0.8-1.1. We incorporated the case of non-detections by considering only earthquake-station pairs with an expected signal-to-noise ratio larger than 10 for the considered body wave. Station noise levels were derived from measured ground motion for existing stations and from the first order ambient noise model for new sites. The stability of the optimization result was tested by repeated optimization runs with changing initial conditions. Due to the highly non linear nature and size of the problem, station locations in the individual solutions show small

  14. Optimizing the De-Noise Neural Network Model for GPS Time-Series Monitoring of Structures

    Directory of Open Access Journals (Sweden)

    Mosbeh R. Kaloop

    2015-09-01

    Full Text Available The Global Positioning System (GPS is recently used widely in structures and other applications. Notwithstanding, the GPS accuracy still suffers from the errors afflicting the measurements, particularly the short-period displacement of structural components. Previously, the multi filter method is utilized to remove the displacement errors. This paper aims at using a novel application for the neural network prediction models to improve the GPS monitoring time series data. Four prediction models for the learning algorithms are applied and used with neural network solutions: back-propagation, Cascade-forward back-propagation, adaptive filter and extended Kalman filter, to estimate which model can be recommended. The noise simulation and bridge’s short-period GPS of the monitoring displacement component of one Hz sampling frequency are used to validate the four models and the previous method. The results show that the Adaptive neural networks filter is suggested for de-noising the observations, specifically for the GPS displacement components of structures. Also, this model is expected to have significant influence on the design of structures in the low frequency responses and measurements’ contents.

  15. Optimization of water-level monitoring networks in the eastern Snake River Plain aquifer using a kriging-based genetic algorithm method

    Science.gov (United States)

    Fisher, Jason C.

    2013-01-01

    Long-term groundwater monitoring networks can provide essential information for the planning and management of water resources. Budget constraints in water resource management agencies often mean a reduction in the number of observation wells included in a monitoring network. A network design tool, distributed as an R package, was developed to determine which wells to exclude from a monitoring network because they add little or no beneficial information. A kriging-based genetic algorithm method was used to optimize the monitoring network. The algorithm was used to find the set of wells whose removal leads to the smallest increase in the weighted sum of the (1) mean standard error at all nodes in the kriging grid where the water table is estimated, (2) root-mean-squared-error between the measured and estimated water-level elevation at the removed sites, (3) mean standard deviation of measurements across time at the removed sites, and (4) mean measurement error of wells in the reduced network. The solution to the optimization problem (the best wells to retain in the monitoring network) depends on the total number of wells removed; this number is a management decision. The network design tool was applied to optimize two observation well networks monitoring the water table of the eastern Snake River Plain aquifer, Idaho; these networks include the 2008 Federal-State Cooperative water-level monitoring network (Co-op network) with 166 observation wells, and the 2008 U.S. Geological Survey-Idaho National Laboratory water-level monitoring network (USGS-INL network) with 171 wells. Each water-level monitoring network was optimized five times: by removing (1) 10, (2) 20, (3) 40, (4) 60, and (5) 80 observation wells from the original network. An examination of the trade-offs associated with changes in the number of wells to remove indicates that 20 wells can be removed from the Co-op network with a relatively small degradation of the estimated water table map, and 40 wells

  16. Optimization of Water-Level Monitoring Networks in the Eastern Snake River Plain Aquifer Using a Kriging-Based Genetic Algorithm Method

    Science.gov (United States)

    Fisher, J. C.

    2013-12-01

    Long-term groundwater monitoring networks can provide essential information for the planning and management of water resources. Budget constraints in water resource management agencies often mean a reduction in the number of observation wells included in a monitoring network. A network design tool, distributed as an R package, was developed to determine which wells to exclude from a monitoring network because they add little or no beneficial information. A kriging-based genetic algorithm method was used to optimize the monitoring network. The algorithm was used to find the set of wells whose removal leads to the smallest increase in the weighted sum of the (1) mean standard error at all nodes in the kriging grid where the water table is estimated, (2) root-mean-squared-error between the measured and estimated water-level elevation at the removed sites, (3) mean standard deviation of measurements across time at the removed sites, and (4) mean measurement error of wells in the reduced network. The solution to the optimization problem (the best wells to retain in the monitoring network) depends on the total number of wells removed; this number is a management decision. The network design tool was applied to optimize two observation well networks monitoring the water table of the eastern Snake River Plain aquifer, Idaho; these networks include the 2008 Federal-State Cooperative water-level monitoring network (Co-op network) with 166 observation wells, and the 2008 U.S. Geological Survey-Idaho National Laboratory water-level monitoring network (USGS-INL network) with 171 wells. Each water-level monitoring network was optimized five times: by removing (1) 10, (2) 20, (3) 40, (4) 60, and (5) 80 observation wells from the original network. An examination of the trade-offs associated with changes in the number of wells to remove indicates that 20 wells can be removed from the Co-op network with a relatively small degradation of the estimated water table map, and 40 wells

  17. Using Maximum Entropy Modeling for Optimal Selection of Sampling Sites for Monitoring Networks

    Directory of Open Access Journals (Sweden)

    Paul H. Evangelista

    2011-05-01

    Full Text Available Environmental monitoring programs must efficiently describe state shifts. We propose using maximum entropy modeling to select dissimilar sampling sites to capture environmental variability at low cost, and demonstrate a specific application: sample site selection for the Central Plains domain (453,490 km2 of the National Ecological Observatory Network (NEON. We relied on four environmental factors: mean annual temperature and precipitation, elevation, and vegetation type. A “sample site” was defined as a 20 km × 20 km area (equal to NEON’s airborne observation platform [AOP] footprint, within which each 1 km2 cell was evaluated for each environmental factor. After each model run, the most environmentally dissimilar site was selected from all potential sample sites. The iterative selection of eight sites captured approximately 80% of the environmental envelope of the domain, an improvement over stratified random sampling and simple random designs for sample site selection. This approach can be widely used for cost-efficient selection of survey and monitoring sites.

  18. Using maximum entropy modeling for optimal selection of sampling sites for monitoring networks

    Science.gov (United States)

    Stohlgren, Thomas J.; Kumar, Sunil; Barnett, David T.; Evangelista, Paul H.

    2011-01-01

    Environmental monitoring programs must efficiently describe state shifts. We propose using maximum entropy modeling to select dissimilar sampling sites to capture environmental variability at low cost, and demonstrate a specific application: sample site selection for the Central Plains domain (453,490 km2) of the National Ecological Observatory Network (NEON). We relied on four environmental factors: mean annual temperature and precipitation, elevation, and vegetation type. A “sample site” was defined as a 20 km × 20 km area (equal to NEON’s airborne observation platform [AOP] footprint), within which each 1 km2 cell was evaluated for each environmental factor. After each model run, the most environmentally dissimilar site was selected from all potential sample sites. The iterative selection of eight sites captured approximately 80% of the environmental envelope of the domain, an improvement over stratified random sampling and simple random designs for sample site selection. This approach can be widely used for cost-efficient selection of survey and monitoring sites.

  19. Optimal design of monitoring networks for multiple groundwater quality parameters using a Kalman filter: application to the Irapuato-Valle aquifer.

    Science.gov (United States)

    Júnez-Ferreira, H E; Herrera, G S; González-Hita, L; Cardona, A; Mora-Rodríguez, J

    2016-01-01

    A new method for the optimal design of groundwater quality monitoring networks is introduced in this paper. Various indicator parameters were considered simultaneously and tested for the Irapuato-Valle aquifer in Mexico. The steps followed in the design were (1) establishment of the monitoring network objectives, (2) definition of a groundwater quality conceptual model for the study area, (3) selection of the parameters to be sampled, and (4) selection of a monitoring network by choosing the well positions that minimize the estimate error variance of the selected indicator parameters. Equal weight for each parameter was given to most of the aquifer positions and a higher weight to priority zones. The objective for the monitoring network in the specific application was to obtain a general reconnaissance of the water quality, including water types, water origin, and first indications of contamination. Water quality indicator parameters were chosen in accordance with this objective, and for the selection of the optimal monitoring sites, it was sought to obtain a low-uncertainty estimate of these parameters for the entire aquifer and with more certainty in priority zones. The optimal monitoring network was selected using a combination of geostatistical methods, a Kalman filter and a heuristic optimization method. Results show that when monitoring the 69 locations with higher priority order (the optimal monitoring network), the joint average standard error in the study area for all the groundwater quality parameters was approximately 90 % of the obtained with the 140 available sampling locations (the set of pilot wells). This demonstrates that an optimal design can help to reduce monitoring costs, by avoiding redundancy in data acquisition.

  20. Optimal Performance Monitoring of Hybrid Mid-Infrared Wavelength MIMO Free Space Optical and RF Wireless Networks in Fading Channels

    Science.gov (United States)

    Schmidt, Barnet Michael

    An optimal performance monitoring metric for a hybrid free space optical and radio-frequency (RF) wireless network, the Outage Capacity Objective Function, is analytically developed and studied. Current and traditional methods of performance monitoring of both optical and RF wireless networks are centered on measurement of physical layer parameters, the most common being signal-to-noise ratio, error rate, Q factor, and eye diagrams, occasionally combined with link-layer measurements such as data throughput, retransmission rate, and/or lost packet rate. Network management systems frequently attempt to predict or forestall network failures by observing degradations of these parameters and to attempt mitigation (such as offloading traffic, increasing transmitter power, reducing the data rate, or combinations thereof) prior to the failure. These methods are limited by the frequent low sensitivity of the physical layer parameters to the atmospheric optical conditions (measured by optical signal-to-noise ratio) and the radio frequency fading channel conditions (measured by signal-to-interference ratio). As a result of low sensitivity, measurements of this type frequently are unable to predict impending failures sufficiently in advance for the network management system to take corrective action prior to the failure. We derive and apply an optimal measure of hybrid network performance based on the outage capacity of the hybrid optical and RF channel, the outage capacity objective function. The objective function provides high sensitivity and reliable failure prediction, and considers both the effects of atmospheric optical impairments on the performance of the free space optical segment as well as the effect of RF channel impairments on the radio frequency segment. The radio frequency segment analysis considers the three most common RF channel fading statistics: Rayleigh, Ricean, and Nakagami-m. The novel application of information theory to the underlying physics of the

  1. Network Monitoring with Nagios

    CERN Document Server

    Dondich, Taylor

    2006-01-01

    Network monitoring can be a complex task to implement and maintain in your IT infrastructure. Nagios, an open-source host, service and network monitoring program can help you streamline your network monitoring tasks and reduce the cost of operation.With this shortcut guide, we'll go over how Nagios fits in the overall network monitoring puzzle. We'll also cover installation and basic usage. Finally, we'll show you how to extend Nagios with other tools to extend functionality.

  2. Design Optimization of Structural Health Monitoring Systems

    Energy Technology Data Exchange (ETDEWEB)

    Flynn, Eric B. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2014-03-06

    Sensor networks drive decisions. Approach: Design networks to minimize the expected total cost (in a statistical sense, i.e. Bayes Risk) associated with making wrong decisions and with installing maintaining and running the sensor network itself. Search for optimal solutions using Monte-Carlo-Sampling-Adapted Genetic Algorithm. Applications include structural health monitoring and surveillance.

  3. Phytoplankton Monitoring Network (PMN)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Phytoplankton Monitoring Network (PMN) is a part of the National Centers for Coastal Ocean Science (NCCOS). The PMN was created as an outreach program to connect...

  4. A geostatistical methodology for the optimal design of space-time hydraulic head monitoring networks and its application to the Valle de Querétaro aquifer.

    Science.gov (United States)

    Júnez-Ferreira, H E; Herrera, G S

    2013-04-01

    This paper presents a new methodology for the optimal design of space-time hydraulic head monitoring networks and its application to the Valle de Querétaro aquifer in Mexico. The selection of the space-time monitoring points is done using a static Kalman filter combined with a sequential optimization method. The Kalman filter requires as input a space-time covariance matrix, which is derived from a geostatistical analysis. A sequential optimization method that selects the space-time point that minimizes a function of the variance, in each step, is used. We demonstrate the methodology applying it to the redesign of the hydraulic head monitoring network of the Valle de Querétaro aquifer with the objective of selecting from a set of monitoring positions and times, those that minimize the spatiotemporal redundancy. The database for the geostatistical space-time analysis corresponds to information of 273 wells located within the aquifer for the period 1970-2007. A total of 1,435 hydraulic head data were used to construct the experimental space-time variogram. The results show that from the existing monitoring program that consists of 418 space-time monitoring points, only 178 are not redundant. The implied reduction of monitoring costs was possible because the proposed method is successful in propagating information in space and time.

  5. Towards Optimal Transport Networks

    Directory of Open Access Journals (Sweden)

    Erik P. Vargo

    2010-08-01

    Full Text Available Our ultimate goal is to design transportation net- works whose dynamic performance metrics (e.g. pas- senger throughput, passenger delay, and insensitivity to weather disturbances are optimized. Here the fo- cus is on optimizing static features of the network that are known to directly affect the network dynamics. First, we present simulation results which support a connection between maximizing the first non-trivial eigenvalue of a network's Laplacian and superior air- port network performance. Then, we explore the ef- fectiveness of a tabu search heuristic for optimizing this metric by comparing experimental results to the- oretical upper bounds. We also consider generating upper bounds on a network's algebraic connectivity via the solution of semidefinite programming (SDP relaxations. A modification of an existing subgraph extraction algorithm is implemented to explore the underlying regional structures in the U.S. airport net- work, with the hope that the resulting localized struc- tures can be optimized independently and reconnected via a "backbone" network to achieve superior network performance.

  6. Airborne Network Optimization with Dynamic Network Update

    Science.gov (United States)

    2015-03-26

    AIRBORNE NETWORK OPTIMIZATION WITH DYNAMIC NETWORK UPDATE THESIS Bradly S. Paul, Capt, USAF AFIT-ENG-MS-15-M-030 DEPARTMENT OF THE AIR FORCE AIR...to copyright protection in the United States. AFIT-ENG-MS-15-M-030 AIRBORNE NETWORK OPTIMIZATION WITH DYNAMIC NETWORK UPDATE THESIS Presented to the...NETWORK OPTIMIZATION WITH DYNAMIC NETWORK UPDATE Bradly S. Paul, B.S.C.P. Capt, USAF Committee Membership: Maj Thomas E. Dube Chair Dr. Kenneth M. Hopkinson

  7. Optimal Design of Air Quality Monitoring Network and its Application in an Oil Refinery Plant: An Approach to Keep Health Status of Workers.

    Science.gov (United States)

    ZoroufchiBenis, Khaled; Fatehifar, Esmaeil; Ahmadi, Javad; Rouhi, Alireza

    2015-01-01

    Industrial air pollution is a growing challenge to humane health, especially in developing countries, where there is no systematic monitoring of air pollution. Given the importance of the availability of valid information on population exposure to air pollutants, it is important to design an optimal Air Quality Monitoring Network (AQMN) for assessing population exposure to air pollution and predicting the magnitude of the health risks to the population. A multi-pollutant method (implemented as a MATLAB program) was explored for configur-ing an AQMN to detect the highest level of pollution around an oil refinery plant. The method ranks potential monitoring sites (grids) according to their ability to represent the ambient concentration. The term of cluster of contiguous grids that exceed a threshold value was used to calculate the Station Dosage. Selection of the best configuration of AQMN was done based on the ratio of a sta-tion's dosage to the total dosage in the network. Six monitoring stations were needed to detect the pollutants concentrations around the study area for estimating the level and distribution of exposure in the population with total network efficiency of about 99%. An analysis of the design procedure showed that wind regimes have greatest effect on the location of monitoring stations. The optimal AQMN enables authorities to implement an effective program of air quality management for protecting human health.

  8. Optimal Design of Air Quality Monitoring Network and its Application in an Oil Refinery Plant: An Approach to Keep Health Satus of Workers

    Directory of Open Access Journals (Sweden)

    Khaled ZoroufchiBenis

    2015-12-01

    Full Text Available Background: Industrial air pollution is a growing challenge to humane health, especially in developing countries, where there is no systematic monitoring of air pollution. Given the importance of the availabil­ity of valid information on population exposure to air pollutants, it is important to design an optimal Air Quality Monitoring Network (AQMN for assessing population exposure to air pollution and predicting the magnitude of the health risks to the population. Methods: A multi-pollutant method (implemented as a MATLAB program was explored for configur­ing an AQMN to detect the highest level of pollution around an oil refinery plant. The method ranks potential monitoring sites (grids according to their ability to represent the ambient concentra­tion. The term of cluster of contiguous grids that exceed a threshold value was used to calculate the Station Dosage. Selection of the best configuration of AQMN was done based on the ratio of a sta­tion’s dosage to the total dosage in the network. Results: Six monitoring stations were needed to detect the pollutants concentrations around the study area for estimating the level and distribution of exposure in the population with total network effi­ciency of about 99%. An analysis of the design procedure showed that wind regimes have greatest effect on the location of monitoring stations. Conclusion: The optimal AQMN enables authorities to implement an effective program of air quality management for protecting human health.

  9. Netherlands grass monitoring network

    NARCIS (Netherlands)

    Stienezen, M.W.J.; Remmelink, G.J.; |Weiden, van der T.; Tjoonk, L.; Nolles, J.E.; Voskamp-Harkema, W.; Pol, van den A.

    2016-01-01

    To support on farm grazing management in the Netheralnds a grass monitoring was established in 2014. The aim of the network is to share and publish data on grass quality, grass growth and soil temperature in different regions of the Netherlands to serve as a benchmark. Grass quality, sward height

  10. Optimal Phase Oscillatory Network

    Science.gov (United States)

    Follmann, Rosangela

    2013-03-01

    Important topics as preventive detection of epidemics, collective self-organization, information flow and systemic robustness in clusters are typical examples of processes that can be studied in the context of the theory of complex networks. It is an emerging theory in a field, which has recently attracted much interest, involving the synchronization of dynamical systems associated to nodes, or vertices, of the network. Studies have shown that synchronization in oscillatory networks depends not only on the individual dynamics of each element, but also on the combination of the topology of the connections as well as on the properties of the interactions of these elements. Moreover, the response of the network to small damages, caused at strategic points, can enhance the global performance of the whole network. In this presentation we explore an optimal phase oscillatory network altered by an additional term in the coupling function. The application to associative-memory network shows improvement on the correct information retrieval as well as increase of the storage capacity. The inclusion of some small deviations on the nodes, when solutions are attracted to a false state, results in additional enhancement of the performance of the associative-memory network. Supported by FAPESP - Sao Paulo Research Foundation, grant number 2012/12555-4

  11. OPTIMAL NETWORK TOPOLOGY DESIGN

    Science.gov (United States)

    Yuen, J. H.

    1994-01-01

    This program was developed as part of a research study on the topology design and performance analysis for the Space Station Information System (SSIS) network. It uses an efficient algorithm to generate candidate network designs (consisting of subsets of the set of all network components) in increasing order of their total costs, and checks each design to see if it forms an acceptable network. This technique gives the true cost-optimal network, and is particularly useful when the network has many constraints and not too many components. It is intended that this new design technique consider all important performance measures explicitly and take into account the constraints due to various technical feasibilities. In the current program, technical constraints are taken care of by the user properly forming the starting set of candidate components (e.g. nonfeasible links are not included). As subsets are generated, they are tested to see if they form an acceptable network by checking that all requirements are satisfied. Thus the first acceptable subset encountered gives the cost-optimal topology satisfying all given constraints. The user must sort the set of "feasible" link elements in increasing order of their costs. The program prompts the user for the following information for each link: 1) cost, 2) connectivity (number of stations connected by the link), and 3) the stations connected by that link. Unless instructed to stop, the program generates all possible acceptable networks in increasing order of their total costs. The program is written only to generate topologies that are simply connected. Tests on reliability, delay, and other performance measures are discussed in the documentation, but have not been incorporated into the program. This program is written in PASCAL for interactive execution and has been implemented on an IBM PC series computer operating under PC DOS. The disk contains source code only. This program was developed in 1985.

  12. Optimization of Pipe Networks

    DEFF Research Database (Denmark)

    Hansen, C. T.; Madsen, Kaj; Nielsen, Hans Bruun

    1991-01-01

    The paper treats a piping system, where the layout of the network is given but the diameters of the pipes should be chosen among a small number of different values. The cost of realizing the system should be minimized while keeping the energy heads at the nodes above some lower limits. A new...... algorithm using successive linear programming is presented. The performance of the algorithm is illustrated by optimizing a network with 201 pipes and 172 nodes. It is concluded that the new algorithm seems to be very efficient and stable, and that it always finds a solution with a cost near the best...

  13. Icinga network monitoring

    CERN Document Server

    Mehta, Viranch

    2013-01-01

    This book is written in a concise and easy-to-follow approach, it will guide you to get you started with Icinga and lead you through the difficult concepts with illustrated examples and screenshots.If you are a system administrator or Linux enthusiast who is looking for a flexible tool to monitor network infrastructure efficiently, or trying to understand the Icinga software, this is a great book for you. You are expected to have solid foundation in Linux.

  14. Application of Multivariate Statistical Methods to Optimize Water Quality Monitoring Network with Emphasis on the Pollution Caused by Fish Farms.

    Science.gov (United States)

    Tavakol, Mitra; Arjmandi, Reza; Shayeghi, Mansoureh; Monavari, Seyed Masoud; Karbassi, Abdolreza

    2017-01-01

    One of the key issues in determining the quality of water in rivers is to create a water quality control network with a suitable performance. The measured qualitative variables at stations should be representative of all the changes in water quality in water systems. Since the increase in water quality monitoring stations increases annual monitoring costs, recognition of the stations with higher importance as well as main parameters can be effective in future decisions to improve the existing monitoring network. Sampling was carried out on 12 physical and chemical parameters measured at 15 stations during 2013-2014 in Haraz River, northern Iran. The results of the measurements were analyzed using multivariate statistical analysis methods including cluster analysis (CA), principal component analysis (PCA), factor analysis (FA), and discriminant analysis (DA). According to the CA, PCA, and FA, the stations were divided into three groups of high pollution, medium pollution, and low pollution. The research findings confirm applicability of multivariate statistical techniques in the interpretation of large data sets, water quality assessment, and source apportionment of different pollution sources.

  15. Application of Frequency of Detection Methods in Design and Optimization of the INL Site Ambient Air Monitoring Network

    Energy Technology Data Exchange (ETDEWEB)

    Rood, Arthur S. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Sondrup, A. Jeffrey [Idaho National Lab. (INL), Idaho Falls, ID (United States)

    2015-11-01

    This report presents an evaluation of a hypothetical INL Site monitoring network and the existing INL air monitoring network using frequency of detection methods. The hypothetical network was designed to address the requirement in 40 CFR Part 61, Subpart H (2006) that “emissions of radionuclides to ambient air from U.S. DOE facilities shall not exceed those amounts that would cause any member of the public to receive in any year an effective dose equivalent exceeding 10 mrem/year.” To meet the requirement for monitoring only, “radionuclide releases that would result in an effective dose of 10% of the standard shall be readily detectable and distinguishable from background.” Thus, the hypothetical network consists of air samplers placed at residence locations that surround INL and at other locations where onsite livestock grazing takes place. Two exposure scenarios were used in this evaluation: a resident scenario and a shepherd/rancher scenario. The resident was assumed to be continuously present at their residence while the shepherd/rancher was assumed to be present 24-hours at a fixed location on the grazing allotment. Important radionuclides were identified from annual INL radionuclide National Emission Standards for Hazardous Pollutants reports. Important radionuclides were defined as those that potentially contribute 1% or greater to the annual total dose at the radionuclide National Emission Standards for Hazardous Pollutants maximally exposed individual location and include H-3, Am-241, Pu-238, Pu 239, Cs-137, Sr-90, and I-131. For this evaluation, the network performance objective was set at achieving a frequency of detection greater than or equal to 95%. Results indicated that the hypothetical network for the resident scenario met all performance objectives for H-3 and I-131 and most performance objectives for Cs-137 and Sr-90. However, all actinides failed to meet the performance objectives for most sources. The shepherd/rancher scenario showed

  16. A sensor network based virtual beam-like structure method for fault diagnosis and monitoring of complex structures with Improved Bacterial Optimization

    Science.gov (United States)

    Wang, H.; Jing, X. J.

    2017-02-01

    This paper proposes a novel method for the fault diagnosis of complex structures based on an optimized virtual beam-like structure approach. A complex structure can be regarded as a combination of numerous virtual beam-like structures considering the vibration transmission path from vibration sources to each sensor. The structural 'virtual beam' consists of a sensor chain automatically obtained by an Improved Bacterial Optimization Algorithm (IBOA). The biologically inspired optimization method (i.e. IBOA) is proposed for solving the discrete optimization problem associated with the selection of the optimal virtual beam for fault diagnosis. This novel virtual beam-like-structure approach needs less or little prior knowledge. Neither does it require stationary response data, nor is it confined to a specific structure design. It is easy to implement within a sensor network attached to the monitored structure. The proposed fault diagnosis method has been tested on the detection of loosening screws located at varying positions in a real satellite-like model. Compared with empirical methods, the proposed virtual beam-like structure method has proved to be very effective and more reliable for fault localization.

  17. Energy optimization in mobile sensor networks

    Science.gov (United States)

    Yu, Shengwei

    Mobile sensor networks are considered to consist of a network of mobile robots, each of which has computation, communication and sensing capabilities. Energy efficiency is a critical issue in mobile sensor networks, especially when mobility (i.e., locomotion control), routing (i.e., communications) and sensing are unique characteristics of mobile robots for energy optimization. This thesis focuses on the problem of energy optimization of mobile robotic sensor networks, and the research results can be extended to energy optimization of a network of mobile robots that monitors the environment, or a team of mobile robots that transports materials from stations to stations in a manufacturing environment. On the energy optimization of mobile robotic sensor networks, our research focuses on the investigation and development of distributed optimization algorithms to exploit the mobility of robotic sensor nodes for network lifetime maximization. In particular, the thesis studies these five problems: 1. Network-lifetime maximization by controlling positions of networked mobile sensor robots based on local information with distributed optimization algorithms; 2. Lifetime maximization of mobile sensor networks with energy harvesting modules; 3. Lifetime maximization using joint design of mobility and routing; 4. Optimal control for network energy minimization; 5. Network lifetime maximization in mobile visual sensor networks. In addressing the first problem, we consider only the mobility strategies of the robotic relay nodes in a mobile sensor network in order to maximize its network lifetime. By using variable substitutions, the original problem is converted into a convex problem, and a variant of the sub-gradient method for saddle-point computation is developed for solving this problem. An optimal solution is obtained by the method. Computer simulations show that mobility of robotic sensors can significantly prolong the lifetime of the whole robotic sensor network while

  18. SNMP Based Network Optimization Technique Using Genetic Algorithms

    Directory of Open Access Journals (Sweden)

    M. Mohamed Surputheen

    2012-03-01

    Full Text Available Genetic Algorithms (GAs has innumerable applications through the optimization techniques and network optimization is one of them. SNMP (Simple Network Management Protocol is used as the basic network protocol for monitoring the network activities health of the systems. This paper deals with adding Intelligence to the various aspects of SNMP by adding optimization techniques derived out of genetic algorithms, which enhances the performance of SNMP processes like routing.

  19. Transport optimization on complex networks

    CERN Document Server

    Danila, Bogdan; Marsh, John A; Bassler, Kevin E

    2007-01-01

    We present a comparative study of the application of a recently introduced heuristic algorithm to the optimization of transport on three major types of complex networks. The algorithm balances network traffic iteratively by minimizing the maximum node betweenness with as little path lengthening as possible. We show that by using this optimal routing, a network can sustain significantly higher traffic without jamming than in the case of shortest path routing. A formula is proved that allows quick computation of the average number of hops along the path and of the average travel times once the betweennesses of the nodes are computed. Using this formula, we show that routing optimization preserves the small-world character exhibited by networks under shortest path routing, and that it significantly reduces the average travel time on congested networks with only a negligible increase in the average travel time at low loads. Finally, we study the correlation between the weights of the links in the case of optimal ...

  20. Optimal Disruption of Complex Networks

    CERN Document Server

    Zhao, Jin-Hua

    2016-01-01

    The collection of all the strongly connected components in a directed graph, among each cluster of which any node has a path to another node, is a typical example of the intertwining structure and dynamics in complex networks, as its relative size indicates network cohesion and it also composes of all the feedback cycles in the network. Here we consider finding an optimal strategy with minimal effort in removal arcs (for example, deactivation of directed interactions) to fragment all the strongly connected components into tree structure with no effect from feedback mechanism. We map the optimal network disruption problem to the minimal feedback arc set problem, a non-deterministically polynomial hard combinatorial optimization problem in graph theory. We solve the problem with statistical physical methods from spin glass theory, resulting in a simple numerical method to extract sub-optimal disruption arc sets with significantly better results than a local heuristic method and a simulated annealing method both...

  1. Performance Monitoring Techniques Supporting Cognitive Optical Networking

    DEFF Research Database (Denmark)

    Caballero Jambrina, Antonio; Borkowski, Robert; Zibar, Darko

    2013-01-01

    to solve this issue by realizing a network that can observe, act, learn and optimize its performance, taking into account end-to-end goals. In this letter we present the approach of cognition applied to heterogeneous optical networks developed in the framework of the EU project CHRON: Cognitive...... Heterogeneous Reconfigurable Optical Network. We focus on the approaches developed in the project for optical performance monitoring, which enable the feedback from the physical layer to the cognitive decision system by providing accurate description of the performance of the established lightpaths.......High degree of heterogeneity of future optical networks, such as services with different quality-of-transmission requirements, modulation formats and switching techniques, will pose a challenge for the control and optimization of different parameters. Incorporation of cognitive techniques can help...

  2. Optimal scales in weighted networks

    CERN Document Server

    Garlaschelli, Diego; Fink, Thomas M A; Caldarelli, Guido

    2013-01-01

    The analysis of networks characterized by links with heterogeneous intensity or weight suffers from two long-standing problems of arbitrariness. On one hand, the definitions of topological properties introduced for binary graphs can be generalized in non-unique ways to weighted networks. On the other hand, even when a definition is given, there is no natural choice of the (optimal) scale of link intensities (e.g. the money unit in economic networks). Here we show that these two seemingly independent problems can be regarded as intimately related, and propose a common solution to both. Using a formalism that we recently proposed in order to map a weighted network to an ensemble of binary graphs, we introduce an information-theoretic approach leading to the least biased generalization of binary properties to weighted networks, and at the same time fixing the optimal scale of link intensities. We illustrate our method on various social and economic networks.

  3. ICFA SCIC Network Monitoring Report

    CERN Document Server

    McKee, Shawn; Babik, Marian; Hayashi, Soichi; Tierney, Brian; Giemza, Henryk; Vukotic, Ilija; O’Connor, Mike; CERN. Geneva. IT Department

    2016-01-01

    This report may be regarded as a follow up to the previous ICFA Standing Committee on Inter-regional Connectivity (SCIC) Monitoring working group’s Network reports dating back to 1997. The current report updates the January 2015 report. As noted, PingER activities will not be covered in the same depth as earlier reports because of a lack of funding for this effort. We will be including some new areas related to network monitoring in HEP including updates and status on the perfSONAR efforts globally as well as the WLCG Network and Transfer Metrics Working Group activities.

  4. Combinatorial optimization networks and matroids

    CERN Document Server

    Lawler, Eugene

    2011-01-01

    Perceptively written text examines optimization problems that can be formulated in terms of networks and algebraic structures called matroids. Chapters cover shortest paths, network flows, bipartite matching, nonbipartite matching, matroids and the greedy algorithm, matroid intersections, and the matroid parity problems. A suitable text or reference for courses in combinatorial computing and concrete computational complexity in departments of computer science and mathematics.

  5. Condition monitoring and thermoeconomic optimization of operation for a hybrid plant using artificial neural networks; Tillstaandsoevervakning och termoekonomisk driftoptimering av en hybridanlaeggning med artificiella neurala naetverk

    Energy Technology Data Exchange (ETDEWEB)

    Fast, Magnus; Assadi, Mohsen

    2007-12-15

    The project aim is to model the hybrid plant at Vaesthamnsverket in Helsingborg using artificial neural networks (ANN) and integrating the ANN models, for online condition monitoring and thermoeconomic optimization, at Vaesthamnsverket. The definition of a hybrid plant is that it uses more than one fuel, in this case a natural gas fuelled gas turbine with heat recovery steam generator (HRSG) and a biomass fuelled steam boiler with steam turbine. The project is a continuation of previous projects where ANN training was done with operational data from the plant. The ANN models have, if required, been updated to better suit the purpose of this project. The thermoeconomic optimization takes into account current electricity prices, taxes, fuel prices etc. and calculates the current production cost along with the 'predicted' production cost. The tool also has a built in feature of predicting when a compressor wash is economically beneficial. The user interface is developed together with co-workers at Vaesthamnsverket to ensure its usefulness. The user interface includes functions for warnings and alarms when possible deviations in operation occur and also includes a feature for plotting parameter trends in optional time intervals, both measured values and predicted. The target group is the plant owners and the original equipment manufacturers (OEM). The power plant owners want to acquire a product for condition monitoring and thermoeconomic optimization of e.g. maintenance. The OEMs main interest lies in investigating the possibilities of delivering ANN models along with their new gas turbines. The project has been carried out at Lund University, Department of Energy Sciences, with support from Vaesthamnsverket and Siemens. Vaesthamnsverket have contributed with operational data from the plant as well as support in plant related questions. They have also been involved in the implementation of the ANN models in their computer system and the development of the

  6. Optimization of Pipe Networks

    DEFF Research Database (Denmark)

    Hansen, C. T.; Madsen, Kaj; Nielsen, Hans Bruun

    1991-01-01

    The paper treats a piping system, where the layout of the network is given but the diameters of the pipes should be chosen among a small number of different values. The cost of realizing the system should be minimized while keeping the energy heads at the nodes above some lower limits. A new...

  7. 网络寿命最优的管道监测传感网节点部署研究%Research on node deployment based on optimal network lifetime in pipeline monitoring sensor networks

    Institute of Scientific and Technical Information of China (English)

    余阳; 吴银锋; 于宁; 冯仁剑; 万江文

    2012-01-01

    This paper puts forward a sort of optimal node deployment scheme of pipeline monitoring sensor networks to lower the network node energy consumption and prolong network lifetime. Network cost-lifetime is adopted as the optimization objective. The relationship among network size, node spacing and data transmission structure is intensively analyzed. And a mathematical model of network deployment optimization problem is set up, which is solved using hybrid genetic algorithm. The algorithm amends the infeasible solution with external function method. In the meantime , the simulated annealing operator is used in the algorithm to enhance the searching capability. Theoretical analysis and experiment result show that compared with existing node deployment schemes, the new scheme not only reduces node energy consumption and balances network load, but also benefits network lifetime.%提出一种管道监测传感网中节点的优化部署方案,以降低天然气管道监测网络的节点能耗和延长网络寿命.采用一种新的性能指标——成本寿命作为优化目标,分析网络规模、节点间距以及数据传输结构对优化目标的影响,并建立求解节点部署优化问题的数学模型.模型的求解采用混合遗传算法,利用外点函数法修正不满足约束条件的解,同时把退火选择算子嵌入到实数编码的遗传算法中,增强其搜索能力.理论分析和实验结果表明,该方案不仅能够降低网络的节点能耗,平衡网络负载,而且对网络寿命有益处.

  8. Analysis and monitoring design for networks

    Energy Technology Data Exchange (ETDEWEB)

    Fedorov, V.; Flanagan, D.; Rowan, T.; Batsell, S.

    1998-06-01

    The idea of applying experimental design methodologies to develop monitoring systems for computer networks is relatively novel even though it was applied in other areas such as meteorology, seismology, and transportation. One objective of a monitoring system should always be to collect as little data as necessary to be able to monitor specific parameters of the system with respect to assigned targets and objectives. This implies a purposeful monitoring where each piece of data has a reason to be collected and stored for future use. When a computer network system as large and complex as the Internet is the monitoring subject, providing an optimal and parsimonious observing system becomes even more important. Many data collection decisions must be made by the developers of a monitoring system. These decisions include but are not limited to the following: (1) The type data collection hardware and software instruments to be used; (2) How to minimize interruption of regular network activities during data collection; (3) Quantification of the objectives and the formulation of optimality criteria; (4) The placement of data collection hardware and software devices; (5) The amount of data to be collected in a given time period, how large a subset of the available data to collect during the period, the length of the period, and the frequency of data collection; (6) The determination of the data to be collected (for instance, selection of response and explanatory variables); (7) Which data will be retained and how long (i.e., data storage and retention issues); and (8) The cost analysis of experiments. Mathematical statistics, and, in particular, optimal experimental design methods, may be used to address the majority of problems generated by 3--7. In this study, the authors focus their efforts on topics 3--5.

  9. Location based Network Optimizations for Mobile Wireless Networks

    DEFF Research Database (Denmark)

    Nielsen, Jimmy Jessen

    selection in Wi-Fi networks and predictive handover optimization in heterogeneous wireless networks. The investigations in this work have indicated that location based network optimizations are beneficial compared to typical link measurement based approaches. Especially the knowledge of geographical...

  10. Route Optimization in Network Mobility

    Directory of Open Access Journals (Sweden)

    Md. Hasan Tareque

    2013-01-01

    Full Text Available NEtwork MObility (NEMO controls mobility of a number of mobile nodes in a comprehensive way using one or more mobile routers. To choose a route optimization scheme, it is very important to have a quantitative comparison of the available route optimization schemes. The focus of this paper is to analyze the degree of Route Optimization (RO, deploy-ability and type of RO supported by each class in general. The comparison shows the differences among the schemes in terms of issues, such as additional header, signaling and memory requirement. We classify the schemes established on the basic method for route optimization, and equal the schemes based on protocol overhead, such as header overhead, amount of signaling, and memory requirements. Lastly the performance of the classes of different schemes has to be estimated under norms such as available bandwidth, topology of the mobile network and mobility type.

  11. Optimization of spatial complex networks

    Science.gov (United States)

    Guillier, S.; Muñoz, V.; Rogan, J.; Zarama, R.; Valdivia, J. A.

    2017-02-01

    First, we estimate the connectivity properties of a predefined (fixed node locations) spatial network which optimizes a connectivity functional that balances construction and transportation costs. In this case we obtain a Gaussian distribution for the connectivity. However, when we consider these spatial networks in a growing process, we obtain a power law distribution for the connectivity. If the transportation costs in the functional involve the shortest geometrical path, we obtain a scaling exponent γ = 2.5. However, if the transportation costs in the functional involve just the shortest path, we obtain γ = 2.2. Both cases may be useful to analyze in some real networks.

  12. Optimizations in Heterogeneous Mobile Networks

    DEFF Research Database (Denmark)

    Popovska Avramova, Andrijana

    in providing efficient flow control, and investigates an optimal traffic rate allocation method. Cloud Radio Access Network (C-RAN) designates a leading technology for the Radio Access Network (RAN) architecture that is able to support dense deployments, while ensuring network level energy and cost efficiency...... with the densification of the base stations, bring into a very complex network management and operation control for the mobile operators. Furthermore, the need to provide always best connection and service with high quality demands for a joint overall network resource management. This thesis addresses this challenge...... significant performance improvement to the achieved user throughput in low as well as in high loads in the cell. The flow control of the data between the nodes is another challenge for effective aggregation of the resources in case of dual connectivity. As such, this thesis discusses the challenges...

  13. Optimization of neutron monitor data correction algorithms

    Energy Technology Data Exchange (ETDEWEB)

    Paschalis, P. [Nuclear and Particle Physics Section, Physics Department, National and Kapodistrian University of Athens, Zografos 15783, Athens (Greece); Mavromichalaki, H., E-mail: emavromi@phys.uoa.gr [Nuclear and Particle Physics Section, Physics Department, National and Kapodistrian University of Athens, Zografos 15783, Athens (Greece)

    2013-06-21

    Nowadays, several neutron monitor stations worldwide, broadcast their cosmic ray data in real time, in order for the scientific community to be able to use these measurements immediately. In parallel, the development of the Neutron Monitor Database (NMDB; (http://www.nmdb.eu)) which collects all the high resolution real time measurements, allows the implementation of various applications and services by using these data instantly. Therefore, it is obvious that the need for high quality real time data is imperative. The quality of the data is handled by different correction algorithms that filter the real time measurements for undesired instrumental variations. In this work, an optimization of the Median Editor that is currently mainly applied to the neutron monitor data and the recently proposed ANN algorithm based on neural networks is presented. This optimization leads to the implementation of the Median Editor Plus and the ANN Plus algorithms. A direct comparison of these algorithms with the newly appeared Edge Editor is performed and the results are presented.

  14. Efficient Network Monitoring for Large Data Acquisition Systems

    CERN Document Server

    Savu, DO; The ATLAS collaboration; Al-Shabibi, A; Sjoen, R; Batraneanu, SM; Stancu, SN

    2011-01-01

    Though constantly evolving and improving, the available network monitoring solutions have limitations when applied to the infrastructure of a high speed real-time data acquisition (DAQ) system. DAQ networks are particular computer networks where experts have to pay attention to both individual subsections as well as system wide traffic flows while monitoring the network. The ATLAS Network at the Large Hadron Collider (LHC) has more than 200 switches interconnecting 3500 hosts and totaling 8500 high speed links. The use of heterogeneous tools for monitoring various infrastructure parameters, in order to assure optimal DAQ system performance, proved to be a tedious and time consuming task for experts. To alleviate this problem we used our networking and DAQ expertise to build a flexible and scalable monitoring system providing an intuitive user interface with the same look and feel irrespective of the data provider that is used. Our system uses custom developed components for critical performance monitoring and...

  15. Overall optimization of distribution networks

    Institute of Scientific and Technical Information of China (English)

    刘莉; 陈学允; 郭志忠

    2001-01-01

    Network reconfiguration and capacitor switching are important measures to reduce power loss and im prove security and economy in automation of distribution. A new method based on parallel genetic algorithm is proposed to search the whole problem space for better solution. Multiple populations evolve independently and communicate periodically, which simulates parallel computing process to save computing time. The results show that the method is robust and has better benefit than the alterafive iteration method. In addition, the effect of overall optimization is better than optimization alone. Power loss can be reduced and the level of voltage can begreatly improved.

  16. Host Event Based Network Monitoring

    Energy Technology Data Exchange (ETDEWEB)

    Jonathan Chugg

    2013-01-01

    The purpose of INL’s research on this project is to demonstrate the feasibility of a host event based network monitoring tool and the effects on host performance. Current host based network monitoring tools work on polling which can miss activity if it occurs between polls. Instead of polling, a tool could be developed that makes use of event APIs in the operating system to receive asynchronous notifications of network activity. Analysis and logging of these events will allow the tool to construct the complete real-time and historical network configuration of the host while the tool is running. This research focused on three major operating systems commonly used by SCADA systems: Linux, WindowsXP, and Windows7. Windows 7 offers two paths that have minimal impact on the system and should be seriously considered. First is the new Windows Event Logging API, and, second, Windows 7 offers the ALE API within WFP. Any future work should focus on these methods.

  17. Optimization of synchronizability in multiplex networks

    CERN Document Server

    Dwivedi, Sanjiv K; Jalan, Sarika

    2015-01-01

    We investigate the optimization of synchronizability in multiplex networks and demonstrate that the interlayer coupling strength is the deciding factor for the efficiency of optimization. The optimized networks have homogeneity in the degree as well as in the betweenness centrality. Additionally, the interlayer coupling strength crucially affects various properties of individual layers in the optimized multiplex networks. We provide an understanding to how the emerged network properties are shaped or affected when the evolution renders them better synchronizable.

  18. Networked Computing in Wireless Sensor Networks for Structural Health Monitoring

    CERN Document Server

    Jindal, Apoorva

    2010-01-01

    This paper studies the problem of distributed computation over a network of wireless sensors. While this problem applies to many emerging applications, to keep our discussion concrete we will focus on sensor networks used for structural health monitoring. Within this context, the heaviest computation is to determine the singular value decomposition (SVD) to extract mode shapes (eigenvectors) of a structure. Compared to collecting raw vibration data and performing SVD at a central location, computing SVD within the network can result in significantly lower energy consumption and delay. Using recent results on decomposing SVD, a well-known centralized operation, into components, we seek to determine a near-optimal communication structure that enables the distribution of this computation and the reassembly of the final results, with the objective of minimizing energy consumption subject to a computational delay constraint. We show that this reduces to a generalized clustering problem; a cluster forms a unit on w...

  19. Performance Monitoring in Transparent Reconfigurable WDM Networks

    Institute of Scientific and Technical Information of China (English)

    Chun-Kit.Chan; Frank; Tong

    2003-01-01

    This paper classifies and surveys different approaches proposed for performance monitoring, in particular the optical signal-to-noise ratio (OSNR) monitoring, in transparent reconfigurable WDM networks. Some considerations for future monitoring schemes are discussed.

  20. Optimization of Actuating Origami Networks

    Science.gov (United States)

    Buskohl, Philip; Fuchi, Kazuko; Bazzan, Giorgio; Joo, James; Gregory, Reich; Vaia, Richard

    2015-03-01

    Origami structures morph between 2D and 3D conformations along predetermined fold lines that efficiently program the form, function and mobility of the structure. By leveraging design concepts from action origami, a subset of origami art focused on kinematic mechanisms, reversible folding patterns for applications such as solar array packaging, tunable antennae, and deployable sensing platforms may be designed. However, the enormity of the design space and the need to identify the requisite actuation forces within the structure places a severe limitation on design strategies based on intuition and geometry alone. The present work proposes a topology optimization method, using truss and frame element analysis, to distribute foldline mechanical properties within a reference crease pattern. Known actuating patterns are placed within a reference grid and the optimizer adjusts the fold stiffness of the network to optimally connect them. Design objectives may include a target motion, stress level, or mechanical energy distribution. Results include the validation of known action origami structures and their optimal connectivity within a larger network. This design suite offers an important step toward systematic incorporation of origami design concepts into new, novel and reconfigurable engineering devices. This research is supported under the Air Force Office of Scientific Research (AFOSR) funding, LRIR 13RQ02COR.

  1. Sensor Network Architectures for Monitoring Underwater Pipelines

    OpenAIRE

    Imad Jawhar; Jameela Al-Jaroodi; Nader Mohamed; Liren Zhang

    2011-01-01

    This paper develops and compares different sensor network architecture designs that can be used for monitoring underwater pipeline infrastructures. These architectures are underwater wired sensor networks, underwater acoustic wireless sensor networks, RF (Radio Frequency) wireless sensor networks, integrated wired/acoustic wireless sensor networks, and integrated wired/RF wireless sensor networks. The paper also discusses the reliability challenges and enhancement approaches for these network...

  2. The Austrian UV monitoring network

    Science.gov (United States)

    Blumthaler, Mario; Klotz, Barbara; Schwarzmann, Michael; Schreder, Josef

    2017-02-01

    The Austrian UV Monitoring network is operational since 1998 providing a large data set of erythemally weighted UV irradiance recorded with broadband UV biometer at 12 stations distributed all over Austria. In order to obtain high quality data all biometer are recalibrated once a year, the detectors are checked regularly for humidity and quality control is done routinely. The collected data are processed and then published on the website http://www.uv-index.at where the UV-Index of all measurement sites is presented in near real time together with a map of the distribution of the UV-Index over Austria. These UV-Index data together with measurements of global radiation and ozone levels from OMI are used to study long term trends for the stations of the monitoring network. Neither for all weather conditions nor for clear sky conditions is a statistically significant trend found for the UV-Index (with one exception) and for ozone. Furthermore, the radiation amplification factor (RAF) is determined experimentally from the power law correlation between UV-Index and ozone level for the site Innsbruck (577 m above sea level, 47.26°N, 11.38°E) for 19°solar elevation. A value of 0.91 ± 0.05 is found for the RAF for clear sky days with low ground albedo and a value of 1.03 ± 0.08 for days with high ground albedo (snow cover).

  3. Optimal Selection of Number and Location of Meteo-Hydrological Monitoring Networks on Vu Gia – Thu Bon River Basin using GIS

    Directory of Open Access Journals (Sweden)

    Nguyen Thi Hong

    2016-05-01

    Full Text Available Meteorological data play a particularly important role in hydrologic research because the climate and weather of an area exert a profound influence on most hydrologic processes. Meanwhile, hydrological data are critical for performing a range of purposes, including water resources assessment, impacts of climate change and flood forecasting and warning. It can be said that the prevention of disasters caused by floods and droughts would be impossible without rational forecasting technology based on an understanding of the rainfall-runoff phenomenon and statistical analysis of past hydrological data, which cannot be achieved without meteo-hydrological observations. The lack of adequate meteo-hydrological data affects the ability to model, predict and plan for catastrophic events such as floods and droughts which have obvious negative impacts on public health and socio-economic aspects. The accurate estimation of the spatial distribution of meteorological and hydrological parameters requires a dense network of instruments, which entails large installation and operational costs. It is thus necessary to optimize the number and location of meteo-hydrological stations. This paper presents a GIS-based approach to establishing an optimal meteo-hydrological station network on Vu Gia- Thu Bon river basin for developing an up-to-date real time flood warning system. Based on statistical analysis of the annual rainfall total data at 9 existing gauges in the study area from 1980 to 2013, it showed that the error of the existing network was about 7.47%. Considering 9 rain gauges as a standard representative of rainfall over the region, if the error decreases from 7.47% to 5%, the number of additional rain gauges should be 20. For adequate and economical network design, these additional rain gauges were spatially distributed between the different isohyetals after considering the relative distances between rain gauges, their accessibility, personnel required for

  4. Environmental Monitoring Using Sensor Networks

    Science.gov (United States)

    Yang, J.; Zhang, C.; Li, X.; Huang, Y.; Fu, S.; Acevedo, M. F.

    2008-12-01

    Environmental observatories, consisting of a variety of sensor systems, computational resources and informatics, are important for us to observe, model, predict, and ultimately help preserve the health of the nature. The commoditization and proliferation of coin-to-palm sized wireless sensors will allow environmental monitoring with unprecedented fine spatial and temporal resolution. Once scattered around, these sensors can identify themselves, locate their positions, describe their functions, and self-organize into a network. They communicate through wireless channel with nearby sensors and transmit data through multi-hop protocols to a gateway, which can forward information to a remote data server. In this project, we describe an environmental observatory called Texas Environmental Observatory (TEO) that incorporates a sensor network system with intertwined wired and wireless sensors. We are enhancing and expanding the existing wired weather stations to include wireless sensor networks (WSNs) and telemetry using solar-powered cellular modems. The new WSNs will monitor soil moisture and support long-term hydrologic modeling. Hydrologic models are helpful in predicting how changes in land cover translate into changes in the stream flow regime. These models require inputs that are difficult to measure over large areas, especially variables related to storm events, such as soil moisture antecedent conditions and rainfall amount and intensity. This will also contribute to improve rainfall estimations from meteorological radar data and enhance hydrological forecasts. Sensor data are transmitted from monitoring site to a Central Data Collection (CDC) Server. We incorporate a GPRS modem for wireless telemetry, a single-board computer (SBC) as Remote Field Gateway (RFG) Server, and a WSN for distributed soil moisture monitoring. The RFG provides effective control, management, and coordination of two independent sensor systems, i.e., a traditional datalogger-based wired

  5. Sensor network architectures for monitoring underwater pipelines.

    Science.gov (United States)

    Mohamed, Nader; Jawhar, Imad; Al-Jaroodi, Jameela; Zhang, Liren

    2011-01-01

    This paper develops and compares different sensor network architecture designs that can be used for monitoring underwater pipeline infrastructures. These architectures are underwater wired sensor networks, underwater acoustic wireless sensor networks, RF (radio frequency) wireless sensor networks, integrated wired/acoustic wireless sensor networks, and integrated wired/RF wireless sensor networks. The paper also discusses the reliability challenges and enhancement approaches for these network architectures. The reliability evaluation, characteristics, advantages, and disadvantages among these architectures are discussed and compared. Three reliability factors are used for the discussion and comparison: the network connectivity, the continuity of power supply for the network, and the physical network security. In addition, the paper also develops and evaluates a hierarchical sensor network framework for underwater pipeline monitoring.

  6. Sensor Network Architectures for Monitoring Underwater Pipelines

    Directory of Open Access Journals (Sweden)

    Imad Jawhar

    2011-11-01

    Full Text Available This paper develops and compares different sensor network architecture designs that can be used for monitoring underwater pipeline infrastructures. These architectures are underwater wired sensor networks, underwater acoustic wireless sensor networks, RF (Radio Frequency wireless sensor networks, integrated wired/acoustic wireless sensor networks, and integrated wired/RF wireless sensor networks. The paper also discusses the reliability challenges and enhancement approaches for these network architectures. The reliability evaluation, characteristics, advantages, and disadvantages among these architectures are discussed and compared. Three reliability factors are used for the discussion and comparison: the network connectivity, the continuity of power supply for the network, and the physical network security. In addition, the paper also develops and evaluates a hierarchical sensor network framework for underwater pipeline monitoring.

  7. Dynamic Shortest Path Monitoring in Spatial Networks

    Institute of Scientific and Technical Information of China (English)

    Shuo Shang; Lisi Chen; Zhe-Wei Wei; Dan-Huai Guo; Ji-Rong Wen

    2016-01-01

    With the increasing availability of real-time traffic information, dynamic spatial networks are pervasive nowa-days and path planning in dynamic spatial networks becomes an important issue. In this light, we propose and investigate a novel problem of dynamically monitoring shortest paths in spatial networks (DSPM query). When a traveler aims to a des-tination, his/her shortest path to the destination may change due to two reasons: 1) the travel costs of some edges have been updated and 2) the traveler deviates from the pre-planned path. Our target is to accelerate the shortest path computing in dynamic spatial networks, and we believe that this study may be useful in many mobile applications, such as route planning and recommendation, car navigation and tracking, and location-based services in general. This problem is challenging due to two reasons: 1) how to maintain and reuse the existing computation results to accelerate the following computations, and 2) how to prune the search space effectively. To overcome these challenges, filter-and-refinement paradigm is adopted. We maintain an expansion tree and define a pair of upper and lower bounds to prune the search space. A series of optimization techniques are developed to accelerate the shortest path computing. The performance of the developed methods is studied in extensive experiments based on real spatial data.

  8. Optimizing neural network forecast by immune algorithm

    Institute of Scientific and Technical Information of China (English)

    YANG Shu-xia; LI Xiang; LI Ning; YANG Shang-dong

    2006-01-01

    Considering multi-factor influence, a forecasting model was built. The structure of BP neural network was designed, and immune algorithm was applied to optimize its network structure and weight. After training the data of power demand from the year 1980 to 2005 in China, a nonlinear network model was obtained on the relationship between power demand and the factors which had impacts on it, and thus the above proposed method was verified. Meanwhile, the results were compared to those of neural network optimized by genetic algorithm. The results show that this method is superior to neural network optimized by genetic algorithm and is one of the effective ways of time series forecast.

  9. 2016 Network Games, Control, and Optimization Conference

    CERN Document Server

    Jimenez, Tania; Solan, Eilon

    2017-01-01

    This contributed volume offers a collection of papers presented at the 2016 Network Games, Control, and Optimization conference (NETGCOOP), held at the University of Avignon in France, November 23-25, 2016. These papers highlight the increasing importance of network control and optimization in many networking application domains, such as mobile and fixed access networks, computer networks, social networks, transportation networks, and, more recently, electricity grids and biological networks. Covering a wide variety of both theoretical and applied topics in the areas listed above, the authors explore several conceptual and algorithmic tools that are needed for efficient and robust control operation, performance optimization, and better understanding the relationships between entities that may be acting cooperatively or selfishly in uncertain and possibly adversarial environments. As such, this volume will be of interest to applied mathematicians, computer scientists, engineers, and researchers in other relate...

  10. Monitoring the Topology of Growing Dynamical Networks

    Science.gov (United States)

    Wu, Zhaoyan; Fu, Xinchu; Chen, Guanrong

    In this paper, topology monitoring of growing networks is studied. When some new nodes are added into a network, the topology of the network is changed, which needs to be monitored in many applications. Some auxiliary systems (network monitors) are designed to achieve this goal. Both linear feedback control and adaptive strategy are applied to designing such network monitors. Based on the Lyapunov function method via constructing a potential or energy function decreasing along any solution of the system, and the LaSalle's invariance principle, which is a generalization of the Lyapunov function method, some sufficient conditions for achieving topology monitoring are obtained. Illustrative examples are provided to demonstrate the effectiveness of the new method.

  11. Configurable Monitoring for Multi-domain Networks

    OpenAIRE

    Belghith, Aymen; Cousin, Bernard; Lahoud, Samer

    2014-01-01

    International audience; In this paper, we review the state-of-the-art monitoring architectures proposed for multi-domain networks. We establish the five requirements a multi-domain monitoring architecture must fulfilled. We note that these architectures do not support measurement configuration that enables the providers to perform flexible multi-domain measurements. Therefore, we propose a configurable multi-domain network monitoring architecture in order to give more flexibility in monitorin...

  12. Optimization of temporal networks under uncertainty

    CERN Document Server

    Wiesemann, Wolfram

    2012-01-01

    Many decision problems in Operations Research are defined on temporal networks, that is, workflows of time-consuming tasks whose processing order is constrained by precedence relations. For example, temporal networks are used to model projects, computer applications, digital circuits and production processes. Optimization problems arise in temporal networks when a decision maker wishes to determine a temporal arrangement of the tasks and/or a resource assignment that optimizes some network characteristic (e.g. the time required to complete all tasks). The parameters of these optimization probl

  13. Bridge monitoring using heterogeneous wireless sensor network

    Science.gov (United States)

    Haran, Shivan; Kher, Shubhalaxmi; Mehndiratta, Vandana

    2010-03-01

    Wireless sensor networks (WSN) are proving to be a good fit where real time monitoring of multiple physical parameters is required. In many applications such as structural health monitoring, patient data monitoring, traffic accident monitoring and analysis, sensor networks may involve interface with conventional P2P systems and it is challenging to handle heterogeneous network systems. Heterogeneous deployments will become increasingly prevalent as it allows for systems to seamlessly integrate and interoperate especially when it comes to applications involving monitoring of large infrastructures. Such networks may have wireless sensor network overlaid on a conventional computer network to pick up data from one distant location and carry out the analysis after relaying it over to another distant location. This paper discusses monitoring of bridges using WSN. As a test bed, a heterogeneous network of WSN and conventional P2P together with a combination of sensing devices (including vibration and strain) is to be used on a bridge model. Issues related to condition assessment of the bridge for situations including faults, overloads, etc., as well as analysis of network and system performance will be discussed. When conducted under controlled conditions, this is an important step towards fine tuning the monitoring system for recommendation of permanent mounting of sensors and collecting data that can help in the development of new methods for inspection and evaluation of bridges. The proposed model, design, and issues therein will be discussed, along with its implementation and results.

  14. Optimal urban networks via mass transportation

    CERN Document Server

    Buttazzo, Giuseppe; Stepanov, Eugene; Solimini, Sergio

    2009-01-01

    Recently much attention has been devoted to the optimization of transportation networks in a given geographic area. One assumes the distributions of population and of services/workplaces (i.e. the network's sources and sinks) are known, as well as the costs of movement with/without the network, and the cost of constructing/maintaining it. Both the long-term optimization and the short-term, "who goes where" optimization are considered. These models can also be adapted for the optimization of other types of networks, such as telecommunications, pipeline or drainage networks. In the monograph we study the most general problem settings, namely, when neither the shape nor even the topology of the network to be constructed is known a priori.

  15. Adaptive optimization and control using neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Mead, W.C.; Brown, S.K.; Jones, R.D.; Bowling, P.S.; Barnes, C.W.

    1993-10-22

    Recent work has demonstrated the ability of neural-network-based controllers to optimize and control machines with complex, non-linear, relatively unknown control spaces. We present a brief overview of neural networks via a taxonomy illustrating some capabilities of different kinds of neural networks. We present some successful control examples, particularly the optimization and control of a small-angle negative ion source.

  16. Mathematical Aspects of Network Routing Optimization

    CERN Document Server

    Oliveira, Carlos AS

    2011-01-01

    Before the appearance of broadband links and wireless systems, networks have been used to connect people in new ways. Now, the modern world is connected through large-scale, computational networked systems such as the Internet. Because of the ever-advancing technology of networking, efficient algorithms have become increasingly necessary to solve some of the problems developing in this area. "Mathematical Aspects of Network Routing Optimization" focuses on computational issues arising from the process of optimizing network routes, such as quality of the resulting links and their reli

  17. Promoting Social Network Awareness: A Social Network Monitoring System

    Science.gov (United States)

    Cadima, Rita; Ferreira, Carlos; Monguet, Josep; Ojeda, Jordi; Fernandez, Joaquin

    2010-01-01

    To increase communication and collaboration opportunities, members of a community must be aware of the social networks that exist within that community. This paper describes a social network monitoring system--the KIWI system--that enables users to register their interactions and visualize their social networks. The system was implemented in a…

  18. Promoting Social Network Awareness: A Social Network Monitoring System

    Science.gov (United States)

    Cadima, Rita; Ferreira, Carlos; Monguet, Josep; Ojeda, Jordi; Fernandez, Joaquin

    2010-01-01

    To increase communication and collaboration opportunities, members of a community must be aware of the social networks that exist within that community. This paper describes a social network monitoring system--the KIWI system--that enables users to register their interactions and visualize their social networks. The system was implemented in a…

  19. Optimizing Dynamical Network Structure for Pinning Control

    Science.gov (United States)

    Orouskhani, Yasin; Jalili, Mahdi; Yu, Xinghuo

    2016-04-01

    Controlling dynamics of a network from any initial state to a final desired state has many applications in different disciplines from engineering to biology and social sciences. In this work, we optimize the network structure for pinning control. The problem is formulated as four optimization tasks: i) optimizing the locations of driver nodes, ii) optimizing the feedback gains, iii) optimizing simultaneously the locations of driver nodes and feedback gains, and iv) optimizing the connection weights. A newly developed population-based optimization technique (cat swarm optimization) is used as the optimization method. In order to verify the methods, we use both real-world networks, and model scale-free and small-world networks. Extensive simulation results show that the optimal placement of driver nodes significantly outperforms heuristic methods including placing drivers based on various centrality measures (degree, betweenness, closeness and clustering coefficient). The pinning controllability is further improved by optimizing the feedback gains. We also show that one can significantly improve the controllability by optimizing the connection weights.

  20. Design of an optimal snow observation network to estimate snowpack

    Science.gov (United States)

    Juan Collados Lara, Antonio; Pardo-Iguzquiza, Eulogio; Pulido-Velazquez, David

    2016-04-01

    Snow is an important water resource in many river basins that must be taken into account in hydrological modeling. Although the snow cover area may be nowadays estimated from satellite data, the snow pack thickness must be estimated from experimental data by using some interpolation procedure or hydrological models that approximates snow accumulation and fusion processes. The experimental data consist of hand probes and snow samples collected in a given number of locations that constitute the monitoring network. Assuming that there is an existing monitoring network, its optimization may imply the selection of an optimal network as a subset of the existing network (decrease of the existing network in the case that there are no funds for maintaining the full existing network) or to increase the existing network by one or more stations (optimal augmentation problem). In this work we propose a multicriterion approach for the optimal design of a snow network. These criteria include the estimation variance from a regression kriging approach for estimating thickness of the snowpack (using ground and satellite data), to minimize the total snow volume and accessibility criteria. We have also proposed a procedure to analyze the sensitivity of the results to the non-snow data deduced from the satellite information. We intent to minimize the uncertities in snowpack estimation. The methodology has been applied to estimation of the snow cover area and the design of the optimal snow observation network in Sierra Nevada mountain range in the Southern of Spain. Acknowledgments: This research has been partially supported by the GESINHIMPADAPT project (CGL2013-48424-C2-2-R) with Spanish MINECO funds. We would also like to thank ERHIN program and NASA DAAC for the data provided for this study.

  1. Online APAN IPv6 Network Monitoring

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    APAN [4] has native IPv6 network across all major APAN exchange points. It is important to validate the performance of the links in the network to ensure the link stability. This paper discusses the technique and mechanism that are used to perform online monitoring of the APAN IPv6 network status. Pchar tool is used to check the performance of the network. Metrics such as bandwidth, hop count and round trip time between nodes in each country's have been adopted for these monitoring activity.

  2. Optimal pricing of capacitated networks

    NARCIS (Netherlands)

    Grigoriev, Alexander; Loon, van Joyce; Sitters, René; Uetz, Marc

    2009-01-01

    We address the algorithmic complexity of a profit maximization problem in capacitated, undirected networks. We are asked to price a set of $m$ capacitated network links to serve a set of $n$ potential customers. Each customer is interested in purchasing a network connection that is specified by a si

  3. Topology Optimization for Urban Traffic Sensor Network

    Institute of Scientific and Technical Information of China (English)

    HU Jianming; SONG Jingyan; ZHANG Mingchen; KANG Xiaojing

    2008-01-01

    This paper presents an optimized topology for urban traffic sensor networks. Small world theory is used to improve the performance of the wireless communication system with a heterogeneous transmission model and an optimal transmission radius. Furthermore, a series of simulations based on the actual road network around the 2nd Ring Road in Beijing demonstrate the practicability of constructing artificial "small worlds". Moreover, the particle swarm optimization method is used to calculate the globally best distribution of the nodes with the large radius. The methods proposed in this paper will be helpful to the sensor nodes deployment of the new urban traffic sensor networks.

  4. IPv6 Network Mobility Route Optimization Survey

    Directory of Open Access Journals (Sweden)

    Samer S. Hassan

    2011-01-01

    Full Text Available Problem statement: This study describes that the Next Generation of Networks (NGN communication will supports multiple technologies, handles the mobility of end users to move through heterogeneous access networks, with ability to connect to different networks. Where the Internet Engineer Task Force maintain (IETF the Mobile IPv6 (MIPv6 to handles the mobility of networks (NEMO, to provide wide band and more scalable network services. One of the MIPv6 built-in features is Route Optimization (RO to solve the inefficient route problem. Conclusion/Recommendations: The main objective of this article is to survey, classify and make a compression between the available schemes for route optimization over the last years depends on the basic criteria generated from the published articles within different network topology. This article presents the problem of suboptimal route which is further increased with increasing of nesting levels and there is no such one scheme is perfect for all network environments.

  5. Airlines Network Optimization using Evolutionary Computation

    Science.gov (United States)

    Inoue, Hiroki; Kato, Yasuhiko; Sakagami, Tomoya

    In recent years, various networks have come to exist in our surroundings. Not only the internet and airline routes can be thought of as networks: protein interactions are also networks. An “economic network design problem” can be discussed by assuming that a vertex is an economic player and that a link represents some connection between economic players. In this paper, the Airlines network is taken up as an example of an “economic network design problem”, and the Airlines network which the profit of the entire Airlines industry is maximized is clarified. The Airlines network is modeled based on connections models proposed by Jackson and Wolinsky, and the utility function of the network is defined. In addition, the optimization simulation using the evolutionary computation is shown for a domestic airline in Japan.

  6. Algorithm of capacity expansion on networks optimization

    Institute of Scientific and Technical Information of China (English)

    2003-01-01

    The paper points out the relationship between the bottleneck and the minimum cutset of the network, and presents a capacity expansion algorithm of network optimization to solve the network bottleneck problem. The complexity of the algorithm is also analyzed. As required by the algorithm, some virtual sources are imported through the whole positive direction subsection in the network, in which a certain capacity value is given. Simultaneously, a corresponding capacity-expanded network is constructed to search all minimum cutsets. For a given maximum flow value of the network, the authors found an adjustment value of each minimum cutset arc's group with gradually reverse calculation and marked out the feasible flow on the capacity-extended networks again with the adjustment value increasing. All this has been done repeatedly until the original topology structure is resumed. So the algorithm can increase the capacity of networks effectively and solve the bottleneck problem of networks.

  7. Optimal Work Effort and Monitoring Cost

    Directory of Open Access Journals (Sweden)

    Tamara Todorova

    2012-12-01

    Full Text Available Using a simple job market equilibrium model we study the relationship between work effort and monitoring by firms. Some other determinants of work effort investigated include the educational level of the worker, the minimum or start-up salary as well as the economic conjuncture. As common logic dictates, optimal work effort increases with the amount of monitoring done by the employer. Quite contrary to common logic, though, we find that at the optimum employers observe and control good workers much more stringently and meticulously than poor workers. This is because under profit maximization most of the employer’s profit and surplus result from good workers and he risks losing a large amount of profit by not observing those. Managers monitor strictly more productive workers, fast learners and those starting at a higher autonomous level of monitoring, as those contribute more substantially to the firm’s profit.

  8. Wireless network topology for monitoring mobile agents

    Science.gov (United States)

    Fraser, Matthew J.; James, Daniel A.; Thiel, David V.

    2005-02-01

    A wireless network of multiple sensor nodes for monitoring large numbers of mobile agents is described and investigated. Wireless monitoring provides time critical information from a number of data sources allowing near real-time analysis of the collected data. The developed wireless network provides a moderate data rate, is able to support many wireless nodes and is a low power solution. Novel network structures have been developed to satisfy all of these requirements. This paper evaluates a number of currently available wireless communication protocols, concluding that a Bluetooth wireless network satisfies the above criteria. To support a large number of devices, topologies using inter-piconet and piconet sharing methods have been developed. These network structures are outlined in detail and have been developed with the current Bluetooth hardware limitations in mind. The proposed wireless networks have been developed to be implemented with current Bluetooth hardware. A summary of network performance is included for each developed network structure, and from these figures an appropriate network structure has been chosen that satisfies the requirements of a wireless sensor network for monitoring mobile agents.

  9. Network Monitoring as a Streaming Analytics Problem

    KAUST Repository

    Gupta, Arpit

    2016-11-02

    Programmable switches make it easier to perform flexible network monitoring queries at line rate, and scalable stream processors make it possible to fuse data streams to answer more sophisticated queries about the network in real-time. Unfortunately, processing such network monitoring queries at high traffic rates requires both the switches and the stream processors to filter the traffic iteratively and adaptively so as to extract only that traffic that is of interest to the query at hand. Others have network monitoring in the context of streaming; yet, previous work has not closed the loop in a way that allows network operators to perform streaming analytics for network monitoring applications at scale. To achieve this objective, Sonata allows operators to express a network monitoring query by considering each packet as a tuple and efficiently partitioning each query between the switches and the stream processor through iterative refinement. Sonata extracts only the traffic that pertains to each query, ensuring that the stream processor can scale traffic rates of several terabits per second. We show with a simple example query involving DNS reflection attacks and traffic traces from one of the world\\'s largest IXPs that Sonata can capture 95% of all traffic pertaining to the query, while reducing the overall data rate by a factor of about 400 and the number of required counters by four orders of magnitude. Copyright 2016 ACM.

  10. Optimal design of network distribution systems

    Directory of Open Access Journals (Sweden)

    U. Passy

    2003-12-01

    Full Text Available The problem of finding the optimal distribution of pressure drop over a network is solved via an unconstrained gradient type algorithm. The developed algorithm is computationally attractive. Problems with several hundred variables and constraints were solved.

  11. Epidemiologically optimal static networks from temporal network data

    CERN Document Server

    Holme, Petter

    2013-01-01

    Network epidemiology's most important assumption is that the contact structure over which infectious diseases propagate can be represented as a static network. However, contacts are highly dynamic, changing at many time scales. In this paper, we investigate conceptually simple methods to construct static graphs for network epidemiology from temporal contact data. We evaluate these methods on empirical and synthetic model data. For almost all our cases, the network representation that captures most relevant information is a so-called exponential-threshold network. In these, each contact contributes with a weight decreasing exponentially with time, and there is an edge between a pair of vertices if the weight between them exceeds a threshold. Networks of aggregated contacts over an optimally chosen time window perform almost as good as the exponential-threshold networks. On the other hand, networks of accumulated contacts over the entire sampling time, and networks of concurrent partnerships, perform worse. We ...

  12. Multi-core Optimization of Network Content Monitoring Class System of Innovative Applied Research%多核优化网络内容监测类系统的创新应用研究

    Institute of Scientific and Technical Information of China (English)

    周慧琴

    2014-01-01

    目前,互联网中充斥着大量不良信息,包括非法信息、色情信息和暴力信息等,这些不良信息通常以电子邮件、网页浏览、论坛发帖的形式进行传播.文章以自主研发的网络内容监测系统(IRCMS)为实例,分析了IRCMS存在的系统网络性能瓶颈问题,根据实际问题提出了一套IRCMS多核平台性能优化策略,经过实验研究发现,当有7个核心处理器同时进行计算时,网络内容监测系统的数据信息吞吐量可以达到优化之前的436.10%,真正提高了系统的网络性能.%Currently,the Internet is full of a lot of bad information,including the illegal information,pornography and violence information,bad information spread usually by e-mail,web browsing,and the form of forum posting. Independent research and development of network content monitoring system (IRCMS ) for instance, analyzed IRCMS system network performance bottlenecks. According to the practical problems,presented the IRCMS multi-core platform performance optimization strategy,the experimental study found that the data throughput of the network content monitoring system can be achieved 436. 10% as before op-timization,when seven core the processors are calculated at the same time. These improved the network performance of the system.

  13. Prototyping Web Services based Network Monitoring

    NARCIS (Netherlands)

    Drevers, Thomas; van de Meent, R.; Pras, Aiko; Harjo, J.; Moltchanov, D.; Silverajan, B.

    Web services is one of the emerging approaches in network management. This paper describes the design and implementation of four Web services based network monitoring prototypes. Each prototype follows a speci��?c approach to retrieve management data, ranging from retrieving a single management

  14. Neural Networks for Optimal Control

    DEFF Research Database (Denmark)

    Sørensen, O.

    1995-01-01

    Two neural networks are trained to act as an observer and a controller, respectively, to control a non-linear, multi-variable process.......Two neural networks are trained to act as an observer and a controller, respectively, to control a non-linear, multi-variable process....

  15. Neural Networks for Optimal Control

    DEFF Research Database (Denmark)

    Sørensen, O.

    1995-01-01

    Two neural networks are trained to act as an observer and a controller, respectively, to control a non-linear, multi-variable process.......Two neural networks are trained to act as an observer and a controller, respectively, to control a non-linear, multi-variable process....

  16. Brocade: Optimal flow placement in SDN networks

    CERN Document Server

    CERN. Geneva

    2015-01-01

    Today' network poses several challanges to network providers. These challanges fall in to a variety of areas ranging from determining efficient utilization of network bandwidth to finding out which user applications consume majority of network resources. Also, how to protect a given network from volumetric and botnet attacks. Optimal placement of flows deal with identifying network issues and addressing them in a real-time. The overall solution helps in building new services where a network is more secure and more efficient. Benefits derived as a result are increased network efficiency due to better capacity and resource planning, better security with real-time threat mitigation, and improved user experience as a result of increased service velocity.

  17. Power consumption optimization strategy for wireless networks

    DEFF Research Database (Denmark)

    Cornean, Horia; Kumar, Sanjay; Marchetti, Nicola

    2011-01-01

    in order to reduce the total power consumption in a multi cellular network. We present an algorithm for power optimization under no interference and in presence of interference conditions, targeting to maximize the network capacity. The convergence of the algorithm is guaranteed if the interference...

  18. Optical Network Optimization(Invited Paper)

    Institute of Scientific and Technical Information of China (English)

    Kwok-wai; Cheung; Michael; K.S.; Ho

    2003-01-01

    A novel low-complexity framework for designing survivable optical mesh networks with undetermined topology is presented. By jointly optimizing the topology planning, working- and spare-capacity planning, a cost saving of over 40% can be achieved for a national-scale network with 31 nodes.

  19. EMMNet: sensor networking for electricity meter monitoring.

    Science.gov (United States)

    Lin, Zhi-Ting; Zheng, Jie; Ji, Yu-Sheng; Zhao, Bao-Hua; Qu, Yu-Gui; Huang, Xu-Dong; Jiang, Xiu-Fang

    2010-01-01

    Smart sensors are emerging as a promising technology for a large number of application domains. This paper presents a collection of requirements and guidelines that serve as a basis for a general smart sensor architecture to monitor electricity meters. It also presents an electricity meter monitoring network, named EMMNet, comprised of data collectors, data concentrators, hand-held devices, a centralized server, and clients. EMMNet provides long-distance communication capabilities, which make it suitable suitable for complex urban environments. In addition, the operational cost of EMMNet is low, compared with other existing remote meter monitoring systems based on GPRS. A new dynamic tree protocol based on the application requirements which can significantly improve the reliability of the network is also proposed. We are currently conducting tests on five networks and investigating network problems for further improvements. Evaluation results indicate that EMMNet enhances the efficiency and accuracy in the reading, recording, and calibration of electricity meters.

  20. Modeling, Optimization & Control of Hydraulic Networks

    DEFF Research Database (Denmark)

    Tahavori, Maryamsadat

    2014-01-01

    to check if the network is controllable. Afterward the pressure control problem in water supply systems is formulated as an optimal control problem. The goal is to minimize the power consumption in pumps and also to regulate the pressure drop at the end-users to a desired value. The formulated optimal...... in water network is pressure management. By reducing the pressure in the water network, the leakage can be reduced significantly. Also it reduces the amount of energy consumption in water networks. The primary purpose of this work is to develop control algorithms for pressure control in water supply...... systems. To have better understanding of water leakage, to control pressure and leakage effectively and for optimal design of water supply system, suitable modeling is an important prerequisite. Therefore a model with the main objective of pressure control and consequently leakage reduction is presented...

  1. Wireless Sensor Network for Wearable Physiological Monitoring

    Directory of Open Access Journals (Sweden)

    P. S. Pandian

    2008-05-01

    Full Text Available Wearable physiological monitoring system consists of an array of sensors embedded into the fabric of the wearer to continuously monitor the physiological parameters and transmit wireless to a remote monitoring station. At the remote monitoring station the data is correlated to study the overall health status of the wearer. In the conventional wearable physiological monitoring system, the sensors are integrated at specific locations on the vest and are interconnected to the wearable data acquisition hardware by wires woven into the fabric. The drawbacks associated with these systems are the cables woven in the fabric pickup noise such as power line interference and signals from nearby radiating sources and thereby corrupting the physiological signals. Also repositioning the sensors in the fabric is difficult once integrated. The problems can be overcome by the use of physiological sensors with miniaturized electronics to condition, process, digitize and wireless transmission integrated into the single module. These sensors are strategically placed at various locations on the vest. Number of sensors integrated into the fabric form a network (Personal Area Network and interacts with the human system to acquire and transmit the physiological data to a wearable data acquisition system. The wearable data acquisition hardware collects the data from various sensors and transmits the processed data to the remote monitoring station. The paper discusses wireless sensor network and its application to wearable physiological monitoring and its applications. Also the problems associated with conventional wearable physiological monitoring are discussed.

  2. Neural networks optimally trained with noisy data

    Science.gov (United States)

    Wong, K. Y. Michael; Sherrington, David

    1993-06-01

    We study the retrieval behaviors of neural networks which are trained to optimize their performance for an ensemble of noisy example patterns. In particular, we consider (1) the performance overlap, which reflects the performance of the network in an operating condition identical to the training condition; (2) the storage overlap, which reflects the ability of the network to merely memorize the stored information; (3) the attractor overlap, which reflects the precision of retrieval for dilute feedback networks; and (4) the boundary overlap, which defines the boundary of the basin of attraction, and hence the associative ability for dilute feedback networks. We find that for sufficiently low training noise, the network optimizes its overall performance by sacrificing the individual performance of a minority of patterns, resulting in a two-band distribution of the aligning fields. For a narrow range of storage level, the network loses and then regains its retrieval capability when the training noise level increases, and we interpret that this reentrant retrieval behavior is related to competing tendencies in structuring the basins of attraction for the stored patterns. Reentrant behavior is also observed in the space of synaptic interactions, in which the replica symmetric solution of the optimal network destabilizes and then restabilizes when the training noise level increases. We summarize these observations by picturing training noises as an instrument for widening the basins of attractions of the stored patterns at the expense of reducing the precision of retrieval.

  3. Optimal pinning controllability of complex networks: dependence on network structure.

    Science.gov (United States)

    Jalili, Mahdi; Askari Sichani, Omid; Yu, Xinghuo

    2015-01-01

    Controlling networked structures has many applications in science and engineering. In this paper, we consider the problem of pinning control (pinning the dynamics into the reference state), and optimally placing the driver nodes, i.e., the nodes to which the control signal is fed. Considering the local controllability concept, a metric based on the eigenvalues of the Laplacian matrix is taken into account as a measure of controllability. We show that the proposed optimal placement strategy considerably outperforms heuristic methods including choosing hub nodes with high degree or betweenness centrality as drivers. We also study properties of optimal drivers in terms of various centrality measures including degree, betweenness, closeness, and clustering coefficient. The profile of these centrality values depends on the network structure. For homogeneous networks such as random small-world networks, the optimal driver nodes have almost the mean centrality value of the population (much lower than the centrality value of hub nodes), whereas the centrality value of optimal drivers in heterogeneous networks such as scale-free ones is much higher than the average and close to that of hub nodes. However, as the degree of heterogeneity decreases in such networks, the profile of centrality approaches the population mean.

  4. Optimization of Sensor Monitoring Strategies for Emissions

    Science.gov (United States)

    Klise, K. A.; Laird, C. D.; Downey, N.; Baker Hebert, L.; Blewitt, D.; Smith, G. R.

    2016-12-01

    Continuous or regularly scheduled monitoring has the potential to quickly identify changes in air quality. However, even with low-cost sensors, only a limited number of sensors can be placed to monitor airborne pollutants. The physical placement of these sensors and the sensor technology used can have a large impact on the performance of a monitoring strategy. Furthermore, sensors can be placed for different objectives, including maximum coverage, minimum time to detection or exposure, or to quantify emissions. Different objectives may require different monitoring strategies, which need to be evaluated by stakeholders before sensors are placed in the field. In this presentation, we outline methods to enhance ambient detection programs through optimal design of the monitoring strategy. These methods integrate atmospheric transport models with sensor characteristics, including fixed and mobile sensors, sensor cost and failure rate. The methods use site specific pre-computed scenarios which capture differences in meteorology, terrain, concentration averaging times, gas concentration, and emission characteristics. The pre-computed scenarios become input to a mixed-integer, stochastic programming problem that solves for sensor locations and types that maximize the effectiveness of the detection program. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.

  5. Wireless Sensor Network for Electric Transmission Line Monitoring

    Energy Technology Data Exchange (ETDEWEB)

    Alphenaar, Bruce

    2009-06-30

    Generally, federal agencies tasked to oversee power grid reliability are dependent on data from grid infrastructure owners and operators in order to obtain a basic level of situational awareness. Since there are many owners and operators involved in the day-to-day functioning of the power grid, the task of accessing, aggregating and analyzing grid information from these sources is not a trivial one. Seemingly basic tasks such as synchronizing data timestamps between many different data providers and sources can be difficult as evidenced during the post-event analysis of the August 2003 blackout. In this project we investigate the efficacy and cost effectiveness of deploying a network of wireless power line monitoring devices as a method of independently monitoring key parts of the power grid as a complement to the data which is currently available to federal agencies from grid system operators. Such a network is modeled on proprietary power line monitoring technologies and networks invented, developed and deployed by Genscape, a Louisville, Kentucky based real-time energy information provider. Genscape measures transmission line power flow using measurements of electromagnetic fields under overhead high voltage transmission power lines in the United States and Europe. Opportunities for optimization of the commercial power line monitoring technology were investigated in this project to enable lower power consumption, lower cost and improvements to measurement methodologies. These optimizations were performed in order to better enable the use of wireless transmission line monitors in large network deployments (perhaps covering several thousand power lines) for federal situational awareness needs. Power consumption and cost reduction were addressed by developing a power line monitor using a low power, low cost wireless telemetry platform known as the ''Mote''. Motes were first developed as smart sensor nodes in wireless mesh networking applications

  6. A Great Lakes atmospheric mercury monitoring network: evaluation and design

    Science.gov (United States)

    Risch, Martin R.; Kenski, Donna M.; ,; David, A.

    2014-01-01

    As many as 51 mercury (Hg) wet-deposition-monitoring sites from 4 networks were operated in 8 USA states and Ontario, Canada in the North American Great Lakes Region from 1996 to 2010. By 2013, 20 of those sites were no longer in operation and approximately half the geographic area of the Region was represented by a single Hg-monitoring site. In response, a Great Lakes Atmospheric Mercury Monitoring (GLAMM) network is needed as a framework for regional collaboration in Hg-deposition monitoring. The purpose of the GLAMM network is to detect changes in regional atmospheric Hg deposition related to changes in Hg emissions. An optimized design for the network was determined to be a minimum of 21 sites in a representative and approximately uniform geographic distribution. A majority of the active and historic Hg-monitoring sites in the Great Lakes Region are part of the National Atmospheric Deposition Program (NADP) Mercury Deposition Network (MDN) in North America and the GLAMM network is planned to be part of the MDN. To determine an optimized network design, active and historic Hg-monitoring sites in the Great Lakes Region were evaluated with a rating system of 21 factors that included characteristics of the monitoring locations and interpretations of Hg data. Monitoring sites were rated according to the number of Hg emissions sources and annual Hg emissions in a geographic polygon centered on each site. Hg-monitoring data from the sites were analyzed for long-term averages in weekly Hg concentrations in precipitation and weekly Hg-wet deposition, and on significant temporal trends in Hg concentrations and Hg deposition. A cluster analysis method was used to group sites with similar variability in their Hg data in order to identify sites that were unique for explaining Hg data variability in the Region. The network design included locations in protected natural areas, urban areas, Great Lakes watersheds, and in proximity to areas with a high density of annual Hg

  7. Network Structure Expert System and Operation Optimization

    Institute of Scientific and Technical Information of China (English)

    刘洪谦; 袁希钢; 麻德贤

    2003-01-01

    It is proposed that double level programming technique may be adopted in synthesis strategy. Optimization of heat exchanger network structural configuration (the master problem) may be solved at the upper level, leaving the rest operating conditions( the slave problem) being optimized at the lower level. With the uniqueness in mind, an HEN synthesis expert system may be employed to address both the logical constraints and the global operation parameters′ optimization using enhanced sequential number optimization theory.Case studies demonstrate that the synthesis strategy proposed can effectively simplify both the problem-solving and the synthesis process. The validity of the strategy recommended is evidenced by case studies′ results compared.

  8. Monitoring air quality in mountains: Designing an effective network

    Science.gov (United States)

    Peterson, D.L.

    2000-01-01

    A quantitatively robust yet parsimonious air-quality monitoring network in mountainous regions requires special attention to relevant spatial and temporal scales of measurement and inference. The design of monitoring networks should focus on the objectives required by public agencies, namely: 1) determine if some threshold has been exceeded (e.g., for regulatory purposes), and 2) identify spatial patterns and temporal trends (e.g., to protect natural resources). A short-term, multi-scale assessment to quantify spatial variability in air quality is a valuable asset in designing a network, in conjunction with an evaluation of existing data and simulation-model output. A recent assessment in Washington state (USA) quantified spatial variability in tropospheric ozone distribution ranging from a single watershed to the western third of the state. Spatial and temporal coherence in ozone exposure modified by predictable elevational relationships ( 1.3 ppbv ozone per 100 m elevation gain) extends from urban areas to the crest of the Cascade Range. This suggests that a sparse network of permanent analyzers is sufficient at all spatial scales, with the option of periodic intensive measurements to validate network design. It is imperative that agencies cooperate in the design of monitoring networks in mountainous regions to optimize data collection and financial efficiencies.

  9. Optical Networks for Cost Monitoring and Reduction

    Directory of Open Access Journals (Sweden)

    R Buvanesvari

    2011-03-01

    Full Text Available This paper focuses on cost reduction and monitoring in optical networks. Optical mesh networks are cost savings with switching systems that are interconnected by point-to-point networks. Transponders play a major role in it. All-optical packet switching has been intensively investigated in recent years as an alternative to static, cross connect based networks. Several switch architectures have been proposed, all of them using buffers made of fiber delay lines. We consider the problem of minimizing the congestion in wireless optical (FSO backbone networks by placing controllable relay nodes. We propose algorithms for placement of relays in the network under node interface constraints. Further reduction in cost is done by the conversion of optical to electrical at the intermediate nodes. Optical transport networks offer a new level of flexibility in the optical layer allowing various services and thereby improving the efficiency, performance and robustness. An optical path with a transparent feature allows the transmission of signals that are optical and also independent of data rate and modulation format. Client layer protocol provides transparency for the transport layer in optical networks. Thus there is a significant challenge in terms of function, flexibility and monitoring cost.

  10. Integrated System for Performance Monitoring of ATLAS TDAQ Network

    CERN Document Server

    Savu, D; The ATLAS collaboration; Martin, B; Sjoen, R; Batraneanu, S; Stancu, S

    2010-01-01

    The ATLAS TDAQ Network consists of three separate networks spanning four levels of the experimental building. Over 200 edge switches and 5 multi-blade chassis routers are used to interconnect 2000 processors, adding up to more than 7000 high speed interfaces. In order to substantially speed-up ad-hoc and post mortem analysis, a scalable, yet flexible, integrated system for monitoring both network statistics and environmental conditions, processor parameters and data taking characteristics was required. For successful up-to-the-minute monitoring, information from many SNMP compliant devices, independent databases and custom APIs was gathered, stored and displayed in an optimal way. Easy navigation and compact aggregation of multiple data sources were the main requirements; characteristics not found in any of the tested products, either open-source or commercial. This paper describes how performance, scalability and display issues were addressed and what challenges the project faced during development and deplo...

  11. IPv6-Based Smart Metering Network for Monitoring Building Electricity

    Directory of Open Access Journals (Sweden)

    Dong Xu

    2013-01-01

    Full Text Available A smart electricity monitoring system of building is presented using ZigBee and internet to establish the network. This system consists of three hardware layers: the host PC, the router, and the sensor nodes. A hierarchical ant colony algorithm is developed for data transmission among the wireless sensor nodes. The wireless communication protocol is also designed based on IPv6 protocol on IEEE 802.15.4 wireless network. All-IP approach and peer-to-peer mode are integrated to optimize the network building. Each node measures the power, current, and voltage and transmits them to the host PC through the router. The host software is designed for building test characteristics, having a tree hierarchy and a friendly interface for the user. The reliability and accuracy of this monitoring system are verified in the experiment and application.

  12. Phase transitions in Pareto optimal complex networks

    CERN Document Server

    Seoane, Luís F

    2015-01-01

    The organization of interactions in complex systems can be described by networks connecting different units. These graphs are useful representations of the local and global complexity of the underlying systems. The origin of their topological structure can be diverse, resulting from different mechanisms including multiplicative processes and optimization. In spatial networks or in graphs where cost constraints are at work, as it occurs in a plethora of situations from power grids to the wiring of neurons in the brain, optimization plays an important part in shaping their organization. In this paper we study network designs resulting from a Pareto optimization process, where different simultaneous constraints are the targets of selection. We analyze three variations on a problem finding phase transitions of different kinds. Distinct phases are associated to different arrangements of the connections; but the need of drastic topological changes does not determine the presence, nor the nature of the phase transit...

  13. Simultaneous optimization of transit network and public bicycle station network

    Institute of Scientific and Technical Information of China (English)

    刘洋; 朱宁; 马寿峰

    2015-01-01

    The traditional manner to design public transportation system is to sequentially design the transit network and public bicycle network. A new public transportation system design problem that simultaneously considers both bus network design and public bicycle network design is proposed. The chemical reaction optimization (CRO) is designed to solve the problem. A shortcoming of CRO is that, when the two-molecule collisions take place, the molecules are randomly picked from the container. Hence, we improve CRO by employing different mating strategies. The computational results confirm the benefits of the mating strategies. Numerical experiments are conducted on the Sioux-Falls network. A comparison with the traditional sequential modeling framework indicates that the proposed approach has a better performance and is more robust. The practical applicability of the approach is proved by employing a real size network.

  14. Optimizing the next generation optical access networks

    DEFF Research Database (Denmark)

    Amaya Fernández, Ferney Orlando; Soto, Ana Cardenas; Tafur Monroy, Idelfonso

    2009-01-01

    of the optical amplification in the performance of the standardized PON is presented comparing the performance of the EDFA (Erbium Doped Fiber Amplifier) and the distributed Raman amplification. The effect of the Raman amplification in extending the reach of the NG-OAN is analyzed and some requirements......Several issues in the design and optimization of the next generation optical access network (NG-OAN) are presented. The noise, the distortion and the fiber optic nonlinearities are considered to optimize the video distribution link in a passive optical network (PON). A discussion of the effect...

  15. Hydrogeological modeling for improving groundwater monitoring network and strategies

    Science.gov (United States)

    Thakur, Jay Krishna

    2016-09-01

    The research aimed to investigate a new approach for spatiotemporal groundwater monitoring network optimization using hydrogeological modeling to improve monitoring strategies. Unmonitored concentrations were incorporated at different potential monitoring locations into the groundwater monitoring optimization method. The proposed method was applied in the contaminated megasite, Bitterfeld/Wolfen, Germany. Based on an existing 3-D geological model, 3-D groundwater flow was obtained from flow velocity simulation using initial and boundary conditions. The 3-D groundwater transport model was used to simulate transport of α-HCH with an initial ideal concentration of 100 mg/L injected at various hydrogeological layers in the model. Particle tracking for contaminant and groundwater flow velocity realizations were made. The spatial optimization result suggested that 30 out of 462 wells in the Quaternary aquifer (6.49 %) and 14 out of 357 wells in the Tertiary aquifer (3.92 %) were redundant. With a gradual increase in the width of the particle track path line, from 0 to 100 m, the number of redundant wells remarkably increased, in both aquifers. The results of temporal optimization showed different sampling frequencies for monitoring wells. The groundwater and contaminant flow direction resulting from particle tracks obtained from hydrogeological modeling was verified by the variogram modeling through α-HCH data from 2003 to 2009. Groundwater monitoring strategies can be substantially improved by removing the existing spatio-temporal redundancy as well as incorporating unmonitored network along with sampling at recommended interval of time. However, the use of this model-based method is only recommended in the areas along with site-specific experts' knowledge.

  16. Utility Optimal Scheduling in Processing Networks

    CERN Document Server

    Huang, Longbo

    2010-01-01

    We consider the problem of utility optimal scheduling in general \\emph{processing networks} with random arrivals and network conditions. These are generalizations of traditional data networks where commodities in one or more queues can be combined to produce new commodities that are delivered to other parts of the network. This can be used to model problems such as in-network data fusion, stream processing, and grid computing. Scheduling actions are complicated by the \\emph{underflow problem} that arises when some queues with required components go empty. In this paper, we develop the Perturbed Max-Weight algorithm (PMW) to achieve optimal utility. The idea of PMW is to perturb the weights used by the usual Max-Weight algorithm to ``push'' queue levels towards non-zero values (avoiding underflows). We show that when the perturbations are carefully chosen, PMW is able to achieve a utility that is within $O(1/V)$ of the optimal value for any $V\\geq1$, while ensuring an average network backlog of $O(V)$.

  17. Flow networks analysis and optimization of repairable flow networks, networks with disturbed flows, static flow networks and reliability networks

    CERN Document Server

    Todinov, Michael T

    2013-01-01

    Repairable flow networks are a new area of research, which analyzes the repair and flow disruption caused by failures of components in static flow networks. This book addresses a gap in current network research by developing the theory, algorithms and applications related to repairable flow networks and networks with disturbed flows. The theoretical results presented in the book lay the foundations of a new generation of ultra-fast algorithms for optimizing the flow in networks after failures or congestion, and the high computational speed creates the powerful possibility of optimal control

  18. BABY MONITORING SYSTEM USING WIRELESS SENSOR NETWORKS

    Directory of Open Access Journals (Sweden)

    G. Rajesh

    2014-09-01

    Full Text Available Sudden Infant Death Syndrome (SIDS is marked by the sudden death of an infant during sleep that is not predicted by the medical history and remains unexplained even after thorough forensic autopsy and detailed death investigation. In this we developed a system that provides solutions for the above problems by making the crib smart using the wireless sensor networks (WSN and smart phones. The system provides visual monitoring service through live video, alert services by crib fencing and awakens alert, monitoring services by temperature reading and light intensity reading, vaccine reminder and weight monitoring.

  19. Gamma-radiation monitoring network at sea

    Energy Technology Data Exchange (ETDEWEB)

    Wedekind, Ch.; Schilling, G.; Gruettmueller, M.; Becker, K

    1999-04-01

    A stationary monitoring network to observe the sea for radioactive contaminations, using a newly constructed NaI-detector system, is described. The monitoring efficiency for total-{gamma} counting and {gamma}-spectrometry as well as a method suppressing the registration of natural radioactivity are discussed. On the basis of three accident scenarios with releases of radioactivity into the sea it is demonstrated that under sea conditions the limit of detection of this 'in situ' method is comparable to the regularly performed monitoring by radiochemical {sup 137}Cs analysis of seawater samples.

  20. Wireless sensor networks and ecological monitoring

    CERN Document Server

    Jiang, Joe-Air

    2013-01-01

    This book presents the state of the art technologies and solutions to tackle the critical challenges faced by the building and development of the WSN and ecological monitoring system but also potential impact on society at social, medical and technological level. This book is dedicated to Sensing systems for Sensors, Wireless Sensor Networks and Ecological Monitoring. The book aims at Master and PhD degree students, researchers, practitioners, especially WSN engineers involved with ecological monitoring. The book will provide an opportunity of a dedicated and a deep approach in order to improve their knowledge in this specific field.  

  1. Entropy-Based Approach to Remove Redundant Monitoring Wells from Regional-Scale Groundwater Network

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    An entropy-based approach is applied to identify redundant wells in the network. In the process of this research, groundwater-monitoring network is considered as a communication system with a capability to transfer information, and monitoring wells are taken as information receivers. The concepts of entropy and mutual information are then applied to measure the information content of individual monitoring well and information relationship between monitoring well pairs. The efficiency of information transfer among monitoring wells is the basis to judge the redundancy in the network. And the capacity of the monitoring wells to provide information on groundwater is the point of evaluation to identify redundant monitoring wells. This approach is demonstrated using the data from a regional-scale groundwater network in Hebei plain, China. The result shows that the entropy-based method is recommendable in optimizing groundwater networks, especially for those within media of higher heterogeneities and anisotropies.

  2. OPTIMAL WELL LOCATOR (OWL): A SCREENING TOOL FOR EVALUATING LOCATIONS OF MONITORING WELLS

    Science.gov (United States)

    The Optimal Well Locator ( OWL) program was designed and developed by USEPA to be a screening tool to evaluate and optimize the placement of wells in long term monitoring networks at small sites. The first objective of the OWL program is to allow the user to visualize the change ...

  3. Use Alkalinity Monitoring to Optimize Bioreactor Performance.

    Science.gov (United States)

    Jones, Christopher S; Kult, Keegan J

    2016-05-01

    In recent years, the agricultural community has reduced flow of nitrogen from farmed landscapes to stream networks through the use of woodchip denitrification bioreactors. Although deployment of this practice is becoming more common to treat high-nitrate water from agricultural drainage pipes, information about bioreactor management strategies is sparse. This study focuses on the use of water monitoring, and especially the use of alkalinity monitoring, in five Iowa woodchip bioreactors to provide insights into and to help manage bioreactor chemistry in ways that will produce desirable outcomes. Results reported here for the five bioreactors show average annual nitrate load reductions between 50 and 80%, which is acceptable according to established practice standards. Alkalinity data, however, imply that nitrous oxide formation may have regularly occurred in at least three of the bioreactors that are considered to be closed systems. Nitrous oxide measurements of influent and effluent water provide evidence that alkalinity may be an important indicator of bioreactor performance. Bioreactor chemistry can be managed by manipulation of water throughput in ways that produce adequate nitrate removal while preventing undesirable side effects. We conclude that (i) water should be retained for longer periods of time in bioreactors where nitrous oxide formation is indicated, (ii) measuring only nitrate and sulfate concentrations is insufficient for proper bioreactor operation, and (iii) alkalinity monitoring should be implemented into protocols for bioreactor management.

  4. WiMax network planning and optimization

    CERN Document Server

    Zhang, Yan

    2009-01-01

    This book offers a comprehensive explanation on how to dimension, plan, and optimize WiMAX networks. The first part of the text introduces WiMAX networks architecture, physical layer, standard, protocols, security mechanisms, and highly related radio access technologies. It covers system framework, topology, capacity, mobility management, handoff management, congestion control, medium access control (MAC), scheduling, Quality of Service (QoS), and WiMAX mesh networks and security. Enabling easy understanding of key concepts and technologies, the second part presents practical examples and illu

  5. Assessment of SRS ambient air monitoring network

    Energy Technology Data Exchange (ETDEWEB)

    Abbott, K. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL); Jannik, T. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL)

    2016-08-03

    Three methodologies have been used to assess the effectiveness of the existing ambient air monitoring system in place at the Savannah River Site in Aiken, SC. Effectiveness was measured using two metrics that have been utilized in previous quantification of air-monitoring network performance; frequency of detection (a measurement of how frequently a minimum number of samplers within the network detect an event), and network intensity (a measurement of how consistent each sampler within the network is at detecting events). In addition to determining the effectiveness of the current system, the objective of performing this assessment was to determine what, if any, changes could make the system more effective. Methodologies included 1) the Waite method of determining sampler distribution, 2) the CAP88- PC annual dose model, and 3) a puff/plume transport model used to predict air concentrations at sampler locations. Data collected from air samplers at SRS in 2015 compared with predicted data resulting from the methodologies determined that the frequency of detection for the current system is 79.2% with sampler efficiencies ranging from 5% to 45%, and a mean network intensity of 21.5%. One of the air monitoring stations had an efficiency of less than 10%, and detected releases during just one sampling period of the entire year, adding little to the overall network intensity. By moving or removing this sampler, the mean network intensity increased to about 23%. Further work in increasing the network intensity and simulating accident scenarios to further test the ambient air system at SRS is planned

  6. Operation of International Monitoring System Network

    Science.gov (United States)

    Nikolova, Svetlana; Araujo, Fernando; Aktas, Kadircan; Malakhova, Marina; Otsuka, Riyo; Han, Dongmei; Assef, Thierry; Nava, Elisabetta; Mickevicius, Sigitas; Agrebi, Abdelouaheb

    2015-04-01

    The IMS is a globally distributed network of monitoring facilities using sensors from four technologies: seismic, hydroacoustic, infrasound and radionuclide. It is designed to detect the seismic and acoustic waves produced by nuclear test explosions and the subsequently released radioactive isotopes. Monitoring stations transmit their data to the IDC in Vienna, Austria, over a global private network known as the GCI. Since 2013, the data availability (DA) requirements for IMS stations account for quality of the data, meaning that in calculation of data availability data should be exclude if: - there is no input from sensor (SHI technology); - the signal consists of constant values (SHI technology); Even more strict are requirements for the DA of the radionuclide (particulate and noble gas) stations - received data have to be analyzed, reviewed and categorized by IDC analysts. In order to satisfy the strict data and network availability requirements of the IMS Network, the operation of the facilities and the GCI are managed by IDC Operations. Operations has following main functions: - to ensure proper operation and functioning of the stations; - to ensure proper operation and functioning of the GCI; - to ensure efficient management of the stations in IDC; - to provide network oversight and incident management. At the core of the IMS Network operations are a series of tools for: monitoring the stations' state of health and data quality, troubleshooting incidents, communicating with internal and external stakeholders, and reporting. The new requirements for data availability increased the importance of the raw data quality monitoring. This task is addressed by development of additional tools for easy and fast identifying problems in data acquisition, regular activities to check compliance of the station parameters with acquired data by scheduled calibration of the seismic network, review of the samples by certified radionuclide laboratories. The DA for the networks of

  7. Value of monitoring in road network management

    NARCIS (Netherlands)

    Zouch, M.; Courage, W.; Napoles-Morales, O.

    2014-01-01

    We present a framework for road network management to assist road authorities in maintenance budget estimations and long-term maintenance strategies definition. Information about road conditions is obtained from monitoring. Available data are used to estimate and update prediction of degradation evo

  8. Optimal transport on supply-demand networks.

    Science.gov (United States)

    Chen, Yu-Han; Wang, Bing-Hong; Zhao, Li-Chao; Zhou, Changsong; Zhou, Tao

    2010-06-01

    In the literature, transport networks are usually treated as homogeneous networks, that is, every node has the same function, simultaneously providing and requiring resources. However, some real networks, such as power grids and supply chain networks, show a far different scenario in which nodes are classified into two categories: supply nodes provide some kinds of services, while demand nodes require them. In this paper, we propose a general transport model for these supply-demand networks, associated with a criterion to quantify their transport capacities. In a supply-demand network with heterogeneous degree distribution, its transport capacity strongly depends on the locations of supply nodes. We therefore design a simulated annealing algorithm to find the near optimal configuration of supply nodes, which remarkably enhances the transport capacity compared with a random configuration and outperforms the degree target algorithm, the betweenness target algorithm, and the greedy method. This work provides a start point for systematically analyzing and optimizing transport dynamics on supply-demand networks.

  9. Optimal Sensor Networks Scheduling in Identification of Distributed Parameter Systems

    CERN Document Server

    Patan, Maciej

    2012-01-01

    Sensor networks have recently come into prominence because they hold the potential to revolutionize a wide spectrum of both civilian and military applications. An ingenious characteristic of sensor networks is the distributed nature of data acquisition. Therefore they seem to be ideally prepared for the task of monitoring processes with spatio-temporal dynamics which constitute one of most general and important classes of systems in modelling of the real-world phenomena. It is clear that careful deployment and activation of sensor nodes are critical for collecting the most valuable information from the observed environment. Optimal Sensor Network Scheduling in Identification of Distributed Parameter Systems discusses the characteristic features of the sensor scheduling problem, analyzes classical and recent approaches, and proposes a wide range of original solutions, especially dedicated for networks with mobile and scanning nodes. Both researchers and practitioners will find the case studies, the proposed al...

  10. Optimizations for High Performance Network Virtualization

    Institute of Scientific and Technical Information of China (English)

    Fan-Fu Zhou; Ru-Hui Ma; Jian Li; Li-Xia Chen; Wei-Dong Qiu; Hai-Bing Guan

    2016-01-01

    The increasing requirements of intensive interoperaterbility among the distributed nodes desiderate the high performance network connections, owing to the substantial growth of cloud computing and datacenters. Network I/O virtualization aggregates the network resource and separates it into manageable parts for particular servers or devices, which provides effective consolidation and elastic management with high agility, flexibility and scalability as well as reduced cost and cabling. However, both network I/O virtualization aggregation and the increasing network speed incur higher traffic density, which generates a heavy system stress for I/O data moving and I/O event processing. Consequently, many researchers have dedicated to enhancing the system performance and alleviating the system overhead for high performance networking virtualization. This paper first elaborates the mainstreaming I/O virtualization methodologies, including device emulation, split-driver model and hardware assisted model. Then, the paper discusses and compares their specific advantages in addition to performance bottlenecks in practical utilities. This paper mainly focuses on the comprehensive survey of state-of-the-art approaches for performance optimizations and improvements as well as the portability management for network I/O virtualization. The approaches include various novel data delivery schemes, overhead mitigations for interrupt processing and adequate resource allocations for dynamic network states. Finally, we highlight the diversity of I/O virtualization besides the performance improvements in network virtualization infrastructure.

  11. Network inference via adaptive optimal design

    Directory of Open Access Journals (Sweden)

    Stigter Johannes D

    2012-09-01

    Full Text Available Abstract Background Current research in network reverse engineering for genetic or metabolic networks very often does not include a proper experimental and/or input design. In this paper we address this issue in more detail and suggest a method that includes an iterative design of experiments based, on the most recent data that become available. The presented approach allows a reliable reconstruction of the network and addresses an important issue, i.e., the analysis and the propagation of uncertainties as they exist in both the data and in our own knowledge. These two types of uncertainties have their immediate ramifications for the uncertainties in the parameter estimates and, hence, are taken into account from the very beginning of our experimental design. Findings The method is demonstrated for two small networks that include a genetic network for mRNA synthesis and degradation and an oscillatory network describing a molecular network underlying adenosine 3’-5’ cyclic monophosphate (cAMP as observed in populations of Dyctyostelium cells. In both cases a substantial reduction in parameter uncertainty was observed. Extension to larger scale networks is possible but needs a more rigorous parameter estimation algorithm that includes sparsity as a constraint in the optimization procedure. Conclusion We conclude that a careful experiment design very often (but not always pays off in terms of reliability in the inferred network topology. For large scale networks a better parameter estimation algorithm is required that includes sparsity as an additional constraint. These algorithms are available in the literature and can also be used in an adaptive optimal design setting as demonstrated in this paper.

  12. Smart Sensor Network System For Environment Monitoring

    Directory of Open Access Journals (Sweden)

    Javed Ali Baloch

    2012-07-01

    Full Text Available SSN (Smart Sensor Network systems could be used to monitor buildings with modern infrastructure, plant sites with chemical pollution, horticulture, natural habitat, wastewater management and modern transport system. To sense attributes of phenomena and make decisions on the basis of the sensed value is the primary goal of such systems. In this paper a Smart Spatially aware sensor system is presented. A smart system, which could continuously monitor the network to observe the functionality and trigger, alerts to the base station if a change in the system occurs and provide feedback periodically, on demand or even continuously depending on the nature of the application. The results of the simulation trials presented in this paper exhibit the performance of a Smart Spatially Aware Sensor Networks.

  13. Fair Optimization and Networks: A Survey

    Directory of Open Access Journals (Sweden)

    Wlodzimierz Ogryczak

    2014-01-01

    Full Text Available Optimization models related to designing and operating complex systems are mainly focused on some efficiency metrics such as response time, queue length, throughput, and cost. However, in systems which serve many entities there is also a need for respecting fairness: each system entity ought to be provided with an adequate share of the system’s services. Still, due to system operations-dependant constraints, fair treatment of the entities does not directly imply that each of them is assigned equal amount of the services. That leads to concepts of fair optimization expressed by the equitable models that represent inequality averse optimization rather than strict inequality minimization; a particular widely applied example of that concept is the so-called lexicographic maximin optimization (max-min fairness. The fair optimization methodology delivers a variety of techniques to generate fair and efficient solutions. This paper reviews fair optimization models and methods applied to systems that are based on some kind of network of connections and dependencies, especially, fair optimization methods for the location problems and for the resource allocation problems in communication networks.

  14. Modular Subsea Monitoring Network (MSM) - Realizing Integrated Environmental Monitoring Solutions

    Science.gov (United States)

    Mosch, Thomas; Fietzek, Peer

    2016-04-01

    In a variety of scientific and industrial application areas, ranging i.e. from the supervision of hydrate fields over the detection and localization of fugitive emissions from subsea oil and gas production to fish farming, fixed point observatories are useful and applied means. They monitor the water column and/or are placed at the sea floor over long periods of time. They are essential oceanographic platforms for providing valuable long-term time series data and multi-parameter measurements. Various mooring and observatory endeavors world-wide contribute valuable data needed for understanding our planet's ocean systems and biogeochemical processes. Continuously powered cabled observatories enable real-time data transmission from spots of interest close to the shore or to ocean infrastructures. Independent of the design of the observatories they all rely on sensors which demands for regular maintenance. This work is in most cases associated with cost-intensive maintenance on a regular time basis for the entire sensor carrying fixed platform. It is mandatory to encounter this asset for long-term monitoring by enhancing hardware efficiency. On the basis of two examples of use from the area of hydrate monitoring (off Norway and Japan) we will present the concept of the Modular Subsea Monitoring Network (MSM). The modular, scalable and networking capabilities of the MSM allow for an easy adaptation to different monitoring tasks. Providing intelligent power management, combining chemical and acoustical sensors, adaptation of the payload according to the monitoring tasks, autonomous powering, modular design for easy transportation, storage and mobilization, Vessel of Opportunity-borne launching and recovery capability with a video-guided launcher system and a rope recovery system are key facts addressed during the development of the MSM. Step by step the MSM concept applied to the observatory hardware will also be extended towards the gathered data to maximize the

  15. Optimal Network Design for Consensus Formation: Wisdom of Networked Agents

    Directory of Open Access Journals (Sweden)

    Eugene S. Kitamura

    2014-08-01

    Full Text Available The wisdom of crowds refers to the phenomenon in which the collective knowledge of a community is greater than the knowledge of any individual. This paper proposes a network design for the fastest and slowest consensus formation under average node degree restrictions, which is one aspect of the wisdom of crowds concept. Consensus and synchronization problems are closely related to variety of issues such as collective behavior in nature, the interaction among agents as a matter of the robot control, and building efficient wireless sensor networks. However, designing networks with desirable properties is complex and it may pose a multi-constraint and multi-criterion optimization problem. For the purpose of realizing such efficient network topology, this paper presents an optimization approach to design networks for better consensus formation by focusing on the eigenvalue spectral of Laplacian matrix. In both the fastest and slowest networks presented, consensus is formed among local structures first, then on a global scale. This suggests that both local and global topology influence the networks dynamics. These findings are useful for those who seek to manage efficient consensus and synchronization in a setting that can be modeled as a multi-agent system.

  16. Speed Optimization in Liner Shipping Network Design

    DEFF Research Database (Denmark)

    Brouer, Berit Dangaard; Karsten, Christian Vad; Pisinger, David

    In the Liner Shipping Network Design Problem (LSNDP) services sail at a given speed throughout a round trip. In reality most services operate with a speed differentiated head- and back-haul, or even individual speeds on every sailing between two ports. The speed of a service is decisive...... for the bunker consumption in the network as well as the transit time of cargo. Speed optimization has been considered for tramp shipping showing significant reductions in fuel consumption. However, variable speeds has not been considered for post optimization of the LSNDP, where speed optimization could result...... in changes to the cargo flow due to transit time restrictions as well as significant savings in fuel consumption and required vessel deployment due to a weekly frequency requirement. We present a heuristic method to calculate variable speed on a service and present computational results for improving...

  17. Online Advertisement, Optimization and Stochastic Networks

    CERN Document Server

    Bo,; Srikant, R

    2010-01-01

    In this paper, we propose a stochastic model to describe how modern search service providers charge client companies based on users' queries for their related "adwords" by using certain advertisement assignment strategies. We formulate an optimization problem to maximize the long-term average revenue for the service provider under each client's long-term average budget constraint, and design an online algorithm which captures the stochastic properties of users' queries and click-through behaviors. We solve the optimization problem by making connections to scheduling problems in wireless networks, queueing theory and stochastic networks. With a small customizable parameter $\\epsilon$ which is the step size used in each iteration of the online algorithm, we have shown that our online algorithm achieves a long-term average revenue which is within $O(\\epsilon)$ of the optimal revenue and the overdraft level of this algorithm is upper-bounded by $O(1/\\epsilon)$.

  18. Assessment of SRS ambient air monitoring network

    Energy Technology Data Exchange (ETDEWEB)

    Abbott, K. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL); Jannik, T. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL)

    2016-08-03

    Three methodologies have been used to assess the effectiveness of the existing ambient air monitoring system in place at the Savannah River Site in Aiken, SC. Effectiveness was measured using two metrics that have been utilized in previous quantification of air-monitoring network performance; frequency of detection (a measurement of how frequently a minimum number of samplers within the network detect an event), and network intensity (a measurement of how consistent each sampler within the network is at detecting events). In addition to determining the effectiveness of the current system, the objective of performing this assessment was to determine what, if any, changes could make the system more effective. Methodologies included 1) the Waite method of determining sampler distribution, 2) the CAP88- PC annual dose model, and 3) a puff/plume transport model used to predict air concentrations at sampler locations. Data collected from air samplers at SRS in 2015 compared with predicted data resulting from the methodologies determined that the frequency of detection for the current system is 79.2% with sampler efficiencies ranging from 5% to 45%, and a mean network intensity of 21.5%. One of the airmonitoring stations had an efficiency of less than 10%, and detected releases during just one sampling period of the entire year, adding little to the overall network intensity. By moving or removing this sampler, the mean network intensity increased to about 23%. Further work in increasing the network intensity and simulating accident scenarios to further test the ambient air system at SRS is planned

  19. Integrated condition monitoring of space information network

    Science.gov (United States)

    Wang, Zhilin; Li, Xinming; Li, Yachen; Yu, Shaolin

    2015-11-01

    In order to solve the integrated condition monitoring problem in space information network, there are three works finished including analyzing the characteristics of tasks process and system health monitoring, adopting the automata modeling method, and respectively establishing the models for state inference and state determination. The state inference model is a logic automaton and is gotten by concluding engineering experiences. The state determination model is a double-layer automaton, the lower automaton is responsible for parameter judge and the upper automaton is responsible for state diagnosis. At last, the system state monitoring algorithm has been proposed, which realizes the integrated condition monitoring for task process and system health, and can avoid the false alarm.

  20. Optimal Energy Aware Clustering in Sensor Networks

    Directory of Open Access Journals (Sweden)

    Majid Sarrafzadeh

    2002-07-01

    Full Text Available Sensor networks is among the fastest growing technologies that have the potential of changing our lives drastically. These collaborative, dynamic and distributed computing and communicating systems will be self organizing. They will have capabilities of distributing a task among themselves for efficient computation. There are many challenges in implementation of such systems: energy dissipation and clustering being one of them. In order to maintain a certain degree of service quality and a reasonable system lifetime, energy needs to be optimized at every stage of system operation. Sensor node clustering is another very important optimization problem. Nodes that are clustered together will easily be able to communicate with each other. Considering energy as an optimization parameter while clustering is imperative. In this paper we study the theoretical aspects of the clustering problem in sensor networks with application to energy optimization. We illustrate an optimal algorithm for clustering the sensor nodes such that each cluster (which has a master is balanced and the total distance between sensor nodes and master nodes is minimized. Balancing the clusters is needed for evenly distributing the load on all master nodes. Minimizing the total distance helps in reducing the communication overhead and hence the energy dissipation. This problem (which we call balanced k-clustering is modeled as a mincost flow problem which can be solved optimally using existing techniques.

  1. Optimal Reverse Carpooling Over Wireless Networks - A Distributed Optimization Approach

    CERN Document Server

    ParandehGheibi, Ali; Effros, Michelle; Medard, Muriel

    2010-01-01

    We focus on a particular form of network coding, reverse carpooling, in a wireless network where the potentially coded transmitted messages are to be decoded immediately upon reception. The network is fixed and known, and the system performance is measured in terms of the number of wireless broadcasts required to meet multiple unicast demands. Motivated by the structure of the coding scheme, we formulate the problem as a linear program by introducing a flow variable for each triple of connected nodes. This allows us to have a formulation polynomial in the number of nodes. Using dual decomposition and projected subgradient method, we present a decentralized algorithm to obtain optimal routing schemes in presence of coding opportunities. We show that the primal sub-problem can be expressed as a shortest path problem on an \\emph{edge-graph}, and the proposed algorithm requires each node to exchange information only with its neighbors.

  2. Optimal search strategies on complex networks

    CERN Document Server

    Di Patti, Francesca; Piazza, Francesco

    2014-01-01

    Complex networks are ubiquitous in nature and play a role of paramount importance in many contexts. Internet and the cyberworld, which permeate our everyday life, are self-organized hierarchical graphs. Urban traffic flows on intricate road networks, which impact both transportation design and epidemic control. In the brain, neurons are cabled through heterogeneous connections, which support the propagation of electric signals. In all these cases, the true challenge is to unveil the mechanisms through which specific dynamical features are modulated by the underlying topology of the network. Here, we consider agents randomly hopping along the links of a graph, with the additional possibility of performing long-range hops to randomly chosen disconnected nodes with a given probability. We show that an optimal combination of the two jump rules exists that maximises the efficiency of target search, the optimum reflecting the topology of the network.

  3. Criteria for the optimal structuring of a groundwater quality monitoring network based on the time-space co-kriging estimation variance; Criterio per la configurazione ottimale di una rete di monitoraggio delle acque sotterranee basata sulla varianza di stima del cokriging spazio-temporale

    Energy Technology Data Exchange (ETDEWEB)

    Passarella, Giuseppe; Vurro, Michele [CNR, Bari (Italy). IRSA, Istituto di Ricerche sulle Acque; D`Agostino, Vito [Tecnopolis - Novus Ortus, Bari (Italy)

    1997-11-01

    Parameters estimation based on sampled data strongly influences managerial choices. A methodology based on cokriging estimation variance (CEV) evaluation is presented, useful to minimise the samples in an existing monitoring network keeping the CEV below a desired threshold. The spatial behaviour of the considered chemical parameter is assumed persistent in time so that the variogram parameters are evaluated using data from previous sampling campaigns. A sequential elimination procedure has been used to assess the optimal sampling arrangement for estimating concentrations in particular critical sites. The methodology has been applied to the monitoring network in the aquifer of Lucca Plain, Central Italy.

  4. Optimal network protection against diverse interdictor strategies

    Energy Technology Data Exchange (ETDEWEB)

    Ramirez-Marquez, Jose E., E-mail: jmarquez@stevens.ed [Systems Development and Maturity Lab, School of Systems and Enterprises, Stevens Institute of Technology, Castle Point on Hudson, Hoboken, NJ 07030 (United States); Rocco, Claudio M. [Facultad de Ingenieria, Universidad Central de Venezuela, Caracas (Venezuela, Bolivarian Republic of); Levitin, Gregory [Collaborative Autonomic Computing Laboratory, School of Computer Science, University of Electronic Science and Technology of China (China); Israel Electric Corporation, Reliability and Equipment Department, Haifa 31000 (Israel)

    2011-03-15

    The objective of this paper is to provide optimal protection configurations for a network with components vulnerable to an interdictor with potentially different attacking strategies. Under this new setting, a solution/configuration describes the defender's optimal amount of defense resources allocated to each link against a potential interdictor strategy. Previous to this research decisions were of a binary nature, restricted to defend or not. Obtaining these configurations is important because along with describing the protection scheme, they are also useful for identifying sets of components critical to the successful performance of the network. The application of the approach can be beneficial for networks in telecommunications, energy, and supply chains to name a few. To obtain an optimal solution, the manuscript describes an evolutionary algorithm that considers continuous decision variables. The results obtained for different examples illustrate that equal resource allocation is optimal for the case of homogeneous component vulnerability. These findings are the basis for discussion and for describing future research directives in this area.

  5. Phase transitions in Pareto optimal complex networks.

    Science.gov (United States)

    Seoane, Luís F; Solé, Ricard

    2015-09-01

    The organization of interactions in complex systems can be described by networks connecting different units. These graphs are useful representations of the local and global complexity of the underlying systems. The origin of their topological structure can be diverse, resulting from different mechanisms including multiplicative processes and optimization. In spatial networks or in graphs where cost constraints are at work, as it occurs in a plethora of situations from power grids to the wiring of neurons in the brain, optimization plays an important part in shaping their organization. In this paper we study network designs resulting from a Pareto optimization process, where different simultaneous constraints are the targets of selection. We analyze three variations on a problem, finding phase transitions of different kinds. Distinct phases are associated with different arrangements of the connections, but the need of drastic topological changes does not determine the presence or the nature of the phase transitions encountered. Instead, the functions under optimization do play a determinant role. This reinforces the view that phase transitions do not arise from intrinsic properties of a system alone, but from the interplay of that system with its external constraints.

  6. Optimizing Retransmission Threshold in Wireless Sensor Networks.

    Science.gov (United States)

    Bi, Ran; Li, Yingshu; Tan, Guozhen; Sun, Liang

    2016-05-10

    The retransmission threshold in wireless sensor networks is critical to the latency of data delivery in the networks. However, existing works on data transmission in sensor networks did not consider the optimization of the retransmission threshold, and they simply set the same retransmission threshold for all sensor nodes in advance. The method did not take link quality and delay requirement into account, which decreases the probability of a packet passing its delivery path within a given deadline. This paper investigates the problem of finding optimal retransmission thresholds for relay nodes along a delivery path in a sensor network. The object of optimizing retransmission thresholds is to maximize the summation of the probability of the packet being successfully delivered to the next relay node or destination node in time. A dynamic programming-based distributed algorithm for finding optimal retransmission thresholds for relay nodes along a delivery path in the sensor network is proposed. The time complexity is O n Δ · max 1 ≤ i ≤ n { u i } , where u i is the given upper bound of the retransmission threshold of sensor node i in a given delivery path, n is the length of the delivery path and Δ is the given upper bound of the transmission delay of the delivery path. If Δ is greater than the polynomial, to reduce the time complexity, a linear programming-based ( 1 + p m i n ) -approximation algorithm is proposed. Furthermore, when the ranges of the upper and lower bounds of retransmission thresholds are big enough, a Lagrange multiplier-based distributed O ( 1 ) -approximation algorithm with time complexity O ( 1 ) is proposed. Experimental results show that the proposed algorithms have better performance.

  7. Exploration of Network Scaling: Variations on Optimal Channel Networks

    CERN Document Server

    Briggs, Lily

    2012-01-01

    Metabolic allometry, a common pattern in nature, is a close-to-3/4-power scaling law between metabolic rate and body mass in organisms, across and within species. An analogous relationship between metabolic rate and water volume in river networks has also been observed. Optimal Channel Networks (OCNs), at local optima, accurately model many scaling properties of river systems, including metabolic allometry. OCNs are embedded in two-dimensional space; this work extends the model to three dimensions. In this paper we compare characteristics of 3d OCNs with 2d OCNs and with organic metabolic networks, studying the scaling behaviors of area, length, volume, and energy. In addition, we take a preliminary look at comparing Steiner trees with OCNs. We find that the three-dimensional OCN has predictable characteristics analogous to those of the two-dimensional version, as well as scaling properties similar to metabolic networks in biological organisms.

  8. Network developments and network monitoring in Internet2

    Science.gov (United States)

    Boyd, E.; Evett, S.

    Given that performance is excellent across backbone networks, and that performance is a problem end-to-end, it is clear that problems are concentrated towards the edge and in network transitions. To achieve good end-to-end performance, we need to diagnose (understand the limits of performance) and address (work with members and application communities to address those performance issues). We envision readily available performance information that is easy to find, ubiquitous, reliable, valuable, actionable (analysis suggests course of action), and automated (applications act on data received). The Internet2 End-to-End Performance Initative (E2Epi) currently focuses on the development and widespread deployment of perfSONAR [1][2], an international consortium developing a performance middleware architecture and a set of protocol standards for inter-operability between measurement and monitoring systems. perfSONAR is a set of open source web services that can be added, piecemeal, and extended to create a performance monitoring framework. It is designed to be standards-based, modular, decentralized, and open source. This makes it applicable to multiple generations of network monitoring systems and encourages outside development while still allowing it to be customized for individual science applications. perfSONAR is a joint effort of ESnet, GÉANT2 JRA1, Internet2, and RNP. The Internet2 Network is a hybrid optical and IP network, that offers dynamic and static wavelength services. The Internet2 Network Observatory supports three types of services: measurement, co-location, and experimental servers to support specific projects. The Observatory collects data and makes it publicly available.

  9. Loop Optimization for Tensor Network Renormalization

    Science.gov (United States)

    Yang, Shuo; Gu, Zheng-Cheng; Wen, Xiao-Gang

    2017-03-01

    We introduce a tensor renormalization group scheme for coarse graining a two-dimensional tensor network that can be successfully applied to both classical and quantum systems on and off criticality. The key innovation in our scheme is to deform a 2D tensor network into small loops and then optimize the tensors on each loop. In this way, we remove short-range entanglement at each iteration step and significantly improve the accuracy and stability of the renormalization flow. We demonstrate our algorithm in the classical Ising model and a frustrated 2D quantum model.

  10. Optimal counter-current exchange networks

    CERN Document Server

    Farr, Robert S

    2016-01-01

    We construct a general analysis for exchange devices linking their efficiency to the (potentially fractal) geometry of the exchange surface and supply network. For certain parameter ranges, we show that the optimal exchanger consists of densely packed pipes which span a thin sheet of large area, which may be crumpled into a fractal surface and supplied with a fractal network of pipes. We present the efficiencies of such fractal exchangers, showing factor gains compared to regular exchangers, using parameters relevant for systems such as pigeon lungs and salmon gills.

  11. Loop Optimization for Tensor Network Renormalization.

    Science.gov (United States)

    Yang, Shuo; Gu, Zheng-Cheng; Wen, Xiao-Gang

    2017-03-17

    We introduce a tensor renormalization group scheme for coarse graining a two-dimensional tensor network that can be successfully applied to both classical and quantum systems on and off criticality. The key innovation in our scheme is to deform a 2D tensor network into small loops and then optimize the tensors on each loop. In this way, we remove short-range entanglement at each iteration step and significantly improve the accuracy and stability of the renormalization flow. We demonstrate our algorithm in the classical Ising model and a frustrated 2D quantum model.

  12. Optimal Sales Schemes for Network Goods

    DEFF Research Database (Denmark)

    Parakhonyak, Alexei; Vikander, Nick

    This paper examines the optimal sequencing of sales in the presence of network externalities. A firm sells a good to a group of consumers whose payoff from buying is increasing in total quantity sold. The firm selects the order to serve consumers so as to maximize expected sales. It can serve all...... consumers simultaneously, serve them all sequentially, or employ any intermediate scheme. We show that the optimal sales scheme is purely sequential, where each consumer observes all previous sales before choosing whether to buy himself. A sequential scheme maximizes the amount of information available...

  13. A Generic Methodology for Superstructure Optimization of Different Processing Networks

    DEFF Research Database (Denmark)

    Bertran, Maria-Ona; Frauzem, Rebecca; Zhang, Lei

    2016-01-01

    In this paper, we propose a generic computer-aided methodology for synthesis of different processing networks using superstructure optimization. The methodology can handle different network optimization problems of various application fields. It integrates databases with a common data architectur...

  14. A Generic Methodology for Superstructure Optimization of Different Processing Networks

    DEFF Research Database (Denmark)

    Bertran, Maria-Ona; Frauzem, Rebecca; Zhang, Lei;

    2016-01-01

    In this paper, we propose a generic computer-aided methodology for synthesis of different processing networks using superstructure optimization. The methodology can handle different network optimization problems of various application fields. It integrates databases with a common data architecture...

  15. Architectural framework for resource management optimization over heterogeneous wireless networks

    Science.gov (United States)

    Tselikas, Nikos; Kapellaki, Sofia; Koutsoloukas, Eleftherios; Venieris, Iakovos S.

    2003-11-01

    The main goal of wireless telecommunication world can be briefly summarized as: "communication anywhere, anytime, any-media and principally at high-data rates." On the other hand, this goal is in conflict with the co-existence of plenty different current and emerging wireless systems covering almost the whole world, since each one follows its own architecture and is based on its particular bedrocks. This results in a heterogeneous depiction of the hyper-set of wireless communications systems. The scope of this paper is to present a highly innovative and scalable architectural framework, which will allow different wireless systems to be interconnected in a common way, able to achieve resource management optimization, augmentation of network performance and maximum utilization of the networks. It will describe a hierarchical management system covering all GSM, GPRS, UMTS and WLAN networks each one individually, as well as a unified and wide wireless telecommunication system including all later, in order to provide enhanced capacity and quality via the accomplished network interworking. The main idea is to monitor all the resources using distributed monitoring components with intention to feed an additional centralized system with alarms, so that a set of management techniques will be selected and applied where needed. In parallel, the centralized system will be able to combine the aforementioned alarms with business models for the efficient use of the available networks according to the type of user, the type of application as well as the user"s location.

  16. Optimal Sales Schemes for Network Goods

    DEFF Research Database (Denmark)

    Parakhonyak, Alexei; Vikander, Nick

    This paper examines the optimal sequencing of sales in the presence of network externalities. A firm sells a good to a group of consumers whose payoff from buying is increasing in total quantity sold. The firm selects the order to serve consumers so as to maximize expected sales. It can serve all...... consumers simultaneously, serve them all sequentially, or employ any intermediate scheme. We show that the optimal sales scheme is purely sequential, where each consumer observes all previous sales before choosing whether to buy himself. A sequential scheme maximizes the amount of information available...... to consumers, allowing success to breed success. Failure can also breed failure, but this is made less likely by consumers’ desire to influence one another’s behavior. We show that when consumers differ in the weight they place on the network externality, the firm would like to serve consumers with lower...

  17. Intrusion detection and monitoring for wireless networks.

    Energy Technology Data Exchange (ETDEWEB)

    Thomas, Eric D.; Van Randwyk, Jamie A.; Lee, Erik J.; Stephano, Amanda (Indiana University); Tabriz, Parisa (University of Illinois at Urbana-Champaign); Pelon, Kristen (Cedarville University); McCoy, Damon (University of Colorado, Boulder); Lodato, Mark (Lafayette College); Hemingway, Franklin (University of New Mexico); Custer, Ryan P.; Averin, Dimitry (Polytechnic University); Franklin, Jason (Carnegie Mellon University); Kilman, Dominique Marie

    2005-11-01

    complete network coverage for use by emergency responders and other municipal agencies. In short, these Wi-Fi networks are being deployed everywhere. Much thought has been and is being put into evaluating cost-benefit analyses of wired vs. wireless networks and issues such as how to effectively cover an office building or municipality, how to efficiently manage a large network of wireless access points (APs), and how to save money by replacing an Internet service provider (ISP) with 802.11 technology. In comparison, very little thought and money are being focused on wireless security and monitoring for security purposes.

  18. Optimization of floodplain monitoring sensors through an entropy approach

    Science.gov (United States)

    Ridolfi, E.; Yan, K.; Alfonso, L.; Di Baldassarre, G.; Napolitano, F.; Russo, F.; Bates, P. D.

    2012-04-01

    To support the decision making processes of flood risk management and long term floodplain planning, a significant issue is the availability of data to build appropriate and reliable models. Often the required data for model building, calibration and validation are not sufficient or available. A unique opportunity is offered nowadays by the globally available data, which can be freely downloaded from internet. However, there remains the question of what is the real potential of those global remote sensing data, characterized by different accuracies, for global inundation monitoring and how to integrate them with inundation models. In order to monitor a reach of the River Dee (UK), a network of cheap wireless sensors (GridStix) was deployed both in the channel and in the floodplain. These sensors measure the water depth, supplying the input data for flood mapping. Besides their accuracy and reliability, their location represents a big issue, having the purpose of providing as much information as possible and at the same time as low redundancy as possible. In order to update their layout, the initial number of six sensors has been increased up to create a redundant network over the area. Through an entropy approach, the most informative and the least redundant sensors have been chosen among all. First, a simple raster-based inundation model (LISFLOOD-FP) is used to generate a synthetic GridStix data set of water stages. The Digital Elevation Model (DEM) used for hydraulic model building is the globally and freely available SRTM DEM. Second, the information content of each sensor has been compared by evaluating their marginal entropy. Those with a low marginal entropy are excluded from the process because of their low capability to provide information. Then the number of sensors has been optimized considering a Multi-Objective Optimization Problem (MOOP) with two objectives, namely maximization of the joint entropy (a measure of the information content) and

  19. Optimal transportation networks models and theory

    CERN Document Server

    Bernot, Marc; Morel, Jean-Michel

    2009-01-01

    The transportation problem can be formalized as the problem of finding the optimal way to transport a given measure into another with the same mass. In contrast to the Monge-Kantorovitch problem, recent approaches model the branched structure of such supply networks as minima of an energy functional whose essential feature is to favour wide roads. Such a branched structure is observable in ground transportation networks, in draining and irrigation systems, in electrical power supply systems and in natural counterparts such as blood vessels or the branches of trees. These lectures provide mathematical proof of several existence, structure and regularity properties empirically observed in transportation networks. The link with previous discrete physical models of irrigation and erosion models in geomorphology and with discrete telecommunication and transportation models is discussed. It will be mathematically proven that the majority fit in the simple model sketched in this volume.

  20. Optimal redundancy against disjoint vulnerabilities in networks

    CERN Document Server

    Krause, Sebastian M; Zlatić, Vinko

    2015-01-01

    Redundancy is commonly used to guarantee continued functionality in networked systems. However, often many nodes are vulnerable to the same failure or adversary. A "backup" path is not sufficient if both paths depend on nodes which share a vulnerability.For example, if two nodes of the Internet cannot be connected without using routers belonging to a given untrusted entity, then all of their communication-regardless of the specific paths utilized-will be intercepted by the controlling entity.In this and many other cases, the vulnerabilities affecting the network are disjoint: each node has exactly one vulnerability but the same vulnerability can affect many nodes. To discover optimal redundancy in this scenario, we describe each vulnerability as a color and develop a "color-avoiding percolation" which uncovers a hidden color-avoiding connectivity. We present algorithms for color-avoiding percolation of general networks and an analytic theory for random graphs with uniformly distributed colors including critic...

  1. LONG-TERM MONITORING SENSOR NETWORK

    Energy Technology Data Exchange (ETDEWEB)

    Stephen P. Farrington; John W. Haas; Neal Van Wyck

    2003-10-16

    Long-term monitoring (LTM) associated with subsurface contamination sites is a key element of Long Term Stewardship and Legacy Management across the Department of Energy (DOE) complex. However, both within the DOE and elsewhere, LTM is an expensive endeavor, often exceeding the costs of the remediation phase of a clean-up project. The primary contributors to LTM costs are associated with labor. Sample collection, storage, preparation, analysis, and reporting can add a significant financial burden to project expense when extended over many years. Development of unattended, in situ monitoring networks capable of providing quantitative data satisfactory to regulatory concerns has the potential to significantly reduce LTM costs. But survival and dependable operation in a difficult environment is a common obstacle to widespread use across the DOE complex or elsewhere. Deploying almost any sensor in the subsurface for extended periods of time will expose it to chemical and microbial degradation. Over the time-scales required for in situ LTM, even the most advanced sensor systems may be rendered useless. Frequent replacement or servicing (cleaning) of sensors is expensive and labor intensive, offsetting most, if not all, of the cost savings realized with unattended, in situ sensors. To enable facile, remote monitoring of contaminants and other subsurface parameters over prolonged periods, Applied Research Associates, Inc has been working to develop an advanced LTM sensor network consisting of three key elements: (1) an anti-fouling sensor chamber that can accommodate a variety of chemical and physical measurement devices based on electrochemical, optical and other techniques; (2) two rapid, cost effective, and gentle means of emplacing sensor packages either at precise locations directly in the subsurface or in pre-existing monitoring wells; and (3) a web browser-based data acquisition and control system (WebDACS) utilizing field-networked microprocessor-controlled smart

  2. Utility Optimal Scheduling in Energy Harvesting Networks

    CERN Document Server

    Huang, Longbo

    2010-01-01

    In this paper, we show how to achieve close-to-optimal utility performance in energy harvesting networks with only finite capacity energy storage devices. In these networks, nodes are capable of harvesting energy from the environment. The amount of energy that can be harvested is time varying and evolves according to some probability law. We develop an \\emph{online} algorithm, called the Energy-limited Scheduling Algorithm (ESA), which jointly manages the energy and makes power allocation decisions for packet transmissions. ESA only has to keep track of the amount of energy left at the network nodes and \\emph{does not require any knowledge} of the harvestable energy process. We show that ESA achieves a utility that is within $O(\\epsilon)$ of the optimal, for any $\\epsilon>0$, while ensuring that the network congestion and the required capacity of the energy storage devices are \\emph{deterministically} upper bounded by bounds of size $O(1/\\epsilon)$. We then also develop the Modified-ESA algorithm (MESA) to ac...

  3. Optimal Performance of a Quantum Network

    CERN Document Server

    Pirandola, Stefano

    2016-01-01

    We show that the most general protocol of quantum communication between two end-points of a quantum network with arbitrary topology can be reduced to an ensemble of Choi matrices subject to local operations and classical communication. This is found by using a teleportation-based technique which applies to a wide range of quantum channels both in discrete- and continuous-variable settings, including lossy channels, quantum-limited amplifiers, dephasing and erasure channels. Thanks to this reduction, we compute the optimal rates (capacities) at which two end-points of a quantum network can transmit quantum information, distil entanglement, or distribute secret keys. These capacities are all bounded or equal to a single quantity, that we call the entanglement flux of the quantum network. As a particular case, we derive these optimal rates for the basic paradigm of a linear chain of quantum repeaters. Thus our results establish the ultimate rates for repeater-based and network-assisted quantum communications und...

  4. Optimal evolution on random networks: from social to airports networks

    CERN Document Server

    Curty, P

    2005-01-01

    Social movements, neurons in the brain or even industrial suppliers are best described by agents evolving on networks with basic interaction rules. In these real systems, the connectivity between agents corresponds to the most efficient state of the system. The new idea is that connectivity adjusts itself because of two opposite tendencies: information percolation, decision making or coordination are better when the network connectivity is small. When agents have many connections, the opinion of a person or the state of a neuron tend to freeze: agents find always a minority among their advisors to support their opinion. A general and new model reproduces these features showing a clear transition between the two tendencies at some critical connectivity. Depending on the noise, the evolution of the system is optimal at a precise critical connectivity since, away from this critical point, the system always ends up in a static phase. When the error tolerance is very small, the optimal connectivity becomes very la...

  5. Reliability-Based Optimization for Maintenance Management in Bridge Networks

    OpenAIRE

    Hu, Xiaofei

    2014-01-01

    This dissertation addresses the problem of optimizing maintenance, repair and reconstruction decisions for bridge networks. Incorporating network topologies into bridge management problems is computationally difficult. Because of the interdependencies among networked bridges, they have to be analyzed together. Simulation-based numerical optimization techniques adopted in past research are limited to networks of moderate sizes. In this dissertation, novel approaches are developed to dete...

  6. Spatio-Temporal Clustering of Monitoring Network

    Science.gov (United States)

    Hussain, I.; Pilz, J.

    2009-04-01

    Pakistan has much diversity in seasonal variation of different locations. Some areas are in desserts and remain very hot and waterless, for example coastal areas are situated along the Arabian Sea and have very warm season and a little rainfall. Some areas are covered with mountains, have very low temperature and heavy rainfall; for instance Karakoram ranges. The most important variables that have an impact on the climate are temperature, precipitation, humidity, wind speed and elevation. Furthermore, it is hard to find homogeneous regions in Pakistan with respect to climate variation. Identification of homogeneous regions in Pakistan can be useful in many aspects. It can be helpful for prediction of the climate in the sub-regions and for optimizing the number of monitoring sites. In the earlier literature no one tried to identify homogeneous regions of Pakistan with respect to climate variation. There are only a few papers about spatio-temporal clustering of monitoring network. Steinhaus (1956) presented the well-known K-means clustering method. It can identify a predefined number of clusters by iteratively assigning centriods to clusters based. Castro et al. (1997) developed a genetic heuristic algorithm to solve medoids based clustering. Their method is based on genetic recombination upon random assorting recombination. The suggested method is appropriate for clustering the attributes which have genetic characteristics. Sap and Awan (2005) presented a robust weighted kernel K-means algorithm incorporating spatial constraints for clustering climate data. The proposed algorithm can effectively handle noise, outliers and auto-correlation in the spatial data, for effective and efficient data analysis by exploring patterns and structures in the data. Soltani and Modarres (2006) used hierarchical and divisive cluster analysis to categorize patterns of rainfall in Iran. They only considered rainfall at twenty-eight monitoring sites and concluded that eight clusters

  7. A quantum network for implementation of the optimal quantum cloning

    Institute of Scientific and Technical Information of China (English)

    Dai Jie-Lin; Zhang Wen-Hai

    2009-01-01

    This paper presents a quantum network to implement the optimal 1→2 quantum cloning in 2 dimensions, including the optimal asymmetric universal, the optimal symmetric phase-covariant, and the asymmetric real state cloning. By only choosing different angles of the single-qubit rotations, the quantum network can implement three optimal quantum cloning.

  8. Functional optimization of the arterial network

    CERN Document Server

    Mauroy, Benjamin

    2014-01-01

    We build an evolutionary scenario that explains how some crucial physiological constraints in the arterial network of mammals - i.e. hematocrit, vessels diameters and arterial pressure drops - could have been selected by evolution. We propose that the arterial network evolved while being constrained by its function as an organ. To support this hypothesis, we focus our study on one of the main function of blood network: oxygen supply to the organs. We consider an idealized organ with a given oxygen need and we optimize blood network geometry and hematocrit with the constraint that it must fulfill the organ oxygen need. Our model accounts for the non-Newtonian behavior of blood, its maintenance cost and F\\aa hr\\ae us effects (decrease in average concentration of red blood cells as the vessel diameters decrease). We show that the mean shear rates (relative velocities of fluid layers) in the tree vessels follow a scaling law related to the multi-scale property of the tree network, and we show that this scaling la...

  9. A network monitor for HTTPS protocol based on proxy

    Science.gov (United States)

    Liu, Yangxin; Zhang, Lingcui; Zhou, Shuguang; Li, Fenghua

    2016-10-01

    With the explosive growth of harmful Internet information such as pornography, violence, and hate messages, network monitoring is essential. Traditional network monitors is based mainly on bypass monitoring. However, we can't filter network traffic using bypass monitoring. Meanwhile, only few studies focus on the network monitoring for HTTPS protocol. That is because HTTPS data is in the encrypted traffic, which makes it difficult to monitor. This paper proposes a network monitor for HTTPS protocol based on proxy. We adopt OpenSSL to establish TLS secure tunes between clients and servers. Epoll is used to handle a large number of concurrent client connections. We also adopt Knuth- Morris-Pratt string searching algorithm (or KMP algorithm) to speed up the search process. Besides, we modify request packets to reduce the risk of errors and modify response packets to improve security. Experiments show that our proxy can monitor the content of all tested HTTPS websites efficiently with little loss of network performance.

  10. Quality control in bio-monitoring networks, Spanish Aerobiology Network.

    Science.gov (United States)

    Oteros, Jose; Galán, Carmen; Alcázar, Purificación; Domínguez-Vilches, Eugenio

    2013-01-15

    Several of the airborne biological particles, such as pollen grains and fungal spores, are known to generate human health problems including allergies and infections. A number of aerobiologists have focused their research on these airborne particles. The Spanish Aerobiology Network (REA) was set up in 1992, and since then dozens of research groups have worked on a range of related topics, including the standardization of study methods and the quality control of data generated by this network. In 2010, the REA started work on an inter-laboratory survey for proficiency testing purposes. The main goal of the study reported in the present paper was to determine the performance of technicians in the REA network using an analytical method that could be implemented by other bio-monitoring networks worldwide. The results recorded by each technician were compared with the scores obtained for a bounded mean of all results. The performance of each technician was expressed in terms of the relative error made in counting each of several pollen types. The method developed and implemented here proved appropriate for proficiency testing in interlaboratory studies involving bio-monitoring networks, and enabled the source of data quality problems to be pinpointed. The test revealed a variation coefficient of 10%. The relative error was significant for 3.5% of observations. In overall terms, the REA staff performed well, in accordance with the REA Management and Quality Manual. These findings serve to guarantee the quality of the data obtained, which can reliably be used for research purposes and published in the media in order to help prevent pollen-related health problems.

  11. Optimization-Based Approaches to Control of Probabilistic Boolean Networks

    Directory of Open Access Journals (Sweden)

    Koichi Kobayashi

    2017-02-01

    Full Text Available Control of gene regulatory networks is one of the fundamental topics in systems biology. In the last decade, control theory of Boolean networks (BNs, which is well known as a model of gene regulatory networks, has been widely studied. In this review paper, our previously proposed methods on optimal control of probabilistic Boolean networks (PBNs are introduced. First, the outline of PBNs is explained. Next, an optimal control method using polynomial optimization is explained. The finite-time optimal control problem is reduced to a polynomial optimization problem. Furthermore, another finite-time optimal control problem, which can be reduced to an integer programming problem, is also explained.

  12. On optimal strategies for upgrading networks

    Energy Technology Data Exchange (ETDEWEB)

    Krumke, S.O.; Noltemeier, H. [Wuerzburg Univ. (Germany). Dept. of Computer Science; Marathe, M.V. [Los Alamos National Lab., NM (United States); Ravi, S.S. [State Univ. of New York, Albany, NY (United States). Dept. of Computer Science; Ravi, R. [Carnegie-Mellon Univ., Pittsburgh, PA (United States). Graduate School of Industrial Administration; Sundaram, R. [Massachusetts Inst. of Tech., Cambridge, MA (United States)

    1996-07-02

    We study {ital budget constrained optimal network upgrading problems}. Such problems aim at finding optimal strategies for improving a network under some cost measure subject to certain budget constraints. Given an edge weighted graph {ital G(V,E)}, in the {ital edge based upgrading model}, it is assumed that each edge {ital e} of the given network has an associated function {ital c(e)} that specifies for each edge {ital e} the amount by which the length {ital l(e)} is to be reduced. In the {ital node based upgrading model} a node {ital v} can be upgraded at an expense of cost {ital (v)}. Such an upgrade reduces the cost of each edge incident on {ital v} by a fixed factor {rho}, where 0 < {rho} < 1. For a given budget, {ital B}, the goal is to find an improvement strategy such that the total cost of reduction is a most the given budget {ital B} and the cost of a subgraph (e.g. minimum spanning tree) under the modified edge lengths is the best over all possible strategies which obey the budget constraint. Define an ({alpha},{beta})-approximation algorithm as a polynomial-time algorithm that produces a solution within {alpha} times the optimal function value, violating the budget constraint by a factor of at most {Beta}. The results obtained in this paper include the following 1. We show that in general the problem of computing optimal reduction strategy for modifying the network as above is {bold NP}-hard. 2. In the node based model, we show how to devise a near optimal strategy for improving the bottleneck spanning tree. The algorithms have a performance guarantee of (2 ln {ital n}, 1). 3. for the edge based improvement problems we present improved (in terms of performance and time) approximation algorithms. 4. We also present pseudo-polynomial time algorithms (extendible to polynomial time approximation schemes) for a number of edge/node based improvement problems when restricted to the class of treewidth-bounded graphs.

  13. Optimal flux patterns in cellular metabolic networks

    Energy Technology Data Exchange (ETDEWEB)

    Almaas, E

    2007-01-20

    The availability of whole-cell level metabolic networks of high quality has made it possible to develop a predictive understanding of bacterial metabolism. Using the optimization framework of flux balance analysis, I investigate metabolic response and activity patterns to variations in the availability of nutrient and chemical factors such as oxygen and ammonia by simulating 30,000 random cellular environments. The distribution of reaction fluxes is heavy-tailed for the bacteria H. pylori and E. coli, and the eukaryote S. cerevisiae. While the majority of flux balance investigations have relied on implementations of the simplex method, it is necessary to use interior-point optimization algorithms to adequately characterize the full range of activity patterns on metabolic networks. The interior-point activity pattern is bimodal for E. coli and S. cerevisiae, suggesting that most metabolic reaction are either in frequent use or are rarely active. The trimodal activity pattern of H. pylori indicates that a group of its metabolic reactions (20%) are active in approximately half of the simulated environments. Constructing the high-flux backbone of the network for every environment, there is a clear trend that the more frequently a reaction is active, the more likely it is a part of the backbone. Finally, I briefly discuss the predicted activity patterns of the central-carbon metabolic pathways for the sample of random environments.

  14. Optimal flux patterns in cellular metabolic networks

    Energy Technology Data Exchange (ETDEWEB)

    Almaas, E

    2007-01-20

    The availability of whole-cell level metabolic networks of high quality has made it possible to develop a predictive understanding of bacterial metabolism. Using the optimization framework of flux balance analysis, I investigate metabolic response and activity patterns to variations in the availability of nutrient and chemical factors such as oxygen and ammonia by simulating 30,000 random cellular environments. The distribution of reaction fluxes is heavy-tailed for the bacteria H. pylori and E. coli, and the eukaryote S. cerevisiae. While the majority of flux balance investigations have relied on implementations of the simplex method, it is necessary to use interior-point optimization algorithms to adequately characterize the full range of activity patterns on metabolic networks. The interior-point activity pattern is bimodal for E. coli and S. cerevisiae, suggesting that most metabolic reaction are either in frequent use or are rarely active. The trimodal activity pattern of H. pylori indicates that a group of its metabolic reactions (20%) are active in approximately half of the simulated environments. Constructing the high-flux backbone of the network for every environment, there is a clear trend that the more frequently a reaction is active, the more likely it is a part of the backbone. Finally, I briefly discuss the predicted activity patterns of the central-carbon metabolic pathways for the sample of random environments.

  15. Developing hydrological monitoring networks with Arduino

    Science.gov (United States)

    Buytaert, Wouter; Vega, Andres; Villacis, Marcos; Moulds, Simon

    2015-04-01

    The open source hardware platform Arduino is very cost-effective and versatile for the development of sensor networks. Here we report on experiments on the use of Arduino-related technologies to develop and implement hydrological monitoring networks. Arduino Uno boards were coupled to a variety of commercially available hydrological sensors and programmed for automatic data collection. Tested sensors include water level, temperature, humidity, radiation, and precipitation. Our experiments show that most of the tested analogue sensors are quite straightforward to couple to Arduino based data loggers, especially if the electronic characteristics of the sensor are available. However, some sensors have internal digital interfaces, which are more challenging to connect. Lastly, tipping bucket rain gauges prove the most challenging because of the very specific methodology, i.e. registration of bucket tips instead of measurements at regular intervals. The typically low data generation rate of hydrological instruments is very compatible with available technologies for wireless data transmission. Mesh networks such as Xbee prove very convenient and robust for dispersed networks, while wifi is also an option for shorter distances and particular topographies. Lastly, the GSM shield of the Arduino can be used to transfer data to centralized databases. In regions where no mobile internet (i.e. 3G) connection is available, data transmission via text messages may be an option, depending on the bandwidth requirements.

  16. Optimal sampling in network performance evaluation

    Energy Technology Data Exchange (ETDEWEB)

    Fedorov, V.; Flanagan, D.; Batsell, S.

    1998-11-01

    Unlike many other experiments, in meteorology and seismology for instance, monitoring measurements on communication networks are cheap and fast. Even the simplest measurement tools, which are usually some interrogating programs, can provide a huge amount of data at almost no expense. The problem is not decreasing the cost of measurements, but rather reducing the amount of stored data and the measurement and analysis time. The authors address the approach that is based on the covariances between the measurements for various sites. The corresponding covariance matrix can be constructed either theoretically under some assumptions about the observed random processes, or can be estimated from some preliminary experiments. The authors compare the proposed algorithm with heuristic procedures that are used in other monitoring problems.

  17. Interconnection Optimization for Multi-Cluster Avionics Networks

    OpenAIRE

    2013-01-01

    National audience; The increasing complexity and heterogeneity of avionics networks make resource optimization a challenging task. In contrast to many previous approaches pursuing the optimization of traffic-source mapping and backbone network analysis, our work presented herein mainly focuses on the optimization of interconnection devices for multi-cluster avionics networks. In this paper, we introduce an optimized interconnection device, integrating novel frame packing strategies and schedu...

  18. The Wireless Sensor Networks Base Layout and Density Optimization Oriented towards Traffic Information Collection

    Directory of Open Access Journals (Sweden)

    Musong Gu

    2015-01-01

    Full Text Available Wireless sensor networks (WSN are applied in Intelligent Transport System for data collection. For the low redundancy rate of the wireless sensor networks nodes of traffic information collection, the senor nodes should be deployed reasonably for the WSN nodes to work effectively, and, thus, the base network structure and the density optimization of the sensor network are one of the main problems of WSN application. This paper establishes the wireless sensor networks design optimization model oriented to the traffic information collection, solving the design optimization model with the chemical reaction optimization (CRO algorithm. The experimental results show that CRO algorithm outperforms the traditional particle swarm optimization (PSO in solving the wireless sensor network design optimization oriented to the traffic information collection, capable of optimizing the wireless sensor network deployment of traffic information collection to contribute to the great improvement of the comprehensive value of the network performance. The reasonable design of the wireless sensor network nodes has great significance for the information collection, post-maintenance-and-extension, and cost saving of a monitoring system.

  19. Optimal Joint Liability Lending and with Costly Peer Monitoring

    NARCIS (Netherlands)

    Carli, F.; Uras, R.B.

    2014-01-01

    This paper characterizes an optimal group loan contract with costly peer monitoring. Using a fairly standard moral hazard framework, we show that the optimal group lending contract could exhibit a joint-liability scheme. However, optimality of joint-liability requires the involvement of a group lead

  20. Autonomous tools for Grid management, monitoring and optimization

    CERN Document Server

    Wislicki, Wojciech

    2007-01-01

    We outline design and lines of development of autonomous tools for the computing Grid management, monitoring and optimization. The management is proposed to be based on the notion of utility. Grid optimization is considered to be application-oriented. A generic Grid simulator is proposed as an optimization tool for Grid structure and functionality.

  1. Network-level optimization method for road network maintenance programming based on network efficiency

    Institute of Scientific and Technical Information of China (English)

    张林雪; 秦进; 贺钰昕; 叶勇; 倪玲霖

    2015-01-01

    To maintain their capacity, transportation infrastructures are in need of regular maintenance and rehabilitation. The major challenge facing transportation engineers is the network-level policies to maintain the deteriorating roads at an acceptable level of serviceability. In this work, a quantitative transportation network efficiency measure is presented and then how to determine optimally network-level road maintenance policy depending on the road importance to the network performance has been demonstrated. The examples show that the different roads should be set different maintenance time points in terms of the retention capacities of the roads, because the different roads play different roles in network and have different important degrees to the network performance. This network-level road maintenance optimization method could not only save lots of infrastructure investments, but also ensure the service level of the existing transportation system.

  2. Optimal Node Placement in Underwater Wireless Sensor Networks

    KAUST Repository

    Felamban, M.

    2013-03-25

    Wireless Sensor Networks (WSN) are expected to play a vital role in the exploration and monitoring of underwater areas which are not easily reachable by humans. However, underwater communication via acoustic waves is subject to several performance limitations that are very different from those used for terresstrial networks. In this paper, we investigate node placement for building an initial underwater WSN infrastructure. We formulate this problem as a nonlinear mathematical program with the objective of minimizing the total transmission loss under a given number of sensor nodes and targeted coverage volume. The obtained solution is the location of each node represented via a truncated octahedron to fill out the 3D space. Experiments are conducted to verify the proposed formulation, which is solved using Matlab optimization tool. Simulation is also conducted using an ns-3 simulator, and the simulation results are consistent with the obtained results from mathematical model with less than 10% error.

  3. Towards Optimal Event Detection and Localization in Acyclic Flow Networks

    KAUST Repository

    Agumbe Suresh, Mahima

    2012-01-03

    Acyclic flow networks, present in many infrastructures of national importance (e.g., oil & gas and water distribution systems), have been attracting immense research interest. Existing solutions for detecting and locating attacks against these infrastructures, have been proven costly and imprecise, especially when dealing with large scale distribution systems. In this paper, to the best of our knowledge for the first time, we investigate how mobile sensor networks can be used for optimal event detection and localization in acyclic flow networks. Sensor nodes move along the edges of the network and detect events (i.e., attacks) and proximity to beacon nodes with known placement in the network. We formulate the problem of minimizing the cost of monitoring infrastructure (i.e., minimizing the number of sensor and beacon nodes deployed), while ensuring a degree of sensing coverage in a zone of interest and a required accuracy in locating events. We propose algorithms for solving these problems and demonstrate their effectiveness with results obtained from a high fidelity simulator.

  4. The seismic monitoring network of Mt. Vesuvius

    Directory of Open Access Journals (Sweden)

    Massimo Orazi

    2013-11-01

    Full Text Available Mt. Vesuvius (southern Italy is one of the most hazardous volcanoes in the world. Its activity is currently characterized by moderate seismicity, with hypocenters located beneath the crater zone with depth rarely exceeding 5 km and magnitudes generally less than 3. The current configuration of the seismic monitoring network of Mt. Vesuvius consists of 18 seismic stations and 7 infrasound microphones. During the period 2006-2010 a seismic array with 48 channels was also operative. The station distribution provides appropriate coverage of the area around the volcanic edifice. The current development of the network and its geometry, under conditions of low seismic noise, allows locating seismic events with M<1. Remote instruments continuously transmit data to the main acquisition center in Naples. Data transmission is realized using different technological solutions based on UHF, Wi-Fi radio links, and TCP/IP client-server applications. Data are collected in the monitoring center of the Osservatorio Vesuviano (Italian National Institute of Geophysics and Volcanology, Naples section, which is equipped with systems for displaying and analyzing signals, using both real-time automatic and manual procedures. 24-hour surveillance allows to immediately communicate any significant anomaly to the Civil Protection authorities.

  5. Optimization of OSPF Routing in IP Networks

    Science.gov (United States)

    Bley, Andreas; Fortz, Bernard; Gourdin, Eric; Holmberg, Kaj; Klopfenstein, Olivier; Pióro, Michał; Tomaszewski, Artur; Ümit, Hakan

    The Internet is a huge world-wide packet switching network comprised of more than 13,000 distinct subnetworks, referred to as Autonomous Systems (ASs) autonomous system AS . They all rely on the Internet Protocol (IP) internet protocol IP for transport of packets across the network. And most of them use shortest path routing protocols shortest path routing!protocols , such as OSPF or IS-IS, to control the routing of IP packets routing!of IP packets within an AS. The idea of the routing is extremely simple — every packet is forwarded on IP links along the shortest route between its source and destination nodes of the AS. The AS network administrator can manage the routing of packets in the AS by supplying the so-called administrative weights of IP links, which specify the link lengths that are used by the routing protocols for their shortest path computations. The main advantage of the shortest path routing policy is its simplicity, allowing for little administrative overhead. From the network engineering perspective, however, shortest path routing can pose problems in achieving satisfactory traffic handling efficiency. As all routing paths depend on the same routing metric routing!metric , it is not possible to configure the routing paths for the communication demands between different pairs of nodes explicitly or individually; the routing can be controlled only indirectly and only as a whole by modifying the routing metric. Thus, one of the main tasks when planning such networks is to find administrative link weights that induce a globally efficient traffic routing traffic!routing configuration of an AS. It turns out that this task leads to very difficult mathematical optimization problems. In this chapter, we discuss and describe exact integer programming models and solution approaches as well as practically efficient smart heuristics for such shortest path routing problems shortest path routing!problems .

  6. A versatile and interoperable network sensors for water resources monitoring

    Science.gov (United States)

    Ortolani, Alberto; Brandini, Carlo; Costantini, Roberto; Costanza, Letizia; Innocenti, Lucia; Sabatini, Francesco; Gozzini, Bernardo

    2010-05-01

    as shortcuts to the heart of the aquifer, causing water contamination much faster than what inferable from average infiltration rates. A new system has been set up, upgrading a legacy sensor network with new sensors to address the monitoring and emergency phase management. Where necessary sensors have been modified in order to manage the whole sensor network through SWE services. The network manage sensors for water parameters (physical and chemical) and for atmospheric ones (for supporting the management of accidental crises). A main property of the developed architecture is that it can be easily reconfigured to pass from the monitoring to the alert phase, by changing sampling frequencies of interesting parameters, or deploying specific additional sensors on identified optimal positions (as in case of the hydrocarbon spill). A hydrogeological model, coupled through a hydrological interface to the atmospheric forcing, has been implemented for the area. Model products (accessed through the same web interface than sensors) give a fundamental added value to the upgraded sensors network (e.g. for data merging procedures). Together with the available measurements, it is shown how the model improves the knowledge of the local hydrogeological system, gives a fundamental support to eventually reconfigure the system (e.g. support on transportable sensors position). The network, basically conceived for real-time monitoring, allow to accumulate an unprecedent amount of information for the aquifer. The availability of such a large set of data (in terms of continuously measured water levels, fluxes, precipitation, concentrations, etc.) from the system, gives a unique opportunity for studying the influences of hydrogeological and geopedological parameters on arsenic and concentrations of other chemicals that are naturally present in water.

  7. A Wireless Sensor Network For Soil Monitoring

    Science.gov (United States)

    Szlavecz, K.; Cogan, J.; Musaloiu-Elefteri, R.; Small, S.; Terzis, A.; Szalay, A.

    2005-12-01

    The most spatially complex stratum of a terrestrial ecosystem is its soil. Among the major challenges of studying the soil ecosystem are the diversity and the cryptic nature of biota, and the enormous heterogeneity of the soil substrate. Often this patchiness drives spatial distribution of soil organisms, yet our knowledge on the spatio-temporal patterns of soil conditions is limited. To monitor the environmental conditions at biologically meaningful spatial scales we have developed and deployed a wireless sensor network of thirty nodes. Each node is based on a MICAz mote connected to a custom-built sensor suite that includes a Watermark soil moisture sensor, an Irrometer soil temperature sensor, and sensors capable of recording ambient temperature and light intensity. To assess CO2 production at the ground level a subset of the nodes is equipped with Telaire 6004 CO2 sensor. We developed the software running on the motes from scratch, using the TinyOS development environment. Each mote collects measurements every minute, and stores them persistently in a non-volatile memory. The decision to store data locally at each node enables us to reliably retrieve the data in the face of network losses and premature node failures due to power depletion. Collected measurements are retrieved over the wireless network through a PC-class computer acting as a gateway between the sensor network and the Internet. Considering that motes are battery powered, the largest obstacle hindering long-term sensor network deployments is power consumption. To address this problem, our software powers down sensors between sampling cycles and turns off the radio (the most energy prohibitive mote component) when not in use. By doing so we were able to increase node lifetime by a factor of ten. We collected field data over several weeks. The data was ingested into a SQL Server database, which provides data access through a .NET web services interface. The database provides functions for spatial

  8. Wireless Sensor Networks for Environmental Monitoring

    Science.gov (United States)

    Liang, X.; Liang, Y.; Navarro, M.; Zhong, X.; Villalba, G.; Li, Y.; Davis, T.; Erratt, N.

    2015-12-01

    Wireless sensor networks (WSNs) have gained an increasing interest in a broad range of new scientific research and applications. WSN technologies can provide high resolution for spatial and temporal data which has not been possible before, opening up new opportunities. On the other hand, WSNs, particularly outdoor WSNs in harsh environments, present great challenges for scientists and engineers in terms of the network design, deployment, operation, management, and maintenance. Since 2010, we have been working on the deployment of an outdoor multi-hop WSN testbed for hydrological/environmental monitoring in a forested hill-sloped region at the Audubon Society of Western Pennsylvania (ASWP), Pennsylvania, USA. The ASWP WSN testbed has continuously evolved and had more than 80 nodes by now. To our knowledge, the ASWP WSN testbed represents one of the first known long-term multi-hop WSN deployments in an outdoor environment. As simulation and laboratory methods are unable to capture the complexity of outdoor environments (e.g., forests, oceans, mountains, or glaciers), which significantly affect WSN operations and maintenance, experimental deployments are essential to investigate and understand WSN behaviors and performances as well as its maintenance characteristics under these harsh conditions. In this talk, based on our empirical studies with the ASWP WSN testbed, we will present our discoveries and investigations on several important aspects including WSN energy profile, node reprogramming, network management system, and testbed maintenance. We will then provide our insight into these critical aspects of outdoor WSN deployments and operations.

  9. Optimal learning paths in information networks.

    Science.gov (United States)

    Rodi, G C; Loreto, V; Servedio, V D P; Tria, F

    2015-06-01

    Each sphere of knowledge and information could be depicted as a complex mesh of correlated items. By properly exploiting these connections, innovative and more efficient navigation strategies could be defined, possibly leading to a faster learning process and an enduring retention of information. In this work we investigate how the topological structure embedding the items to be learned can affect the efficiency of the learning dynamics. To this end we introduce a general class of algorithms that simulate the exploration of knowledge/information networks standing on well-established findings on educational scheduling, namely the spacing and lag effects. While constructing their learning schedules, individuals move along connections, periodically revisiting some concepts, and sometimes jumping on very distant ones. In order to investigate the effect of networked information structures on the proposed learning dynamics we focused both on synthetic and real-world graphs such as subsections of Wikipedia and word-association graphs. We highlight the existence of optimal topological structures for the simulated learning dynamics whose efficiency is affected by the balance between hubs and the least connected items. Interestingly, the real-world graphs we considered lead naturally to almost optimal learning performances.

  10. Performance Optimization of Multiple Interconnected Heterogeneous Sensor Networks via Collaborative Information Sharing

    CERN Document Server

    Pal, Sougata; Bellalta, Boris; Oliver, Miquel

    2012-01-01

    Interconnecting multiple sensor networks is a relatively new research field which has emerged in the Wireless Sensor Network domain. Wireless Sensor Networks (WSNs) have typically been seen as logically separate, and few works have considered interconnection and interaction between them. Interconnecting multiple heterogeneous sensor networks therefore opens up a new field besides more traditional research on, e.g., routing, self organization, or MAC layer development. Up to now, some approaches have been proposed for interconnecting multiple sensor networks with goals like information sharing or monitoring multiple sensor networks. In this paper, we propose to utilize inter-WSN communication to enable Collaborative Performance Optimization, i.e., our approach aims to optimize the performance of individual WSNs by taking into account measured information from others. The parameters to be optimized are energy consumption on the one hand and sensing quality on the other.

  11. Optimal Brain Surgeon on Artificial Neural Networks in

    DEFF Research Database (Denmark)

    Christiansen, Niels Hørbye; Job, Jonas Hultmann; Klyver, Katrine;

    2012-01-01

    It is shown how the procedure know as optimal brain surgeon can be used to trim and optimize artificial neural networks in nonlinear structural dynamics. Beside optimizing the neural network, and thereby minimizing computational cost in simulation, the surgery procedure can also serve as a quick...

  12. Routing Protocol with Optimal Location of Aggregation Point in Wireless Sensor Networks

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    A wireless sensor network is typically composed of hundreds, even thousands of tiny sensors used to monitor physical phenomena. As data collected by the sensors are often redundant, data aggregation is important for conserving energy. In this paper, we present a new routing protocol with optimal data aggregation. This routing protocol has good performance due to its optimal selection of aggregation point locations. This paper details the optimal selection of aggregation point locations.

  13. A stochastic method for optimal location of groundwater monitoring sites at aquifer scale

    Science.gov (United States)

    Barca, E.; Passarella, G.

    2009-04-01

    With the growth of public environmental awareness and the improvement in national and EU legislation regarding the environment, monitoring assumed great importance in the frame of all managerial activities related to territories. In particular, recently, a number of public environmental agencies have invested great resources in planning and operating improvements on existing monitoring networks within their regions. In this framework, and, at the light of the Water Framework Directive, the optimal monitoring of the qualitative and quantitative state of groundwater becomes a priority, particularly, when severe economic constraints must be imposed and the territory to be monitored is quite wide. There are a lot of reasons justifying the optimal extension of a monitoring network. In fact, a modest coverage of the monitored area often makes impossible to provide the manager with a sufficient knowledge for decision-making processes. In general, monitoring networks are characterized by a scarce number of existing wells, irregularly spread over the considered area. This is a typical case of optimization and it may be solved seeking among existing, but unused, wells, all and only those able to make the monitoring network coverage, the most uniform among any arrangement. Using existing wells as new monitoring sites, allows one to drastically reduce the needed budget. In this paper, a four step method, based on simulated annealing, has been implemented with the aim of identifying scarcely monitored zones within the groundwater system boundaries. The steps are the following: I. Define aquifer boundaries, number and location of the existing monitoring sites and number and location of candidate new monitoring sites. Any constraint about the network size, and wells' location and characteristics need also to be identified at this step; II. Carry out stochastic simulations producing a large number of possible realizations of the improved monitoring network and choose the transient

  14. An Enhanced PSO-Based Clustering Energy Optimization Algorithm for Wireless Sensor Network

    Directory of Open Access Journals (Sweden)

    C. Vimalarani

    2016-01-01

    Full Text Available Wireless Sensor Network (WSN is a network which formed with a maximum number of sensor nodes which are positioned in an application environment to monitor the physical entities in a target area, for example, temperature monitoring environment, water level, monitoring pressure, and health care, and various military applications. Mostly sensor nodes are equipped with self-supported battery power through which they can perform adequate operations and communication among neighboring nodes. Maximizing the lifetime of the Wireless Sensor networks, energy conservation measures are essential for improving the performance of WSNs. This paper proposes an Enhanced PSO-Based Clustering Energy Optimization (EPSO-CEO algorithm for Wireless Sensor Network in which clustering and clustering head selection are done by using Particle Swarm Optimization (PSO algorithm with respect to minimizing the power consumption in WSN. The performance metrics are evaluated and results are compared with competitive clustering algorithm to validate the reduction in energy consumption.

  15. An Enhanced PSO-Based Clustering Energy Optimization Algorithm for Wireless Sensor Network.

    Science.gov (United States)

    Vimalarani, C; Subramanian, R; Sivanandam, S N

    2016-01-01

    Wireless Sensor Network (WSN) is a network which formed with a maximum number of sensor nodes which are positioned in an application environment to monitor the physical entities in a target area, for example, temperature monitoring environment, water level, monitoring pressure, and health care, and various military applications. Mostly sensor nodes are equipped with self-supported battery power through which they can perform adequate operations and communication among neighboring nodes. Maximizing the lifetime of the Wireless Sensor networks, energy conservation measures are essential for improving the performance of WSNs. This paper proposes an Enhanced PSO-Based Clustering Energy Optimization (EPSO-CEO) algorithm for Wireless Sensor Network in which clustering and clustering head selection are done by using Particle Swarm Optimization (PSO) algorithm with respect to minimizing the power consumption in WSN. The performance metrics are evaluated and results are compared with competitive clustering algorithm to validate the reduction in energy consumption.

  16. Transmission network expansion planning with simulation optimization

    Energy Technology Data Exchange (ETDEWEB)

    Bent, Russell W [Los Alamos National Laboratory; Berscheid, Alan [Los Alamos National Laboratory; Toole, G. Loren [Los Alamos National Laboratory

    2010-01-01

    Within the electric power literatW''e the transmi ssion expansion planning problem (TNEP) refers to the problem of how to upgrade an electric power network to meet future demands. As this problem is a complex, non-linear, and non-convex optimization problem, researchers have traditionally focused on approximate models. Often, their approaches are tightly coupled to the approximation choice. Until recently, these approximations have produced results that are straight-forward to adapt to the more complex (real) problem. However, the power grid is evolving towards a state where the adaptations are no longer easy (i.e. large amounts of limited control, renewable generation) that necessitates new optimization techniques. In this paper, we propose a generalization of the powerful Limited Discrepancy Search (LDS) that encapsulates the complexity in a black box that may be queJied for information about the quality of a proposed expansion. This allows the development of a new optimization algOlitlun that is independent of the underlying power model.

  17. Helicopter Rotor Blade Monitoring using Autonomous Wireless Sensor Network

    NARCIS (Netherlands)

    Sanchez Ramirez, Andrea; Loendersloot, Richard; Tinga, Tiedo; Basu, B.

    2013-01-01

    The advancement on Wireless Sensor Networks for vibration monitoring presents important possibilities for helicopter rotor health and usage monitoring. While main rotor blades account for the main source of lift for helicopters, rotor induced vibration establishes an important source for

  18. Air Quality System (AQS) Monitoring Network, EPA OAR OAQPS

    Data.gov (United States)

    U.S. Environmental Protection Agency — This GIS dataset contains points which depict air quality monitors within EPA's Air Quality System (AQS) monitoring network. This dataset is updated weekly to...

  19. Intrinsic Monitoring Using Behaviour Models in IPv6 Networks

    Science.gov (United States)

    Höfig, Edzard; Coşkun, Hakan

    In conventional networks, correlating path information to resource utilisation on the granularity of packets is a hard problem when using policy-based traffic handling schemes. We introduce a new approach termed ‘intrinsic monitoring’ which relies on the use of IPv6 extension headers in combination with formal behaviour models to gather resource information along a path. This allows a network monitoring system to delegate monitoring functionality to the network devices themselves, with the result of a drastic reduction in management traffic due to the increased autonomy of the monitoring system. As monitoring information travels in-band with the network traffic, path information remains perfectly accurate.

  20. An infrastructure for passive network monitoring of application data streams

    Energy Technology Data Exchange (ETDEWEB)

    Agarwal, Deb [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Gonzalez, Jose Maria [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Jin, Guojun [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Tierney, Brian [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

    2003-03-01

    When diagnosing network problems, it is often desirable to have a view of traffic inside the network. In this paper we describe an infrastructure for passive monitoring that can be used to determine which segments of the network are the source of problems for an application data stream. The monitoring hosts are relatively low-cost, off-the-shelf PCs. A unique feature of the infrastructure is secure activation of monitoring hosts in the core of the network without direct network administrator intervention.

  1. OPTIMIZATION METHODS FOR HYDROECOLOGICAL MONITORING SYSTEMS

    OpenAIRE

    Inna Pivovarova

    2016-01-01

    The paper describes current approaches to the rational distribution of monitoring stations. A short review and the organization of the system of hydro-geological observations in different countries are presented. On the basis of real data we propose a solution to the problem of how to calculate the average area per one hydrological station, which is the main indicator of the efficiency and performance of the monitoring system in general. We conclude that a comprehensive approach to the monito...

  2. Optimisation of Lilla Edet Landslide GPS Monitoring Network

    Science.gov (United States)

    Alizadeh-Khameneh, M. A.; Eshagh, M.; Sjöberg, L. E.

    2015-06-01

    Since the year 2000, some periodic investigations have been performed in the Lilla Edet region to monitor and possibly determine the landslide of the area with GPS measurements. The responsible consultant has conducted this project by setting up some stable stations for GPS receivers in the risky areas of Lilla Edet and measured the independent baselines amongst the stations according to their observation plan. Here, we optimise the existing surveying network and determine the optimal configuration of the observation plan based on different criteria.We aim to optimise the current network to become sensitive to detect 5 mm possible displacements in each net point. The network quality criteria of precision, reliability and cost are used as object functions to perform single-, bi- and multi-objective optimisation models. It has been shown in the results that the single-objective model of reliability, which is constrained to the precision, provides much higher precision than the defined criterion by preserving almost all of the observations. However, in this study, the multi-objective model can fulfil all the mentioned quality criteria of the network by 17% less measurements than the original observation plan, meaning 17%of saving time, cost and effort in the project.

  3. An Optimal Design Model for New Water Distribution Networks in ...

    African Journals Online (AJOL)

    An Optimal Design Model for New Water Distribution Networks in Kigali City. ... a Linear Programming Problem (LPP) which involves the design of a new network of water distribution considering the cost in the form of unit price ... Article Metrics.

  4. Optimization Design based on BP Neural Network and GA Method

    Directory of Open Access Journals (Sweden)

    Bing Wang

    2013-12-01

    Full Text Available This study puts forward one kind optimization controlling solution method on complicated system. At first modeling using neural network then adopt the real data to structure the neural network model of pertinence, make the parameter to seek to the neural network model excellently by mixing GA finally, thus got intelligence to the complicated system to optimize and control. The method can identify network configuration and network training methods. By adopting the number coding and effectively reducing the network size and the network convergence time, increase the network training speed. The study provides this and optimizes relevant MATLAB procedure which controls the method, so long as adjust a little to the concrete problem, can believe this procedure well the optimization of the complicated system controls the problem in the reality of solving.

  5. Parallel Evolutionary Optimization for Neuromorphic Network Training

    Energy Technology Data Exchange (ETDEWEB)

    Schuman, Catherine D [ORNL; Disney, Adam [University of Tennessee (UT); Singh, Susheela [North Carolina State University (NCSU), Raleigh; Bruer, Grant [University of Tennessee (UT); Mitchell, John Parker [University of Tennessee (UT); Klibisz, Aleksander [University of Tennessee (UT); Plank, James [University of Tennessee (UT)

    2016-01-01

    One of the key impediments to the success of current neuromorphic computing architectures is the issue of how best to program them. Evolutionary optimization (EO) is one promising programming technique; in particular, its wide applicability makes it especially attractive for neuromorphic architectures, which can have many different characteristics. In this paper, we explore different facets of EO on a spiking neuromorphic computing model called DANNA. We focus on the performance of EO in the design of our DANNA simulator, and on how to structure EO on both multicore and massively parallel computing systems. We evaluate how our parallel methods impact the performance of EO on Titan, the U.S.'s largest open science supercomputer, and BOB, a Beowulf-style cluster of Raspberry Pi's. We also focus on how to improve the EO by evaluating commonality in higher performing neural networks, and present the result of a study that evaluates the EO performed by Titan.

  6. Acoustic network event classification using swarm optimization

    Science.gov (United States)

    Burman, Jerry

    2013-05-01

    Classifying acoustic signals detected by distributed sensor networks is a difficult problem due to the wide variations that can occur in the transmission of terrestrial, subterranean, seismic and aerial events. An acoustic event classifier was developed that uses particle swarm optimization to perform a flexible time correlation of a sensed acoustic signature to reference data. In order to mitigate the effects from interference such as multipath, the classifier fuses signatures from multiple sensors to form a composite sensed acoustic signature and then automatically matches the composite signature with reference data. The approach can classify all types of acoustic events but is particularly well suited to explosive events such as gun shots, mortar blasts and improvised explosive devices that produce an acoustic signature having a shock wave component that is aperiodic and non-linear. The classifier was applied to field data and yielded excellent results in terms of reconstructing degraded acoustic signatures from multiple sensors and in classifying disparate acoustic events.

  7. Low Cost Wireless Sensor Network for Continuous Bridge monitoring

    DEFF Research Database (Denmark)

    Han, Bo; Kalis, A; Tragas, P

    2012-01-01

    Continuous monitoring wireless sensor networks (WSN) are considered as one of the most promising means to harvest information from large structures in order to assist in structural health monitoring and management. At the same time, continuous monitoring WSNs suffer from limited network lifetimes...... the network increases. Therefore, in order for WSNs to be considered as an efficient tool to monitor the health state of large structures, their energy consumption should be reduced to a bare minimum. In this work we consider a couple of novel techniques for increasing the life-time of the sensor network......, related to both node and network architecture. Namely, we consider new node de-signs that are of low cost, low complexity, and low energy consumption. Moreover, we present a new net-work architecture for such small nodes, that would enable them to reach a base station at large distances from the network...

  8. OPTIMIZATION METHODS FOR HYDROECOLOGICAL MONITORING SYSTEMS

    Directory of Open Access Journals (Sweden)

    Inna Pivovarova

    2016-09-01

    Full Text Available The paper describes current approaches to the rational distribution of monitoring stations. A short review and the organization of the system of hydro-geological observations in different countries are presented. On the basis of real data we propose a solution to the problem of how to calculate the average area per one hydrological station, which is the main indicator of the efficiency and performance of the monitoring system in general. We conclude that a comprehensive approach to the monitoring system organization is important, because only hydrometric and hydrochemical activities coordinated in time provide possibilities needed to analyse the underline causes of the observed pollutants content dynamics in water bodies in the long term.

  9. Design and validation of wireless acceleration sensor network for structural health monitoring

    Institute of Scientific and Technical Information of China (English)

    Yu Yan; Ou Jinping

    2006-01-01

    A wireless sensor network is proposed to monitor the acceleration of structures for the purpose of structural health monitoring of civil engineering structures. Using commercially available parts, several modules are constructed and integrated into complete wireless sensors and base stations. The communication protocol is designed and the fusion arithmetic of the temperature and acceleration is embedded in the wireless sensor node so that the measured acceleration values are more accurate. Measures are adopted to finish energy optimization, which is an important issue for a wireless sensor network. The test is performed on an offshore platform model, and the experimental results are given to show the feasibility of the designed wireless sensor network.

  10. Groundwater remediation optimization using artificial neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Rogers, L. L., LLNL

    1998-05-01

    One continuing point of research in optimizing groundwater quality management is reduction of computational burden which is particularly limiting in field-scale applications. Often evaluation of a single pumping strategy, i.e. one call to the groundwater flow and transport model (GFTM) may take several hours on a reasonably fast workstation. For computational flexibility and efficiency, optimal groundwater remediation design at Lawrence Livermore National Laboratory (LLNL) has relied on artificial neural networks (ANNS) trained to approximate the outcome of 2-D field-scale, finite difference/finite element GFTMs. The search itself has been directed primarily by the genetic algorithm (GA) or the simulated annealing (SA) algorithm. This approach has advantages of (1) up to a million fold increase in speed of remediation pattern assessment during the searches and sensitivity analyses for the 2-D LLNL work, (2) freedom from sequential runs of the GFTM (enables workstation farming), and (3) recycling of the knowledge base (i.e. runs of the GFTM necessary to train the ANNS). Reviewed here are the background and motivation for such work, recent applications, and continuing issues of research.

  11. District Heating Network Design and Configuration Optimization with Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    Hongwei Li

    2013-12-01

    Full Text Available In this paper, the configuration of a district heating network which connects from the heating plant to the end users is optimized. Each end user in the network represents a building block. The connections between the heat generation plant and the end users are represented with mixed integer and the pipe friction and heat loss formulations are non-linear. In order to find the optimal district heating network configuration, genetic algorithm which handles the mixed integer nonlinear programming problem is chosen. The network configuration is represented with binary and integer encoding and is optimized in terms of the net present cost. The optimization results indicates that the optimal DH network configuration is determined by multiple factors such as the consumer heating load, the distance between the heating plant to the consumer, the design criteria regarding the pressure and temperature limitation, as well as the corresponding network heat loss.

  12. Neural network for constrained nonsmooth optimization using Tikhonov regularization.

    Science.gov (United States)

    Qin, Sitian; Fan, Dejun; Wu, Guangxi; Zhao, Lijun

    2015-03-01

    This paper presents a one-layer neural network to solve nonsmooth convex optimization problems based on the Tikhonov regularization method. Firstly, it is shown that the optimal solution of the original problem can be approximated by the optimal solution of a strongly convex optimization problems. Then, it is proved that for any initial point, the state of the proposed neural network enters the equality feasible region in finite time, and is globally convergent to the unique optimal solution of the related strongly convex optimization problems. Compared with the existing neural networks, the proposed neural network has lower model complexity and does not need penalty parameters. In the end, some numerical examples and application are given to illustrate the effectiveness and improvement of the proposed neural network. Copyright © 2014 Elsevier Ltd. All rights reserved.

  13. Improving resource utilization in hierarchy network by optimizing topological structure

    Science.gov (United States)

    Liu, G. L.; Peng, H. P.; Li, L. X.; Sun, F.; Yang, Y. X.

    2012-02-01

    We study the performance of peer-to-peer (P2P) network built on the top of hierarchy topological structure of local area networks (LAN). We find that the topological structure of the underlying physical network has significant impacts on the resource utilization of the P2P overlay network. The larger size of the physical network is, the lower resource utilization of the overlay network is. Through optimizing the topological structure of physical network, we propose two novel schemes to improve the resource utilization. The experimental results show that in any case the resource utilization of P2P network can always achieve 100% by these two schemes.

  14. Optimization-based topology identification of complex networks

    Institute of Scientific and Technical Information of China (English)

    Tang Sheng-Xue; Chen Li; He Yi-Gang

    2011-01-01

    In many cases,the topological structures of a complex network are unknown or uncertain,and it is of significance to identify the exact topological structure.An optimization-based method of identifying the topological structure of a complex network is proposed in this paper.Identification of the exact network topological structure is converted into a minimal optimization problem by using the estimated network.Then,an improved quantum-behaved particle swarm optimization algorithm is used to solve the optimization problem.Compared with the previous adaptive synchronizationbased method,the proposed method is simple and effective and is particularly valid to identify the topological structure of synchronization complex networks.In some cases where the states of a complex network are only partially observable,the exact topological structure of a network can also be identified by using the proposed method.Finally,numerical simulations are provided to show the effectiveness of the proposed method.

  15. PSO optimized Feed Forward Neural Network for offline Signature Classification

    Directory of Open Access Journals (Sweden)

    Pratik R. Hajare

    2015-07-01

    Full Text Available The paper is based on feed forward neural network (FFNN optimization by particle swarm intelligence (PSI used to provide initial weights and biases to train neural network. Once the weights and biases are found using Particle swarm optimization (PSO with neural network used as training algorithm for specified epoch, the same are used to train the neural network for training and classification of benchmark problems. Further the approach is tested for offline signature classifications. A comparison is made between normal FFNN with random weights and biases and FFNN with particle swarm optimized weights and biases. Firstly, the performance is tested on two benchmark databases for neural network, The Breast Cancer Database and the Diabetic Database. Result shows that neural network performs better with initial weights and biases obtained by Particle Swarm optimization. The network converges faster with PSO obtained initial weights and biases for FFNN and classification accuracy is increased.

  16. Surface Water Quality Monitoring Site Optimization for Poyang Lake, the Largest Freshwater Lake in China

    Directory of Open Access Journals (Sweden)

    Hua Wang

    2014-11-01

    Full Text Available In this paper, we propose a coupled method to optimize the surface water quality monitoring sites for a huge freshwater lake based on field investigations, mathematical analysis, and numerical simulation tests. Poyang Lake, the largest freshwater lake in China, was selected as the research area. Based on the field investigated water quality data in the 5 years from 2008 to 2012, the water quality inter-annual variation coefficients at all the present sites and the water quality correlation coefficients between adjacent sites were calculated and analyzed to present an optimization scheme. A 2-D unsteady water quality model was established to get the corresponding water quality data at the optimized monitoring sites, which were needed for the rationality test on the optimized monitoring network. We found that: (1 the water quality of Piaoshan (No. 10 fluctuated most distinguishably and the inter-annual variation coefficient of NH3-N and TP could reach 99.77% and 73.92%, respectively. The four studied indexes were all closely related at Piaoshan (No. 10 and Tangyin (No. 11, and the correlation coefficients of COD and NH3-N could reach 0.91 and 0.94 separately. (2 It was suggested that the present site No. 10 be removed to avoid repeatability, and it was suggested that the three sites of Changling, Huzhong, and Nanjiang be added to improve the representativeness of the monitoring sites. (3 According to the rationality analysis, the 21 optimized water quality monitoring sites could scientifically replace the primary network, and the new monitoring network could better reflect the water quality of the whole lake.

  17. Edge orientation for optimizing controllability of complex networks.

    Science.gov (United States)

    Xiao, Yan-Dong; Lao, Song-Yang; Hou, Lv-Lin; Bai, Liang

    2014-10-01

    Recently, as the controllability of complex networks attracts much attention, how to design and optimize the controllability of networks has become a common and urgent problem in the field of controlling complex networks. Previous work focused on the structural perturbation and neglected the role of edge direction to optimize the network controllability. In a recent work [Phys. Rev. Lett. 103, 228702 (2009)], the authors proposed a simple method to enhance the synchronizability of networks by assignment of link direction while keeping network topology unchanged. However, the controllability is fundamentally different from synchronization. In this work, we systematically propose the definition of assigning direction to optimize controllability, which is called the edge orientation for optimal controllability problem (EOOC). To solve the EOOC problem, we construct a switching network and transfer the EOOC problem to find the maximum independent set of the switching network. We prove that the principle of our optimization method meets the sense of unambiguity and optimum simultaneously. Furthermore, the relationship between the degree-degree correlations and EOOC are investigated by experiments. The results show that the disassortativity pattern could weaken the orientation for optimal controllability, while the assortativity pattern has no correlation with EOOC. All the experimental results of this work verify that the network structure determines the network controllability and the optimization effects.

  18. Study on optimization control method based on artificial neural network

    Institute of Scientific and Technical Information of China (English)

    FU Hua; SUN Shao-guang; XU Zhen-Iiang

    2005-01-01

    In the goal optimization and control optimization process the problems with common artificial neural network algorithm are unsure convergence, insufficient post-training network precision, and slow training speed, in which partial minimum value question tends to occur. This paper conducted an in-depth study on the causes of the limitations of the algorithm, presented a rapid artificial neural network algorithm, which is characterized by integrating multiple algorithms and by using their complementary advantages. The salient feature of the method is self-organization, which can effectively prevent the optimized results from tending to be partial minimum values. Overall optimization can be achieved with this method, goal function can be searched for in overall scope. With optimization control of coal mine ventilator as a practical application, the paper proves that by integrating multiple artificial neural network algorithms, best control optimization and goal optimized can be achieved.

  19. OPTIMAL WELL LOCATOR (OWL): A SCREENING TOOL FOR EVALUATING LOCATIONS OF MONITORING WELLS: USER'S GUIDE VERSION 1.2

    Science.gov (United States)

    The Optimal Well Locator ( OWL) program was designed and developed by USEPA to be a screening tool to evaluate and optimize the placement of wells in long term monitoring networks at small sites. The first objective of the OWL program is to allow the user to visualize the change ...

  20. Signal processing for solar array monitoring, fault detection, and optimization

    CERN Document Server

    Braun, Henry; Spanias, Andreas

    2012-01-01

    Although the solar energy industry has experienced rapid growth recently, high-level management of photovoltaic (PV) arrays has remained an open problem. As sensing and monitoring technology continues to improve, there is an opportunity to deploy sensors in PV arrays in order to improve their management. In this book, we examine the potential role of sensing and monitoring technology in a PV context, focusing on the areas of fault detection, topology optimization, and performance evaluation/data visualization. First, several types of commonly occurring PV array faults are considered and detection algorithms are described. Next, the potential for dynamic optimization of an array's topology is discussed, with a focus on mitigation of fault conditions and optimization of power output under non-fault conditions. Finally, monitoring system design considerations such as type and accuracy of measurements, sampling rate, and communication protocols are considered. It is our hope that the benefits of monitoring presen...

  1. A Bi-directional Energy Splitable Model for Energy Optimization in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    A. Rajeswari

    2011-01-01

    Full Text Available Wireless Sensor Networks is a budding  prototype of networking and computing, where a node may be self powered and individual node have the capability to sense and compute and communicate. Wireless Sensor Networks have been proposed for variety of applications such as Industrial control and monitoring and home automation and consumer electronics and security andMilitary sensing, Asset tracking and supply chain management, Intelligent Agriculture, Missile directing, Fire alarming, Landslide Warning, Environmental monitoring and health monitoring and commercial applications. In Wireless Sensor Network large number of nodes are deployed randomly. Depends on the network architecture the application may be personalized such as Energy Efficiency, Routing and Power Management and data dissemination. Energy Optimization involves in minimizing an energy expenditure and maximizing the lifetime of the complete network. In the proposed work, the placement of nodes are directly involved with residual energy. Energy Optimization in sensor network is very difficult task to achieve it. The optimization of energy is performed through Bidirectional Energy Splitable Model. The data flow in both forward and backward directions are considered, In order to achieve the best QOS in transmission, some parameters such as load, delay and direction of individual nodes are considered. A mathematical model is developed to determine the data flow of  individual node based on the residual energy.

  2. Exploiting node mobility for energy optimization in wireless sensor networks

    Science.gov (United States)

    El-Moukaddem, Fatme Mohammad

    Wireless Sensor Networks (WSNs) have become increasingly available for data-intensive applications such as micro-climate monitoring, precision agriculture, and audio/video surveillance. A key challenge faced by data-intensive WSNs is to transmit the sheer amount of data generated within an application's lifetime to the base station despite the fact that sensor nodes have limited power supplies such as batteries or small solar panels. The availability of numerous low-cost robotic units (e.g. Robomote and Khepera) has made it possible to construct sensor networks consisting of mobile sensor nodes. It has been shown that the controlled mobility offered by mobile sensors can be exploited to improve the energy efficiency of a network. In this thesis, we propose schemes that use mobile sensor nodes to reduce the energy consumption of data-intensive WSNs. Our approaches differ from previous work in two main aspects. First, our approaches do not require complex motion planning of mobile nodes, and hence can be implemented on a number of low-cost mobile sensor platforms. Second, we integrate the energy consumption due to both mobility and wireless communications into a holistic optimization framework. We consider three problems arising from the limited energy in the sensor nodes. In the first problem, the network consists of mostly static nodes and contains only a few mobile nodes. In the second and third problems, we assume essentially that all nodes in the WSN are mobile. We first study a new problem called max-data mobile relay configuration (MMRC ) that finds the positions of a set of mobile sensors, referred to as relays, that maximize the total amount of data gathered by the network during its lifetime. We show that the MMRC problem is surprisingly complex even for a trivial network topology due to the joint consideration of the energy consumption of both wireless communication and mechanical locomotion. We present optimal MMRC algorithms and practical distributed

  3. LinkMind: Link Optimization in Swarming Mobile Sensor Networks

    DEFF Research Database (Denmark)

    Ngo, Trung Dung

    2012-01-01

    optimization of swarming mobile sensor networks. The new method is based on combination of the artificial potential force guaranteeing connectivities of the mobile sensor nodes and the max-flow min-cut theorem of graph theory ensuring optimization of the network link capacity. The developed algorithm...

  4. Neural Network for Optimization of Existing Control Systems

    DEFF Research Database (Denmark)

    Madsen, Per Printz

    1995-01-01

    The purpose of this paper is to develop methods to use Neural Network based Controllers (NNC) as an optimization tool for existing control systems.......The purpose of this paper is to develop methods to use Neural Network based Controllers (NNC) as an optimization tool for existing control systems....

  5. Optimization Techniques for Analysis of Biological and Social Networks

    Science.gov (United States)

    2012-03-28

    systematic fashion under a unifying theoretical and algorithmic framework . Optimization, Complex Networks, Social Network Analysis, Computational...analyzing a new metaheuristic technique, variable objective search. 3. Experimentation and application: Implement the proposed algorithms, test and fine...exact solutions are presented. In [3], we introduce the variable objective search framework for combinatorial optimization. The method utilizes

  6. Energy Monitoring and Management Mechanism for Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Papadakis Andreas

    2016-01-01

    Full Text Available In this work we discuss a mechanism for the monitoring and management of energy consumption in Wireless Sensor Networks. We consider that the Wireless Sensor Network consists of nodes that operate individually and collaborate with each other. After briefly discussing the typical network topologies and associating with the expected communications needs, we describe a conceptual framework for monitoring and managing the energy consumption on per process basis.

  7. Learning Bayesian Networks from Data by Particle Swarm Optimization

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    Learning Bayesian network is an NP-hard problem. When the number of variables is large, the process of searching optimal network structure could be very time consuming and tends to return a structure which is local optimal. The particle swarm optimization (PSO) was introduced to the problem of learning Bayesian networks and a novel structure learning algorithm using PSO was proposed. To search in directed acyclic graphs spaces efficiently, a discrete PSO algorithm especially for structure learning was proposed based on the characteristics of Bayesian networks. The results of experiments show that our PSO based algorithm is fast for convergence and can obtain better structures compared with genetic algorithm based algorithms.

  8. Optimal Grouping and Matching for Network-Coded Cooperative Communications

    Energy Technology Data Exchange (ETDEWEB)

    Sharma, S; Shi, Y; Hou, Y T; Kompella, S; Midkiff, S F

    2011-11-01

    Network-coded cooperative communications (NC-CC) is a new advance in wireless networking that exploits network coding (NC) to improve the performance of cooperative communications (CC). However, there remains very limited understanding of this new hybrid technology, particularly at the link layer and above. This paper fills in this gap by studying a network optimization problem that requires joint optimization of session grouping, relay node grouping, and matching of session/relay groups. After showing that this problem is NP-hard, we present a polynomial time heuristic algorithm to this problem. Using simulation results, we show that our algorithm is highly competitive and can produce near-optimal results.

  9. GENETIC ALGORITHM BASED CONCEPT DESIGN TO OPTIMIZE NETWORK LOAD BALANCE

    Directory of Open Access Journals (Sweden)

    Ashish Jain

    2012-07-01

    Full Text Available Multiconstraints optimal network load balancing is an NP-hard problem and it is an important part of traffic engineering. In this research we balance the network load using classical method (brute force approach and dynamic programming is used but result shows the limitation of this method but at a certain level we recognized that the optimization of balanced network load with increased number of nodes and demands is intractable using the classical method because the solution set increases exponentially. In such case the optimization techniques like evolutionary techniques can employ for optimizing network load balance. In this paper we analyzed proposed classical algorithm and evolutionary based genetic approach is devise as well as proposed in this paper for optimizing the balance network load.

  10. Self-Optimization of LTE Networks Utilizing Celnet Xplorer

    CERN Document Server

    Buvaneswari, A; Polakos, Paul; Buvaneswari, Arumugam

    2010-01-01

    In order to meet demanding performance objectives in Long Term Evolution (LTE) networks, it is mandatory to implement highly efficient, autonomic self-optimization and configuration processes. Self-optimization processes have already been studied in second generation (2G) and third generation (3G) networks, typically with the objective of improving radio coverage and channel capacity. The 3rd Generation Partnership Project (3GPP) standard for LTE self-organization of networks (SON) provides guidelines on self-configuration of physical cell ID and neighbor relation function and self-optimization for mobility robustness, load balancing, and inter-cell interference reduction. While these are very important from an optimization perspective of local phenomenon (i.e., the eNodeB's interaction with its neighbors), it is also essential to architect control algorithms to optimize the network as a whole. In this paper, we propose a Celnet Xplorer-based SON architecture that allows detailed analysis of network performan...

  11. Optimal Planning of Communication System of CPS for Distribution Network

    Directory of Open Access Journals (Sweden)

    Ting Yang

    2017-01-01

    Full Text Available IoT is the technical basis to realize the CPS (Cyber Physical System for distribution networks, with which the complex system becomes more intelligent and controllable. Because of the multihop and self-organization characteristics, the large-scale heterogeneous CPS network becomes more difficult to plan. Using topological potential theory, one of typical big data analysis technologies, this paper proposed a novel optimal CPS planning model. Topological potential equalization is considered as the optimization objective function in heterogeneous CPS network with the constraints of communication requirements, physical infrastructures, and network reliability. An improved binary particle swarm optimization algorithm is proposed to solve this complex optimal problem. Two IEEE classic examples are adopted in the simulation, and the results show that, compared with benchmark algorithms, our proposed method can provide an effective topology optimization scheme to improve the network reliability and transmitting performance.

  12. Research on Optimization Operation of Urban Gas Pipeline Network

    Institute of Scientific and Technical Information of China (English)

    田一梅; 迟海燕; 李鸿; 周颖

    2003-01-01

    The optimization operation of gas pipeline network is investigated in this paper. Based on the theories of system optimization and the multi-object decision, a mathematical model about the multi-object optimization operation of gas pipeline network is established, in line with the demand of urban gas pipeline network operation. At the same time, an effective solution of the mathematical model is presented. A calculating software about optimization operation is compiled, coupling the actual operation of gas pipeline network. It can be applied to the operation of the gas pipeline network. The software was examined by real examples. The results indicated that 2.13%00 energy consumption and 3.12%oo gas supply cost can be reduced through optimization operation.

  13. UMTS network planning, optimization, and inter-operation with GSM

    CERN Document Server

    Rahnema, Moe

    2008-01-01

    UMTS Network Planning, Optimization, and Inter-Operation with GSM is an accessible, one-stop reference to help engineers effectively reduce the time and costs involved in UMTS deployment and optimization. Rahnema includes detailed coverage from both a theoretical and practical perspective on the planning and optimization aspects of UMTS, and a number of other new techniques to help operators get the most out of their networks. Provides an end-to-end perspective, from network design to optimizationIncorporates the hands-on experiences of numerous researchersSingle

  14. Optimal operation of water distribution networks under local pipe failures

    Institute of Scientific and Technical Information of China (English)

    TIAN Yi-mei; G.Y.FU; CHI Hai-yan; LIU Ye

    2007-01-01

    The optimal operation of water distribution networks under local pipe failures, such as water main breaks, was proposed.Based on a hydraulic analysis and a simulation of water distribution networks, a macroscopic model for a network under a local pipe failure was established by the statistical regression. After the operation objectives under a local pipe failure were determined, the optimal operation model was developed and solved by the genetic algorithm. The program was developed and examined by a city distribution network. The optimal operation alternative shows that the electricity cost is saved approximately 11%, the income of the water corporation is increased approximately 5%, and the pressure in the water distribution network is distributed evenly to ensure the network safe operation. Therefore, the proposed method for optimal operation under local pipe failure is feasible and cost-effective.

  15. Wireless sensor networks for structural health monitoring

    CERN Document Server

    Cao, Jiannong

    2016-01-01

    This brief covers the emerging area of wireless sensor network (WSN)-based structural health monitoring (SHM) systems, and introduces the authors’ WSN-based platform called SenetSHM. It helps the reader differentiate specific requirements of SHM applications from other traditional WSN applications, and demonstrates how these requirements are addressed by using a series of systematic approaches. The brief serves as a practical guide, explaining both the state-of-the-art technologies in domain-specific applications of WSNs, as well as the methodologies used to address the specific requirements for a WSN application. In particular, the brief offers instruction for problem formulation and problem solving based on the authors’ own experiences implementing SenetSHM. Seven concise chapters cover the development of hardware and software design of SenetSHM, as well as in-field experiments conducted while testing the platform. The brief’s exploration of the SenetSHM platform is a valuable feature for civil engine...

  16. Modeling Wireless Sensor Networks for Monitoring in Biological Processes

    DEFF Research Database (Denmark)

    Nadimi, Esmaeil

    parameters, as the use of wired sensors is impractical. In this thesis, a ZigBee based wireless sensor network was employed and only a part of the herd was monitored, as monitoring each individual animal in a large herd under practical conditions is inefficient. Investigations to show that the monitored...

  17. FREQUENCY OPTIMIZATION FOR SECURITY MONITORING OF COMPUTER SYSTEMS

    Directory of Open Access Journals (Sweden)

    Вogatyrev V.A.

    2015-03-01

    Full Text Available The subject areas of the proposed research are monitoring facilities for protection of computer systems exposed to destructive attacks of accidental and malicious nature. The interval optimization model of test monitoring for the detection of hazardous states of security breach caused by destructive attacks is proposed. Optimization function is to maximize profit in case of requests servicing in conditions of uncertainty, and intensity variance of the destructive attacks including penalties when servicing of requests is in dangerous conditions. The vector task of system availability maximization and minimization of probabilities for its downtime and dangerous conditions is proposed to be reduced to the scalar optimization problem based on the criterion of profit maximization from information services (service of requests that integrates these private criteria. Optimization variants are considered with the definition of the averaged periodic activities of monitoring and adapting of these periods to the changes in the intensity of destructive attacks. Adaptation efficiency of the monitoring frequency to changes in the activity of the destructive attacks is shown. The proposed solutions can find their application for optimization of test monitoring intervals to detect hazardous conditions of security breach that makes it possible to increase the system effectiveness, and specifically, to maximize the expected profit from information services.

  18. LinkMind: link optimization in swarming mobile sensor networks.

    Science.gov (United States)

    Ngo, Trung Dung

    2011-01-01

    A swarming mobile sensor network is comprised of a swarm of wirelessly connected mobile robots equipped with various sensors. Such a network can be applied in an uncertain environment for services such as cooperative navigation and exploration, object identification and information gathering. One of the most advantageous properties of the swarming wireless sensor network is that mobile nodes can work cooperatively to organize an ad-hoc network and optimize the network link capacity to maximize the transmission of gathered data from a source to a target. This paper describes a new method of link optimization of swarming mobile sensor networks. The new method is based on combination of the artificial potential force guaranteeing connectivities of the mobile sensor nodes and the max-flow min-cut theorem of graph theory ensuring optimization of the network link capacity. The developed algorithm is demonstrated and evaluated in simulation.

  19. A Projection Neural Network for Constrained Quadratic Minimax Optimization.

    Science.gov (United States)

    Liu, Qingshan; Wang, Jun

    2015-11-01

    This paper presents a projection neural network described by a dynamic system for solving constrained quadratic minimax programming problems. Sufficient conditions based on a linear matrix inequality are provided for global convergence of the proposed neural network. Compared with some of the existing neural networks for quadratic minimax optimization, the proposed neural network in this paper is capable of solving more general constrained quadratic minimax optimization problems, and the designed neural network does not include any parameter. Moreover, the neural network has lower model complexities, the number of state variables of which is equal to that of the dimension of the optimization problems. The simulation results on numerical examples are discussed to demonstrate the effectiveness and characteristics of the proposed neural network.

  20. LinkMind: Link Optimization in Swarming Mobile Sensor Networks

    Directory of Open Access Journals (Sweden)

    Trung Dung Ngo

    2011-08-01

    Full Text Available A swarming mobile sensor network is comprised of a swarm of wirelessly connected mobile robots equipped with various sensors. Such a network can be applied in an uncertain environment for services such as cooperative navigation and exploration, object identification and information gathering. One of the most advantageous properties of the swarming wireless sensor network is that mobile nodes can work cooperatively to organize an ad-hoc network and optimize the network link capacity to maximize the transmission of gathered data from a source to a target. This paper describes a new method of link optimization of swarming mobile sensor networks. The new method is based on combination of the artificial potential force guaranteeing connectivities of the mobile sensor nodes and the max-flow min-cut theorem of graph theory ensuring optimization of the network link capacity. The developed algorithm is demonstrated and evaluated in simulation.

  1. Topology Optimization for Energy Management in Underwater Sensor Networks

    Science.gov (United States)

    2015-02-01

    1 To appear in International Journal of Control as a regular paper Topology Optimization for Energy Management in Underwater Sensor Networks⋆ Devesh... topology that maximizes the probability of successful search (of a target) over a surveillance region. In a two-stage optimization, a genetic algorithm (GA...Adaptation to energy variations across the network is shown to be manifested as a change in the optimal network topology by using sensing and

  2. Supplemental Assessment of the Y-12 Groundwater Protection Program Using Monitoring and Remediation Optimization System Software

    Energy Technology Data Exchange (ETDEWEB)

    Elvado Environmental LLC; GSI Environmental LLC

    2009-01-01

    A supplemental quantitative assessment of the Groundwater Protection Program (GWPP) at the Y-12 National Security Complex (Y-12) in Oak Ridge, TN was performed using the Monitoring and Remediation Optimization System (MAROS) software. This application was previously used as part of a similar quantitative assessment of the GWPP completed in December 2005, hereafter referenced as the 'baseline' MAROS assessment (BWXT Y-12 L.L.C. [BWXT] 2005). The MAROS software contains modules that apply statistical analysis techniques to an existing GWPP analytical database in conjunction with hydrogeologic factors, regulatory framework, and the location of potential receptors, to recommend an improved groundwater monitoring network and optimum sampling frequency for individual monitoring locations. The goal of this supplemental MAROS assessment of the Y-12 GWPP is to review and update monitoring network optimization recommendations resulting from the 2005 baseline report using data collected through December 2007. The supplemental MAROS assessment is based on the findings of the baseline MAROS assessment and includes only the groundwater sampling locations (wells and natural springs) currently granted 'Active' status in accordance with the Y-12 GWPP Monitoring Optimization Plan (MOP). The results of the baseline MAROS assessment provided technical rationale regarding the 'Active' status designations defined in the MOP (BWXT 2006). One objective of the current report is to provide a quantitative review of data collected from Active but infrequently sampled wells to confirm concentrations at these locations. This supplemental MAROS assessment does not include the extensive qualitative evaluations similar to those presented in the baseline report.

  3. Wireless Sensor Network for Wearable Physiological Monitoring

    OpenAIRE

    P. S. Pandian; K. P. Safeer; Pragati Gupta; D. T. Shakunthala; B. S. Sundersheshu; V. C. Padaki

    2008-01-01

    Wearable physiological monitoring system consists of an array of sensors embedded into the fabric of the wearer to continuously monitor the physiological parameters and transmit wireless to a remote monitoring station. At the remote monitoring station the data is correlated to study the overall health status of the wearer. In the conventional wearable physiological monitoring system, the sensors are integrated at specific locations on the vest and are interconnected to the wearable data acqui...

  4. The Distributed Network Monitoring Model with Bounded Delay Constraints

    Institute of Scientific and Technical Information of China (English)

    LIU Xiang-hui; YIN Jian-ping; LU Xi-cheng; CAI Zhi-ping; ZHAO Jian-min

    2004-01-01

    We address the problem of optimizing a distributed monitoring system and the goal of the optimization is to reduce the cost of deployment of the monitoring infrastructure by identifying a minimum aggregating set subject to delay constraint on the aggregating path. We show that this problem is NP-hard and propose approximation algorithm proving the approximation ratio with ln m+1, where is the number of monitoring nodes. At last we extend our modal with more constraint of bounded delay variation.

  5. Hierarchical control based on Hopfield network for nonseparable optimization problems

    Institute of Scientific and Technical Information of China (English)

    2005-01-01

    The nonseparable optimization control problem is considered, where the overall objective function is not of an additive form with respect to subsystems. Since there exists the problem that computation is very slow when using iterative algorithms in multiobjective optimization, Hopfield optimization hierarchical network based on IPM is presented to overcome such slow computation difficulty. Asymptotic stability of this Hopfield network is proved and its equilibrium point is the optimal point of the original problem. The simulation shows that the net is effective to deal with the optimization control problem for large-scale nonseparable steady state systems.

  6. Perspective Application of Passive Optical Network with Optimized Bus Topology

    Directory of Open Access Journals (Sweden)

    P. Lafata

    2012-06-01

    Full Text Available Passive optical networks (PONs represent a promising solution for modern access telecommunication networks.These networks are able to meet the increasing demands on transmission rate for demanding multimedia services,while they can offer typical shared transmission speed of 1.25 or 2.5 Gbps. The major role in deploying opticaldistribution networks ODNs plays the maximum attenuable loss, which is caused mainly by passive optical splitters.This paper proposes an innovative application of passive optical networks with optimized bus topology especially forlocal backbone data networks. Due to using only passive components, it is necessary to optimize certain parameters,especially an overall attenuation balance. Considering the possibility of such optimization, the passive optical networkwith optimized bus topology provides several interesting opportunities for specific applications. This paper will presentselected aspects of passive optical networks and splitters with asymmetric splitting ratio. The essential part is focusedon the practical demonstration of their use to optimize the passive optical network with bus topology, which acts as alocal backbone network for structured cabling systems, and for local data networks in large buildings.

  7. Dynamic groundwater monitoring networks: a manageable method for reviewing sampling frequency.

    Science.gov (United States)

    Moreau-Fournier, Magali F; Daughney, Christopher J

    2012-12-01

    Optimization of a water quality network through a change in sampling frequency is the only way to increase cost-efficiency without any reduction in the robustness of the data. Existing techniques define optimal sampling frequency based on analysis of historical data from the monitoring network under investigation. Their application to a large network comprised of many sites and many monitored parameters is both technical and challenging. This paper presents a simple non-parametric method for reviewing sampling frequency that is consistent with highly censored environmental data and oriented towards reduction of sampling frequency as a cost-saving measure. Based on simple descriptive statistics, the method is applicable to large networks with long time series and many monitored parameters. The method also provides metrics for interpretation of newly collected data, which enables identification of sites for which a future change in sampling frequency may be necessary, ensuring that the monitoring network is both current and adaptive. Application of this method to the New Zealand National Groundwater Monitoring Programme indicates that reduction of sampling frequency at any site would result in a significant loss of information. This paper also discusses the potential for reducing analysis frequency as an alternative to reduction of sampling frequency.

  8. Optimizing controllability of complex networks by minimum structural perturbations.

    Science.gov (United States)

    Wang, Wen-Xu; Ni, Xuan; Lai, Ying-Cheng; Grebogi, Celso

    2012-02-01

    To drive a large, complex, networked dynamical system toward some desired state using as few external signals as possible is a fundamental issue in the emerging field of controlling complex networks. Optimal control is referred to the situation where such a network can be fully controlled using only one driving signal. We propose a general approach to optimizing the controllability of complex networks by judiciously perturbing the network structure. The principle of our perturbation method is validated theoretically and demonstrated numerically for homogeneous and heterogeneous random networks and for different types of real networks as well. The applicability of our method is discussed in terms of the relative costs of establishing links and imposing external controllers. Besides the practical usage of our approach, its implementation elucidates, interestingly, the intricate relationship between certain structural properties of the network and its controllability.

  9. Designing Networks: A Mixed-Integer Linear Optimization Approach

    CERN Document Server

    Gounaris, Chrysanthos E; Kevrekidis, Ioannis G; Floudas, Christodoulos A

    2015-01-01

    Designing networks with specified collective properties is useful in a variety of application areas, enabling the study of how given properties affect the behavior of network models, the downscaling of empirical networks to workable sizes, and the analysis of network evolution. Despite the importance of the task, there currently exists a gap in our ability to systematically generate networks that adhere to theoretical guarantees for the given property specifications. In this paper, we propose the use of Mixed-Integer Linear Optimization modeling and solution methodologies to address this Network Generation Problem. We present a number of useful modeling techniques and apply them to mathematically express and constrain network properties in the context of an optimization formulation. We then develop complete formulations for the generation of networks that attain specified levels of connectivity, spread, assortativity and robustness, and we illustrate these via a number of computational case studies.

  10. Global Optimization for Transport Network Expansion and Signal Setting

    Directory of Open Access Journals (Sweden)

    Haoxiang Liu

    2015-01-01

    Full Text Available This paper proposes a model to address an urban transport planning problem involving combined network design and signal setting in a saturated network. Conventional transport planning models usually deal with the network design problem and signal setting problem separately. However, the fact that network capacity design and capacity allocation determined by network signal setting combine to govern the transport network performance requires the optimal transport planning to consider the two problems simultaneously. In this study, a combined network capacity expansion and signal setting model with consideration of vehicle queuing on approaching legs of intersection is developed to consider their mutual interactions so that best transport network performance can be guaranteed. We formulate the model as a bilevel program and design an approximated global optimization solution method based on mixed-integer linearization approach to solve the problem, which is inherently nnonlinear and nonconvex. Numerical experiments are conducted to demonstrate the model application and the efficiency of solution algorithm.

  11. Multilayer Traffic Network Optimized by Multiobjective Genetic Clustering Algorithm

    Science.gov (United States)

    Wen, Feng; Gen, Mitsuo; Yu, Xinjie

    This paper introduces a multilayer traffic network model and traffic network clustering method for solving the route selection problem (RSP) in car navigation system (CNS). The purpose of the proposed method is to reduce the computation time of route selection substantially with acceptable loss of accuracy by preprocessing the large size traffic network into new network form. The proposed approach further preprocesses the traffic network than the traditional hierarchical network method by clustering method. The traffic network clustering considers two criteria. We specify a genetic clustering algorithm for traffic network clustering and use NSGA-II for calculating the multiple objective Pareto optimal set. The proposed method can overcome the size limitations when solving route selection in CNS. Solutions provided by the proposed algorithm are compared with the optimal solutions to analyze and quantify the loss of accuracy.

  12. Putting Man in the Machine: Exploiting Expertise to Enhance Multiobjective Design of Water Supply Monitoring Network

    Science.gov (United States)

    Bode, F.; Nowak, W.; Reed, P. M.; Reuschen, S.

    2016-12-01

    Drinking-water well catchments need effective early-warning monitoring networks. Groundwater water supply wells in complex urban environments are in close proximity to a myriad of potential industrial pollutant sources that could irreversibly damage their source aquifers. These urban environments pose fiscal and physical challenges to designing monitoring networks. Ideal early-warning monitoring networks would satisfy three objectives: to detect (1) all potential contaminations within the catchment (2) as early as possible before they reach the pumping wells, (3) while minimizing costs. Obviously, the ideal case is nonexistent, so we search for tradeoffs using multiobjective optimization. The challenge of this optimization problem is the high number of potential monitoring-well positions (the search space) and the non-linearity of the underlying groundwater flow-and-transport problem. This study evaluates (1) different ways to effectively restrict the search space in an efficient way, with and without expert knowledge, (2) different methods to represent the search space during the optimization and (3) the influence of incremental increases in uncertainty in the system. Conductivity, regional flow direction and potential source locations are explored as key uncertainties. We show the need and the benefit of our methods by comparing optimized monitoring networks for different uncertainty levels with networks that seek to effectively exploit expert knowledge. The study's main contributions are the different approaches restricting and representing the search space. The restriction algorithms are based on a point-wise comparison of decision elements of the search space. The representation of the search space can be either binary or continuous. For both cases, the search space must be adjusted properly. Our results show the benefits and drawbacks of binary versus continuous search space representations and the high potential of automated search space restriction

  13. Network synchronization: optimal and pessimal scale-free topologies

    Energy Technology Data Exchange (ETDEWEB)

    Donetti, Luca [Departamento de Electronica y Tecnologia de Computadores and Instituto de Fisica Teorica y Computacional Carlos I, Facultad de Ciencias, Universidad de Granada, 18071 Granada (Spain); Hurtado, Pablo I; Munoz, Miguel A [Departamento de Electromagnetismo y Fisica de la Materia and Instituto Carlos I de Fisica Teorica y Computacional Facultad de Ciencias, Universidad de Granada, 18071 Granada (Spain)], E-mail: mamunoz@onsager.ugr.es

    2008-06-06

    By employing a recently introduced optimization algorithm we construct optimally synchronizable (unweighted) networks for any given scale-free degree distribution. We explore how the optimization process affects degree-degree correlations and observe a generic tendency toward disassortativity. Still, we show that there is not a one-to-one correspondence between synchronizability and disassortativity. On the other hand, we study the nature of optimally un-synchronizable networks, that is, networks whose topology minimizes the range of stability of the synchronous state. The resulting 'pessimal networks' turn out to have a highly assortative string-like structure. We also derive a rigorous lower bound for the Laplacian eigenvalue ratio controlling synchronizability, which helps understanding the impact of degree correlations on network synchronizability.

  14. A generalized optimization principle for asymmetric branching in fluidic networks

    Science.gov (United States)

    Stephenson, David; Lockerby, Duncan A.

    2016-07-01

    When applied to a branching network, Murray's law states that the optimal branching of vascular networks is achieved when the cube of the parent channel radius is equal to the sum of the cubes of the daughter channel radii. It is considered integral to understanding biological networks and for the biomimetic design of artificial fluidic systems. However, despite its ubiquity, we demonstrate that Murray's law is only optimal (i.e. maximizes flow conductance per unit volume) for symmetric branching, where the local optimization of each individual channel corresponds to the global optimum of the network as a whole. In this paper, we present a generalized law that is valid for asymmetric branching, for any cross-sectional shape, and for a range of fluidic models. We verify our analytical solutions with the numerical optimization of a bifurcating fluidic network for the examples of laminar, turbulent and non-Newtonian fluid flows.

  15. Using Wireless Sensor Networks to Achieve Intelligent Monitoring for High-Temperature Gas-Cooled Reactor

    Directory of Open Access Journals (Sweden)

    Jianghai Li

    2017-01-01

    Full Text Available High-temperature gas-cooled reactors (HTGR can incorporate wireless sensor network (WSN technology to improve safety and economic competitiveness. WSN has great potential in monitoring the equipment and processes within nuclear power plants (NPPs. This technology not only reduces the cost of regular monitoring but also enables intelligent monitoring. In intelligent monitoring, large sets of heterogeneous data collected by the WSN can be used to optimize the operation and maintenance of the HTGR. In this paper, WSN-based intelligent monitoring schemes that are specific for applications of HTGR are proposed. Three major concerns regarding wireless technology in HTGR are addressed: wireless devices interference, cybersecurity of wireless networks, and wireless standards selected for wireless platform. To process nonlinear and non-Gaussian data obtained by WSN for fault diagnosis, novel algorithms combining Kernel Entropy Component Analysis (KECA and support vector machine (SVM are developed.

  16. Electronic Commerce Logistics Network Optimization Based on Swarm Intelligent Algorithm

    Directory of Open Access Journals (Sweden)

    Yabing Jiao

    2013-09-01

    Full Text Available This article establish an efficient electronic commerce logistics operation system to reduce distribution costs and build a logistics network operation model based on around the B2C electronic commerce enterprise logistics network operation system. B2C electronic commerce transactions features in the enterprise network platform. To solve the NP-hard problem this article use hybrid ant colony algorithm, particle swarm algorithm and group swarm intelligence algorithm to get a best solution. According to the intelligent algorithm, design of electronic commerce logistics network optimization system, enter the national 22 electronic commerce logistics network for validation. Through the experiment to verify the optimized logistics cost greatly decreased. This research can help B2C electronic commerce enterprise logistics network to optimize decision-making under the premise of ensuring the interests of consumers and service levels also can be an effective way for enterprises to improve the efficiency of logistics services and reduce operation costs

  17. Power Optimization on a Network: The effects of randomness

    CERN Document Server

    Moustakas, Aris L

    2012-01-01

    Consider a wireless network of transmitter-receiver pairs. The transmitters adjust their powers to maintain a particular SINR target in the presence of interference from neighboring transmitters. In this paper we analyze the optimal power vector that may achieve this target in the presence of randomness in the network. Specifically, we start from a regular grid of transmitter-receiver pairs and randomly turn-off a finite fraction of them. We apply concepts from random matrix theory to evaluate the asymptotic mean optimal power per link, as well as its variance. Our analytical results show remarkable agreement with numerically generated networks, not only in one-dimensional network arrays but also in two dimensional network geometries. Remarkably, we observe that the optimal power in random networks does not go to infinity in a continuous fashion as in regular grids. Rather, beyond a certain point, no finite power solution exists.

  18. Home medical monitoring network based on embedded technology

    Science.gov (United States)

    Liu, Guozhong; Deng, Wenyi; Yan, Bixi; Lv, Naiguang

    2006-11-01

    Remote medical monitoring network for long-term monitoring of physiological variables would be helpful for recovery of patients as people are monitored at more comfortable conditions. Furthermore, long-term monitoring would be beneficial to investigate slowly developing deterioration in wellness status of a subject and provide medical treatment as soon as possible. The home monitor runs on an embedded microcomputer Rabbit3000 and interfaces with different medical monitoring module through serial ports. The network based on asymmetric digital subscriber line (ADSL) or local area network (LAN) is established and a client - server model, each embedded home medical monitor is client and the monitoring center is the server, is applied to the system design. The client is able to provide its information to the server when client's request of connection to the server is permitted. The monitoring center focuses on the management of the communications, the acquisition of medical data, and the visualization and analysis of the data, etc. Diagnosing model of sleep apnea syndrome is built basing on ECG, heart rate, respiration wave, blood pressure, oxygen saturation, air temperature of mouth cavity or nasal cavity, so sleep status can be analyzed by physiological data acquired as people in sleep. Remote medical monitoring network based on embedded micro Internetworking technology have advantages of lower price, convenience and feasibility, which have been tested by the prototype.

  19. Analysis and optimization of delays in networked control systems

    Institute of Scientific and Technical Information of China (English)

    2005-01-01

    The minimization problem of time delays in networked control system (NCS) is concered, which is a hot area of such research field. First, some analysis and comments on time-delayed NCS model listed in previous work are given.Then, time delay minimization problem based on average behavior of network queuing delay is presented. Under fixed routing scheme and certain optimization performance indexes, the delay minimization problem is translated into convex optimization problem. And the solution of the delay minimization problems is attained through optimized allocation of flow rates among network links.

  20. Design of the Network Monitoring Applications Using SNMP (Simple Network Management Protocol with Early Warning System and Network Mapping

    Directory of Open Access Journals (Sweden)

    Muazam Nugroho

    2014-03-01

    Full Text Available Simple Network Management Protocol (SNMP adalah sebuah protokol yang digunakan untuk kebutuhan monitoring pada jaringan komputer. Dalam bekerja, SNMP terdiri dari Network Management Station (NMS atau manager dan SNMP agent. NMS berfungsi sebagai mesin pengolahan informasi dari perangkat-perangkat jaringan yang dipantau (yang disebut sebagai SNMP agent. SNMP agent  terimplementasi  pada manageable node seperti router, server, dan perangkat jaringan lainnya.Pada periode sebelumnya,di Laboratorium Jaringan Telekomunikasi Jurusan Teknik Elektro ITS telah dibuat tiga sistem monitoring jaringan, yaitu network monitor yang dilengkapi dengan database, sistem peringatan dini, dan pemetaan jaringan (Network Mapping. Ketiga sistem ini masih berdiri sendiri, sehingga perlu dilakukan integrasi agar didapat suatu sistem yang memiliki fungsi lengkap.Dalam tugas akhir ini dilakukan perancangan dan pembuatan suatu Network Monitoring System yang merupakan integrasi antara Network Monitoring, Network Mapping, dan Sistem Peringatan Dini.

  1. Energy Harvesting for Structural Health Monitoring Sensor Networks

    Energy Technology Data Exchange (ETDEWEB)

    Park, G.; Farrar, C. R.; Todd, M. D.; Hodgkiss, T.; Rosing, T.

    2007-02-26

    This report has been developed based on information exchanges at a 2.5-day workshop on energy harvesting for embedded structural health monitoring (SHM) sensing systems that was held June 28-30, 2005, at Los Alamos National Laboratory. The workshop was hosted by the LANL/UCSD Engineering Institute (EI). This Institute is an education- and research-focused collaboration between Los Alamos National Laboratory (LANL) and the University of California, San Diego (UCSD), Jacobs School of Engineering. A Statistical Pattern Recognition paradigm for SHM is first presented and the concept of energy harvesting for embedded sensing systems is addressed with respect to the data acquisition portion of this paradigm. Next, various existing and emerging sensing modalities used for SHM and their respective power requirements are summarized, followed by a discussion of SHM sensor network paradigms, power requirements for these networks and power optimization strategies. Various approaches to energy harvesting and energy storage are discussed and limitations associated with the current technology are addressed. This discussion also addresses current energy harvesting applications and system integration issues. The report concludes by defining some future research directions and possible technology demonstrations that are aimed at transitioning the concept of energy harvesting for embedded SHM sensing systems from laboratory research to field-deployed engineering prototypes.

  2. NEURAL NETWORK TRAINING WITH PARALLEL PARTICLE SWARM OPTIMIZER

    Institute of Scientific and Technical Information of China (English)

    Qin Zheng; Liu Yu; Wang Yu

    2006-01-01

    Objective To reduce the execution time of neural network training. Methods Parallel particle swarm optimization algorithm based on master-slave model is proposed to train radial basis function neural networks, which is implemented on a cluster using MPI libraries for inter-process communication. Results High speed-up factor is achieved and execution time is reduced greatly. On the other hand, the resulting neural network has good classification accuracy not only on training sets but also on test sets. Conclusion Since the fitness evaluation is intensive, parallel particle swarm optimization shows great advantages to speed up neural network training.

  3. Optimal Node Placement in Underwater Acoustic Sensor Network

    KAUST Repository

    Felemban, Muhamad

    2011-10-01

    Almost 70% of planet Earth is covered by water. A large percentage of underwater environment is unexplored. In the past two decades, there has been an increase in the interest of exploring and monitoring underwater life among scientists and in industry. Underwater operations are extremely difficult due to the lack of cheap and efficient means. Recently, Wireless Sensor Networks have been introduced in underwater environment applications. However, underwater communication via acoustic waves is subject to several performance limitations, which makes the relevant research issues very different from those on land. In this thesis, we investigate node placement for building an initial Underwater Wireless Sensor Network infrastructure. Firstly, we formulated the problem into a nonlinear mathematic program with objectives of minimizing the total transmission loss under a given number of sensor nodes and targeted volume. We conducted experiments to verify the proposed formulation, which is solved using Matlab optimization tool. We represented each node with a truncated octahedron to fill out the 3D space. The truncated octahedrons are tiled in the 3D space with each node in the center where locations of the nodes are given using 3D coordinates. Results are supported using ns-3 simulator. Results from simulation are consistent with the obtained results from mathematical model with less than 10% error.

  4. Optimal finite horizon control in gene regulatory networks

    Science.gov (United States)

    Liu, Qiuli

    2013-06-01

    As a paradigm for modeling gene regulatory networks, probabilistic Boolean networks (PBNs) form a subclass of Markov genetic regulatory networks. To date, many different stochastic optimal control approaches have been developed to find therapeutic intervention strategies for PBNs. A PBN is essentially a collection of constituent Boolean networks via a probability structure. Most of the existing works assume that the probability structure for Boolean networks selection is known. Such an assumption cannot be satisfied in practice since the presence of noise prevents the probability structure from being accurately determined. In this paper, we treat a case in which we lack the governing probability structure for Boolean network selection. Specifically, in the framework of PBNs, the theory of finite horizon Markov decision process is employed to find optimal constituent Boolean networks with respect to the defined objective functions. In order to illustrate the validity of our proposed approach, an example is also displayed.

  5. Identifying optimal targets of network attack by belief propagation

    CERN Document Server

    Mugisha, Salomon

    2016-01-01

    For a network formed by nodes and undirected links between pairs of nodes, the network optimal attack problem aims at deleting a minimum number of target nodes to break the network down into many small components. This problem is intrinsically related to the feedback vertex set problem that was successfully tackled by spin glass theory and an associated belief propagation-guided decimation (BPD) algorithm [H.-J. Zhou, Eur.~Phys.~J.~B 86 (2013), 455]. In the present work we apply a slightly adjusted version of the BPD algorithm to the network optimal attack problem, and demonstrate that it has much better performance than a recently proposed Collective Information algorithm [F. Morone and H. A. Makse, Nature 524 (2015), 63--68] for different types of random networks and real-world network instances. The BPD-guided attack scheme often induces an abrupt collapse of the whole network, which may make it very difficult to defend.

  6. ENERGY OPTIMIZATION IN CLUSTER BASED WIRELESS SENSOR NETWORKS

    Directory of Open Access Journals (Sweden)

    T. SHANKAR

    2014-04-01

    Full Text Available Wireless sensor networks (WSN are made up of sensor nodes which are usually battery-operated devices, and hence energy saving of sensor nodes is a major design issue. To prolong the networks lifetime, minimization of energy consumption should be implemented at all layers of the network protocol stack starting from the physical to the application layer including cross-layer optimization. Optimizing energy consumption is the main concern for designing and planning the operation of the WSN. Clustering technique is one of the methods utilized to extend lifetime of the network by applying data aggregation and balancing energy consumption among sensor nodes of the network. This paper proposed new version of Low Energy Adaptive Clustering Hierarchy (LEACH, protocols called Advanced Optimized Low Energy Adaptive Clustering Hierarchy (AOLEACH, Optimal Deterministic Low Energy Adaptive Clustering Hierarchy (ODLEACH, and Varying Probability Distance Low Energy Adaptive Clustering Hierarchy (VPDL combination with Shuffled Frog Leap Algorithm (SFLA that enables selecting best optimal adaptive cluster heads using improved threshold energy distribution compared to LEACH protocol and rotating cluster head position for uniform energy dissipation based on energy levels. The proposed algorithm optimizing the life time of the network by increasing the first node death (FND time and number of alive nodes, thereby increasing the life time of the network.

  7. Optimization of Routine Monitoring of Workers Exposed to Plutonium Aerosols.

    Science.gov (United States)

    Davesne, Estelle; Quesne, Benoit; De Vita, Antoine; Chojnacki, Eric; Blanchardon, Eric; Franck, Didier

    2016-10-01

    In case of incidental confinement failure, mixed oxide (MOX) fuel preparation may expose workers to plutonium aerosols. Due to its potential toxicity, occupational exposure to plutonium compounds should be kept as low as reasonably achievable. To ensure the absence of significant intake of radionuclides, workers at risk of internal contamination are monitored by periodic bioassay planned in a routine monitoring programme. From bioassay results, internal dose may be estimated. However, accurate dose calculation relies on known exposure conditions, which are rarely available when the exposure is demonstrated by routine monitoring only. Therefore, internal dose calculation is subject to uncertainty from unknown exposure conditions and from activity measurement variability. The present study calculates the minimum detectable dose (MDD) for a routine monitoring programme by considering all plausible conditions of exposure and measurement uncertainty. The MDD evaluates the monitoring quality and can be used for optimization. Here, MDDs were calculated for the monitoring of workers preparing MOX fuel. Uncertain parameters were modelled by probability distributions defined according to information provided by experts of routine monitoring, of workplace radiological protection and of bioassay analysis. Results show that the current monitoring is well adapted to potential exposure. A sensitivity study of MDD highlights high dependence on exposure condition modelling. Integrating all expert knowledge is therefore crucial to obtain reliable MDD estimates, stressing the value of a holistic approach to worker monitoring.

  8. Stochastic network optimization with application to communication and queueing systems

    CERN Document Server

    Neely, Michael

    2010-01-01

    This text presents a modern theory of analysis, control, and optimization for dynamic networks. Mathematical techniques of Lyapunov drift and Lyapunov optimization are developed and shown to enable constrained optimization of time averages in general stochastic systems. The focus is on communication and queueing systems, including wireless networks with time-varying channels, mobility, and randomly arriving traffic. A simple drift-plus-penalty framework is used to optimize time averages such as throughput, throughput-utility, power, and distortion. Explicit performance-delay tradeoffs are prov

  9. Optimal path for a quantum teleportation protocol in entangled networks

    Science.gov (United States)

    di Franco, C.; Ballester, D.

    2012-01-01

    Bellman's optimality principle has been of enormous importance in the development of whole branches of applied mathematics, computer science, optimal control theory, economics, decision making, and classical physics. Examples are numerous: dynamic programming, Markov chains, stochastic dynamics, calculus of variations, and the brachistochrone problem. Here we show that Bellman's optimality principle is violated in a teleportation problem on a quantum network. This implies that finding the optimal fidelity route for teleporting a quantum state between two distant nodes on a quantum network with bipartite entanglement will be a tough problem and will require further investigation.

  10. Perancangan Network Monitoring Tools Menggunakan Autonomous Agent Java

    Directory of Open Access Journals (Sweden)

    Khurniawan Eko S

    2016-08-01

    Full Text Available Tugas pengelolaan jaringan yang dilakukan administrator jaringan diantaranya yaitu pengumpulan informasi resource jaringan yang tersedia. Teknologi SNMP (Simple Network Management Protocol memberikan fleksibilitas bagi administrator jaringan dalam mengatur network secara keseluruhan dari satu lokasi. Aplikasi Network Monitoring Tools berbasis Agent JAVA terdiri dari Master agent yang bertugas untuk melakukan management Request agent serta akses database. Request agent yang bertugas untuk melakukan pemantauan server yang mengimplementasi library SNMP4j dengan sistem multi-agent. Disisi interface, aplikasi Network Monitoring Tools menggunakan media web sebagai interface administrator sehingga dapat digunakan darimana saja  dan kapan saja.  Hasil dari penelitian ini memperlihatkan bahwa aplikasi yang dibuat bekerja sebagai Network Monitoring Tools mampu bekerja dengan persen error pada kisaran 0-18%. Selain itu Aplikasi ini menghasilkan tren pembacaan data server lebih stabil dan cepat dibandingkan dengan aplikasi Cacti. Hal ini didukung oleh kemampuan Request Agent yang mampu merespon tingkat beban kerja server yang di pantau.

  11. Distributed and Redundant Design of Ship Monitoring and Control Network

    Institute of Scientific and Technical Information of China (English)

    ZHANG; Jun-dong; SUI; Jiang-hua

    2002-01-01

    The world trend in ship automation is to integrate the monitoring, intelligent control and systematic management of the instruments and equipments both on bridge and in engine room. The paper presents a design scheme of the ship integrated monitoring and operating system based on two layers distributed and redundant computer network. The lower layer network is the field bus network connected mainly by CAN bus; the upper one is the PC local network in TCP/IP protocol, which consisted of a database server, monitoring and operating computers, industrial computers and a set of switches. Distributed schemes are fully applied to both software and hardware. This paper specifically describes the composition, software distribution and redundant technology of the upper local network and gives some important sample codes for the implement of the redundant and distributed design. The technologies here have been proved in the many applications and it may be applied to other industrial fields.

  12. Entropy based groundwater monitoring network design considering spatial distribution of annual recharge

    Science.gov (United States)

    Leach, James M.; Coulibaly, Paulin; Guo, Yiping

    2016-10-01

    This study explores the inclusion of a groundwater recharge based design objective and the impact it has on the design of optimum groundwater monitoring networks. The study was conducted in the Hamilton, Halton, and Credit Valley regions of Ontario, Canada, in which the existing Ontario Provincial Groundwater Monitoring Network was augmented with additional monitoring wells. The Dual Entropy-Multiobjective Optimization (DEMO) model was used in these analyses. The value of using this design objective is rooted in the information contained within the estimated recharge. Recharge requires knowledge of climate, geomorphology, and geology of the area, thus using this objective function can help account for these physical characteristics. Two sources of groundwater recharge data were examined and compared, the first was calculated using the Precipitation-Runoff Modeling System (PRMS), and the second was an aggregation of recharge found using both the PRMS and Hydrological Simulation Program-Fortran (HSP-F). The entropy functions are used to identify optimal trade-offs between the maximum information content and the minimum shared information between the monitoring wells. The recharge objective will help to quantify hydrological characteristics of the vadose zone, and thus provide more information to the optimization algorithm. Results show that by including recharge as a design objective, the spatial coverage of the monitoring network can be improved. The study also highlights the flexibility of DEMO and its ability to incorporate additional design objectives such as the groundwater recharge.

  13. Katz Centrality of Markovian Temporal Networks: Analysis and Optimization

    CERN Document Server

    Ogura, Masaki

    2016-01-01

    Identifying important nodes in complex networks is a fundamental problem in network analysis. Although a plethora of measures has been proposed to identify important nodes in static (i.e., time-invariant) networks, there is a lack of tools in the context of temporal networks (i.e., networks whose connectivity dynamically changes over time). The aim of this paper is to propose a system-theoretic approach for identifying important nodes in temporal networks. In this direction, we first propose a generalization of the popular Katz centrality measure to the family of Markovian temporal networks using tools from the theory of Markov jump linear systems. We then show that Katz centrality in Markovian temporal networks can be efficiently computed using linear programming. Finally, we propose a convex program for optimizing the Katz centrality of a given node by tuning the weights of the temporal network in a cost-efficient manner. Numerical simulations illustrate the effectiveness of the obtained results.

  14. Energy optimal routing for long chain-type wireless sensor networks in underground mines

    Institute of Scientific and Technical Information of China (English)

    Jiang Haifeng; Qian Jiansheng; Sun Yanjing; Zhang Guoyong

    2011-01-01

    Wireless sensor networks are useful complements to existing monitoring systems in underground mines.They play an important role of enhancing and improving coverage and flexibility of safety monitoring systems. Regions prone to danger and enyironments after disasters in underground mines require saving and balancing energy consumption of nodes to prolong the lifespan of networks. Based on the structure of a tunnel, we present a Long Chain-type Wireless Sensor Network (LC-WSN) to monitor the safety of underground mine tunnels. We define the optimal transmission distance and the range of the key region and present an Energy Optimal Routing (EOR) algorithm for LC-WSN to balance the energy consumption of nodes and maximize the lifespan of networks. EOR constructs routing paths based on an optimal transmission distance and uses an energy balancing strategy in the key region. Simulation results show that the EOR algorithm extends the lifespan of a network, balances the energy consumption of nodes in the key region and effectively limits the length of routing paths, compared with similar algorithms.

  15. Interpolation and optimal monitoring in space and time

    NARCIS (Netherlands)

    Boer, E.P.J.

    2002-01-01

    This thesis shows how statistics can be used for both analysing data and for determining the (optimal) design for collecting data in environmental research. An important question is often where to place monitoring stations to meet the objective of measuring as good as possible. In thi

  16. Variability of multifractal parameters in an urban precipitation monitoring network

    Science.gov (United States)

    Licznar, Paweł; De Michele, Carlo; Dżugaj, Dagmara; Niesobska, Maria

    2014-05-01

    Precipitation especially over urban areas is considered a highly non-linear process, with wide variability over a broad range of temporal and spatial scales. Despite obvious limitations of rainfall gauges location at urban sites, rainfall monitoring by gauge networks is a standard solution of urban hydrology. Often urban precipitation gauge networks are formed by modern electronic gauges and connected to control units of centralized urban drainage systems. Precipitation data, recorded online through these gauge networks, are used in so called Real-Time-Control (RTC) systems for the development of optimal strategies of urban drainage outflows management. As a matter of fact, the operation of RTC systems is motivated mainly by the urge of reducing the severity of urban floods and combined sewerage overflows, but at the same time, it creates new valuable precipitation data sources. The variability of precipitation process could be achieved by investigating multifractal behavior displayed by the temporal structure of precipitation data. There are multiply scientific communications concerning multifractal properties of point-rainfall data from different worldwide locations. However, very little is known about the close variability of multifractal parameters among closely located gauges, at the distances of single kilometers. Having this in mind, here we assess the variability of multifractal parameters among gauges of the urban precipitation monitoring network in Warsaw, Poland. We base our analysis on the set of 1-minute rainfall time series recorded in the period 2008-2011 by 25 electronic weighing type gauges deployed around the city by the Municipal Water Supply and Sewerage Company in Warsaw as a part of local RTC system. The presence of scale invariance and multifractal properties in the precipitation process was investigated with spectral analysis, functional box counting method and studying the probability distributions and statistical moments of the rainfall

  17. 大庆油田西部地区地下水动态监测网优化设计%Optimal design of groundwater monitoring network in west Daqing oil field

    Institute of Scientific and Technical Information of China (English)

    秦延军; 宋雷鸣; 刘梅侠; 刘金和

    2001-01-01

    大庆油田地下水动态监测网(用水文地质定性方法建立)历经30多年的开采,需要进行定量优化设计。本次研究采用卡尔曼滤波技术与地下水流系统确定-随机性数值模型相耦合的方法,首先对现有监测网进行质量评价,计算结果表明:监测网在漏斗区(地下水集中开采区)应增加监测孔的数目,调整监测孔的位置。为此,我们拟订了6套12个备选方案,从中选取了由88个监测孔组成的监测网,此监测网无论从监测目标上还是经费上都是最优的。%The groundwater regime observation network of Daqing,qualitatively estabilished by way of Hydro-geologic approach,required a quantitative optimal design after having been operated for over thirty years. By means of combining kalman filter algorithm and deterministic-stochastic numerical model of the groundwater flow system,the reserch estimates the quality of the existing groundwater regime observation network. The calculation vesults indicate that the numbers of observation wells should be increased in the cone region of groundwater level deproession and the positions of the observation wells should be adjusted. For this purpose, we design six different sets of plans (twelve individual ones)and select among them one plan in which the observation network is made up of eighty-eight observation wells.

  18. Optimal selection of nodes to propagate influence on networks

    Science.gov (United States)

    Sun, Yifan

    2016-11-01

    How to optimize the spreading process on networks has been a hot issue in complex networks, marketing, epidemiology, finance, etc. In this paper, we investigate a problem of optimizing locally the spreading: identifying a fixed number of nodes as seeds which would maximize the propagation of influence to their direct neighbors. All the nodes except the selected seeds are assumed not to spread their influence to their neighbors. This problem can be mapped onto a spin glass model with a fixed magnetization. We provide a message-passing algorithm based on replica symmetrical mean-field theory in statistical physics, which can find the nearly optimal set of seeds. Extensive numerical results on computer-generated random networks and real-world networks demonstrate that this algorithm has a better performance than several other optimization algorithms.

  19. Optimization of underwater wet welding process parameters using neural network

    National Research Council Canada - National Science Library

    Omajene, Joshua Emuejevoke; Martikainen, Jukka; Wu, Huapeng; Kah, Paul

    2014-01-01

    .... The soundness of a weld can be predicted from the weld bead geometry.This paper illustrates the application of artificial neural network approach in the optimization of the welding process parameter and the influence of the water environment...

  20. Online Algorithms for Adaptive Optimization in Heterogeneous Delay Tolerant Networks

    Directory of Open Access Journals (Sweden)

    Wissam Chahin

    2013-12-01

    Full Text Available Delay Tolerant Networks (DTNs are an emerging type of networks which do not need a predefined infrastructure. In fact, data forwarding in DTNs relies on the contacts among nodes which may possess different features, radio range, battery consumption and radio interfaces. On the other hand, efficient message delivery under limited resources, e.g., battery or storage, requires to optimize forwarding policies. We tackle optimal forwarding control for a DTN composed of nodes of different types, forming a so-called heterogeneous network. Using our model, we characterize the optimal policies and provide a suitable framework to design a new class of multi-dimensional stochastic approximation algorithms working for heterogeneous DTNs. Crucially, our proposed algorithms drive online the source node to the optimal operating point without requiring explicit estimation of network parameters. A thorough analysis of the convergence properties and stability of our algorithms is presented.

  1. Optimal traffic control in highway transportation networks using linear programming

    KAUST Repository

    Li, Yanning

    2014-06-01

    This article presents a framework for the optimal control of boundary flows on transportation networks. The state of the system is modeled by a first order scalar conservation law (Lighthill-Whitham-Richards PDE). Based on an equivalent formulation of the Hamilton-Jacobi PDE, the problem of controlling the state of the system on a network link in a finite horizon can be posed as a Linear Program. Assuming all intersections in the network are controllable, we show that the optimization approach can be extended to an arbitrary transportation network, preserving linear constraints. Unlike previously investigated transportation network control schemes, this framework leverages the intrinsic properties of the Halmilton-Jacobi equation, and does not require any discretization or boolean variables on the link. Hence this framework is very computational efficient and provides the globally optimal solution. The feasibility of this framework is illustrated by an on-ramp metering control example.

  2. Identification of community structure in networks with convex optimization

    CERN Document Server

    Hildebrand, Roland

    2008-01-01

    We reformulate the problem of modularity maximization over the set of partitions of a network as a conic optimization problem over the completely positive cone, converting it from a combinatorial optimization problem to a convex continuous one. A semidefinite relaxation of this conic program then allows to compute upper bounds on the maximum modularity of the network. Based on the solution of the corresponding semidefinite program, we design a randomized algorithm generating partitions of the network with suboptimal modularities. We apply this algorithm to several benchmark networks, demonstrating that it is competitive in accuracy with the best algorithms previously known. We use our method to provide the first proof of optimality of a partition for a real-world network.

  3. Medical Optimization Network for Space Telemedicine Resources

    Science.gov (United States)

    Rubin, D.; Shah, R. V.; Kerstman, E. L.; Reyes, D.; Mulcahy, R.; Antonsen, E.

    2017-01-01

    INTRODUCTION: Long-duration missions beyond low Earth orbit introduce new constraints to the space medical system. Beyond the traditional limitations in mass, power, and volume, consideration must be given to other factors such as the inability to evacuate to Earth, communication delays, and limitations in clinical skillsets. As NASA develops the medical system for an exploration mission, it must have an ability to evaluate the trade space of what resources will be most important. The Medical Optimization Network for Space Telemedicine Resources (MONSTR) was developed over the past year for this reason, and is now a system for managing data pertaining to medical resources and their relative importance when addressing medical conditions. METHODS: The MONSTR web application with a Microsoft SQL database backend was developed and made accessible to Tableau v9.3 for analysis and visualization. The database was initially populated with a list of medical conditions of concern for an exploration mission taken from the Integrated Medical Model (IMM), a probabilistic model designed to quantify in-flight medical risk. A team of physicians working within the Exploration Medical Capability Element of NASA's Human Research Program compiled a list diagnostic and treatment medical resources required to address best- and worst-case scenarios of each medical condition using a terrestrial standard of care and entered this data into the system. This list included both tangible resources (e.g. medical equipment, medications) and intangible resources (e.g. clinical skills required to perform a procedure). The physician team then assigned criticality values to each instance of a resource, representing the importance of that resource to diagnosing or treating its associated condition(s). Medical condition probabilities of occurrence during a Mars mission were pulled from the IMM and imported into the MONSTR database for use within a resource criticality-weighting algorithm. DISCUSSION

  4. Medical Optimization Network for Space Telemedicine Resources

    Science.gov (United States)

    Shah, R. V.; Mulcahy, R.; Rubin, D.; Antonsen, E. L.; Kerstman, E. L.; Reyes, D.

    2017-01-01

    INTRODUCTION: Long-duration missions beyond low Earth orbit introduce new constraints to the space medical system such as the inability to evacuate to Earth, communication delays, and limitations in clinical skillsets. NASA recognizes the need to improve capabilities for autonomous care on such missions. As the medical system is developed, it is important to have an ability to evaluate the trade space of what resources will be most important. The Medical Optimization Network for Space Telemedicine Resources was developed for this reason, and is now a system to gauge the relative importance of medical resources in addressing medical conditions. METHODS: A list of medical conditions of potential concern for an exploration mission was referenced from the Integrated Medical Model, a probabilistic model designed to quantify in-flight medical risk. The diagnostic and treatment modalities required to address best and worst-case scenarios of each medical condition, at the terrestrial standard of care, were entered into a database. This list included tangible assets (e.g. medications) and intangible assets (e.g. clinical skills to perform a procedure). A team of physicians working within the Exploration Medical Capability Element of NASA's Human Research Program ranked each of the items listed according to its criticality. Data was then obtained from the IMM for the probability of occurrence of the medical conditions, including a breakdown of best case and worst case, during a Mars reference mission. The probability of occurrence information and criticality for each resource were taken into account during analytics performed using Tableau software. RESULTS: A database and weighting system to evaluate all the diagnostic and treatment modalities was created by combining the probability of condition occurrence data with the criticalities assigned by the physician team. DISCUSSION: Exploration Medical Capabilities research at NASA is focused on providing a medical system to

  5. Optimization model for the design of distributed wastewater treatment networks

    Directory of Open Access Journals (Sweden)

    Ibrić Nidret

    2012-01-01

    Full Text Available In this paper we address the synthesis problem of distributed wastewater networks using mathematical programming approach based on the superstructure optimization. We present a generalized superstructure and optimization model for the design of the distributed wastewater treatment networks. The superstructure includes splitters, treatment units, mixers, with all feasible interconnections including water recirculation. Based on the superstructure the optimization model is presented. The optimization model is given as a nonlinear programming (NLP problem where the objective function can be defined to minimize the total amount of wastewater treated in treatment operations or to minimize the total treatment costs. The NLP model is extended to a mixed integer nonlinear programming (MINLP problem where binary variables are used for the selection of the wastewater treatment technologies. The bounds for all flowrates and concentrations in the wastewater network are specified as general equations. The proposed models are solved using the global optimization solvers (BARON and LINDOGlobal. The application of the proposed models is illustrated on the two wastewater network problems of different complexity. First one is formulated as the NLP and the second one as the MINLP. For the second one the parametric and structural optimization is performed at the same time where optimal flowrates, concentrations as well as optimal technologies for the wastewater treatment are selected. Using the proposed model both problems are solved to global optimality.

  6. Online Monitor Framework for Network Distributed Data Acquisition Systems

    Science.gov (United States)

    Konno, Tomoyuki; Cabrera, Anatael; Ishitsuka, Masaki; Kuze, Masahiro; Sakamoto, Yasunobu; the Double Chooz Collaboration

    Data acquisition (DAQ) systems for recent high energy physics experiments consist of lots of subsystems distributed in the local area network. Therefore, scalability for the number of connections from subsystems and availability of access via the Internet are required. "Online monitor framework" is a general software framework for online data monitoring, which provides a way to collect monitoring information distributed in the network and pass them though the firewalls. The framework consists of two subsystems; "Monitor Sever" and "Monitor Viewer". Monitor Server is a core system of the framework. The server collects monitoring information from the DAQ subsystems to provide them to Monitor Viewer. Monitor Viewer is a graphical user interface of the monitor framework, which displays plots in itself. We adapted two types of technologies; Java and HTML5 with Google Web Toolkit, which are independent of operating systems or plugin-libraries like ROOT and contain some functionalities of communicating via the Internet and drawing graphics. The monitoring framework was developed for the Double Chooz reactor neutrino oscillation experiment but is general enough for other experiments. This document reports the structure of the online monitor framework with some examples from the adaption to the Double Chooz experiment.

  7. Optimization of PERT Network and Compression of Time

    Institute of Scientific and Technical Information of China (English)

    Li Ping; Hu Jianbing; Gu Xinyi

    2005-01-01

    In the traditional methods of program evaluation and review technique (PERT) network optimization and compression of time limit for project, the uncertainty of free time difference and total time difference were not considered as well as its time risk. The anthors of this paper use the theory of dependent-chance programming to establish a new model about compression of time for project and multi-objective network optimization, which can overcome the shortages of traditional methods and realize the optimization of PERT network directly. By calculating an example with genetic algorithms, the following conclusions are drawn: (1) compression of time is restricted by cost ratio and completion probability of project; (2) activities with maximal standard difference of duration and minimal cost will be compressed in order of precedence; (3) there is no optimal solutions but noninferior solutions between chance and cost, and the most optimal node time depends on decision-maker's preference.

  8. Optimal Redesign of the Dutch Road Network

    NARCIS (Netherlands)

    Snelder, M.; Wagelmans, A.P.M.; Schrijver, J.M.; Van Zuylen, H.J.; Immers, L.H.

    2007-01-01

    The Dutch national road network has been developed over several decades. In the past, roads were constructed according to the then current spatial and transportation planning philosophies. Because the existing road network is a result of a long process of successive developments, the question can be

  9. Network inference via adaptive optimal design

    NARCIS (Netherlands)

    Stigter, J.D.; Molenaar, J.

    2012-01-01

    Background Current research in network reverse engineering for genetic or metabolic networks very often does not include a proper experimental and/or input design. In this paper we address this issue in more detail and suggest a method that includes an iterative design of experiments based, on the m

  10. Monitoring and optimization of energy consumption of base transceiver stations

    CERN Document Server

    Spagnuolo, Antonio; Vetromile, Carmela; Formosi, Roberto; Lubritto, Carmine

    2015-01-01

    The growth and development of the mobile phone network has led to an increased demand for energy by the telecommunications sector, with a noticeable impact on the environment. Monitoring of energy consumption is a great tool for understanding how to better manage this consumption and find the best strategy to adopt in order to maximize reduction of unnecessary usage of electricity. This paper reports on a monitoring campaign performed on six Base Transceiver Stations (BSs) located central Italy, with different technology, typology and technical characteristics. The study focuses on monitoring energy consumption and environmental parameters (temperature, noise, and global radiation), linking energy consumption with the load of telephone traffic and with the air conditioning functions used to cool the transmission equipment. Moreover, using experimental data collected, it is shown, with a Monte Carlo simulation based on power saving features, how the BS monitored could save energy.

  11. Helicopter Rotor Blade Monitoring using Autonomous Wireless Sensor Network

    NARCIS (Netherlands)

    Sanchez Ramirez, Andrea; Loendersloot, Richard; Tinga, Tiedo; Basu, B.

    2013-01-01

    The advancement on Wireless Sensor Networks for vibration monitoring presents important possibilities for helicopter rotor health and usage monitoring. While main rotor blades account for the main source of lift for helicopters, rotor induced vibration establishes an important source for understandi

  12. Optimality: from neural networks to universal grammar.

    Science.gov (United States)

    Prince, A; Smolensky, P

    1997-03-14

    Can concepts from the theory of neural computation contribute to formal theories of the mind? Recent research has explored the implications of one principle of neural computation, optimization, for the theory of grammar. Optimization over symbolic linguistic structures provides the core of a new grammatical architecture, optimality theory. The proposition that grammaticality equals optimality sheds light on a wide range of phenomena, from the gulf between production and comprehension in child language, to language learnability, to the fundamental questions of linguistic theory: What is it that the grammars of all languages share, and how may they differ?

  13. Mesh networking optimized for robotic teleoperation

    Science.gov (United States)

    Hart, Abraham; Pezeshkian, Narek; Nguyen, Hoa

    2012-06-01

    Mesh networks for robot teleoperation pose different challenges than those associated with traditional mesh networks. Unmanned ground vehicles (UGVs) are mobile and operate in constantly changing and uncontrollable environments. Building a mesh network to work well under these harsh conditions presents a unique challenge. The Manually Deployed Communication Relay (MDCR) mesh networking system extends the range of and provides non-line-of-sight (NLOS) communications for tactical and explosive ordnance disposal (EOD) robots currently in theater. It supports multiple mesh nodes, robots acting as nodes, and works with all Internet Protocol (IP)-based robotic systems. Under MDCR, the performance of different routing protocols and route selection metrics were compared resulting in a modified version of the Babel mesh networking protocol. This paper discusses this and other topics encountered during development and testing of the MDCR system.

  14. A Novel Method for Enhancing Network Monitoring in Remote Medical Applications Using Software Defined Networks

    Directory of Open Access Journals (Sweden)

    Mohammad Reza Parsaei

    2016-01-01

    Full Text Available The most important way for providing health in a large population, particularly developing countries, is developing efficient health care services such that everyone can use the services equally and justly. Telemedicine is a new area which uses modern communication technology for exchanging medical information. This communication might be between a patient and a doctor or two medical centers for consultation. Implementation of a Telemedicine system requires creating the necessary infrastructures, among which network monitoring is one of the most important ones. From hundreds to thousands of computers, hubs to switched networks, and Ethernet to either ATM or 10Gbps Ethernet, administrators need more sophisticated network traffic monitoring and analysis tools in order to deal with development. These tools are needed, not only to fix network problems on time, but also to prevent network failure, to detect inside and outside threats, and make good decisions for network planning. In this paper, a comprehensive survey on Telemedicine and network monitoring is performed. Afterward, network monitoring techniques and methods in current networks are discussed. Finally, an efficient architecture based on Software Defined Networks (SDNs in remote surgical applications is presented which significantly improves monitoring of the communication networks. The results showed the effectiveness of the proposed method.

  15. Network and Service Monitoring in Heterogeneous Home Networks

    NARCIS (Netherlands)

    Delphinanto, A.

    2012-01-01

    Home networks are becoming dynamic and technologically heterogeneous. They consist of an increasing number of devices which offer several functionalities and can be used for many different services. In the home, these devices are interconnected using a mixture of networking technologies (for

  16. Network and Service Monitoring in Heterogeneous Home Networks

    NARCIS (Netherlands)

    Delphinanto, A.

    2012-01-01

    Home networks are becoming dynamic and technologically heterogeneous. They consist of an increasing number of devices which offer several functionalities and can be used for many different services. In the home, these devices are interconnected using a mixture of networking technologies (for example

  17. Growing homophilic networks are natural optimal navigable small worlds

    CERN Document Server

    Malkov, Yury A

    2015-01-01

    Navigability, an ability to find a short path between elements using only local information is one of the most fascinating properties of real-life networks. However the exact mechanism responsible for the formation of navigation properties remained unknown. We show that navigability can be achieved by using only two ingredients present in majority of networks: network growth and local homophily, giving the answer why the navigation feature appears in real-life networks. Incremental insertion of metric elements in random order by adding connections to the closest neighbors produces a self-similar optimally wired navigable small world network with an exponential degree distribution. Adding a preferential attachment produces a scale-free network which has shorter greedy paths, but worse (polynomial) scaling of the information extraction locality. Several features of the proposed model are observed in real-life networks, in particular in the brain neural networks, supporting earlier suggestions that they are navi...

  18. Optimization Strategies to Increase Electrical Distribution Networks Robustness

    Directory of Open Access Journals (Sweden)

    Dorin Sarchiz

    2010-12-01

    Full Text Available The paper aims to present a mathematical model to optimize power distribution network graph, in terms of increasing its robustness, ie to reduce the risk of destruction (its removal from service – accidentally or intentionally, with applications to the distribution networks 20 kV and 110 kV, County Mures.

  19. District Heating Network Design and Configuration Optimization with Genetic Algorithm

    DEFF Research Database (Denmark)

    Li, Hongwei; Svendsen, Svend

    2013-01-01

    and the pipe friction and heat loss formulations are non-linear. In order to find the optimal district heating network configuration, genetic algorithm which handles the mixed integer nonlinear programming problem is chosen. The network configuration is represented with binary and integer encoding...

  20. Optimization of recurrent neural networks for time series modeling

    DEFF Research Database (Denmark)

    Pedersen, Morten With

    1997-01-01

    The present thesis is about optimization of recurrent neural networks applied to time series modeling. In particular is considered fully recurrent networks working from only a single external input, one layer of nonlinear hidden units and a li near output unit applied to prediction of discrete time...

  1. Applied network security monitoring collection, detection, and analysis

    CERN Document Server

    Sanders, Chris

    2013-01-01

    Applied Network Security Monitoring is the essential guide to becoming an NSM analyst from the ground up. This book takes a fundamental approach to NSM, complete with dozens of real-world examples that teach you the key concepts of NSM. Network security monitoring is based on the principle that prevention eventually fails. In the current threat landscape, no matter how much you try, motivated attackers will eventually find their way into your network. At that point, it is your ability to detect and respond to that intrusion that can be the difference between a small incident and a major di

  2. The Technique of Building a Networked Manufacturing Process Monitoring System

    Institute of Scientific and Technical Information of China (English)

    XIE Yong; ZHANG Yu; YANG Musheng

    2006-01-01

    This paper introduces the constitute, structure and the software model of a set of networked manufacturing process monitoring system, using JAVA network technique to realize a set of three layer distributed manufacturing process monitoring system which is comprised with remote manage center, manufacturing process supervision center and the units of measure and control layer such as displacement sensor, the device of temperature measure and alarm etc. The network integration of the production management layer, the process control layer and the hard ware control layer is realized via using this approach. The design using object-oriented technique based on JAVA can easily transport to different operation systems with high performance of the expansibility.

  3. Is a salinity monitoring network "Worth its salt"?

    Science.gov (United States)

    Prinos, Scott T.

    2013-01-01

    Saltwater intrusion threatens the water supplies of many coastal communities. Management of these water supplies requires well-designed and properly maintained and operated salinity monitoring networks. Long-standing deficiencies identified in a salinity monitoring network in southwest Florida during a 2013 study (Prinos, 2013) help to illustrate the types of problems that can occur in aging and poorly maintained networks. This cooperative U.S. Geological Survey (USGS) and South Florida Water Management District (SFWMD) study also describes improvements that can be implemented to overcome these deficiencies.

  4. Coal mine gas monitoring system based on wireless sensor network

    Institute of Scientific and Technical Information of China (English)

    WANG Jian; WANG Ru-lin; WANG Xue-min; SHEN Chuan-he

    2007-01-01

    Based on the nowadays'condition.it is urgent that the gas detection cable communication system must be replaced by the wireless communication systems.The wireless sensors distributed in the environment can achieve the intelligent gas monitoring system.Apply with multilayer data fuse to design working tactics,and import the artificial neural networks to analyze detecting result.The wireless sensors system communicates with the controI center through the optical fiber cable.All the gas sensor nodes distributed in coal mine are combined into an intelligent,flexible structure wireless network system.forming coal mine gas monitoring system based on wireless sensor network.

  5. Optimized, budget-constrained monitoring well placement using DREAM

    Energy Technology Data Exchange (ETDEWEB)

    Yonkofski, Catherine MR; Davidson, Casie L.; Rodriguez, Luke R.; Porter, Ellen A.; Bender, Sadie R.; Brown, Christopher F.

    2017-07-01

    Defining the ideal suite of monitoring technologies to be deployed at a carbon capture and storage (CCS) site presents a challenge to project developers, financers, insurers, regulators and other stakeholders. The monitoring, verification, and accounting (MVA) toolkit offers a suite of technologies to monitor an extensive range of parameters across a wide span of spatial and temporal resolutions, each with their own degree of sensitivity to changes in the parameter being monitored. Understanding how best to optimize MVA budgets to minimize the time to leak detection could help to address issues around project risks, and in turn help support broad CCS deployment. This paper presents a case study demonstrating an application of the Designs for Risk Evaluation and Management (DREAM) tool using an ensemble of CO2 leakage scenarios taken from a previous study on leakage impacts to groundwater. Impacts were assessed and monitored as a function of pH, total dissolved solids (TDS), and trace metal concentrations of arsenic (As), cadmium (Cd), chromium (Cr), and lead (Pb). Using output from the previous study, DREAM was used to optimize monitoring system designs based on variable sampling locations and parameters. The algorithm requires the user to define a finite budget to limit the number of monitoring wells and technologies deployed, and then iterates well placement and sensor type and location until it converges on the configuration with the lowest time to first detection of the leak averaged across all scenarios. To facilitate an understanding of the optimal number of sampling wells, DREAM was used to assess the marginal utility of additional sampling locations. Based on assumptions about monitoring costs and replacement costs of degraded water, the incremental cost of each additional sampling well can be compared against its marginal value in terms of avoided aquifer degradation. Applying this method, DREAM identified the most cost-effective ensemble with 14

  6. LTE/MVNO NETWORKS STRUCTURE OPTIMIZATION BASED ON TENSOR DECOMPOSITION

    OpenAIRE

    Strelkovskaya, Iryna; Solovskaya, Iryna

    2015-01-01

    The usage of tensor methods on the decomposition basis is offered for the tasks solution of structure optimization for LTE/MVNO networks mobile communication. The choice problem of optimum topology of e-Node B base stations connectionsin the radio access of E-UTRAN/LTE network was solved. The assessment problem of QoS quality characteristics of complex LTE/MVNO network architecture was solved.

  7. Optimal passive optical network planning under demand uncertainty

    OpenAIRE

    2014-01-01

    As a result of ever-increasing demand for access level bandwidth, long deployment cycles and the popularisation of more economically viable Point-to-Multipoint (P2MP) networks, service providers are moving to extensively future-proof fibre technologies to connect consumers. Of these, the Passive Optical Network (PON) is the most prevalent. Though the optimal planning of these networks have been studied by a number of authors recently, the typical situation where consumer ...

  8. Optimizing Synchronizability of Scale-Free Networks in Geographical Space

    Institute of Scientific and Technical Information of China (English)

    WANG Bing; TANG Huan-Wen; XIU Zhi-Long; GUO Chong-Hui

    2006-01-01

    @@ We investigate the relationship between the structure and the synchronizability of scale-free networks in geographical space. With an optimization approach, the numerical results indicate that when the network synchronizability is improved, the geographical distance becomes larger while the maximal load decreases. Thus the maximal betweenness can be a candidate factor that affects the network synchronizability both in topological space and in geographical space.

  9. Designing of optimal double loop networks

    Institute of Scientific and Technical Information of China (English)

    徐俊明

    1999-01-01

    The double loop network G(N; r, s) has N vertices and 2N directed edges. A natural question is how to choose r and s such that G(N; r, s) has diameter as short as possible for a given N. In 1993, Li, Xu and Zhang proposed a method of constructing double loop networks with the minimum diameter for the case of r=1.The method is developed to construct such networks that none of their minimum diameters can be reached at r=1.As a by-product, a flaw in an assertation by Esqu et al. is pointed out.

  10. Genetic algorithm for neural networks optimization

    Science.gov (United States)

    Setyawati, Bina R.; Creese, Robert C.; Sahirman, Sidharta

    2004-11-01

    This paper examines the forecasting performance of multi-layer feed forward neural networks in modeling a particular foreign exchange rates, i.e. Japanese Yen/US Dollar. The effects of two learning methods, Back Propagation and Genetic Algorithm, in which the neural network topology and other parameters fixed, were investigated. The early results indicate that the application of this hybrid system seems to be well suited for the forecasting of foreign exchange rates. The Neural Networks and Genetic Algorithm were programmed using MATLAB«.

  11. Design of water quality monitoring networks with two information scenarios in tropical Andean basins.

    Science.gov (United States)

    Bastidas, Juan Carlos; Vélez, Jorge Julián; Zambrano, Jeannette; Londoño, Adela

    2017-04-21

    Design and redesign of water quality monitoring networks were evaluated for two similarly sized watersheds in the tropical Andes via optimization techniques using geographic information system technology (GIS) and a matter-element analysis of 5-day biological oxygen demand (BOD5) and total suspended solids (TSS). This resulted in a flexible, objectively based design for a 1128-km(2) watershed without prior water quality data (La Miel River), and a network redesign of a 1052-km(2) watershed with historical water quality monitoring (Chinchiná River). Monitoring design for the undocumented basin incorporated mathematical expressions for physical, anthropological, and historical factors-and was based on clear objectives for diagnosis and intervention of water pollution. Network redesign identified network redundancy, which resulted in a 64% reduction in the number of water quality monitoring stations along the channel, and a 78% reduction of stations throughout the basin. Most tropical drainage basins throughout the world have little to no prior water quality data. But even in well-studied drainage basins like the Chinchiná River, which is among the most thoroughly studied basins in Colombia, redesign of historical and existing monitoring networks will become a standard tool to advance the restoration of polluted surface waters, not only in Colombia, but also throughout the world.

  12. Optimizing controllability of edge dynamics in complex networks by perturbing network structure

    Science.gov (United States)

    Pang, Shaopeng; Hao, Fei

    2017-03-01

    Using the minimum input signals to drive the dynamics in complex networks toward some desired state is a fundamental issue in the field of network controllability. For a complex network with the dynamical process defined on its edges, the controllability of this network is optimal if it can be fully controlled by applying one input signal to an arbitrary non-isolated vertex of it. In this paper, the adding-edge strategy and turning-edge strategy are proposed to optimize the controllability by minimum structural perturbations. Simulations and analyses indicate that the minimum number of adding-edges required for the optimal controllability is equal to the minimum number of turning-edges, and networks with positively correlated in- and out-degrees are easier to achieve optimal controllability. Furthermore, both the strategies have the capacity to reveal the relationship between certain structural properties of a complex network and its controllability of edge dynamics.

  13. Optimal scope of supply chain network & operations design

    NARCIS (Netherlands)

    Ma, N.

    2014-01-01

    The increasingly complex supply chain networks and operations call for the development of decision support systems and optimization techniques that take a holistic view of supply chain issues and provide support for integrated decision-making. The economic impacts of optimized supply chain are signi

  14. Optimal scope of supply chain network & operations design

    NARCIS (Netherlands)

    Ma, N.

    2014-01-01

    The increasingly complex supply chain networks and operations call for the development of decision support systems and optimization techniques that take a holistic view of supply chain issues and provide support for integrated decision-making. The economic impacts of optimized supply chain are signi

  15. Modeling and Multi-objective Optimization of Refinery Hydrogen Network

    Institute of Scientific and Technical Information of China (English)

    焦云强; 苏宏业; 廖祖维; 侯卫锋

    2011-01-01

    The demand of hydrogen in oil refinery is increasing as market forces and environmental legislation, so hydrogen network management is becoming increasingly important in refineries. Most studies focused on single-objective optimization problem for the hydrogen network, but few account for the multi-objective optimization problem. This paper presents a novel approach for modeling and multi-objective optimization for hydrogen network in refineries. An improved multi-objective optimization model is proposed based on the concept of superstructure. The optimization includes minimization of operating cost and minimization of investment cost of equipment. The proposed methodology for the multi-objective optimization of hydrogen network takes into account flow rate constraints, pressure constraints, purity constraints, impurity constraints, payback period, etc. The method considers all the feasible connections and subjects this to mixed-integer nonlinear programming (MINLP). A deterministic optimization method is applied to solve this multi-objective optimization problem. Finally, a real case study is intro-duced to illustrate the applicability of the approach.

  16. Optimization with PDE constraints ESF networking program 'OPTPDE'

    CERN Document Server

    2014-01-01

    This book on PDE Constrained Optimization contains contributions on the mathematical analysis and numerical solution of constrained optimal control and optimization problems where a partial differential equation (PDE) or a system of PDEs appears as an essential part of the constraints. The appropriate treatment of such problems requires a fundamental understanding of the subtle interplay between optimization in function spaces and numerical discretization techniques and relies on advanced methodologies from the theory of PDEs and numerical analysis as well as scientific computing. The contributions reflect the work of the European Science Foundation Networking Programme ’Optimization with PDEs’ (OPTPDE).

  17. Optimization in spectrum-sliced optical networks

    Science.gov (United States)

    Day Rosario Assis, Karcius; Ferreira dos Santos, Alex; Almeida, Raul C.

    2013-12-01

    Current communication in optical networks presents a wide range of granularities, making it hard to use the optical spectrum efficiently under the WDM framework. In Spectrum Sliced Optical Networks, the WDM rigid frequency grid is replaced by a more flexible structure, in which the spectrum is organized in frequency slots, and each traffic flow is assigned to an appropriate set of contiguous slots. The classical Routing and Wavelength Assignment (RWA) problem is then replaced by a Routing and Spectrum assignment (RSA) problem. This paper addresses an iterativa approach to balance the network load during the routing decision in Spectrum-Elastic Optical Path Networks. We have built numerical examples to illustrate the performance of our routing approach. Comparisons to other routing techniques show that our approach mitigates the lightpath requests blocking probability.

  18. Optimal planning for cellular networks for smart metering infrastructure in rural and remote areas

    Directory of Open Access Journals (Sweden)

    Andrés Masache

    2015-07-01

    Full Text Available Smart metering is used to control, monitor and know the system status in real time; to this effect, the incorporation of smart grids primarily benefits the electrical system; similarly, the reuse of infrastructure and cellular spectrum help mitigate the time and cost of its implementation. In order to reduce traffic and saturation of cellular networks, this paper aims at determining the optimal route for information transmission analyzing the optimal routing through distances and optimal routing through traffic flow. This analysis helps determine what the optimal route is, when there is no traffic on the wireless network, or when there is prolonged traffic, and what the traffic tendencies are, that may occur by excessive information transmission of smart meters to electric distribution companies.

  19. Optimal path for a quantum teleportation protocol in entangled networks

    OpenAIRE

    Di Franco, C.; Ballester, D.

    2010-01-01

    Bellman's optimality principle has been of enormous importance in the development of whole branches of applied mathematics, computer science, optimal control theory, economics, decision making, and classical physics. Examples are numerous: dynamic programming, Markov chains, stochastic dynamics, calculus of variations, and the brachistochrone problem. Here we show that Bellman's optimality principle is violated in a teleportation problem on a quantum network. This implies that finding the opt...

  20. Optimal search strategies on complex multi-linked networks

    Science.gov (United States)

    Di Patti, Francesca; Fanelli, Duccio; Piazza, Francesco

    2015-01-01

    In this paper we consider the problem of optimal search strategies on multi-linked networks, i.e. graphs whose nodes are endowed with several independent sets of links. We focus preliminarily on agents randomly hopping along the links of a graph, with the additional possibility of performing non-local hops to randomly chosen nodes with a given probability. We show that an optimal combination of the two jump rules exists that maximises the efficiency of target search, the optimum reflecting the topology of the network. We then generalize our results to multi-linked networks with an arbitrary number of mutually interfering link sets. PMID:25950716

  1. Optimizing Neural Network Architectures Using Generalization Error Estimators

    DEFF Research Database (Denmark)

    Larsen, Jan

    1994-01-01

    This paper addresses the optimization of neural network architectures. It is suggested to optimize the architecture by selecting the model with minimal estimated averaged generalization error. We consider a least-squares (LS) criterion for estimating neural network models, i.e., the associated...... neural network applications, it is impossible to suggest a perfect model, and consequently the ability to handle incomplete models is urgent. A concise derivation of the GEN-estimator is provided, and its qualities are demonstrated by comparative numerical studies...

  2. Optimizing Neural Network Architectures Using Generalization Error Estimators

    DEFF Research Database (Denmark)

    Larsen, Jan

    1994-01-01

    This paper addresses the optimization of neural network architectures. It is suggested to optimize the architecture by selecting the model with minimal estimated averaged generalization error. We consider a least-squares (LS) criterion for estimating neural network models, i.e., the associated...... neural network applications, it is impossible to suggest a perfect model, and consequently the ability to handle incomplete models is urgent. A concise derivation of the GEN-estimator is provided, and its qualities are demonstrated by comparative numerical studies...

  3. Trajectory Based Optimal Segment Computation in Road Network Databases

    DEFF Research Database (Denmark)

    Li, Xiaohui; Ceikute, Vaida; Jensen, Christian S.

    that adopt different approaches to computing the query. Algorithm AUG uses graph augmentation, and ITE uses iterative road-network partitioning. Empirical studies with real data sets demonstrate that the algorithms are capable of offering high performance in realistic settings....... that are shown empirically to be scalable. Given a road network, a set of existing facilities, and a collection of customer route traversals, an optimal segment query returns the optimal road network segment(s) for a new facility. We propose a practical framework for computing this query, where each route...

  4. Trajectory Based Optimal Segment Computation in Road Network Databases

    DEFF Research Database (Denmark)

    Li, Xiaohui; Ceikute, Vaida; Jensen, Christian S.

    2013-01-01

    that adopt different approaches to computing the query. Algorithm AUG uses graph augmentation, and ITE uses iterative road-network partitioning. Empirical studies with real data sets demonstrate that the algorithms are capable of offering high performance in realistic settings....... that are shown empirically to be scalable. Given a road network, a set of existing facilities, and a collection of customer route traversals, an optimal segment query returns the optimal road network segment(s) for a new facility. We propose a practical framework for computing this query, where each route...

  5. Selecting Optimal Parameters of Random Linear Network Coding for Wireless Sensor Networks

    DEFF Research Database (Denmark)

    Heide, Janus; Zhang, Qi; Fitzek, Frank

    2013-01-01

    This work studies how to select optimal code parameters of Random Linear Network Coding (RLNC) in Wireless Sensor Networks (WSNs). With Rateless Deluge [1] the authors proposed to apply Network Coding (NC) for Over-the-Air Programming (OAP) in WSNs, and demonstrated that with NC a significant...

  6. Control and Optimization of Network in Networked Control System

    Directory of Open Access Journals (Sweden)

    Wang Zhiwen

    2014-01-01

    Full Text Available In order to avoid quality of performance (QoP degradation resulting from quality of service (QoS, the solution to network congestion from the point of control theory, which marks departure of our results from the existing methods, is proposed in this paper. The congestion and bandwidth are regarded as state and control variables, respectively; then, the linear time-invariant (LTI model between congestion state and bandwidth of network is established. Consequently, linear quadratic method is used to eliminate the network congestion by allocating bandwidth dynamically. At last, numerical simulation results are given to illustrate the effectiveness of this modeling approach.

  7. Optimizing Soil Moisture Sampling Locations for Validation Networks for SMAP

    Science.gov (United States)

    Roshani, E.; Berg, A. A.; Lindsay, J.

    2013-12-01

    Soil Moisture Active Passive satellite (SMAP) is scheduled for launch on Oct 2014. Global efforts are underway for establishment of soil moisture monitoring networks for both the pre- and post-launch validation and calibration of the SMAP products. In 2012 the SMAP Validation Experiment, SMAPVEX12, took place near Carman Manitoba, Canada where nearly 60 fields were sampled continuously over a 6 week period for soil moisture and several other parameters simultaneous to remotely sensed images of the sampling region. The locations of these sampling sites were mainly selected on the basis of accessibility, soil texture, and vegetation cover. Although these criteria are necessary to consider during sampling site selection, they do not guarantee optimal site placement to provide the most efficient representation of the studied area. In this analysis a method for optimization of sampling locations is presented which combines the state-of-art multi-objective optimization engine (non-dominated sorting genetic algorithm, NSGA-II), with the kriging interpolation technique to minimize the number of sampling sites while simultaneously minimizing the differences between the soil moisture map resulted from the kriging interpolation and soil moisture map from radar imaging. The algorithm is implemented in Whitebox Geospatial Analysis Tools, which is a multi-platform open-source GIS. The optimization framework is subject to the following three constraints:. A) sampling sites should be accessible to the crew on the ground, B) the number of sites located in a specific soil texture should be greater than or equal to a minimum value, and finally C) the number of sampling sites with a specific vegetation cover should be greater than or equal to a minimum constraint. The first constraint is implemented into the proposed model to keep the practicality of the approach. The second and third constraints are considered to guarantee that the collected samples from each soil texture categories

  8. Optimal Power Flow Solution Using Ant Manners for Electrical Network

    Directory of Open Access Journals (Sweden)

    ALLAOUA, B.

    2009-02-01

    Full Text Available This paper presents ant manners and the collective intelligence for electrical network. Solutions for Optimal Power Flow (OPF problem of a power system deliberate via an ant colony optimization metaheuristic method. The objective is to minimize the total fuel cost of thermal generating units and also conserve an acceptable system performance in terms of limits on generator real and reactive power outputs, bus voltages, shunt capacitors/reactors, transformers tap-setting and power flow of transmission lines. Simulation results on the IEEE 30-bus electrical network show that the ant colony optimization method converges quickly to the global optimum.

  9. Optimal network proxy caching for image-rich contents

    Science.gov (United States)

    Yang, Xuguang; Ramchandran, Kannan

    1999-12-01

    This paper addresses optimizing cache allocation in a distributed image database system over computer networks. We consider progressive image file formats, and `soft' caching strategies, in which each image is allocated a variable amount of cache memory, in an effort to minimize the expected image transmission delay time. A simple and efficient optimization algorithm is proposed, and is generalized to include multiple proxies in a network scenario. With optimality proven, our algorithms are surprisingly simple, and are based on sorting the images according to a special priority index. We also present an adaptive cache allocation/replacement strategy that can be incorporated into web browsers with little computational overhead. Simulation results are presented.

  10. Green mobile devices and networks energy optimization and scavenging techniques

    CERN Document Server

    Venkataraman, Hrishikesh

    2012-01-01

    While battery capacity fails to keep up with the power-demanding features of the latest mobile devices, powering the functional advancement of wireless devices requires a revolution in the concept of battery life and recharge capability. Future hand-held devices and wireless networks should be able to recharge themselves automatically from the environment and optimize their energy consumption. Green Mobile Devices and Networks: Energy Optimization and Scavenging Techniques provides insights into the principles and technical challenges behind both automatic optimization of energy consumption an

  11. Design of a monitoring network over France in case of a radiological accidental release

    Science.gov (United States)

    Abida, Rachid; Bocquet, Marc; Vercauteren, Nikki; Isnard, Olivier

    The Institute of Radiation Protection and Nuclear Safety (France) is planning the set-up of an automatic nuclear aerosol monitoring network over the French territory. Each of the stations will be able to automatically sample the air aerosol content and provide activity concentration measurements on several radionuclides. This should help monitor the French and neighbouring countries nuclear power plants set. It would help evaluate the impact of a radiological incident occurring at one of these nuclear facilities. This paper is devoted to the spatial design of such a network. Here, any potential network is judged on its ability to extrapolate activity concentrations measured on the network stations over the whole domain. The performance of a network is quantitatively assessed through a cost function that measures the discrepancy between the extrapolation and the true concentration fields. These true fields are obtained through the computation of a database of dispersion accidents over one year of meteorology and originating from 20 French nuclear sites. A close to optimal network is then looked for using a simulated annealing optimisation. The results emphasise the importance of the cost function in the design of a network aimed at monitoring an accidental dispersion. Several choices of norm used in the cost function are studied and give way to different designs. The influence of the number of stations is discussed. A comparison with a purely geometric approach which does not involve simulations with a chemistry-transport model is performed.

  12. Network Traffic Anomalies Detection and Identification with Flow Monitoring

    CERN Document Server

    Nguyen, Huy; Kim, Dong Il; Choi, Deokjai

    2010-01-01

    Network management and security is currently one of the most vibrant research areas, among which, research on detecting and identifying anomalies has attracted a lot of interest. Researchers are still struggling to find an effective and lightweight method for anomaly detection purpose. In this paper, we propose a simple, robust method that detects network anomalous traffic data based on flow monitoring. Our method works based on monitoring the four predefined metrics that capture the flow statistics of the network. In order to prove the power of the new method, we did build an application that detects network anomalies using our method. And the result of the experiments proves that by using the four simple metrics from the flow data, we do not only effectively detect but can also identify the network traffic anomalies.

  13. The Reliability of Wireless Sensor Network on Pipeline Monitoring System

    Directory of Open Access Journals (Sweden)

    Hafizh Prihtiadi

    2017-06-01

    Full Text Available The wireless sensor network (WSN is an attractive technology, which combines embedded systems and communication networks making them more efficient and effective. Currently, WSNs have been developed for various monitoring applications. In this research, a wireless mesh network for a pipeline monitoring system was designed and developed. Sensor nodes were placed at each branch in the pipe system. Some router fails were simulated and the response of each node in the network was evaluated. Three different scenarios were examined to test the data transmission performance. The results proved that the wireless mesh network was reliable and robust. The system is able to perform link reconfiguration, automatic routing and safe data transmission from the beginning node to the end node.

  14. Resource optimization scheme for multimedia-enabled wireless mesh networks.

    Science.gov (United States)

    Ali, Amjad; Ahmed, Muhammad Ejaz; Piran, Md Jalil; Suh, Doug Young

    2014-08-08

    Wireless mesh networking is a promising technology that can support numerous multimedia applications. Multimedia applications have stringent quality of service (QoS) requirements, i.e., bandwidth, delay, jitter, and packet loss ratio. Enabling such QoS-demanding applications over wireless mesh networks (WMNs) require QoS provisioning routing protocols that lead to the network resource underutilization problem. Moreover, random topology deployment leads to have some unused network resources. Therefore, resource optimization is one of the most critical design issues in multi-hop, multi-radio WMNs enabled with multimedia applications. Resource optimization has been studied extensively in the literature for wireless Ad Hoc and sensor networks, but existing studies have not considered resource underutilization issues caused by QoS provisioning routing and random topology deployment. Finding a QoS-provisioned path in wireless mesh networks is an NP complete problem. In this paper, we propose a novel Integer Linear Programming (ILP) optimization model to reconstruct the optimal connected mesh backbone topology with a minimum number of links and relay nodes which satisfies the given end-to-end QoS demands for multimedia traffic and identification of extra resources, while maintaining redundancy. We further propose a polynomial time heuristic algorithm called Link and Node Removal Considering Residual Capacity and Traffic Demands (LNR-RCTD). Simulation studies prove that our heuristic algorithm provides near-optimal results and saves about 20% of resources from being wasted by QoS provisioning routing and random topology deployment.

  15. A New Wavelength Optimization and Energy-Saving Scheme Based on Network Coding in Software-Defined WDM-PON Networks

    Science.gov (United States)

    Ren, Danping; Wu, Shanshan; Zhang, Lijing

    2016-09-01

    In view of the characteristics of the global control and flexible monitor of software-defined networks (SDN), we proposes a new optical access network architecture dedicated to Wavelength Division Multiplexing-Passive Optical Network (WDM-PON) systems based on SDN. The network coding (NC) technology is also applied into this architecture to enhance the utilization of wavelength resource and reduce the costs of light source. Simulation results show that this scheme can optimize the throughput of the WDM-PON network, greatly reduce the system time delay and energy consumption.

  16. Optimal quantum networks and one-shot entropies

    Science.gov (United States)

    Chiribella, Giulio; Ebler, Daniel

    2016-09-01

    We develop a semidefinite programming method for the optimization of quantum networks, including both causal networks and networks with indefinite causal structure. Our method applies to a broad class of performance measures, defined operationally in terms of interative tests set up by a verifier. We show that the optimal performance is equal to a max relative entropy, which quantifies the informativeness of the test. Building on this result, we extend the notion of conditional min-entropy from quantum states to quantum causal networks. The optimization method is illustrated in a number of applications, including the inversion, charge conjugation, and controlization of an unknown unitary dynamics. In the non-causal setting, we show a proof-of-principle application to the maximization of the winning probability in a non-causal quantum game.

  17. Search for the optimality signature of river network development.

    Science.gov (United States)

    Paik, Kyungrock

    2012-10-01

    Whether the evolution of natural river networks pursues a certain optimal state has been a most intriguing and fundamental question. There have been many optimality hypotheses proposed but it has yet to be proved which of these best serves as a quantitative signature of river network development. Here, this fundamental question is investigated for the five hypotheses of "minimum total energy expenditure," "minimum total energy dissipation rate," "minimum total stream power," "minimum global energy expenditure rate," and "minimum topological energy." Using simple example landscapes, I examined whether any of these hypotheses pursues both the treelike river network formation and the concave stream longitudinal profile, the two characteristic patterns of natural landscapes. It is found that none of these hypotheses captures both patterns under the steady-state condition where the balance between tectonic uplift and sediment loss is satisfied. These findings are further verified through simulations of landscapes that satisfy given optimality criteria using an optimization method.

  18. A study of reactor monitoring method with neural network

    Energy Technology Data Exchange (ETDEWEB)

    Nabeshima, Kunihiko [Japan Atomic Energy Research Inst., Tokai, Ibaraki (Japan). Tokai Research Establishment

    2001-03-01

    The purpose of this study is to investigate the methodology of Nuclear Power Plant (NPP) monitoring with neural networks, which create the plant models by the learning of the past normal operation patterns. The concept of this method is to detect the symptom of small anomalies by monitoring the deviations between the process signals measured from an actual plant and corresponding output signals from the neural network model, which might not be equal if the abnormal operational patterns are presented to the input of the neural network. Auto-associative network, which has same output as inputs, can detect an kind of anomaly condition by using normal operation data only. The monitoring tests of the feedforward neural network with adaptive learning were performed using the PWR plant simulator by which many kinds of anomaly conditions can be easily simulated. The adaptively trained feedforward network could follow the actual plant dynamics and the changes of plant condition, and then find most of the anomalies much earlier than the conventional alarm system during steady state and transient operations. Then the off-line and on-line test results during one year operation at the actual NPP (PWR) showed that the neural network could detect several small anomalies which the operators or the conventional alarm system didn't noticed. Furthermore, the sensitivity analysis suggests that the plant models by neural networks are appropriate. Finally, the simulation results show that the recurrent neural network with feedback connections could successfully model the slow behavior of the reactor dynamics without adaptive learning. Therefore, the recurrent neural network with adaptive learning will be the best choice for the actual reactor monitoring system. (author)

  19. Optimal structure of complex networks for minimizing traffic congestion.

    Science.gov (United States)

    Zhao, Liang; Cupertino, Thiago Henrique; Park, Kwangho; Lai, Ying-Cheng; Jin, Xiaogang

    2007-12-01

    To design complex networks to minimize traffic congestion, it is necessary to understand how traffic flow depends on network structure. We study data packet flow on complex networks, where the packet delivery capacity of each node is not fixed. The optimal configuration of capacities to minimize traffic congestion is derived and the critical packet generating rate is determined, below which the network is at a free flow state but above which congestion occurs. Our analysis reveals a direct relation between network topology and traffic flow. Optimal network structure, free of traffic congestion, should have two features: uniform distribution of load over all nodes and small network diameter. This finding is confirmed by numerical simulations. Our analysis also makes it possible to theoretically compare the congestion conditions for different types of complex networks. In particular, we find that network with low critical generating rate is more susceptible to congestion. The comparison has been made on the following complex-network topologies: random, scale-free, and regular.

  20. Autonomous Optimization of Targeted Stimulation of Neuronal Networks.

    Science.gov (United States)

    Kumar, Sreedhar S; Wülfing, Jan; Okujeni, Samora; Boedecker, Joschka; Riedmiller, Martin; Egert, Ulrich

    2016-08-01

    Driven by clinical needs and progress in neurotechnology, targeted interaction with neuronal networks is of increasing importance. Yet, the dynamics of interaction between intrinsic ongoing activity in neuronal networks and their response to stimulation is unknown. Nonetheless, electrical stimulation of the brain is increasingly explored as a therapeutic strategy and as a means to artificially inject information into neural circuits. Strategies using regular or event-triggered fixed stimuli discount the influence of ongoing neuronal activity on the stimulation outcome and are therefore not optimal to induce specific responses reliably. Yet, without suitable mechanistic models, it is hardly possible to optimize such interactions, in particular when desired response features are network-dependent and are initially unknown. In this proof-of-principle study, we present an experimental paradigm using reinforcement-learning (RL) to optimize stimulus settings autonomously and evaluate the learned control strategy using phenomenological models. We asked how to (1) capture the interaction of ongoing network activity, electrical stimulation and evoked responses in a quantifiable 'state' to formulate a well-posed control problem, (2) find the optimal state for stimulation, and (3) evaluate the quality of the solution found. Electrical stimulation of generic neuronal networks grown from rat cortical tissue in vitro evoked bursts of action potentials (responses). We show that the dynamic interplay of their magnitudes and the probability to be intercepted by spontaneous events defines a trade-off scenario with a network-specific unique optimal latency maximizing stimulus efficacy. An RL controller was set to find this optimum autonomously. Across networks, stimulation efficacy increased in 90% of the sessions after learning and learned latencies strongly agreed with those predicted from open-loop experiments. Our results show that autonomous techniques can exploit quantitative

  1. Multiple Tipping Points and Optimal Repairing in Interacting Networks

    CERN Document Server

    Majdandzic, Antonio; Curme, Chester; Vodenska, Irena; Levy-Carciente, Sary; Stanley, H Eugene; Havlin, Shlomo

    2015-01-01

    Systems that comprise many interacting dynamical networks, such as the human body with its biological networks or the global economic network consisting of regional clusters, often exhibit complicated collective dynamics. To understand the collective behavior of these systems, we investigate a model of interacting networks exhibiting the fundamental processes of failure, damage spread, and recovery. We find a very rich phase diagram that becomes exponentially more complex as the number of networks is increased. In the simplest example of $n=2$ interacting networks we find two critical points, 4 triple points, 10 allowed transitions, and two "forbidden" transitions, as well as a manifold of metastable regions represented by complex hysteresis. Knowing and understanding the phase diagram have an immediate practical implication; it enables us to find the optimal strategy for repairing partially or fully damaged interconnected networks. To support our model, we analyze an example of real interacting financial net...

  2. Topological Effects and Performance Optimization in Transportation Continuous Network Design

    Directory of Open Access Journals (Sweden)

    Jianjun Wu

    2014-01-01

    Full Text Available Because of the limitation of budget, in the planning of road works, increased efforts should be made on links that are more critical to the whole traffic system. Therefore, it would be helpful to model and evaluate the vulnerability and reliability of the transportation network when the network design is processing. This paper proposes a bilevel transportation network design model, in which the upper level is to minimize the performance of the network under the given budgets, while the lower level is a typical user equilibrium assignment problem. A new solution approach based on particle swarm optimization (PSO method is presented. The topological effects on the performance of transportation networks are studied with the consideration of three typical networks, regular lattice, random graph, and small-world network. Numerical examples and simulations are presented to demonstrate the proposed model.

  3. Transport on Complex Networks: Flow, Jamming and Optimization

    CERN Document Server

    Tadic, B; Thurner, S; Tadic, Bosiljka; Thurner, Stefan

    2006-01-01

    Many transport processes on networks depend crucially on the underlying network geometry, although the exact relationship between the structure of the network and the properties of transport processes remain elusive. In this paper we address this question by using numerical models in which both structure and dynamics are controlled systematically. We consider the traffic of information packets that include driving, searching and queuing. We present the results of extensive simulations on two classes of networks; a correlated cyclic scale-free network and an uncorrelated homogeneous weakly clustered network. By measuring different dynamical variables in the free flow regime we show how the global statistical properties of the transport are related to the temporal fluctuations at individual nodes (the traffic noise) and the links (the traffic flow). We then demonstrate that these two network classes appear as representative topologies for optimal traffic flow in the regimes of low density and high density traff...

  4. Application of the optimal Latin hypercube design and radial basis function network to collaborative optimization

    Institute of Scientific and Technical Information of China (English)

    ZHAO Min; CUI Wei-cheng

    2007-01-01

    Improving the efficiency of ship optimization is crucial for modern ship design. Compared with traditional methods, multidisciplinary design optimization (MDO) is a more promising approach. For this reason, Collaborative Optimization (CO) is discussed and analyzed in this paper. As one of the most frequently applied MDO methods, CO promotes autonomy of disciplines while providing a coordinating mechanism guaranteeing progress toward an optimum and maintaining interdisciplinary compatibility. However, there are some difficulties in applying the conventional CO method, such as difficulties in choosing an initial point and tremendous computational requirements. For the purpose of overcoming these problems, optimal Latin hypercube design and Radial basis function network were applied to CO. Optimal Latin hypercube design is a modified Latin Hypercube design. Radial basis function network approximates the optimization model, and is updated during the optimization process to improve accuracy. It is shown by examples that the computing efficiency and robustness of this CO method are higher than with the conventional CO method.

  5. Integrating wireless sensor network for monitoring subsidence phenomena

    Science.gov (United States)

    Marturià, Jordi; Lopez, Ferran; Gigli, Giovanni; Intrieri, Emanuele; Mucchi, Lorenzo; Fornaciai, Alessandro

    2016-04-01

    An innovative wireless sensor network (WSN) for the 3D superficial monitoring of deformations (such as landslides and subsidence) is being developed in the frame of the Wi-GIM project (Wireless sensor network for Ground Instability Monitoring - LIFE12 ENV/IT/001033). The surface movement is detected acquiring the position (x, y and z) by integrating large bandwidth technology able to detect the 3D coordinates of the sensor with a sub-meter error, with continuous wave radar, which allows decreasing the error down to sub-cm. The Estació neighborhood in Sallent is located over the old potassium mine Enrique. This zone has been affected by a subsidence process over more than twenty years. The implementation of a wide network for ground auscultation has allowed monitoring the process of subsidence since 1997. This network consists of: i) a high-precision topographic leveling network to control the subsidence in surface; ii) a rod extensometers network to monitor subsurface deformation; iii) an automatic Leica TCA Total Station to monitor building movements; iv) an inclinometers network to measure the horizontal displacements on subsurface and v) a piezometer to measure the water level. Those networks were implemented within an alert system for an organized an efficient response of the civil protection authorities in case of an emergency. On 23rd December 2008, an acceleration of subsoil movements (of approx. 12-18 cm/year) provoked the activation of the emergency plan by the Catalan Civil Protection. This implied the preventive and scheduled evacuation of the neighbours (January 2009) located in the area with a higher risk of collapse: around 120 residents of 43 homes. As a consequence, the administration implemented a compensation plan for the evacuation of the whole neighbourhood residents and the demolition of 405 properties. In this work, the adaptation and integration process of Wi-GIM system with those conventional monitoring network are presented for its testing

  6. Optimal Resource Allocation for Network Protection: A Geometric Programming Approach

    CERN Document Server

    Preciado, Victor M; Enyioha, Chinwendu; Jadbabaie, Ali; Pappas, George

    2013-01-01

    We study the problem of containing spreading processes in arbitrary directed networks by distributing protection resources throughout the nodes of the network. We consider two types of protection resources are available: (i) Preventive resources able to defend nodes against the spreading (such as vaccines in a viral infection process), and (ii) corrective resources able to neutralize the spreading after it has reached a node (such as antidotes). We assume that both preventive and corrective resources have an associated cost and study the problem of finding the cost-optimal distribution of resources throughout the nodes of the network. We analyze these questions in the context of viral spreading processes in directed networks. We study the following two problems: (i) Given a fixed budget, find the optimal allocation of preventive and corrective resources in the network to achieve the highest level of containment, and (ii) when a budget is not specified, find the minimum budget required to control the spreading...

  7. Complex Quantum Networks: From Universal Breakdown to Optimal Transport

    CERN Document Server

    Muelken, Oliver; Galiceanu, Mircea

    2015-01-01

    We show that all sequentially growing networks yield the same universal behavior at the breakdown of single-particle quantum transport. For this, we study the global time-averaged transport efficiency of excitations on complex quantum networks. Further, we observe the transition to optimal transport by starting from a network with complete-graph-like sequential subgraphs and systematically reducing the number of loops. These effects are explained on the basis of the spectral properties of the network's Hamiltonian. Our theoretical considerations are supported by numerical Monte-Carlo simulations for complex quantum networks with a scale-free size distribution of sequential subgraphs and a small-world-type transition to optimal transport.

  8. Optimal Distributed Voltage Regulation in Power Distribution Networks

    CERN Document Server

    Lam, Albert Y S; Dominguez-Garcia, Alejandro; Tse, David

    2012-01-01

    In this paper, we address the problem of voltage regulation in power distribution networks with deep-penetration of distributed energy resources (DERs), e.g., renewable-based generation, and storage-capable loads such as plug-in hybrid electric vehicles. We cast the problem as an optimization program, where the objective is to minimize the losses in the network subject to constraints on bus voltage magnitudes, limits on active and reactive power injections, transmission line thermal limits and losses. We provide sufficient conditions under which the optimization problem can be solved via its convex relaxation. Using data from existing networks, we show that the conditions are expected to be satisfied by most networks. We also provide an efficient distributed algorithm to solve the problem. The algorithm is asynchronous, with a communication topology that is the same as the electrical network topology. We illustrate the algorithm's performance in the IEEE 34-bus and the 123-bus feeder test systems.

  9. Dale's Principle is necessary for an optimal neuronal network's dynamics

    CERN Document Server

    Catsigeras, Eleonora

    2013-01-01

    We study a mathematical model of biological neuronal networks composed by any finite number $N \\geq 2$ of non necessarily identical cells. The model is a deterministic dynamical system governed by finite-dimensional impulsive differential equations. The statical structure of the network is described by a directed and weighted graph whose nodes are certain subsets of neurons, and whose edges are the groups of synaptical connections among those subsets. First, we prove that among all the possible networks such that their respective graphs are mutually isomorphic, there exists a dynamical optimum. This optimal network exhibits the richest dynamics: namely, it is capable to show the most diverse set of responses (i.e. orbits in the future) under external stimulus or signals. Second, we prove that all the neurons of a dynamically optimal neuronal network necessarily satisfy Dale's Principle, i.e. each neuron must be either excitatory or inhibitory, but not mixed. So, Dale's Principle is a mathematical necessary co...

  10. Geostatistics-based groundwater-level monitoring network design and its application to the Upper Floridan aquifer, USA.

    Science.gov (United States)

    Bhat, Shirish; Motz, Louis H; Pathak, Chandra; Kuebler, Laura

    2015-01-01

    A geostatistical method was applied to optimize an existing groundwater-level monitoring network in the Upper Floridan aquifer for the South Florida Water Management District in the southeastern United States. Analyses were performed to determine suitable numbers and locations of monitoring wells that will provide equivalent or better quality groundwater-level data compared to an existing monitoring network. Ambient, unadjusted groundwater heads were expressed as salinity-adjusted heads based on the density of freshwater, well screen elevations, and temperature-dependent saline groundwater density. The optimization of the numbers and locations of monitoring wells is based on a pre-defined groundwater-level prediction error. The newly developed network combines an existing network with the addition of new wells that will result in a spatial distribution of groundwater monitoring wells that better defines the regional potentiometric surface of the Upper Floridan aquifer in the study area. The network yields groundwater-level predictions that differ significantly from those produced using the existing network. The newly designed network will reduce the mean prediction standard error by 43% compared to the existing network. The adoption of a hexagonal grid network for the South Florida Water Management District is recommended to achieve both a uniform level of information about groundwater levels and the minimum required accuracy. It is customary to install more monitoring wells for observing groundwater levels and groundwater quality as groundwater development progresses. However, budget constraints often force water managers to implement cost-effective monitoring networks. In this regard, this study provides guidelines to water managers concerned with groundwater planning and monitoring.

  11. Leveraging network connectivity for quality assurance of clinical display monitors.

    Science.gov (United States)

    Gersten, Jennifer

    2012-01-01

    The VA Midwest Health Care Network, VISN 23, is one of 21 veteran integrated health service networks (VISN) under the Department of Veterans Affairs. There are approximately 300,000 imaging studies generated per year and currently more than 14,000 picture archiving and communication system (PACS) users in VISN 23. Biomedical Engineering Services within VISN 23 coordinates the provision of medical technology support. One emerging technology leverages network connectivity as a method of calibrating and continuously monitoring clinical display monitors in support of PACS. Utilizing a continuous calibration monitoring system, clinical displays can be identified as out of Digital Imaging and Communications in Medicine (DICOM) compliance through a centralized server. The technical group can receive immediate notification via e-mail and respond proactively. Previously, this problem could go unnoticed until the next scheduled preventive maintenance was performed. This system utilizes simple network management protocols (SNMP) and simple mail transfer protocols (SMTP) across a wide area network for real-time alerts from a centralized location. This central server supports and monitors approximately 320 clinical displays deployed across five states. Over the past three years of implementation in VISN 23, the remote calibration and monitoring capability has allowed for more efficient support of clinical displays and has enhanced patient safety by ensuring a consistent display of images on these clinical displays.

  12. Optimization of wireless sensor networks based on chicken swarm optimization algorithm

    Science.gov (United States)

    Wang, Qingxi; Zhu, Lihua

    2017-05-01

    In order to reduce the energy consumption of wireless sensor network and improve the survival time of network, the clustering routing protocol of wireless sensor networks based on chicken swarm optimization algorithm was proposed. On the basis of LEACH agreement, it was improved and perfected that the points on the cluster and the selection of cluster head using the chicken group optimization algorithm, and update the location of chicken which fall into the local optimum by Levy flight, enhance population diversity, ensure the global search capability of the algorithm. The new protocol avoided the die of partial node of intensive using by making balanced use of the network nodes, improved the survival time of wireless sensor network. The simulation experiments proved that the protocol is better than LEACH protocol on energy consumption, also is better than that of clustering routing protocol based on particle swarm optimization algorithm.

  13. Representativeness of air quality monitoring networks

    NARCIS (Netherlands)

    Duyzer, J.; Hout, D. van den; Zandveld, P.; Ratingen, S. van

    2015-01-01

    The suitability of European networks to check compliance with air quality standards and to assess exposure of the population was investigated. An air quality model (URBIS) was applied to estimate and compare the spatial distribution of the concentration of nitrogen dioxide (NO2) in ambient air in

  14. Optimal Band Allocation for Cognitive Cellular Networks

    CERN Document Server

    Liu, Tingting

    2011-01-01

    FCC new regulation for cognitive use of the TV white space spectrum provides a new means for improving traditional cellular network performance. But it also introduces a number of technical challenges. This letter studies one of the challenges, that is, given the significant differences in the propagation property and the transmit power limitations between the cellular band and the TV white space, how to jointly utilize both bands such that the benefit from the TV white space for improving cellular network performance is maximized. Both analytical and simulation results are provided.

  15. Optimization of multicast optical networks with genetic algorithm

    Science.gov (United States)

    Lv, Bo; Mao, Xiangqiao; Zhang, Feng; Qin, Xi; Lu, Dan; Chen, Ming; Chen, Yong; Cao, Jihong; Jian, Shuisheng

    2007-11-01

    In this letter, aiming to obtain the best multicast performance of optical network in which the video conference information is carried by specified wavelength, we extend the solutions of matrix games with the network coding theory and devise a new method to solve the complex problems of multicast network switching. In addition, an experimental optical network has been testified with best switching strategies by employing the novel numerical solution designed with an effective way of genetic algorithm. The result shows that optimal solutions with genetic algorithm are accordance with the ones with the traditional fictitious play method.

  16. Routing Protocol Design and Performance Optimization in Cognitive Radio Networks

    Directory of Open Access Journals (Sweden)

    Zhenguo Wu

    2013-10-01

    Full Text Available Routing protocol is an important issue in cognitive radio networks. This paper explored the issues and challenges of routing protocol in cognitive radio network from five aspects: hidden terminal, exposed terminal, deafness, cross-layer design, and topology. The existed protocols are classified by the metrics: the establishment of active routing, cross-layer routing, and network performance indicators. Focusing on analyzing performance of routing protocols and design optimized schemes in cognitive radio networks, the advantage and disadvantage of related work were discussed in detail.

  17. Exact Convex Relaxation of Optimal Power Flow in Radial Networks

    Energy Technology Data Exchange (ETDEWEB)

    Gan, LW; Li, N; Topcu, U; Low, SH

    2015-01-01

    The optimal power flow (OPF) problem determines a network operating point that minimizes a certain objective such as generation cost or power loss. It is nonconvex. We prove that a global optimum of OPF can be obtained by solving a second-order cone program, under a mild condition after shrinking the OPF feasible set slightly, for radial power networks. The condition can be checked a priori, and holds for the IEEE 13, 34, 37, 123-bus networks and two real-world networks.

  18. NEAR OPTIMAL CLUSTER-HEAD SELECTION FOR WIRELESS SENSOR NETWORKS

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    Clustering in wireless sensor networks is an effective way to save energy and reuse bandwidth. To our best knowledge, most of the clustering protocols proposed in literature are of a dynamic type, where cluster heads are selected in each period, followed by cluster formation. In this paper, a new static type clustering method called Hausdorff clustering, which is based on the location of sensor nodes as well as communication efficiency and network connectivity, is proposed. The cluster head, however,is rotated within the cluster by a fuzzy logic algorithm that optimizes the network lifetime. Simulation results show that this approach can significantly increase the lifetime of the sensor network.

  19. An Optimal Routing Algorithm in Service Customized 5G Networks

    Directory of Open Access Journals (Sweden)

    Haipeng Yao

    2016-01-01

    Full Text Available With the widespread use of Internet, the scale of mobile data traffic grows explosively, which makes 5G networks in cellular networks become a growing concern. Recently, the ideas related to future network, for example, Software Defined Networking (SDN, Content-Centric Networking (CCN, and Big Data, have drawn more and more attention. In this paper, we propose a service-customized 5G network architecture by introducing the ideas of separation between control plane and data plane, in-network caching, and Big Data processing and analysis to resolve the problems traditional cellular radio networks face. Moreover, we design an optimal routing algorithm for this architecture, which can minimize average response hops in the network. Simulation results reveal that, by introducing the cache, the network performance can be obviously improved in different network conditions compared to the scenario without a cache. In addition, we explore the change of cache hit rate and average response hops under different cache replacement policies, cache sizes, content popularity, and network topologies, respectively.

  20. Optimal vaccination and treatment of an epidemic network model

    Energy Technology Data Exchange (ETDEWEB)

    Chen, Lijuan [Department of Mathematics, Tongji University, Shanghai 200092 (China); College of Mathematics and Computer Science, Fuzhou University, Fuzhou, Fujian 350002 (China); Sun, Jitao, E-mail: sunjt@sh163.net [Department of Mathematics, Tongji University, Shanghai 200092 (China)

    2014-08-22

    In this Letter, we firstly propose an epidemic network model incorporating two controls which are vaccination and treatment. For the constant controls, by using Lyapunov function, global stability of the disease-free equilibrium and the endemic equilibrium of the model is investigated. For the non-constant controls, by using the optimal control strategy, we discuss an optimal strategy to minimize the total number of the infected and the cost associated with vaccination and treatment. Table 1 and Figs. 1–5 are presented to show the global stability and the efficiency of this optimal control. - Highlights: • Propose an optimally controlled SIRS epidemic model on heterogeneous networks. • Obtain criteria of global stability of the disease-free equilibrium and the endemic equilibrium. • Investigate existence of optimal control for the control problem. • The results be illustrated by some numerical simulations.

  1. Optimization of TTEthernet Networks to Support Best-Effort Traffic

    DEFF Research Database (Denmark)

    Tamas-Selicean, Domitian; Pop, Paul

    2014-01-01

    This paper focuses on the optimization of the TTEthernet communication protocol, which offers three traffic classes: time-triggered (TT), sent according to static schedules, rate-constrained (RC) that has bounded end-to-end latency, and best-effort (BE), the classic Ethernet traffic, with no timing...... guarantees. In our earlier work we have proposed an optimization approach named DOTTS that performs the routing, scheduling and packing / fragmenting of TT and RC messages, such that the TT and RC traffic is schedulable. Although backwards compatibility with classic Ethernet networks is one of TTEthernet......’s strong points, there is little research on this topic. However, in this paper, we extend our DOTTS optimization approach to optimize TTEthernet networks, such that not only the TT and RC messages are schedulable, but we also maximize the available bandwidth for BE messages. The proposed optimization has...

  2. Mobile sensor networks for environmental monitoring

    NARCIS (Netherlands)

    Ballari, D.E.

    2012-01-01

    Vulnerability to natural disasters and the human pressure on natural resources have increased the need for environmental monitoring. Proper decisions, based on real-time information gathered from the environment, are critical to protecting human lives and natural resources. To this end, mobile senso

  3. Mobile sensor networks for environmental monitoring

    NARCIS (Netherlands)

    Ballari, D.E.

    2012-01-01

    Vulnerability to natural disasters and the human pressure on natural resources have increased the need for environmental monitoring. Proper decisions, based on real-time information gathered from the environment, are critical to protecting human lives and natural resources. To this end, mobile

  4. Locomotive monitoring system using wireless sensor networks

    CSIR Research Space (South Africa)

    Croucamp, PL

    2014-07-01

    Full Text Available Theft of cables used for powering a locomotive not only stops the train from functioning but also paralyzes the signalling and monitoring system. This means that information on certain locomotive's cannot be passed onto other locomotives which may...

  5. Monitoring activities in the Dutch National Air Quality Monitoring Network in 2000 and 2001

    NARCIS (Netherlands)

    Elzakker BG van; LLO

    2001-01-01

    The Dutch National Air Quality Monitoring Network (LML in Dutch) is one of the responsibilities of the Air Research Laboratory of the National Institute of Public Health and the Environment. The main objectives of the LML are to monitor ambient air quality, facilitate implementation of air quality

  6. Monitoring activities in the Dutch National Air Quality Monitoring Network in 2000 and 2001

    NARCIS (Netherlands)

    Elzakker BG van; LLO

    2001-01-01

    The Dutch National Air Quality Monitoring Network (LML in Dutch) is one of the responsibilities of the Air Research Laboratory of the National Institute of Public Health and the Environment. The main objectives of the LML are to monitor ambient air quality, facilitate implementation of air quality s

  7. Optimized Radar Remote Sensing for Levee Health Monitoring

    Science.gov (United States)

    Jones, Cathleen E.

    2013-01-01

    Radar remote sensing offers great potential for high resolution monitoring of ground surface changes over large areas at one time to detect movement on and near levees and for location of seepage through levees. Our NASA-funded projects to monitor levees in the Sacramento Delta and the Mississippi River have developed and demonstrated methods to use radar remote sensing to measure quantities relevant to levee health and of great value to emergency response. The DHS-funded project will enable us is to define how to optimally monitor levees in this new way and set the stage for transition to using satellite SAR (synthetic aperture radar) imaging for better temporal and spatial coverage at lower cost to the end users.

  8. Optimizing Key Updates in Sensor Networks

    DEFF Research Database (Denmark)

    Yuksel, Ender; Nielson, Hanne Riis; Nielson, Flemming

    2011-01-01

    Sensor networks offer the advantages of simple and low–resource communication. Nevertheless, security is of particular importance in many cases such as when sensitive data is communicated or tamper-resistance is required. Updating the security keys is one of the key points in security, which rest...

  9. Optimization of network protection against virus spread

    NARCIS (Netherlands)

    Gourdin, E.; Omic, J.; Van Mieghem, P.

    2011-01-01

    The effect of virus spreading in a telecommunication network, where a certain curing strategy is deployed, can be captured by epidemic models. In the N-intertwined model proposed and studied in [1], [2], the probability of each node to be infected depends on the curing and infection rate of its neig

  10. Optimally designed quantum transport across disordered networks.

    Science.gov (United States)

    Walschaers, Mattia; Diaz, Jorge Fernandez-de-Cossio; Mulet, Roberto; Buchleitner, Andreas

    2013-11-01

    We establish a general mechanism for highly efficient quantum transport through finite, disordered 3D networks. It relies on the interplay of disorder with centrosymmetry and a dominant doublet spectral structure and can be controlled by the proper tuning of only coarse-grained quantities. Photosynthetic light harvesting complexes are discussed as potential biological incarnations of this design principle.

  11. PlayNCool: Opportunistic Network Coding for Local Optimization of Routing in Wireless Mesh Networks

    DEFF Research Database (Denmark)

    Pahlevani, Peyman; Roetter, Daniel Enrique Lucani; Pedersen, Morten Videbæk;

    2013-01-01

    This paper introduces PlayNCool, an opportunistic protocol with local optimization based on network coding to increase the throughput of a wireless mesh network (WMN). PlayNCool aims to enhance current routing protocols by (i) allowing random linear network coding transmissions end-to-end, (ii...... in large scale mesh networks. We show that PlayNCool can provide gains of more than 3x in individual links, which translates into a large end-to-end throughput improvement, and that it provides higher gains when more nodes in the network contend for the channel at the MAC layer, making it particularly...... relevant for dense mesh networks....

  12. Energy-Efficient Design and Optimization of Wireline Access Networks

    CERN Document Server

    Bhaumik, Sourjya; Narlikar, Girija; Wilfong, Gordon

    2011-01-01

    Access networks, in particular, Digital Subscriber Line (DSL) equipment, are a significant source of energy consumption for wireline operators. Replacing large monolithic DSLAMs with smaller remote DSLAM units closer to customers can reduce the energy consumption as well as increase the reach of the access network. This paper attempts to formalize the design and optimization of the "last mile" wireline access network with energy as one of the costs to be minimized. In particular, the placement of remote DSLAM units needs to be optimized. We propose solutions for two scenarios. For the scenario where an existing all-copper network from the central office to the customers is to be transformed into a fiber-copper network with remote DSLAM units, we present optimal polynomial-time solutions. In the green-field scenario, both the access network layout and the placement of remote DSLAM units must be determined. We show that this problem is NP-complete. We present an optimal ILP formulation and also design an effici...

  13. SURFmap: A Network Monitoring Tool Based on the Google Maps API

    NARCIS (Netherlands)

    Hofstede, R.J.; Hofstede, R. J.; Fioreze, Tiago

    2009-01-01

    Network monitoring allows network managers to get a better insight in the network traffic transiting in a managed network. In order to make the tasks of a network manager easier, many network monitoring tools are made available for a wide range of purposes (e.g., traffic accounting, performance

  14. SURFmap: A Network Monitoring Tool Based on the Google Maps API

    NARCIS (Netherlands)

    Hofstede, R. J.; Fioreze, T.

    2009-01-01

    Network monitoring allows network managers to get a better insight in the network traffic transiting in a managed network. In order to make the tasks of a network manager easier, many network monitoring tools are made available for a wide range of purposes (e.g., traffic accounting, performance anal

  15. Hermes: Distributed social network monitoring system

    OpenAIRE

    Cea Royes, Daniel

    2014-01-01

    [ANGLÈS] Nowadays, social network services play a very important role in the way people interact with each other and with the world. This generates big amounts of data that can be used to study social relationships and extract useful information about preferences and trends. When analysing this information, two main problems emerge: The need to aggregate dif- ferent data coming from multiple sources, and hardware limitations due to the incapability traditional systems have to d...

  16. A Wireless Sensor Network Air Pollution Monitoring System

    CERN Document Server

    Khedo, Kavi K; Mungur, Avinash; Mauritius, University of; Mauritius,; 10.5121/ijwmn.2010.2203

    2010-01-01

    Sensor networks are currently an active research area mainly due to the potential of their applications. In this paper we investigate the use of Wireless Sensor Networks (WSN) for air pollution monitoring in Mauritius. With the fast growing industrial activities on the island, the problem of air pollution is becoming a major concern for the health of the population. We proposed an innovative system named Wireless Sensor Network Air Pollution Monitoring System (WAPMS) to monitor air pollution in Mauritius through the use of wireless sensors deployed in huge numbers around the island. The proposed system makes use of an Air Quality Index (AQI) which is presently not available in Mauritius. In order to improve the efficiency of WAPMS, we have designed and implemented a new data aggregation algorithm named Recursive Converging Quartiles (RCQ). The algorithm is used to merge data to eliminate duplicates, filter out invalid readings and summarise them into a simpler form which significantly reduce the amount of dat...

  17. LTE-Advanced Radio and Network Optimization

    DEFF Research Database (Denmark)

    Velez, Fernando J.; Sousa, Sofia; Flores, Jessica Acevedo

    2017-01-01

    In cellular optimization, the UL and DL the values from carrier-to-noise-plus-interference ratio (CNIR) from/at the mobile station are very important parameters. From a detailed analysis of its variation with the coverage and reuse distances for different values of the Channel Quality Indicator (...

  18. A Two-stage Optimal Network Reconfiguration Approach for Minimizing Energy Loss of Distribution Networks Using Particle Swarm Optimization Algorithm

    Directory of Open Access Journals (Sweden)

    Wei-Tzer Huang

    2015-12-01

    Full Text Available This study aimed to minimize energy losses in traditional distribution networks and microgrids through a network reconfiguration and phase balancing approach. To address this problem, an algorithm composed of a multi-objective function and operation constraints is proposed. Network connection matrices based on graph theory and the backward/forward sweep method are used to analyze power flow. A minimizing energy loss approach is developed for network reconfiguration and phase balancing, and the particle swarm optimization (PSO algorithm is adopted to solve this optimal combination problem. The proposed approach is tested on the IEEE 37-bus test system and the first outdoor microgrid test bed established by the Institute of Nuclear Energy Research (INER in Taiwan. Simulation results demonstrate that the proposed two-stage approach can be applied in network reconfiguration to minimize energy loss.

  19. Practice-Oriented Optimization of Distribution Network Planning Using Metaheuristic Algorithms

    NARCIS (Netherlands)

    Grond, M.O.W.; Luong, N.H.; Morren, J.; Bosman, P.A.N.; Slootweg, J.G.; La Poutré, J.A.

    2014-01-01

    Distribution network operators require more advanced planning tools to deal with the challenges of future network planning. An appropriate planning and optimization tool can identify which option for network extension should be selected from available alternatives. However, many optimization approac

  20. Optimization of stochastic discrete systems and control on complex networks computational networks

    CERN Document Server

    Lozovanu, Dmitrii

    2014-01-01

    This book presents the latest findings on stochastic dynamic programming models and on solving optimal control problems in networks. It includes the authors' new findings on determining the optimal solution of discrete optimal control problems in networks and on solving game variants of Markov decision problems in the context of computational networks. First, the book studies the finite state space of Markov processes and reviews the existing methods and algorithms for determining the main characteristics in Markov chains, before proposing new approaches based on dynamic programming and combinatorial methods. Chapter two is dedicated to infinite horizon stochastic discrete optimal control models and Markov decision problems with average and expected total discounted optimization criteria, while Chapter three develops a special game-theoretical approach to Markov decision processes and stochastic discrete optimal control problems. In closing, the book's final chapter is devoted to finite horizon stochastic con...

  1. Robust Optimization of Fourth Party Logistics Network Design under Disruptions

    Directory of Open Access Journals (Sweden)

    Jia Li

    2015-01-01

    Full Text Available The Fourth Party Logistics (4PL network faces disruptions of various sorts under the dynamic and complex environment. In order to explore the robustness of the network, the 4PL network design with consideration of random disruptions is studied. The purpose of the research is to construct a 4PL network that can provide satisfactory service to customers at a lower cost when disruptions strike. Based on the definition of β-robustness, a robust optimization model of 4PL network design under disruptions is established. Based on the NP-hard characteristic of the problem, the artificial fish swarm algorithm (AFSA and the genetic algorithm (GA are developed. The effectiveness of the algorithms is tested and compared by simulation examples. By comparing the optimal solutions of the 4PL network for different robustness level, it is indicated that the robust optimization model can evade the market risks effectively and save the cost in the maximum limit when it is applied to 4PL network design.

  2. Energy Efficient Networks for Monitoring Water Quality in Subterranean Rivers

    Directory of Open Access Journals (Sweden)

    Fei Ge

    2016-05-01

    Full Text Available The fresh water in rivers beneath the Earth’s surface is as significant to humans as that on the surface. However, the water quality is difficult to monitor due to its unapproachable nature. In this work, we consider building networks to monitor water quality in subterranean rivers. The network node is designed to have limited functions of floating and staying in these rivers when necessary. We provide the necessary conditions to set up such networks and a topology building method, as well as the communication process between nodes. Furthermore, we provide every an node’s energy consumption model in the network building stage, the data acquiring and transmission stage. The numerical results show that the energy consumption in every node is different, and the node number should be moderate to ensure energy efficiency.

  3. Optimizing bulk milk dioxin monitoring based on costs and effectiveness.

    Science.gov (United States)

    Lascano-Alcoser, V H; Velthuis, A G J; van der Fels-Klerx, H J; Hoogenboom, L A P; Oude Lansink, A G J M

    2013-07-01

    Dioxins are environmental pollutants, potentially present in milk products, which have negative consequences for human health and for the firms and farms involved in the dairy chain. Dioxin monitoring in feed and food has been implemented to detect their presence and estimate their levels in food chains. However, the costs and effectiveness of such programs have not been evaluated. In this study, the costs and effectiveness of bulk milk dioxin monitoring in milk trucks were estimated to optimize the sampling and pooling monitoring strategies aimed at detecting at least 1 contaminated dairy farm out of 20,000 at a target dioxin concentration level. Incidents of different proportions, in terms of the number of contaminated farms, and concentrations were simulated. A combined testing strategy, consisting of screening and confirmatory methods, was assumed as well as testing of pooled samples. Two optimization models were built using linear programming. The first model aimed to minimize monitoring costs subject to a minimum required effectiveness of finding an incident, whereas the second model aimed to maximize the effectiveness for a given monitoring budget. Our results show that a high level of effectiveness is possible, but at high costs. Given specific assumptions, monitoring with 95% effectiveness to detect an incident of 1 contaminated farm at a dioxin concentration of 2 pg of toxic equivalents/g of fat [European Commission's (EC) action level] costs €2.6 million per month. At the same level of effectiveness, a 73% cost reduction is possible when aiming to detect an incident where 2 farms are contaminated at a dioxin concentration of 3 pg of toxic equivalents/g of fat (EC maximum level). With a fixed budget of €40,000 per month, the probability of detecting an incident with a single contaminated farm at a dioxin concentration equal to the EC action level is 4.4%. This probability almost doubled (8.0%) when aiming to detect the same incident but with a dioxin

  4. DESIGN OF GROUNDWATER LEVEL MONITORING NETWORK WITH ORDINARY KRIGING

    Institute of Scientific and Technical Information of China (English)

    YANG Feng-guang; CAO Shu-you; LIU Xing-nian; YANG Ke-jun

    2008-01-01

    The primary network of groundwater level observation wells aims at realizing a regional groundwater management policy. It may give a regional picture of groundwater level with emphasis on the natural situation. Observation data from the primary network can be used to estimate the actual state of groundwater system. Since the cost of the installation and maintenance of a groundwater monitoring network is extremely high, the assessment of effectiveness of the network becomes very necessary. Groundwater level monitoring networks are the examples of discontinuous sampling on variables presenting spatial continuity and highly skewed frequency distributions. Anywhere in the aquifer, ordinary kriging provides estimates of the variable sampled and a standard error of the estimate. In this article, the average Kriging standard deviation was used as a criterion for the determination of network density,and the GIS-based approach was analysized. A case study of groundwater level network simulation in the Chaiwopu Basin, Xinjiang Uygur Autonomous Region, China, was presented. In the case study, the initial phreatic water observation wells were 18, a comparison of the three variogram parameters of the three defferent variogram models shows that the Gaussian model is the best. Finally, a network with 55 wells was constructed.

  5. Applying neural networks to optimize instrumentation performance

    Energy Technology Data Exchange (ETDEWEB)

    Start, S.E.; Peters, G.G.

    1995-06-01

    Well calibrated instrumentation is essential in providing meaningful information about the status of a plant. Signals from plant instrumentation frequently have inherent non-linearities, may be affected by environmental conditions and can therefore cause calibration difficulties for the people who maintain them. Two neural network approaches are described in this paper for improving the accuracy of a non-linear, temperature sensitive level probe ised in Expermental Breeder Reactor II (EBR-II) that was difficult to calibrate.

  6. Optimal Transmitter Placement in Wireless Mesh Networks

    Science.gov (United States)

    2009-06-01

    overcome snags. This list is certainly not exhaustive: LtCols Serg Posadas and Carl Oros, Carlos Borges, Jerry Brown, Matt Carlyle, Michael Clement...transceiver sites. Their results compare the performance of greedy, Darwinism , and genetic algorithms in solving the network design problem. Calegari...greedy algorithm is prone to falling into inferior local optima. The Darwinism algorithm iteratively guesses the number of APs needed, then

  7. Optimal design of virtual topology reconfiguration in WDM optical networks

    Institute of Scientific and Technical Information of China (English)

    Fengqing Liu(刘逢清); Qingji Zeng(曾庆济); Xu Zhu(朱栩); Shilin Xiao(肖石林)

    2003-01-01

    Virtual topology of WDM optical networks is often designed for some specific traffic matrix to get thebest network performance. When traffic demand imposed on WDM optical networks changes, the networkperformance may degrade and even become unacceptable. So virtual topology need to be reconfigured.In previous works, virtual topology is reconfigured to achieve the best network performance, in which alarge number of lightpaths need to be set up or torn down. In this paper, we try to get a tradeoff betweenthe network performance and traffic disruption (or implementing cost). The problem of virtual topologyreconfiguration for changing traffic patterns is formulated as an optimization problem and a mixed integerlinear programming (MILP) algorithm is presented. Numerical results show that a large cost reduction ofreconfiguration can be achieved at the expense of network performance.

  8. Multiple tipping points and optimal repairing in interacting networks

    Science.gov (United States)

    Majdandzic, Antonio; Braunstein, Lidia A.; Curme, Chester; Vodenska, Irena; Levy-Carciente, Sary; Eugene Stanley, H.; Havlin, Shlomo

    2016-03-01

    Systems composed of many interacting dynamical networks--such as the human body with its biological networks or the global economic network consisting of regional clusters--often exhibit complicated collective dynamics. Three fundamental processes that are typically present are failure, damage spread and recovery. Here we develop a model for such systems and find a very rich phase diagram that becomes increasingly more complex as the number of interacting networks increases. In the simplest example of two interacting networks we find two critical points, four triple points, ten allowed transitions and two `forbidden' transitions, as well as complex hysteresis loops. Remarkably, we find that triple points play the dominant role in constructing the optimal repairing strategy in damaged interacting systems. To test our model, we analyse an example of real interacting financial networks and find evidence of rapid dynamical transitions between well-defined states, in agreement with the predictions of our model.

  9. Grid Computing based on Game Optimization Theory for Networks Scheduling

    Directory of Open Access Journals (Sweden)

    Peng-fei Zhang

    2014-05-01

    Full Text Available The resource sharing mechanism is introduced into grid computing algorithm so as to solve complex computational tasks in heterogeneous network-computing problem. However, in the Grid environment, it is required for the available resource from network to reasonably schedule and coordinate, which can get a good workflow and an appropriate network performance and network response time. In order to improve the performance of resource allocation and task scheduling in grid computing method, a game model based on non-cooperation game is proposed. Setting the time and cost of user’s resource allocation can increase the performance of networks, and incentive resource of networks uses an optimization scheduling algorithm, which minimizes the time and cost of resource scheduling. Simulation experiment results show the feasibility and suitability of model. In addition, we can see from the experiment result that model-based genetic algorithm is the best resource scheduling algorithm

  10. Hybrid wireless sensor network for rescue site monitoring after earthquake

    Science.gov (United States)

    Wang, Rui; Wang, Shuo; Tang, Chong; Zhao, Xiaoguang; Hu, Weijian; Tan, Min; Gao, Bowei

    2016-07-01

    This paper addresses the design of a low-cost, low-complexity, and rapidly deployable wireless sensor network (WSN) for rescue site monitoring after earthquakes. The system structure of the hybrid WSN is described. Specifically, the proposed hybrid WSN consists of two kinds of wireless nodes, i.e., the monitor node and the sensor node. Then the mechanism and the system configuration of the wireless nodes are detailed. A transmission control protocol (TCP)-based request-response scheme is proposed to allow several monitor nodes to communicate with the monitoring center. UDP-based image transmission algorithms with fast recovery have been developed to meet the requirements of in-time delivery of on-site monitor images. In addition, the monitor node contains a ZigBee module that used to communicate with the sensor nodes, which are designed with small dimensions to monitor the environment by sensing different physical properties in narrow spaces. By building a WSN using these wireless nodes, the monitoring center can display real-time monitor images of the monitoring area and visualize all collected sensor data on geographic information systems. In the end, field experiments were performed at the Training Base of Emergency Seismic Rescue Troops of China and the experimental results demonstrate the feasibility and effectiveness of the monitor system.

  11. Optimal Marketing Policy in a Random Network

    CERN Document Server

    Amini, Hamed

    2008-01-01

    Viral marketing takes advantage of preexisting social networks among customers to achieve large changes in behavior. Models of influence spread have been studied in a number of domains, including the effect of 'word of mouth' in the promotion of new products or the diffusion of technologies. A social network can be represented by a graph where the nodes are individuals and the edges indicate a form of social relationship. The flow of influence through this network can be thought of as an increasing process of active nodes: as individuals become aware of new technologies, they have the potential to pass them on to their neighbors. The goal of marketing is to trigger a large cascade of adoptions. In this paper, we present and solve an analytical model where the individuals are connected according to a large sparse random graph. Borrowing ideas and techniques from Markov random fields, we derive analytical results for various threshold models. The parameters of the model (like the initial fraction of active indi...

  12. Chemical sensor network for pH monitoring

    Directory of Open Access Journals (Sweden)

    Claudia Manjarrés

    2016-02-01

    Full Text Available Monitoring of water sources is a major concern worldwide. Wireless sensor networks (WSN may be used for this monitoring. However, current systems employ mainly physical sensors for variables such as temperature, pressure, humidity and light. Wireless chemical sensors networks (WCSNs for environmental monitoring are scarce due to the lack of autonomy of conventional sensors. This paper presents results of a WCSN for monitoring pH based on ion selective field effect transistors (ISFETs. Sensing nodes employ a human interface required for in situ calibration of chemical sensors. Unlike most studies, our work evaluates the network employing chemical measurements and wireless network metrics. Results show zero packet losses by using a time division multiple access (TDMA protocol. The network allows wireless communication within 300 m including attenuation from buildings and trees. Therefore, the system presented in this paper is suitable for long range applications with unobstructed line of sight. pH measurements present a standard deviation below 1%, showing high repeatability. When compared to a commercial pH meter, difference in measurements is below 5%. As a consequence, accuracy is adequate for the application. Measurements also presented high stability during 3 h of continuous measurement.

  13. Biologically Inspired Optimization of Building District Heating Networks

    Directory of Open Access Journals (Sweden)

    Leiming Shang

    2013-07-01

    Full Text Available In this paper we show that a biologically inspired model can be successfully applied to problems of building optimal district heating network. The model is based on physiological observations of the true slime mold Physarumpolycephalum, but can also be used for path-finding in the complicated networks of mazes and road maps. A strategy of optimally building heating distribution network was guided by the model and a well-tuned ant colony algorithm and genetic algorithm. The results indicate that although there are not large-scale efficiency savings to be made, the biologically inspired amoeboid movement model is capable of finding results of equal or better optimality than a comparable ant colony algorithm and genetic algorithm.

  14. Singularities in minimax optimization of networks

    DEFF Research Database (Denmark)

    Madsen, Kaj; Schjær-Jacobsen, Hans

    1976-01-01

    A theoretical treatment of singularities in nonlinear minimax optimization problems, which allows for a classification in regular and singular problems, is presented. A theorem for determining a singularity that is present in a given problem is formulated. A group of problems often used...... in the literature to test nonlinear minimax algorithms, i.e., minimax design of multisection quarter-wave transformers, is shown to exhibit singularities and the reason for this is pointed out. Based on the theoretical results presented an algorithm for nonlinear minimax optimization is developed. The new algorithm...... maintains the quadratic convergence property of a recent algorithm by Madsen et al. when applied to regular problems and it is demonstrated to significantly improve the final convergence on singular problems....

  15. Optimal Hydro-Thermal Generation Scheduling Using an Efficient Feedback Neural Network Optimization Model

    Directory of Open Access Journals (Sweden)

    V. Sharma

    2011-08-01

    Full Text Available This study demonstrates the use of a high-performance feedback neural network optimizer based on a new idea of successive approximation for finding the hourly optimal release schedules of interconnected multi-reservoir power system in such a way to minimize the overall cost of thermal generations spanned over the planning period. The main advantages of the proposed neural network optimizer over the existing neural network optimization models are that no dual variables, penalty parameters or lagrange multipliers are required. This network uses a simple structure with the least number of state variables and has better asymptotic stability. For an arbitrarily chosen initial point, the trajectory of the network converges to an optimal solution of the convex nonlinear programming problem. The proposed optimizer has been tested on a nonlinear practical system consisting of a multi-chain cascade of four linked reservoir type hydro-plants and a number of thermal units represented by a single equivalent thermal power plant and so obtained results have been validated using conventional conjugate gradient method and genetic algorithm based approach.

  16. Theory, Design, and Algorithms for Optimal Control of wireless Networks

    Science.gov (United States)

    2010-06-09

    significantly outperform existing protocols (such as AODV ) in terms of total network cost Furthermore, we have shown that even when components of our...achieved through distributed control algorithms that jointly optimize power control, routing , and congestion factors. A second stochastic model approach...updates the network queue state, node-transmission powers amongst others, allowing for power control, scheduling, and routing algorithms to maximize

  17. SEWER NETWORK DISCHARGE OPTIMIZATION USING THE DYNAMIC PROGRAMMING

    Directory of Open Access Journals (Sweden)

    Viorel MINZU

    2015-12-01

    Full Text Available It is necessary to adopt an optimal control that allows an efficient usage of the existing sewer networks, in order to avoid the building of new retention facilities. The main objective of the control action is to minimize the overflow volume of a sewer network. This paper proposes a method to apply a solution obtained by discrete dynamic programming through a realistic closed loop system.

  18. Power Optimization Techniques for Next Generation Wireless Networks

    Directory of Open Access Journals (Sweden)

    Ratheesh R

    2016-02-01

    Full Text Available The massive data traffic and the need for high speed wireless communication is increasing day by day corresponds to an exponential increase in the consumption of power by Information and Communication Technology (ICT sector. Reducing consumption of power in wireless network is a challenging topic and has attracted the attention of researches around the globe. Many techniques like multiple-input multiple-output (MIMO, cognitive radio, cooperative heterogeneous communications and new network strategies such as heterogeneous networks, scattered antennas, multi-hop communication, etc., as well as radio and resource managing techniques like various sleep mode algorithms, cross layer optimization etc., have been proposed as solutions for this problem. In this paper, we present an overview of some of these techniques to optimize power in cellular network and MANET from various literatures. The green energy approaches as an alternate to grid power to optimize power consumption of BS is also reviewed. We also proposed a methodology to optimize power consumption in LTE-A network by jointly deploying RSs at cell edges.

  19. On limited fan-in optimal neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Beiu, V.; Makaruk, H.E. [Los Alamos National Lab., NM (United States); Draghici, S. [Wayne State Univ., Detroit, MI (United States). Vision and Neural Networks Lab.

    1998-03-01

    Because VLSI implementations do not cope well with highly interconnected nets the area of a chip growing as the cube of the fan-in--this paper analyses the influence of limited fan in on the size and VLSI optimality of such nets. Two different approaches will show that VLSI- and size-optimal discrete neural networks can be obtained for small (i.e. lower than linear) fan-in values. They have applications to hardware implementations of neural networks. The first approach is based on implementing a certain sub class of Boolean functions, IF{sub n,m} functions. The authors will show that this class of functions can be implemented in VLSI optimal (i.e., minimizing AT{sup 2}) neural networks of small constant fan ins. The second approach is based on implementing Boolean functions for which the classical Shannon`s decomposition can be used. Such a solution has already been used to prove bounds on neural networks with fan-ins limited to 2. They generalize the result presented there to arbitrary fan-in, and prove that the size is minimized by small fan in values, while relative minimum size solutions can be obtained for fan-ins strictly lower than linear. Finally, a size-optimal neural network having small constant fan-ins will be suggested for IF{sub n,m} functions.

  20. Influence maximization in complex networks through optimal percolation

    Science.gov (United States)

    Morone, Flaviano; Makse, Hernan; CUNY Collaboration; CUNY Collaboration

    The whole frame of interconnections in complex networks hinges on a specific set of structural nodes, much smaller than the total size, which, if activated, would cause the spread of information to the whole network, or, if immunized, would prevent the diffusion of a large scale epidemic. Localizing this optimal, that is, minimal, set of structural nodes, called influencers, is one of the most important problems in network science. Here we map the problem onto optimal percolation in random networks to identify the minimal set of influencers, which arises by minimizing the energy of a many-body system, where the form of the interactions is fixed by the non-backtracking matrix of the network. Big data analyses reveal that the set of optimal influencers is much smaller than the one predicted by previous heuristic centralities. Remarkably, a large number of previously neglected weakly connected nodes emerges among the optimal influencers. Reference: F. Morone, H. A. Makse, Nature 524,65-68 (2015)

  1. Multi-objective optimization in computer networks using metaheuristics

    CERN Document Server

    Donoso, Yezid

    2007-01-01

    Metaheuristics are widely used to solve important practical combinatorial optimization problems. Many new multicast applications emerging from the Internet-such as TV over the Internet, radio over the Internet, and multipoint video streaming-require reduced bandwidth consumption, end-to-end delay, and packet loss ratio. It is necessary to design and to provide for these kinds of applications as well as for those resources necessary for functionality. Multi-Objective Optimization in Computer Networks Using Metaheuristics provides a solution to the multi-objective problem in routing computer networks. It analyzes layer 3 (IP), layer 2 (MPLS), and layer 1 (GMPLS and wireless functions). In particular, it assesses basic optimization concepts, as well as several techniques and algorithms for the search of minimals; examines the basic multi-objective optimization concepts and the way to solve them through traditional techniques and through several metaheuristics; and demonstrates how to analytically model the compu...

  2. Electronic Nose Based on an Optimized Competition Neural Network

    Directory of Open Access Journals (Sweden)

    Haiping Zhang

    2011-05-01

    Full Text Available In view of the fact that there are disadvantages in that the class number must be determined in advance, the value of learning rates are hard to fix, etc., when using traditional competitive neural networks (CNNs in electronic noses (E-noses, an optimized CNN method was presented. The optimized CNN was established on the basis of the optimum class number of samples according to the changes of the Davies and Bouldin (DB value and it could increase, divide, or delete neurons in order to adjust the number of neurons automatically. Moreover, the learning rate changes according to the variety of training times of each sample. The traditional CNN and the optimized CNN were applied to five kinds of sorted vinegars with an E-nose. The results showed that optimized network structures could adjust the number of clusters dynamically and resulted in good classifications.

  3. Rainfall monitoring with microwave link networks -state of the art

    Science.gov (United States)

    de Vos, Lotte; Overeem, Aart; Ríos Gaona, Manuel; van Leth, Tommy; Uijlenhoet, Remko

    2017-04-01

    For the purpose of hydrological applications, meteorology, climate monitoring and agriculture, accurate high resolution rainfall monitoring is highly desirable. Often used techniques to measure rainfall include rain gauge networks and radar. However, accurate rainfall information is lacking in large areas in the world, and the number of rain gauges is even severely declining in Europe, South-America and Africa. The investments required for the installation and maintenance of dense sensor networks can form a large obstacle. Over the past decade, various investigations have shown that microwave links from cellular communication networks may be used for rainfall monitoring. These commercial networks are installed for the purpose of cellular communication. These consist of antennas that transmit microwave link signals through the atmosphere over a path of typically several kilometers. Microwave signals are sensitive to rainfall at the frequencies that are typically used. The loss of signal (attenuation) over the link-path, which is logged in real-time by cellular communication companies for quality monitoring, can therefore be interpreted as a rainfall measurement. In recent years, various techniques have been developed to quantitatively determine rainfall from these microwave link attenuations. An overview of error sources in this process, quantitative rainfall determination techniques, as well as the results of various validation studies are provided. These studies show that there is considerable potential in using commercial microwave link networks for rainfall monitoring. This is a promising development, as these networks cover 20% of the land surface of the earth and have high density, especially in urban areas where there is generally a lack of in situ ground measurements.

  4. Applied research of correspondence analysis method in waste tailings reservoir heavy metal pollution monitoring points optimization

    Institute of Scientific and Technical Information of China (English)

    WANG Cong-lu; WU Chao; LI Zi-jun; XUE Sheng-guo

    2010-01-01

    In order to optimize monitoring points and monitoring factor, the relationship between pollutants and soil sample were established by correspondence analysis. The study results show that the reflecting monitoring points and monitoring factors in the graphic on the same factor axis can clearly express the intrinsic link between pollutants and monitoring points and distribution characteristics. To determine the main monitoring point and the main monitoring indicators can reduce and optimize the number of monitoring points under the premise of ensuring the typical and representative of monitoring data.Using the correlation of pollutants can reduce the number of monitoring indicators and improve the effectiveness of data collection.

  5. On the Efficiency of Recurrent Neural Network Optimization Algorithms

    OpenAIRE

    Krause, Ben; Lu, Liang; Murray, Iain; Renals, Steve

    2015-01-01

    This study compares the sequential and parallel efficiency of training Recurrent Neural Networks (RNNs) with Hessian-free optimization versus a gradient descent variant. Experiments are performed using the long short term memory (LSTM)architecture and the newly proposed multiplicative LSTM (mLSTM) architecture.Results demonstrate a number of insights into these architectures and optimizationalgorithms, including that Hessian-free optimization has the potential for largeefficiency gains in a h...

  6. Performance of Network and Service Monitoring Frameworks

    CERN Document Server

    Lahmadi, Abdelkader; Festor, Olivier

    2009-01-01

    The efficiency and the performance of anagement systems is becoming a hot research topic within the networks and services management community. This concern is due to the new challenges of large scale managed systems, where the management plane is integrated within the functional plane and where management activities have to carry accurate and up-to-date information. We defined a set of primary and secondary metrics to measure the performance of a management approach. Secondary metrics are derived from the primary ones and quantifies mainly the efficiency, the scalability and the impact of management activities. To validate our proposals, we have designed and developed a benchmarking platform dedicated to the measurement of the performance of a JMX manager-agent based management system. The second part of our work deals with the collection of measurement data sets from our JMX benchmarking platform. We mainly studied the effect of both load and the number of agents on the scalability, the impact of management...

  7. Network-Oriented Radiation Monitoring System (NORMS)

    Energy Technology Data Exchange (ETDEWEB)

    Rahmat Aryaeinejad; David F. Spencer

    2007-10-01

    We have developed a multi-functional pocket radiation monitoring system capable of detecting and storing gamma ray and neutron data and then sending the data through a wireless connection to a remote central facility upon request. The device has programmable alarm trigger levels that can be modified for specific applications. The device could be used as a stand-alone device or in conjunction with an array to cover a small or large area. The data is stored with a date/time stamp. The device may be remotely configured. Data can be transferred and viewed on a PDA via direct connection or wirelessly. Functional/bench tests have been completed successfully. The device detects low-level neutron and gamma sources within a shielded container in a radiation field of 10 uR/hr above the ambient background level.

  8. Multicriteria relocation analysis of an off-site radioactive monitoring network for a nuclear power plant.

    Science.gov (United States)

    Chang, Ni-Bin; Ning, Shu-Kuang; Chen, Jen-Chang

    2006-08-01

    Due to increasing environmental consciousness in most countries, every utility that owns a commercial nuclear power plant has been required to have both an on-site and off-site emergency response plan since the 1980s. A radiation monitoring network, viewed as part of the emergency response plan, can provide information regarding the radiation dosage emitted from a nuclear power plant in a regular operational period and/or abnormal measurements in an emergency event. Such monitoring information might help field operators and decision-makers to provide accurate responses or make decisions to protect the public health and safety. This study aims to conduct an integrated simulation and optimization analysis looking for the relocation strategy of a long-term regular off-site monitoring network at a nuclear power plant. The planning goal is to downsize the current monitoring network but maintain its monitoring capacity as much as possible. The monitoring sensors considered in this study include the thermoluminescence dosimetry (TLD) and air sampling system (AP) simultaneously. It is designed for detecting the radionuclide accumulative concentration, the frequency of violation, and the possible population affected by a long-term impact in the surrounding area regularly while it can also be used in an accidental release event. With the aid of the calibrated Industrial Source Complex-Plume Rise Model Enhancements (ISC-PRIME) simulation model to track down the possible radionuclide diffusion, dispersion, transport, and transformation process in the atmospheric environment, a multiobjective evaluation process can be applied to achieve the screening of monitoring stations for the nuclear power plant located at Hengchun Peninsula, South Taiwan. To account for multiple objectives, this study calculated preference weights to linearly combine objective functions leading to decision-making with exposure assessment in an optimization context. Final suggestions should be useful for

  9. GENASIS national and international monitoring networks for persistent organic pollutants

    Science.gov (United States)

    Brabec, Karel; Dušek, Ladislav; Holoubek, Ivan; Hřebíček, Jiří; Kubásek, Miroslav; Urbánek, Jaroslav

    2010-05-01

    Persistent organic pollutants (POPs) remain in the centre of scientific attention due to their slow rates of degradation, their toxicity, and potential for both long-range transport and bioaccumulation in living organisms. This group of compounds covers large number of various chemicals from industrial products, such as polychlorinated biphenyls, etc. The GENASIS (Global Environmental Assessment and Information System) information system utilizes data from national and international monitoring networks to obtain as-complete-as-possible set of information and a representative picture of environmental contamination by persistent organic pollutants (POPs). There are data from two main datasets on POPs monitoring: 1.Integrated monitoring of POPs in Košetice Observatory (Czech Republic) which is a long term background site of the European Monitoring and Evaluation Programme (EMEP) for the Central Europe; the data reveals long term trends of POPs in all environmental matrices. The Observatory is the only one in Europe where POPs have been monitored not only in ambient air, but also in wet atmospheric deposition, surface waters, sediments, soil, mosses and needles (integrated monitoring). Consistent data since the year 1996 are available, earlier data (up to 1998) are burdened by high variability and high detection limits. 2.MONET network is ambient air monitoring activities in the Central and Eastern European region (CEEC), Central Asia, Africa and Pacific Islands driven by RECETOX as the Regional Centre of the Stockholm Convention for the region of Central and Eastern Europe under the common name of the MONET networks (MONitoring NETwork). For many of the participating countries these activities generated first data on the atmospheric levels of POPs. The MONET network uses new technologies of air passive sampling, which was developed, tested, and calibrated by RECETOX in cooperation with Environment Canada and Lancaster University, and was originally launched as a

  10. 5G heterogeneous networks self-organizing and optimization

    CERN Document Server

    Rong, Bo; Kadoch, Michel; Sun, Songlin; Li, Wenjing

    2016-01-01

    This SpringerBrief provides state-of-the-art technical reviews on self-organizing and optimization in 5G systems. It covers the latest research results from physical-layer channel modeling to software defined network (SDN) architecture. This book focuses on the cutting-edge wireless technologies such as heterogeneous networks (HetNets), self-organizing network (SON), smart low power node (LPN), 3D-MIMO, and more. It will help researchers from both the academic and industrial worlds to better understand the technical momentum of 5G key technologies.

  11. Optimal multi-community network modularity for information diffusion

    Science.gov (United States)

    Wu, Jiaocan; Du, Ruping; Zheng, Yingying; Liu, Dong

    2016-02-01

    Studies demonstrate that community structure plays an important role in information spreading recently. In this paper, we investigate the impact of multi-community structure on information diffusion with linear threshold model. We utilize extended GN network that contains four communities and analyze dynamic behaviors of information that spreads on it. And we discover the optimal multi-community network modularity for information diffusion based on the social reinforcement. Results show that, within the appropriate range, multi-community structure will facilitate information diffusion instead of hindering it, which accords with the results derived from two-community network.

  12. Service network design of bike sharing systems analysis and optimization

    CERN Document Server

    Vogel, Patrick

    2016-01-01

    This monograph presents a tactical planning approach for service network design in metropolitan areas. Designing the service network requires the suitable aggregation of demand data as well as the anticipation of operational relocation decisions. To this end, an integrated approach of data analysis and mathematical optimization is introduced. The book also includes a case study based on real-world data to demonstrate the benefit of the proposed service network design approach. The target audience comprises primarily research experts in the field of traffic engineering, but the book may also be beneficial for graduate students.

  13. An Evolutionary Optimization Framework for Neural Networks and Neuromorphic Architectures

    Energy Technology Data Exchange (ETDEWEB)

    Schuman, Catherine D [ORNL; Plank, James [University of Tennessee (UT); Disney, Adam [University of Tennessee (UT); Reynolds, John [University of Tennessee (UT)

    2016-01-01

    As new neural network and neuromorphic architectures are being developed, new training methods that operate within the constraints of the new architectures are required. Evolutionary optimization (EO) is a convenient training method for new architectures. In this work, we review a spiking neural network architecture and a neuromorphic architecture, and we describe an EO training framework for these architectures. We present the results of this training framework on four classification data sets and compare those results to other neural network and neuromorphic implementations. We also discuss how this EO framework may be extended to other architectures.

  14. Traffic optimization in transport networks based on local routing

    Science.gov (United States)

    Scellato, S.; Fortuna, L.; Frasca, M.; Gómez-Gardeñes, J.; Latora, V.

    2010-01-01

    Congestion in transport networks is a topic of theoretical interest and practical importance. In this paper we study the flow of vehicles in urban street networks. In particular, we use a cellular automata model on a complex network to simulate the motion of vehicles along streets, coupled with a congestion-aware routing at street crossings. Such routing makes use of the knowledge of agents about traffic in nearby roads and allows the vehicles to dynamically update the routes towards their destinations. By implementing the model in real urban street patterns of various cities, we show that it is possible to achieve a global traffic optimization based on local agent decisions.

  15. Optimal Network Reconfiguration with Distributed Generation Using NSGA II Algorithm

    Directory of Open Access Journals (Sweden)

    Jasna Hivziefendic

    2016-10-01

    Full Text Available This paper presents a method to solve electrical network reconfiguration problem in the presence of distributed generation (DG with an objective of minimizing real power loss and energy not supplied function in distribution system. A method based on NSGA II multi-objective algorithm is used to simultaneously minimize two objective functions and to identify the optimal distribution network topology. The constraints of voltage and branch current carrying capacity are included in the evaluation of the objective function. The method has been tested on radial electrical distribution network with 213 nodes, 248 lines and 72 switches. Numerical results are presented to demonstrate the performance and effectiveness of the proposed methodology.

  16. Autonomous and Decentralized Optimization of Large-Scale Heterogeneous Wireless Networks by Neural Network Dynamics

    Science.gov (United States)

    Hasegawa, Mikio; Tran, Ha Nguyen; Miyamoto, Goh; Murata, Yoshitoshi; Harada, Hiroshi; Kato, Shuzo

    We propose a neurodynamical approach to a large-scale optimization problem in Cognitive Wireless Clouds, in which a huge number of mobile terminals with multiple different air interfaces autonomously utilize the most appropriate infrastructure wireless networks, by sensing available wireless networks, selecting the most appropriate one, and reconfiguring themselves with seamless handover to the target networks. To deal with such a cognitive radio network, game theory has been applied in order to analyze the stability of the dynamical systems consisting of the mobile terminals' distributed behaviors, but it is not a tool for globally optimizing the state of the network. As a natural optimization dynamical system model suitable for large-scale complex systems, we introduce the neural network dynamics which converges to an optimal state since its property is to continually decrease its energy function. In this paper, we apply such neurodynamics to the optimization problem of radio access technology selection. We compose a neural network that solves the problem, and we show that it is possible to improve total average throughput simply by using distributed and autonomous neuron updates on the terminal side.

  17. Gene regulatory network modeling via global optimization of high-order dynamic Bayesian network

    Directory of Open Access Journals (Sweden)

    Xuan Nguyen

    2012-06-01

    Full Text Available Abstract Background Dynamic Bayesian network (DBN is among the mainstream approaches for modeling various biological networks, including the gene regulatory network (GRN. Most current methods for learning DBN employ either local search such as hill-climbing, or a meta stochastic global optimization framework such as genetic algorithm or simulated annealing, which are only able to locate sub-optimal solutions. Further, current DBN applications have essentially been limited to small sized networks. Results To overcome the above difficulties, we introduce here a deterministic global optimization based DBN approach for reverse engineering genetic networks from time course gene expression data. For such DBN models that consist only of inter time slice arcs, we show that there exists a polynomial time algorithm for learning the globally optimal network structure. The proposed approach, named GlobalMIT+, employs the recently proposed information theoretic scoring metric named mutual information test (MIT. GlobalMIT+ is able to learn high-order time delayed genetic interactions, which are common to most biological systems. Evaluation of the approach using both synthetic and real data sets, including a 733 cyanobacterial gene expression data set, shows significantly improved performance over other techniques. Conclusions Our studies demonstrate that deterministic global optimization approaches can infer large scale genetic networks.

  18. Differential Evolution Algorithm for Route Optimization Problems of Engineering Networks

    Directory of Open Access Journals (Sweden)

    O. G. Monahov

    2015-01-01

    Full Text Available The paper considers problems of structure optimization of engineering networks to provide a minimum total cost of engineering networks in construction and operation. The mathematical statement of the problem in terms of the hyper-network theory takes into account the interdependence of indicators of hyper-network elements, a layout area and a projected network. A digital model of terrain presents the placement area of engineering networks (a territory. In our case, it will be a weighted mesh (graph of primary network of dedicated vertices-consumers and a vertex-source for the utilities. The edges weights will be determined by the costs of construction and operation of the route between the given vertices of the network. The initial solution of the problem of minimizing the total cost will be using the minimum spanning tree, obtained on a weighted complete graph the vertices of which are defined by vertices-consumers and the vertexsource for the utilities, and the weights of edges are the distance between the vertices on the given weighted graph of the primary network. The work offers a method of differential evolution to solve the problem in hyper-network formulation that improves the initial solution by the mapping the edges of the secondary network in the primary network using additional Steiner points. As numerical experiments have shown, a differential evolution algorithm allows us to reduce the average total cost for a given engineering network compared to the initial solution by 5% - 15%, depending on the configuration, parameters, and layout area.

  19. A Flexible Acoustic Sensor Network for Various Monitoring Applications

    NARCIS (Netherlands)

    Basten, T.G.H.; Wessels, P.W.

    2013-01-01

    Acoustic monitoring using a sensor network is a powerful instrument to assess and manage complex noise situations. It can provide a basis to identify appropriate and cost effective measures, and to assess their effect by comparing before and after implementation. It can also be an instrument for com

  20. BANip: Enabling Remote Healthcare Monitoring with Body Area Networks

    NARCIS (Netherlands)

    Dokovski, Nikolay; Halteren, van Aart; Widya, Ing; Guelfi, Nicolas; Astesiano, Egidio; Reggio, Gianna

    2004-01-01

    This paper presents a Java service platform for mobile healthcare that enables remote health monitoring using 2.5/3G public wireless networks. The platform complies with todayrsquos healthcare delivery models, in particular it incorporates some functionality of a healthcare call center, a healthport

  1. A proposed ground-water quality monitoring network for Idaho

    Science.gov (United States)

    Whitehead, R.L.; Parliman, D.J.

    1979-01-01

    A ground water quality monitoring network is proposed for Idaho. The network comprises 565 sites, 8 of which will require construction of new wells. Frequencies of sampling at the different sites are assigned at quarterly, semiannual, annual, and 5 years. Selected characteristics of the water will be monitored by both laboratory- and field-analysis methods. The network is designed to: (1) Enable water managers to keep abreast of the general quality of the State 's ground water, and (2) serve as a warning system for undesirable changes in ground-water quality. Data were compiled for hydrogeologic conditions, ground-water quality, cultural elements, and pollution sources. A ' hydrologic unit priority index ' is used to rank 84 hydrologic units (river basins or segments of river basins) of the State for monitoring according to pollution potential. Emphasis for selection of monitoring sites is placed on the 15 highest ranked units. The potential for pollution is greatest in areas of privately owned agricultural land. Other areas of pollution potential are residential development, mining and related processes, and hazardous waste disposal. Data are given for laboratory and field analyses, number of site visits, manpower, subsistence, and mileage, from which costs for implementing the network can be estimated. Suggestions are made for data storage and retrieval and for reporting changes in water quality. (Kosco-USGS)

  2. BANip: Enabling Remote Healthcare Monitoring with Body Area Networks

    NARCIS (Netherlands)

    Dokovski, N.T.; van Halteren, Aart; Widya, I.A.; Guelfi, Nicolas; Astesiano, Egidio; Reggio, Gianna

    2004-01-01

    This paper presents a Java service platform for mobile healthcare that enables remote health monitoring using 2.5/3G public wireless networks. The platform complies with todayrsquos healthcare delivery models, in particular it incorporates some functionality of a healthcare call center, a healthport

  3. Combine harvester monitor system based on wireless sensor network

    Science.gov (United States)

    A measurement method based on Wireless Sensor Network (WSN) was developed to monitor the working condition of combine harvester for remote application. Three JN5139 modules were chosen for sensor data acquisition and another two as a router and a coordinator, which could create a tree topology netwo...

  4. A multiobjective optimization framework for multicontaminant industrial water network design.

    Science.gov (United States)

    Boix, Marianne; Montastruc, Ludovic; Pibouleau, Luc; Azzaro-Pantel, Catherine; Domenech, Serge

    2011-07-01

    The optimal design of multicontaminant industrial water networks according to several objectives is carried out in this paper. The general formulation of the water allocation problem (WAP) is given as a set of nonlinear equations with binary variables representing the presence of interconnections in the network. For optimization purposes, three antagonist objectives are considered: F(1), the freshwater flow-rate at the network entrance, F(2), the water flow-rate at inlet of regeneration units, and F(3), the number of interconnections in the network. The multiobjective problem is solved via a lexicographic strategy, where a mixed-integer nonlinear programming (MINLP) procedure is used at each step. The approach is illustrated by a numerical example taken from the literature involving five processes, one regeneration unit and three contaminants. The set of potential network solutions is provided in the form of a Pareto front. Finally, the strategy for choosing the best network solution among those given by Pareto fronts is presented. This Multiple Criteria Decision Making (MCDM) problem is tackled by means of two approaches: a classical TOPSIS analysis is first implemented and then an innovative strategy based on the global equivalent cost (GEC) in freshwater that turns out to be more efficient for choosing a good network according to a practical point of view. Copyright © 2011 Elsevier Ltd. All rights reserved.

  5. Identifying optimal targets of network attack by belief propagation

    Science.gov (United States)

    Mugisha, Salomon; Zhou, Hai-Jun

    2016-07-01

    For a network formed by nodes and undirected links between pairs of nodes, the network optimal attack problem aims at deleting a minimum number of target nodes to break the network down into many small components. This problem is intrinsically related to the feedback vertex set problem that was successfully tackled by spin-glass theory and an associated belief propagation-guided decimation (BPD) algorithm [Zhou, Eur. Phys. J. B 86, 455 (2013), 10.1140/epjb/e2013-40690-1]. In the present work we apply the BPD algorithm (which has approximately linear time complexity) to the network optimal attack problem and demonstrate that it has much better performance than a recently proposed collective information algorithm [Morone and Makse, Nature 524, 65 (2015), 10.1038/nature14604] for different types of random networks and real-world network instances. The BPD-guided attack scheme often induces an abrupt collapse of the whole network, which may make it very difficult to defend.

  6. Self-organization in neural networks - Applications in structural optimization

    Science.gov (United States)

    Hajela, Prabhat; Fu, B.; Berke, Laszlo

    1993-01-01

    The present paper discusses the applicability of ART (Adaptive Resonance Theory) networks, and the Hopfield and Elastic networks, in problems of structural analysis and design. A characteristic of these network architectures is the ability to classify patterns presented as inputs into specific categories. The categories may themselves represent distinct procedural solution strategies. The paper shows how this property can be adapted in the structural analysis and design problem. A second application is the use of Hopfield and Elastic networks in optimization problems. Of particular interest are problems characterized by the presence of discrete and integer design variables. The parallel computing architecture that is typical of neural networks is shown to be effective in such problems. Results of preliminary implementations in structural design problems are also included in the paper.

  7. Near-Optimal Random Walk Sampling in Distributed Networks

    CERN Document Server

    Sarma, Atish Das; Pandurangan, Gopal

    2012-01-01

    Performing random walks in networks is a fundamental primitive that has found numerous applications in communication networks such as token management, load balancing, network topology discovery and construction, search, and peer-to-peer membership management. While several such algorithms are ubiquitous, and use numerous random walk samples, the walks themselves have always been performed naively. In this paper, we focus on the problem of performing random walk sampling efficiently in a distributed network. Given bandwidth constraints, the goal is to minimize the number of rounds and messages required to obtain several random walk samples in a continuous online fashion. We present the first round and message optimal distributed algorithms that present a significant improvement on all previous approaches. The theoretical analysis and comprehensive experimental evaluation of our algorithms show that they perform very well in different types of networks of differing topologies. In particular, our results show h...

  8. A fuzzy neural network evolved by particle swarm optimization

    Institute of Scientific and Technical Information of China (English)

    PENG Zhi-ping; PENG Hong

    2007-01-01

    A cooperative system of a fuzzy logic model and a fuzzy neural network (CSFLMFNN) is proposed,in which a fuzzy logic model is acquired from domain experts and a fuzzy neural network is generated and prewired according to the model. Then PSO-CSFLMFNN is constructed by introducing particle swarm optimization (PSO) into the cooperative system instead of the commonly used evolutionary algorithms to evolve the prewired fuzzy neural network. The evolutionary fuzzy neural network implements accuracy fuzzy inference without rule matching. PSO-CSFLMFNN is applied to the intelligent fault diagnosis for a petrochemical engineering equipment, in which the cooperative system is proved to be effective. It is shown by the applied results that the performance of the evolutionary fuzzy neural network outperforms remarkably that of the one evolved by genetic algorithm in the convergence rate and the generalization precision.

  9. Optimization of piezoelectric energy harvester for wireless smart sensors in railway health monitoring

    Science.gov (United States)

    Li, Jingcheng; Jang, Shinae; Tang, Jiong

    2013-04-01

    Wireless sensor network is one of the prospective methods for railway monitoring due to the long-term operation and low-maintenance performances. How to supply power to the wireless sensor nodes has drawn much attention recently. In railway monitoring, the idea of converting ambient vibration energy from vibration of railway track induced by passing trains to electric energy has made it a potential way for powering the wireless sensor nodes. Nowadays, most of vibration based energy harvesters are designed at resonance. However, as railway vibration frequency is a wide band range, how to design an energy harvester working at that range is critical. In this paper, the energy consumption of the wireless smart sensor platform, Imote2, at different working states were investigated. Based on the energy consumption, a design of a bimorph cantilever piezoelectric energy harvester has been optimized to generate maximum average power between a wide-band frequency range. Significant power and current outputs have been increased after optimal design. Finally, the rechargeable battery life for supplying the Imote2 for railway monitoring is predicted by using the optimized piezoelectric energy harvesting system.

  10. Using models for the optimization of hydrologic monitoring

    Science.gov (United States)

    Fienen, Michael N.; Hunt, Randall J.; Doherty, John E.; Reeves, Howard W.

    2011-01-01

    Hydrologists are often asked what kind of monitoring network can most effectively support science-based water-resources management decisions. Currently (2011), hydrologic monitoring locations often are selected by addressing observation gaps in the existing network or non-science issues such as site access. A model might then be calibrated to available data and applied to a prediction of interest (regardless of how well-suited that model is for the prediction). However, modeling tools are available that can inform which locations and types of data provide the most 'bang for the buck' for a specified prediction. Put another way, the hydrologist can determine which observation data most reduce the model uncertainty around a specified prediction. An advantage of such an approach is the maximization of limited monitoring resources because it focuses on the difference in prediction uncertainty with or without additional collection of field data. Data worth can be calculated either through the addition of new data or subtraction of existing information by reducing monitoring efforts (Beven, 1993). The latter generally is not widely requested as there is explicit recognition that the worth calculated is fundamentally dependent on the prediction specified. If a water manager needs a new prediction, the benefits of reducing the scope of a monitoring effort, based on an old prediction, may be erased by the loss of information important for the new prediction. This fact sheet focuses on the worth or value of new data collection by quantifying the reduction in prediction uncertainty achieved be adding a monitoring observation. This calculation of worth can be performed for multiple potential locations (and types) of observations, which then can be ranked for their effectiveness for reducing uncertainty around the specified prediction. This is implemented using a Bayesian approach with the PREDUNC utility in the parameter estimation software suite PEST (Doherty, 2010). The

  11. Optimal vaccination and treatment of an epidemic network model

    Science.gov (United States)

    Chen, Lijuan; Sun, Jitao

    2014-08-01

    In this Letter, we firstly propose an epidemic network model incorporating two controls which are vaccination and treatment. For the constant controls, by using Lyapunov function, global stability of the disease-free equilibrium and the endemic equilibrium of the model is investigated. For the non-constant controls, by using the optimal control strategy, we discuss an optimal strategy to minimize the total number of the infected and the cost associated with vaccination and treatment. Table 1 and Figs. 1-5 are presented to show the global stability and the efficiency of this optimal control.

  12. Active Low Intrusion Hybrid Monitor for Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Marlon Navia

    2015-09-01

    Full Text Available Several systems have been proposed to monitor wireless sensor networks (WSN. These systems may be active (causing a high degree of intrusion or passive (low observability inside the nodes. This paper presents the implementation of an active hybrid (hardware and software monitor with low intrusion. It is based on the addition to the sensor node of a monitor node (hardware part which, through a standard interface, is able to receive the monitoring information sent by a piece of software executed in the sensor node. The intrusion on time, code, and energy caused in the sensor nodes by the monitor is evaluated as a function of data size and the interface used. Then different interfaces, commonly available in sensor nodes, are evaluated: serial transmission (USART, serial peripheral interface (SPI, and parallel. The proposed hybrid monitor provides highly detailed information, barely disturbed by the measurement tool (interference, about the behavior of the WSN that may be used to evaluate many properties such as performance, dependability, security, etc. Monitor nodes are self-powered and may be removed after the monitoring campaign to be reused in other campaigns and/or WSNs. No other hardware-independent monitoring platforms with such low interference have been found in the literature.

  13. Active Low Intrusion Hybrid Monitor for Wireless Sensor Networks.

    Science.gov (United States)

    Navia, Marlon; Campelo, Jose C; Bonastre, Alberto; Ors, Rafael; Capella, Juan V; Serrano, Juan J

    2015-09-18

    Several systems have been proposed to monitor wireless sensor networks (WSN). These systems may be active (causing a high degree of intrusion) or passive (low observability inside the nodes). This paper presents the implementation of an active hybrid (hardware and software) monitor with low intrusion. It is based on the addition to the sensor node of a monitor node (hardware part) which, through a standard interface, is able to receive the monitoring information sent by a piece of software executed in the sensor node. The intrusion on time, code, and energy caused in the sensor nodes by the monitor is evaluated as a function of data size and the interface used. Then different interfaces, commonly available in sensor nodes, are evaluated: serial transmission (USART), serial peripheral interface (SPI), and parallel. The proposed hybrid monitor provides highly detailed information, barely disturbed by the measurement tool (interference), about the behavior of the WSN that may be used to evaluate many properties such as performance, dependability, security, etc. Monitor nodes are self-powered and may be removed after the monitoring campaign to be reused in other campaigns and/or WSNs. No other hardware-independent monitoring platforms with such low interference have been found in the literature.

  14. Pipelining in structural health monitoring wireless sensor network

    Science.gov (United States)

    Li, Xu; Dorvash, Siavash; Cheng, Liang; Pakzad, Shamim

    2010-04-01

    Application of wireless sensor network (WSN) for structural health monitoring (SHM), is becoming widespread due to its implementation ease and economic advantage over traditional sensor networks. Beside advantages that have made wireless network preferable, there are some concerns regarding their performance in some applications. In long-span Bridge monitoring the need to transfer data over long distance causes some challenges in design of WSN platforms. Due to the geometry of bridge structures, using multi-hop data transfer between remote nodes and base station is essential. This paper focuses on the performances of pipelining algorithms. We summarize several prevent pipelining approaches, discuss their performances, and propose a new pipelining algorithm, which gives consideration to both boosting of channel usage and the simplicity in deployment.

  15. A Unified Monitoring Framework for Energy Consumption and Network Traffic

    Directory of Open Access Journals (Sweden)

    Florentin Clouet

    2015-08-01

    Full Text Available Providing experimenters with deep insight about the effects of their experiments is a central feature of testbeds. In this paper, we describe Kwapi, a framework designed in the context of the Grid'5000 testbed, that unifies measurements for both energy consumption and network traffic. Because all measurements are taken at the infrastructure level (using sensors in power and network equipment, using this framework has no dependencies on the experiments themselves. Initially designed for OpenStack infrastructures, the Kwapi framework allows monitoring and reporting of energy consumption of distributed platforms. In this article, we present the extension of Kwapi to network monitoring, and outline how we overcame several challenges: scaling to a testbed the size of Grid'5000 while still providing high-frequency measurements; providing long-term loss-less storage of measurements; handling operational issues when deploying such a tool on a real infrastructure.

  16. IDMA-Based Compressed Sensing for Ocean Monitoring Information Acquisition with Sensor Networks

    Directory of Open Access Journals (Sweden)

    Gongliang Liu

    2014-01-01

    Full Text Available The ocean monitoring sensor network is a typically energy-limited and bandwidth-limited system, and the technical bottleneck of which is the asymmetry between the demand for large-scale and high-resolution information acquisition and the limited network resources. The newly arising compressed sensing theory provides a chance for breaking through the bottleneck. In view of this and considering the potential advantages of the emerging interleave-division multiple access (IDMA technology in underwater channels, this paper proposes an IDMA-based compressed sensing scheme in underwater sensor networks with applications to environmental monitoring information acquisition. Exploiting the sparse property of the monitored objects, only a subset of sensors is required to measure and transmit the measurements to the monitoring center for accurate information reconstruction, reducing the requirements for channel bandwidth and energy consumption significantly. Furthermore, with the aid of the semianalytical technique of IDMA, the optimal sensing probability of each sensor is determined to minimize the reconstruction error of the information map. Simulation results with real oceanic monitoring data validate the efficiency of the proposed scheme.

  17. Novel method for fog monitoring using cellular networks infrastructures

    Science.gov (United States)

    David, N.; Alpert, P.; Messer, H.

    2012-08-01

    A major detrimental effect of fog is visibility limitation which can result in serious transportation accidents, traffic delays and therefore economic damage. Existing monitoring techniques including satellites, transmissometers and human observers - suffer from low spatial resolution, high cost or lack of precision when measuring near ground level. Here we show a novel technique for fog monitoring using wireless communication systems. Communication networks widely deploy commercial microwave links across the terrain at ground level. Operating at frequencies of tens of GHz they are affected by fog and are, effectively, an existing, spatially world-wide distributed sensor network that can provide crucial information about fog concentration and visibility. Fog monitoring potential is demonstrated for a heavy fog event that took place in Israel. The correlation between transmissomters and human eye observations to the visibility estimates from the nearby microwave links was found to be 0.53 and 0.61, respectively. These values indicate the high potential of the proposed method.

  18. Patient Health Monitoring Using Wireless Body Area Network

    Directory of Open Access Journals (Sweden)

    Hsu Myat Thwe

    2015-06-01

    Full Text Available Abstract Nowadays remote patient health monitoring using wireless technology plays very vigorous role in a society. Wireless technology helps monitoring of physiological parameters like body temperature heart rate respiration blood pressure and ECG. The main aim of this paper is to propose a wireless sensor network system in which both heart rate and body temperature ofmultiplepatients can monitor on PC at the same time via RF network. The proposed prototype system includes two sensor nodes and receiver node base station. The sensor nodes are able to transmit data to receiver using wireless nRF transceiver module.The nRF transceiver module is used to transfer the data from microcontroller to PC and a graphical user interface GUI is developed to display the measured data and save to database. This system can provide very cheaper easier and quick respondent history of patient.

  19. Wireless sensor networks for monitoring physiological signals of multiple patients.

    Science.gov (United States)

    Dilmaghani, R S; Bobarshad, H; Ghavami, M; Choobkar, S; Wolfe, C

    2011-08-01

    This paper presents the design of a novel wireless sensor network structure to monitor patients with chronic diseases in their own homes through a remote monitoring system of physiological signals. Currently, most of the monitoring systems send patients' data to a hospital with the aid of personal computers (PC) located in the patients' home. Here, we present a new design which eliminates the need for a PC. The proposed remote monitoring system is a wireless sensor network with the nodes of the network installed in the patients' homes. These nodes are then connected to a central node located at a hospital through an Internet connection. The nodes of the proposed wireless sensor network are created by using a combination of ECG sensors, MSP430 microcontrollers, a CC2500 low-power wireless radio, and a network protocol called the SimpliciTI protocol. ECG signals are first sampled by a small portable device which each patient carries. The captured signals are then wirelessly transmitted to an access point located within the patients' home. This connectivity is based on wireless data transmission at 2.4-GHz frequency. The access point is also a small box attached to the Internet through a home asynchronous digital subscriber line router. Afterwards, the data are sent to the hospital via the Internet in real time for analysis and/or storage. The benefits of this remote monitoring are wide ranging: the patients can continue their normal lives, they do not need a PC all of the time, their risk of infection is reduced, costs significantly decrease for the hospital, and clinicians can check data in a short time.

  20. On the Optimization of a Probabilistic Data Aggregation Framework for Energy Efficiency in Wireless Sensor Networks.

    Science.gov (United States)

    Kafetzoglou, Stella; Aristomenopoulos, Giorgos; Papavassiliou, Symeon

    2015-08-11

    Among the key aspects of the Internet of Things (IoT) is the integration of heterogeneous sensors in a distributed system that performs actions on the physical world based on environmental information gathered by sensors and application-related constraints and requirements. Numerous applications of Wireless Sensor Networks (WSNs) have appeared in various fields, from environmental monitoring, to tactical fields, and healthcare at home, promising to change our quality of life and facilitating the vision of sensor network enabled smart cities. Given the enormous requirements that emerge in such a setting-both in terms of data and energy-data aggregation appears as a key element in reducing the amount of traffic in wireless sensor networks and achieving energy conservation. Probabilistic frameworks have been introduced as operational efficient and performance effective solutions for data aggregation in distributed sensor networks. In this work, we introduce an overall optimization approach that improves and complements such frameworks towards identifying the optimal probability for a node to aggregate packets as well as the optimal aggregation period that a node should wait for performing aggregation, so as to minimize the overall energy consumption, while satisfying certain imposed delay constraints. Primal dual decomposition is employed to solve the corresponding optimization problem while simulation results demonstrate the operational efficiency of the proposed approach under different traffic and topology scenarios.

  1. Distributed Optimization of Multi Beam Directional Communication Networks

    Science.gov (United States)

    2017-06-30

    Distributed Optimization of Multi-Beam Directional Communication Networks Theodoros Tsiligkaridis MIT Lincoln Laboratory Lexington, MA 02141, USA...based routing. I. INTRODUCTION Missions where multiple communication goals are of in- terest are becoming more prevalent in military applications...Multilayer communications may occur within a coalition; for example, a team consisting of ground vehicles and an airborne set of assets may desire to

  2. Optimization of composite panels using neural networks and genetic algorithms

    NARCIS (Netherlands)

    Ruijter, W.; Spallino, R.; Warnet, Laurent; de Boer, Andries

    2003-01-01

    The objective of this paper is to present first results of a running study on optimization of aircraft components (composite panels of a typical vertical tail plane) by using Genetic Algorithms (GA) and Neural Networks (NN). The panels considered are standardized to some extent but still there is a

  3. Optimizing Knowledge Sharing in Learning Networks through Peer Tutoring

    NARCIS (Netherlands)

    Hsiao, Amy; Brouns, Francis; Kester, Liesbeth; Sloep, Peter

    2009-01-01

    Hsiao, Y. P., Brouns, F., Kester, L., & Sloep, P. (2009). Optimizing Knowledge Sharing in Learning Networks through Peer Tutoring. Presentation at the IADIS international conference on Cognition and Exploratory in Digital Age (CELDA 2009). November, 20-22, 2009, Rome, Italy.

  4. Optimizing Knowledge Sharing In Learning Networks Through Peer Tutoring

    NARCIS (Netherlands)

    Hsiao, Amy; Brouns, Francis; Kester, Liesbeth; Sloep, Peter

    2009-01-01

    Hsiao, Y. P., Brouns, F., Kester, L., & Sloep, P. B. (2009). Optimizing Knowledge Sharing In Learning Networks Through Peer Tutoring. In D. Kinshuk, J. Sampson, J. Spector, P. Isaías, P. Barbosa & D. Ifenthaler (Eds.). Proceedings of IADIS International Conference Cognition and Exploratory Learning

  5. Nonlinear Non-convex Optimization of Hydraulic Networks

    DEFF Research Database (Denmark)

    Tahavori, Maryamsadat; Kallesøe, Carsten; Leth, John-Josef

    2013-01-01

    Pressure management in water supply systems is an effective way to reduce the leakage in a system. In this paper, the pressure management and the reduction of power consumption of a water supply system is formulated as an optimization problem. The problem is to minimize the power consumption...... in pumps and also to regulate the pressure at the end-user valves to a desired value. The optimization problem which is solved is a nonlinear and non-convex optimization. The barrier method is used to solve this problem. The modeling framework and the optimization technique which are used are general....... They can be used for a general hydraulic networks to optimize the leakage and energy consumption and to satisfy the demands at the end-users. The results in this paper show that the power consumption of the pumps is reduced....

  6. Influence maximization in complex networks through optimal percolation

    CERN Document Server

    Morone, Flaviano

    2015-01-01

    The whole frame of interconnections in complex networks hinges on a specific set of structural nodes, much smaller than the total size, which, if activated, would cause the spread of information to the whole network [1]; or, if immunized, would prevent the diffusion of a large scale epidemic [2,3]. Localizing this optimal, i.e. minimal, set of structural nodes, called influencers, is one of the most important problems in network science [4,5]. Despite the vast use of heuristic strategies to identify influential spreaders [6-14], the problem remains unsolved. Here, we map the problem onto optimal percolation in random networks to identify the minimal set of influencers, which arises by minimizing the energy of a many-body system, where the form of the interactions is fixed by the non-backtracking matrix [15] of the network. Big data analyses reveal that the set of optimal influencers is much smaller than the one predicted by previous heuristic centralities. Remarkably, a large number of previously neglected we...

  7. Event localization in underwater wireless sensor networks using Monitoring Courses

    KAUST Repository

    Debont, Matthew John Robert

    2012-08-01

    We propose m-courses (Monitoring Courses), a novel solution to localize events in an underwater wireless sensor network. These networks consists of surface gateways and relay nodes. GPS can localize the position of surface gateways which can then distribute their locations through the network using acoustic modems. Relay nodes are deployed to remain static, but these untethered nodes may drift due to water currents, resulting in disruption of communication links. We develop a novel underwater alarm system using a cyclic graph model. In the event of link failure, a series of alarm packets are broadcast in the network. These alarms are then captured by the underwater m-courses, which can also be used to assure network connectivity and identify node failures. M-courses also allow the network to localize events and identify network issues locally before forwarding results upwards to a Surface Gateway node. This reduces communication overhead and allows for efficient management of nodes in a mobile network. Our results show that m-course routing reduces the number of sends required to report an event to a Surface Gateway by up to 80% when compared to a naïve routing implementation.

  8. Optimal access to large databases via networks

    Energy Technology Data Exchange (ETDEWEB)

    Munro, J.K.; Fellows, R.L.; Phifer, D. Carrick, M.R.; Tarlton, N.

    1997-10-01

    A CRADA with Stephens Engineering was undertaken in order to transfer knowledge and experience about access to information in large text databases, with results of queries and searches provided using the multimedia capabilities of the World Wide Web. Data access is optimized by the use of intelligent agents. Technology Logic Diagram documents published for the DOE facilities in Oak Ridge (K-25, X-10, Y-12) were chosen for this effort because of the large number of technologies identified, described, evaluated, and ranked for possible use in the environmental remediation of these facilities. Fast, convenient access to this information is difficult because of the volume and complexity of the data. WAIS software used to provide full-text, field-based search capability can also be used, through the development of an appropriate hierarchy of menus, to provide tabular summaries of technologies satisfying a wide range of criteria. The menu hierarchy can also be used to regenerate dynamically many of the tables that appeared in the original hardcopy publications, all from a single text database of the technology descriptions. Use of the Web environment permits linking many of the Technology Logic Diagram references to on-line versions of these publications, particularly the DOE Orders and related directives providing the legal requirements that were the basis for undertaking the Technology Logic Diagram studies in the first place.

  9. Optimized algorithm for balancing clusters in wireless sensor networks

    Institute of Scientific and Technical Information of China (English)

    Mucheol KIM; Sun-hong KIM; Hyungjin BYUN; Sang-yong HAN

    2009-01-01

    Wireless sensor networks consist of hundreds or thousands of sensor nodes that involve numerous restrictions including computation capability and battery capacity. Topology control is an important issue for achieving a balanced placement of sensor nodes. The clustering scheme is a widely known and efficient means of topology control for transmitting information to the base station in two hops. The automatic routing scheme of the self-organizing technique is another critical element of wireless sensor networks. In this paper we propose an optimal algorithm with cluster balance taken into consideration, and compare it with three well known and widely used approaches, I.e., LEACH, MEER, and VAP-E, in performance evaluation. Experimental results show that the proposed approach increases the overall network lifetime, indicating that the amount of energy required for communication to the base station will be reduced for locating an optimal cluster.

  10. EPMOSt: An Energy-Efficient Passive Monitoring System for Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Fernando P. Garcia

    2014-06-01

    Full Text Available Monitoring systems are important for debugging and analyzing Wireless Sensor Networks (WSN. In passive monitoring, a monitoring network needs to be deployed in addition to the network to be monitored, named the target network. The monitoring network captures and analyzes packets transmitted by the target network. An energy-efficient passive monitoring system is necessary when we need to monitor a WSN in a real scenario because the lifetime of the monitoring network is extended and, consequently, the target network benefits from the monitoring for a longer time. In this work, we have identified, analyzed and compared the main passive monitoring systems proposed for WSN. During our research, we did not identify any passive monitoring system for WSN that aims to reduce the energy consumption of the monitoring network. Therefore, we propose an Energy-efficient Passive MOnitoring SysTem for WSN named EPMOSt that provides monitoring information using a Simple Network Management Protocol (SNMP agent. Thus, any management tool that supports the SNMP protocol can be integrated with this monitoring system. Experiments with real sensors were performed in several scenarios. The results obtained show the energy efficiency of the proposed monitoring system and the viability of using it to monitor WSN in real scenarios.

  11. An optimal control approach to probabilistic Boolean networks

    Science.gov (United States)

    Liu, Qiuli

    2012-12-01

    External control of some genes in a genetic regulatory network is useful for avoiding undesirable states associated with some diseases. For this purpose, a number of stochastic optimal control approaches have been proposed. Probabilistic Boolean networks (PBNs) as powerful tools for modeling gene regulatory systems have attracted considerable attention in systems biology. In this paper, we deal with a problem of optimal intervention in a PBN with the help of the theory of discrete time Markov decision process. Specifically, we first formulate a control model for a PBN as a first passage model for discrete time Markov decision processes and then find, using a value iteration algorithm, optimal effective treatments with the minimal expected first passage time over the space of all possible treatments. In order to demonstrate the feasibility of our approach, an example is also displayed.

  12. Neural network learning of optimal Kalman prediction and control

    CERN Document Server

    Linsker, Ralph

    2008-01-01

    Although there are many neural network (NN) algorithms for prediction and for control, and although methods for optimal estimation (including filtering and prediction) and for optimal control in linear systems were provided by Kalman in 1960 (with nonlinear extensions since then), there has been, to my knowledge, no NN algorithm that learns either Kalman prediction or Kalman control (apart from the special case of stationary control). Here we show how optimal Kalman prediction and control (KPC), as well as system identification, can be learned and executed by a recurrent neural network composed of linear-response nodes, using as input only a stream of noisy measurement data. The requirements of KPC appear to impose significant constraints on the allowed NN circuitry and signal flows. The NN architecture implied by these constraints bears certain resemblances to the local-circuit architecture of mammalian cerebral cortex. We discuss these resemblances, as well as caveats that limit our current ability to draw ...

  13. Congestion Relief of Contingent Power Network with Evolutionary Optimization Algorithm

    Directory of Open Access Journals (Sweden)

    Abhinandan De

    2012-03-01

    Full Text Available This paper presents a differential evolution optimization technique based methodology for congestion management cost optimization of contingent power networks. In Deregulated systems, line congestion apart from causing stability problems can increase the cost of electricity. Restraining line flow to a particular level of congestion is quite imperative from stability as well as economy point of view. Employing ‘Congestion Sensitivity Index’ proposed in this paper, the algorithm proposed can be adopted for selecting the congested lines in a power networks and then to search for a congestion constrained optimal generation schedule at the cost of a minimum ‘congestion management charge’ without any load curtailment and installation of FACTS devices. It has been depicted that the methodology on application can provide better operating conditions in terms of improvement of bus voltage and loss profile of the system. The efficiency of the proposed methodology has been tested on an IEEE 30 bus benchmark system and the results look promising.

  14. Multi-objective optimization framework for networked predictive controller design.

    Science.gov (United States)

    Das, Sourav; Das, Saptarshi; Pan, Indranil

    2013-01-01

    Networked Control Systems (NCSs) often suffer from random packet dropouts which deteriorate overall system's stability and performance. To handle the ill effects of random packet losses in feedback control systems, closed over communication network, a state feedback controller with predictive gains has been designed. To achieve improved performance, an optimization based controller design framework has been proposed in this paper with Linear Matrix Inequality (LMI) constraints, to ensure guaranteed stability. Different conflicting objective functions have been optimized with Non-dominated Sorting Genetic Algorithm-II (NSGA-II). The methodology proposed in this paper not only gives guaranteed closed loop stability in the sense of Lyapunov, even in the presence of random packet losses, but also gives an optimization trade-off between two conflicting time domain control objectives.

  15. Performance Evaluation and Optimization of Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Dr Jayant Dubey

    2013-06-01

    Full Text Available A wireless sensor network (WSN is an ad-hoc network composed of small sensor nodes deployed in large numbers to sense the physical world. Wireless sensor networks have very broad application prospects including both military and civilian usage. They include surveillance, tracking at critical facilities, or monitoring animal habitats. Sensor networks have the potential to radically change the way people observe and interact with their environment. With current wireless sensor network technology, people will gain advanced knowledge of physical and social systems, and the advent of a ubiquitous sensing era is coming. In-network processing or data aggregation is an essential function of WSNs to collect raw sensory data and get aggregated statistics about the measured environment, and help queries capture the major feature or changes of the measured systems. As more and more applications of WSNs collect sensitive measurements of people’s everyday life, privacy and security concerns draw more and more attention. If privacy of sensory content is not preserved, it is not feasible to deploy the WSNs for information collection. On the other hand, if integrity of the collected sensory information is not protected, no queries or users can trust and/or use the collected information. Hence, two important issues should be addressed before wireless sensor network systems can realize their promise in civilian applications: (1 protect data privacy, so the deployment of the wireless sensor network systems is feasible; (2 enforce integrity, so users can trust the collected or aggregated information.

  16. Parameter identifiability-based optimal observation remedy for biological networks.

    Science.gov (United States)

    Wang, Yulin; Miao, Hongyu

    2017-05-04

    To systematically understand the interactions between numerous biological components, a variety of biological networks on different levels and scales have been constructed and made available in public databases or knowledge repositories. Graphical models such as structural equation models have long been used to describe biological networks for various quantitative analysis tasks, especially key biological parameter estimation. However, limited by resources or technical capacities, partial observation is a common problem in experimental observations of biological networks, and it thus becomes an important problem how to select unobserved nodes for additional measurements such that all unknown model parameters become identifiable. To the best knowledge of our authors, a solution to this problem does not exist until this study. The identifiability-based observation problem for biological networks is mathematically formulated for the first time based on linear recursive structural equation models, and then a dynamic programming strategy is developed to obtain the optimal observation strategies. The efficiency of the dynamic programming algorithm is achieved by avoiding both symbolic computation and matrix operations as used in other studies. We also provided necessary theoretical justifications to the proposed method. Finally, we verified the algorithm using synthetic network structures and illustrated the application of the proposed method in practice using a real biological network related to influenza A virus infection. The proposed approach is the first solution to the structural identifiability-based optimal observation remedy problem. It is applicable to an arbitrary directed acyclic biological network (recursive SEMs) without bidirectional edges, and it is a computerizable method. Observation remedy is an important issue in experiment design for biological networks, and we believe that this study provides a solid basis for dealing with more challenging design

  17. Optimization of remediation strategies using vadose zone monitoring systems

    Science.gov (United States)

    Dahan, Ofer

    2016-04-01

    In-situ bio-remediation of the vadose zone depends mainly on the ability to change the subsurface hydrological, physical and chemical conditions in order to enable development of specific, indigenous, pollutants degrading bacteria. As such the remediation efficiency is much dependent on the ability to implement optimal hydraulic and chemical conditions in deep sections of the vadose zone. These conditions are usually determined in laboratory experiments where parameters such as the chemical composition of the soil water solution, redox potential and water content of the sediment are fully controlled. Usually, implementation of desired optimal degradation conditions in deep vadose zone at full scale field setups is achieved through infiltration of water enriched with chemical additives on the land surface. It is assumed that deep percolation into the vadose zone would create chemical conditions that promote biodegradation of specific compounds. However, application of water with specific chemical conditions near land surface dose not necessarily results in promoting of desired chemical and hydraulic conditions in deep sections of the vadose zone. A vadose-zone monitoring system (VMS) that was recently developed allows continuous monitoring of the hydrological and chemical properties of deep sections of the unsaturated zone. The VMS includes flexible time-domain reflectometry (FTDR) probes which allow continuous monitoring of the temporal variation of the vadose zone water content, and vadose-zone sampling ports (VSPs) which are designed to allow frequent sampling of the sediment pore-water and gas at multiple depths. Implementation of the vadose zone monitoring system in sites that undergoes active remediation provides real time information on the actual chemical and hydrological conditions in the vadose zone as the remediation process progresses. Up-to-date the system has been successfully implemented in several studies on water flow and contaminant transport in

  18. Optimal network modification for spectral radius dependent phase transitions

    Science.gov (United States)

    Rosen, Yonatan; Kirsch, Lior; Louzoun, Yoram

    2016-09-01

    The dynamics of contact processes on networks is often determined by the spectral radius of the networks adjacency matrices. A decrease of the spectral radius can prevent the outbreak of an epidemic, or impact the synchronization among systems of coupled oscillators. The spectral radius is thus tightly linked to network dynamics and function. As such, finding the minimal change in network structure necessary to reach the intended spectral radius is important theoretically and practically. Given contemporary big data resources such as large scale communication or social networks, this problem should be solved with a low runtime complexity. We introduce a novel method for the minimal decrease in weights of edges required to reach a given spectral radius. The problem is formulated as a convex optimization problem, where a global optimum is guaranteed. The method can be easily adjusted to an efficient discrete removal of edges. We introduce a variant of the method which finds optimal decrease with a focus on weights of vertices. The proposed algorithm is exceptionally scalable, solving the problem for real networks of tens of millions of edges in a short time.

  19. An Optimal Path Computation Architecture for the Cloud-Network on Software-Defined Networking

    Directory of Open Access Journals (Sweden)

    Hyunhun Cho

    2015-05-01

    Full Text Available Legacy networks do not open the precise information of the network domain because of scalability, management and commercial reasons, and it is very hard to compute an optimal path to the destination. According to today’s ICT environment change, in order to meet the new network requirements, the concept of software-defined networking (SDN has been developed as a technological alternative to overcome the limitations of the legacy network structure and to introduce innovative concepts. The purpose of this paper is to propose the application that calculates the optimal paths for general data transmission and real-time audio/video transmission, which consist of the major services of the National Research & Education Network (NREN in the SDN environment. The proposed SDN routing computation (SRC application is designed and applied in a multi-domain network for the efficient use of resources, selection of the optimal path between the multi-domains and optimal establishment of end-to-end connections.

  20. OPTIMAL CONFIGURATION OF A COMMAND AND CONTROL NETWORK: BALANCING PERFORMANCE AND RECONFIGURATION CONSTRAINTS

    Energy Technology Data Exchange (ETDEWEB)

    L. DOWELL

    1999-08-01

    The optimization of the configuration of communications and control networks is important for assuring the reliability and performance of the networks. This paper presents techniques for determining the optimal configuration for such a network in the presence of communication and connectivity constraints. reconfiguration to restore connectivity to a data-fusion network following the failure of a network component.

  1. Gateway Deployment optimization in Cellular Wi-Fi Mesh Networks

    Directory of Open Access Journals (Sweden)

    Rajesh Prasad

    2006-07-01

    Full Text Available With the standardization of IEEE 802.11, there has been an explosive growth of wireless local area networks (WLAN. Recently, this cost effective technology is being developed aggressively for establishing metro-scale “cellular Wi-Fi” network to support seamless Internet access in the urban area. We envision a large scale WLAN system in the future where Access Points (APs will be scattered over an entire city enabling people to use their mobile devices ubiquitously. The problem addressed in this paper involves finding the minimum number of gateways and their optimal placement so as to minimize the network installation costs while maintaining reliability, flexibility and an acceptable grade of service. The problem is modeled taking a network graph, where the nodes represents either the Access Points of IEEE 802.11 or wired backbone gateways. In this paper, we present two methods (1 an innovative approach using integer linear programming (ILP for gateway selection in the cellular Wi-Fi network, and (2 a completely new heuristic (OPEN/CLOSE to solve the gateway selection problem. In the ILP model, we developed a set of linear inequalities based on various constraints. The ILP model is solved by using lp-solve, a simplex-based software for linear and integer programming problems. The second approach is an OPEN/CLOSE heuristic, tailored for cellular Wi-Fi, which arrives at a sub-optimal solution. Java programming language is used for simulation in OPEN/CLOSE heuristic. Extensive simulations are carried out for performance evaluation. Simulation results show that the proposed approaches can effectively identify a set of gateways at optimal locations in a cellular Wi-Fi network, resulting in an overall cost reduction of up to 50%. The technique presented in this paper is generalized and can be used for gateway selection for other networks as well.

  2. A Spectrum Handoff Scheme for Optimal Network Selection in NEMO Based Cognitive Radio Vehicular Networks

    Directory of Open Access Journals (Sweden)

    Krishan Kumar

    2017-01-01

    Full Text Available When a mobile network changes its point of attachments in Cognitive Radio (CR vehicular networks, the Mobile Router (MR requires spectrum handoff. Network Mobility (NEMO in CR vehicular networks is concerned with the management of this movement. In future NEMO based CR vehicular networks deployment, multiple radio access networks may coexist in the overlapping areas having different characteristics in terms of multiple attributes. The CR vehicular node may have the capability to make call for two or more types of nonsafety services such as voice, video, and best effort simultaneously. Hence, it becomes difficult for MR to select optimal network for the spectrum handoff. This can be done by performing spectrum handoff using Multiple Attributes Decision Making (MADM methods which is the objective of the paper. The MADM methods such as grey relational analysis and cost based methods are used. The application of MADM methods provides wider and optimum choice among the available networks with quality of service. Numerical results reveal that the proposed scheme is effective for spectrum handoff decision for optimal network selection with reduced complexity in NEMO based CR vehicular networks.

  3. Depth optimal sorting networks resistant to k passive faults

    Energy Technology Data Exchange (ETDEWEB)

    Piotrow, M. [Univ. of Wroclaw (Poland)

    1996-12-31

    In this paper, we study the problem of constructing a sorting network that is tolerant to faults and whose running time (i.e. depth) is as small as possible. We consider the scenario of worst-case comparator faults and follow the model of passive comparator failure proposed by Yao and Yao, in which a faulty comparator outputs directly its inputs without comparison. Our main result is the first construction of an N-input, k-fault-tolerant sorting network that is of an asymptotically optimal depth {theta}(log N+k). That improves over the recent result of Leighton and Ma, whose network is of depth O(log N + k log log N/log k). Actually, we present a fault-tolerant correction network that can be added after any N-input sorting network to correct its output in the presence of at most k faulty comparators. Since the depth of the network is O(log N + k) and the constants hidden behind the {open_quotes}O{close_quotes} notation are not big, the construction can be of practical use. Developing the techniques necessary to show the main result, we construct a fault-tolerant network for the insertion problem. As a by-product, we get an N-input, O(log N)-depth INSERT-network that is tolerant to random faults, thereby answering a question posed by Ma in his PhD thesis. The results are based on a new notion of constant delay comparator networks, that is, networks in which each register is used (compared) only in a period of time of a constant length. Copies of such networks can be put one after another with only a constant increase in depth per copy.

  4. Vibration monitoring of EDF rotating machinery using artificial neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Alguindigue, I.E.; Loskiewicz-Buczak, A.; Uhrig, R.E. (Tennessee Univ., Knoxville, TN (United States). Dept. of Nuclear Engineering); Hamon, L.; Lefevre, F. (Electricite de France, 78 - Chatou (France). Direction des Etudes et Recherches)

    1991-01-01

    Vibration monitoring of components in nuclear power plants has been used for a number of years. This technique involves the analysis of vibration data coming from vital components of the plant to detect features which reflect the operational state of machinery. The analysis leads to the identification of potential failures and their causes, and makes it possible to perform efficient preventive maintenance. Earlydetection is important because it can decrease the probability of catastrophic failures, reduce forced outgage, maximize utilization of available assets, increase the life of the plant, and reduce maintenance costs. This paper documents our work on the design of a vibration monitoring methodology based on neural network technology. This technology provides an attractive complement to traditional vibration analysis because of the potential of neural networks to operate in real-time mode and to handle data which may be distorted or noisy. Our efforts have been concentrated on the analysis and classification of vibration signatures collected by Electricite de France (EDF). Two neural networks algorithms were used in our project: the Recirculation algorithm and the Backpropagation algorithm. Although this project is in the early stages of development it indicates that neural networks may provide a viable methodology for monitoring and diagnostics of vibrating components. Our results are very encouraging.

  5. Vibration monitoring of EDF rotating machinery using artificial neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Alguindigue, I.E.; Loskiewicz-Buczak, A.; Uhrig, R.E. [Tennessee Univ., Knoxville, TN (United States). Dept. of Nuclear Engineering; Hamon, L.; Lefevre, F. [Electricite de France, 78 - Chatou (France). Direction des Etudes et Recherches

    1991-12-31

    Vibration monitoring of components in nuclear power plants has been used for a number of years. This technique involves the analysis of vibration data coming from vital components of the plant to detect features which reflect the operational state of machinery. The analysis leads to the identification of potential failures and their causes, and makes it possible to perform efficient preventive maintenance. Earlydetection is important because it can decrease the probability of catastrophic failures, reduce forced outgage, maximize utilization of available assets, increase the life of the plant, and reduce maintenance costs. This paper documents our work on the design of a vibration monitoring methodology based on neural network technology. This technology provides an attractive complement to traditional vibration analysis because of the potential of neural networks to operate in real-time mode and to handle data which may be distorted or noisy. Our efforts have been concentrated on the analysis and classification of vibration signatures collected by Electricite de France (EDF). Two neural networks algorithms were used in our project: the Recirculation algorithm and the Backpropagation algorithm. Although this project is in the early stages of development it indicates that neural networks may provide a viable methodology for monitoring and diagnostics of vibrating components. Our results are very encouraging.

  6. Network Distributed Monitoring System Based on Robot Technology Middleware

    Directory of Open Access Journals (Sweden)

    Kunikatsu Takase

    2008-11-01

    Full Text Available In this paper, a network distributed monitoring system for human assistance robot system was developed to improve the interaction among the users and local service robotic system and enable a remote user to get a better understanding of what is going on in the local environment. Home integration robot system and network monitoring system using QuickCam Orbit cameras were developed and demonstrated from June 9 to June 19 at the 2005 World Exposition, Aichi, Japan. Improvements of network distributed monitoring system using IEEE1394 cameras with high performance and high resolution have been done in order to extend the application of system. Robot Technology Middleware (RTM was used in the developed system. By using RTM, we can develop cameras functional elements as RT software components that can be implemented by different programming languages, run in different operating system, or connected in different networks to interoperate.It is also easy to create comprehensive robot system application by reusing existing modules thus facilitating networkdistributed software sharing and improving the cost of writing and maintaining software.

  7. Monitoring and Optimization of ATLAS Tier 2 Center GoeGrid

    CERN Document Server

    AUTHOR|(INSPIRE)INSPIRE-00219638; Yahyapour, Ramin

    The demand on computational and storage resources is growing along with the amount of information that needs to be processed and preserved. In order to ease the provisioning of the digital services to the growing number of consumers, more and more distributed computing systems and platforms are actively developed and employed. The building block of the distributed computing infrastructure are single computing centers, similar to the Worldwide LHC Computing Grid, Tier 2 centre GoeGrid. The main motivation of this thesis was the optimization of GoeGrid performance by efficient monitoring. The goal has been achieved by means of the GoeGrid monitoring information analysis. The data analysis approach was based on the adaptive-network-based fuzzy inference system (ANFIS) and machine learning algorithm such as Linear Support Vector Machine (SVM). The main object of the research was the digital service, since availability, reliability and serviceability of the computing platform can be measured according to the const...

  8. Optimality and Approximate Optimality of Source-Channel Separation in Networks

    CERN Document Server

    Tian, Chao; Diggavi, Suhas; Shamai, Shlomo

    2010-01-01

    We consider the source-channel separation architecture for lossy source coding in general communication networks. It is shown that the separation approach is optimal in two general scenarios, and is approximately optimal in a third scenario. The two general scenarios for which separation is optimal complement each other: the first scenario is when the memoryless sources at source nodes are arbitrarily correlated, each of which is to be reconstructed at possibly multiple destinations within certain distortions, but the channels in this network are synchronized, orthogonal and memoryless; the second scenario is when the memoryless sources are mutually independent, each of which is to be reconstructed only at one destination within a certain distortion, but the channels are general, including finite-memory multi-user channels such as multiple access, broadcast, interference and relay channels. The third general scenario, for which we demonstrate approximate optimality of source-channel separation, relaxes the se...

  9. A simplified recurrent neural network for pseudoconvex optimization subject to linear equality constraints

    Science.gov (United States)

    Qin, Sitian; Fan, Dejun; Su, Peng; Liu, Qinghe

    2014-04-01

    In this paper, the optimization techniques for solving pseudoconvex optimization problems are investigated. A simplified recurrent neural network is proposed according to the optimization problem. We prove that the optimal solution of the optimization problem is just the equilibrium point of the neural network, and vice versa if the equilibrium point satisfies the linear constraints. The proposed neural network is proven to be globally stable in the sense of Lyapunov and convergent to an exact optimal solution of the optimization problem. A numerical simulation is given to illustrate the global convergence of the neural network. Applications in business and chemistry are given to demonstrate the effectiveness of the neural network.

  10. Velocity model optimization for surface microseismic monitoring via amplitude stacking

    Science.gov (United States)

    Jiang, Haiyu; Wang, Zhongren; Zeng, Xiaoxian; Lü, Hao; Zhou, Xiaohua; Chen, Zubin

    2016-12-01

    A usable velocity model in microseismic projects plays a crucial role in achieving statistically reliable microseismic event locations. Existing methods for velocity model optimization rely mainly on picking arrival times at individual receivers. However, for microseismic monitoring with surface stations, seismograms of perforation shots have such low signal-to-noise ratios (S/N) that they do not yield sufficiently reliable picks. In this study, we develop a framework for constructing a 1-D flat-layered a priori velocity model using a non-linear optimization technique based on amplitude stacking. The energy focusing of the perforation shot is improved thanks to very fast simulated annealing (VFSA), and the accuracies of shot relocations are used to evaluate whether the resultant velocity model can be used for microseismic event location. Our method also includes a conventional migration-based location technique that utilizes successive grid subdivisions to improve computational efficiency and source location accuracy. Because unreasonable a priori velocity model information and interference due to additive noise are the major contributors to inaccuracies in perforation shot locations, we use velocity model optimization as a compensation scheme. Using synthetic tests, we show that accurate locations of perforation shots can be recovered to within 2 m, even with pre-stack S/N ratios as low as 0.1 at individual receivers. By applying the technique to a coal-bed gas reservoir in Western China, we demonstrate that perforation shot location can be recovered to within the tolerance of the well tip location.

  11. Environmental Monitoring and Greenhouse Control by Distributed Sensor Network

    Directory of Open Access Journals (Sweden)

    S.R.BOSELIN PRABHU

    2014-03-01

    Full Text Available A sensor is a miniature component which measure physical parameters from the environment. Sensors measure the physical parameters and transmit them either by wired or wireless medium. In wireless medium the sensor and its associated components are called as node. A node is self-possessed by a processor, local memory, sensors, radio, battery and a base station responsible for receiving and processing data collected by the nodes. They carry out joint activities due to limited resources such as battery, processor and memory. Nowadays, the applications of these networks are numerous, varied and the applications in agriculture are still budding. One interesting application is in environmental monitoring and greenhouse control, where the crop conditions such as climate and soil do not depend on natural agents. To control and monitor the environmental factors, sensors and actuators are necessary. Under these circumstances, these devices must be used to make a distributed measure, spreading sensors all over the greenhouse using distributed clustering. This paper reveals an idea of environmental monitoring and greenhouse control using a sensor network. The hardware implementation shows periodic monitoring and control of greenhouse gases in an enhanced manner. Future work is concentrated in application of the same mechanism using wireless sensor network.

  12. A Distributed Algorithm for Energy Optimization in Hydraulic Networks

    DEFF Research Database (Denmark)

    Kallesøe, Carsten; Wisniewski, Rafal; Jensen, Tom Nørgaard

    2014-01-01

    is distributed in the sense that all calculations are implemented where the necessary information is available, including both parameters and measurements. A communication network between the pumps is implemented for global optimization. The local implementation of the algorithm means that the system becomes......An industrial case study in the form of a large-scale hydraulic network underlying a district heating system is considered. A distributed control is developed that minimizes the aggregated electrical energy consumption of the pumps in the network without violating the control demands. The algorithm...... a Plug & Play control system as most commissioning can be done during the manufacture of the pumps. Only information on the graph-structure of the hydraulic network is needed during installation....

  13. An optimal routing strategy on scale-free networks

    Science.gov (United States)

    Yang, Yibo; Zhao, Honglin; Ma, Jinlong; Qi, Zhaohui; Zhao, Yongbin

    Traffic is one of the most fundamental dynamical processes in networked systems. With the traditional shortest path routing (SPR) protocol, traffic congestion is likely to occur on the hub nodes on scale-free networks. In this paper, we propose an improved optimal routing (IOR) strategy which is based on the betweenness centrality and the degree centrality of nodes in the scale-free networks. With the proposed strategy, the routing paths can accurately bypass hub nodes in the network to enhance the transport efficiency. Simulation results show that the traffic capacity as well as some other indexes reflecting transportation efficiency are further improved with the IOR strategy. Owing to the significantly improved traffic performance, this study is helpful to design more efficient routing strategies in communication or transportation systems.

  14. The use of a wireless sensor network to monitor the spectrum in urban areas

    Science.gov (United States)

    Malon, Krzysztof; Skokowski, Paweł; Łopatka, Jerzy

    2017-04-01

    Wireless sensor networks are a tool increasingly used to monitor various environmental parameters. They can also be used for monitoring the electromagnetic spectrum. Wireless sensors, due to their small size, typically have simplified radio receivers with reduced sensitivity and use small antennas. As a result, their effective performance area is similarly limited. This is especially important in urban areas where there are various kinds of adverse propagation phenomena related to area coverage. The aim of the article is to present the phenomena in the wireless sensor networks and propose criteria and methods to optimize their deployment to ensure maximizing the probability of detection of emissions, minimization of unmonitored areas and to provide the necessary hardware redundancy in the priority areas.

  15. Cross-layer optimization in ultra wideband networks

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    Ultra wideband (UWB) network brings both chance and challenge to personal area wireless communications. Compared with other IEEE 802 small range wireless protocols (such as WLAN and Bluetooth), UWB has both extremely high bandwidth (up to 480 Mbps) and low radiation. Moreover, the structured MAC layer of UWB is the fundamental difference to WLAN. The top one is that only when two UWB devices belong to the same piconet can they communicate with each other directly, which means that we must jointly consider topology formation and routing when deploying UWB networks because the interaction between routing and topology formation makes separate optimization ineffective. This paper tries to optimize UWB network from a cross-layer point of view. Specifically, given device spatial distribution and traffic requirement, we want to form piconets and determine routing jointly, to maximize the overall throughput. We formulate the problem of joint optimization to mixed-integer programming and give a practical lower bound that is very close to the theoretical upper bound in our simulation. Furthermore, our lower bound is much better than an algorithm that only considers topology formation in UWB networks.

  16. Applications of the Renewable Energy Network Optimization Tool

    Science.gov (United States)

    Alliss, R.; Link, R.; Apling, D.; Kiley, H.; Mason, M.; Darmenova, K.

    2010-12-01

    As the renewable energy industry continues to grow so does the requirement for atmospheric modeling and analysis tools to maximize both wind and solar power. Renewable energy generation is variable however; presenting challenges for electrical grid operation and requires a variety of measures to adequately firm power. These measures include the production of non-renewable generation during times when renewables are not available. One strategy for minimizing the variability of renewable energy production is site diversity. Assuming that a network of renewable energy systems feed a common electrical grid, site diversity ensures that when one system on the network has a reduction in generation others on the same grid make up the difference. The site-diversity strategy can be used to mitigate the intermittency in alternative energy production systems while still maximizing saleable energy. The Renewable Energy Network Optimization Tool (ReNOT) has recently been developed to study the merits of site optimization for wind farms. The modeling system has a plug-in architecture that allows us to accommodate a wide variety of renewable energy system designs and performance metrics. The Weather Research and Forecasting (WRF) mesoscale model is applied to generate high-resolution wind databases to support the site selection of wind farms. These databases are generated on High Performance Computing systems such as the Rocky Mountain Supercomputing Center (RMSC). The databases are then accessed by ReNOT and an optimized site selection is developed. We can accommodate numerous constraints (e.g., number of sites, the geographic extent of the optimization, proximity to high-voltage transport lines, etc.). As part of our collaboration with RMSC and the State of Montana a study was performed to estimate the optimal locations of a network of wind farms. Comparisons were made to four existing wind farm locations in Montana including Glacier with a 210 MW name plate capacity, Horseshoe

  17. Novel anomaly detection approach for telecommunication network proactive performance monitoring

    Institute of Scientific and Technical Information of China (English)

    Yanhua YU; Jun WANG; Xiaosu ZHAN; Junde SONG

    2009-01-01

    The mode of telecommunication network management is changing from "network oriented" to "subscriber oriented". Aimed at enhancing subscribers'feeling, proactive performance monitoring (PPM) can enable a fast fault correction by detecting anomalies designating performance degradation. In this paper, a novel anomaly detection approach is the proposed taking advantage of time series prediction and the associated confidence interval based on multiplicative autoregressive integrated moving average (ARIMA). Furthermore, under the assumption that the training residual is a white noise process following a normal distribution, the associated confidence interval of prediction can be figured out under any given confidence degree 1-α by constructing random variables satisfying t distribution. Experimental results verify the method's effectiveness.

  18. An Air-Ground Wireless Sensor Network for Crop Monitoring

    Directory of Open Access Journals (Sweden)

    Claudio Rossi

    2011-06-01

    Full Text Available This paper presents a collaborative system made up of a Wireless Sensor Network (WSN and an aerial robot, which is applied to real-time frost monitoring in vineyards. The core feature of our system is a dynamic mobile node carried by an aerial robot, which ensures communication between sparse clusters located at fragmented parcels and a base station. This system overcomes some limitations of the wireless networks in areas with such characteristics. The use of a dedicated communication channel enables data routing to/from unlimited distances.

  19. The Networked Manufacturing Resources Optimizing Configuration System and Its Partners Selection Method

    Institute of Scientific and Technical Information of China (English)

    DONG Zhao-yang; SUN Shu-dong

    2006-01-01

    The three levels optimizing strategy is put forward for the networked manufacturing resources optimizing configuration, namely, the optimizing of a logical manufacturing process,the optimizing of simulation-based integration of process planning and scheduling, and the optimizing of networked production scheduling. Then, the web services-based architecture of networked manufacturing resources optimizing configuration is brought forward. Finally, the key algorithm of the networked manufacturing resources optimizing configuration is discussed, namely, the two phases manufacturing partners selection method, which including the group technology-based manufacturing resources pre-configuration and the genetic algorithm-based executable manufacturing process optimizing.

  20. Mobile Wireless Sensor Networks for Advanced Soil Sensing and Ecosystem Monitoring

    Science.gov (United States)

    Mollenhauer, Hannes; Schima, Robert; Remmler, Paul; Mollenhauer, Olaf; Hutschenreuther, Tino; Toepfer, Hannes; Dietrich, Peter; Bumberger, Jan

    2015-04-01

    For an adequate characterization of ecosystems it is necessary to detect individual processes with suitable monitoring strategies and methods. Due to the natural complexity of all environmental compartments, single point or temporally and spatially fixed measurements are mostly insufficient for an adequate representation. The application of mobile wireless sensor networks for soil and atmosphere sensing offers significant benefits, due to the simple adjustment of the sensor distribution, the sensor types and the sample rate (e.g. by using optimization approaches or event triggering modes) to the local test conditions. This can be essential for the monitoring of heterogeneous and dynamic environmental systems and processes. One significant advantage in the application of mobile ad-hoc wireless sensor networks is their self-organizing behavior. Thus, the network autonomously initializes and optimizes itself. Due to the localization via satellite a major reduction in installation and operation costs and time is generated. In addition, single point measurements with a sensor are significantly improved by measuring at several optimized points continuously. Since performing analog and digital signal processing and computation in the sensor nodes close to the sensors a significant reduction of the data to be transmitted can be achieved which leads to a better energy management of nodes. Furthermore, the miniaturization of the nodes and energy harvesting are current topics under investigation. First results of field measurements are given to present the potentials and limitations of this application in environmental science. In particular, collected in-situ data with numerous specific soil and atmosphere parameters per sensor node (more than 25) recorded over several days illustrates the high performance of this system for advanced soil sensing and soil-atmosphere interaction monitoring. Moreover, investigations of biotic and abiotic process interactions and optimization