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.

The use of hierarchical clustering for the design of optimized monitoring networks

Science.gov (United States)

Soares, Joana; Makar, Paul Andrew; Aklilu, Yayne; Akingunola, Ayodeji

2018-05-01

Associativity analysis is a powerful tool to deal with large-scale datasets by clustering the data on the basis of (dis)similarity and can be used to assess the efficacy and design of air quality monitoring networks. We describe here our use of Kolmogorov-Zurbenko filtering and hierarchical clustering of NO2 and SO2 passive and continuous monitoring data to analyse and optimize air quality networks for these species in the province of Alberta, Canada. The methodology applied in this study assesses dissimilarity between monitoring station time series based on two metrics: 1 - R, R being the Pearson correlation coefficient, and the Euclidean distance; we find that both should be used in evaluating monitoring site similarity. We have combined the analytic power of hierarchical clustering with the spatial information provided by deterministic air quality model results, using the gridded time series of model output as potential station locations, as a proxy for assessing monitoring network design and for network optimization. We demonstrate that clustering results depend on the air contaminant analysed, reflecting the difference in the respective emission sources of SO2 and NO2 in the region under study. Our work shows that much of the signal identifying the sources of NO2 and SO2 emissions resides in shorter timescales (hourly to daily) due to short-term variation of concentrations and that longer-term averages in data collection may lose the information needed to identify local sources. However, the methodology identifies stations mainly influenced by seasonality, if larger timescales (weekly to monthly) are considered. We have performed the first dissimilarity analysis based on gridded air quality model output and have shown that the methodology is capable of generating maps of subregions within which a single station will represent the entire subregion, to a given level of dissimilarity. We have also shown that our approach is capable of identifying different

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

Science.gov (United States)

Chen, Kai; Ni, Minjie; Wang, Jun; Huang, Dongren; Chen, Huorong; Wang, Xiao; Liu, Mengyang

2016-01-01

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. PMID:27777951

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.

Two-Layer Hierarchy Optimization Model for Communication Protocol in Railway Wireless Monitoring Networks

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Xiaoping Ma

2018-01-01

Full Text Available The wireless monitoring system is always destroyed by the insufficient energy of the sensors in railway. Hence, how to optimize the communication protocol and extend the system lifetime is crucial to ensure the stability of system. However, the existing studies focused primarily on cluster-based or multihop protocols individually, which are ineffective in coping with the complex communication scenarios in the railway wireless monitoring system (RWMS. This study proposes a hybrid protocol which combines the cluster-based and multihop protocols (CMCP to minimize and balance the energy consumption in different sections of the RWMS. In the first hierarchy, the total energy consumption is minimized by optimizing the cluster quantities in the cluster-based protocol and the number of hops and the corresponding hop distances in the multihop protocol. In the second hierarchy, the energy consumption is balanced through rotating the cluster head (CH in the subnetworks and further optimizing the hops and the corresponding hop distances in the backbone network. On this basis, the system lifetime is maximized with the minimum and balance energy consumption among the sensors. Furthermore, the hybrid particle swarm optimization and genetic algorithm (PSO-GA are adopted to optimize the energy consumption from the two-layer hierarchy. Finally, the effectiveness of the proposed CMCP is verified in the simulation. The performances of the proposed CMCP in system lifetime, residual energy, and the corresponding variance are all superior to the LEACH protocol widely applied in the previous research. The effective protocol proposed in this study can facilitate the application of the wireless monitoring network in the railway system and enhance safety operation of the railway.

Optical Performance Monitoring and Signal Optimization in Optical Networks

DEFF Research Database (Denmark)

Petersen, Martin Nordal

2006-01-01

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-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...... 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...

Static and mobile networks design for atmospheric accidental releases monitoring

International Nuclear Information System (INIS)

Abida, R.

2010-01-01

The global context of my PhD thesis work is the optimization of air pollution monitoring networks, but more specifically it concerns the monitoring of accidental releases of radionuclides in air. The optimization problem of air quality measuring networks has been addresses in the literature. However, it has not been addresses in the context of surveillance of accidental atmospheric releases. The first part of my thesis addresses the optimization of a permanent network of monitoring of radioactive aerosols in the air, covering France. The second part concerns the problem of targeting of observations in case of an accidental release of radionuclides from a nuclear plant. (author)

Extending Resolution of Fault Slip With Geodetic Networks Through Optimal Network Design

Science.gov (United States)

Sathiakumar, Sharadha; Barbot, Sylvain Denis; Agram, Piyush

2017-12-01

Geodetic networks consisting of high precision and high rate Global Navigation Satellite Systems (GNSS) stations continuously monitor seismically active regions of the world. These networks measure surface displacements and the amount of geodetic strain accumulated in the region and give insight into the seismic potential. SuGar (Sumatra GPS Array) in Sumatra, GEONET (GNSS Earth Observation Network System) in Japan, and PBO (Plate Boundary Observatory) in California are some examples of established networks around the world that are constantly expanding with the addition of new stations to improve the quality of measurements. However, installing new stations to existing networks is tedious and expensive. Therefore, it is important to choose suitable locations for new stations to increase the precision obtained in measuring the geophysical parameters of interest. Here we describe a methodology to design optimal geodetic networks that augment the existing system and use it to investigate seismo-tectonics at convergent and transform boundaries considering land-based and seafloor geodesy. The proposed network design optimization would be pivotal to better understand seismic and tsunami hazards around the world. Land-based and seafloor networks can monitor fault slip around subduction zones with significant resolution, but transform faults are more challenging to monitor due to their near-vertical geometry.

Optimal spatio-temporal design of water quality monitoring networks for reservoirs: Application of the concept of value of information

Science.gov (United States)

Maymandi, Nahal; Kerachian, Reza; Nikoo, Mohammad Reza

2018-03-01

This paper presents a new methodology for optimizing Water Quality Monitoring (WQM) networks of reservoirs and lakes using the concept of the value of information (VOI) and utilizing results of a calibrated numerical water quality simulation model. With reference to the value of information theory, water quality of every checkpoint with a specific prior probability differs in time. After analyzing water quality samples taken from potential monitoring points, the posterior probabilities are updated using the Baye's theorem, and VOI of the samples is calculated. In the next step, the stations with maximum VOI is selected as optimal stations. This process is repeated for each sampling interval to obtain optimal monitoring network locations for each interval. The results of the proposed VOI-based methodology is compared with those obtained using an entropy theoretic approach. As the results of the two methodologies would be partially different, in the next step, the results are combined using a weighting method. Finally, the optimal sampling interval and location of WQM stations are chosen using the Evidential Reasoning (ER) decision making method. The efficiency and applicability of the methodology are evaluated using available water quantity and quality data of the Karkheh Reservoir in the southwestern part of Iran.

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.

Context-Aware Local Optimization of Sensor Network Deployment

Directory of Open Access Journals (Sweden)

Meysam Argany

2015-07-01

Full Text Available Wireless sensor networks are increasingly used for tracking and monitoring dynamic phenomena in urban and natural areas. Spatial coverage is an important issue in sensor networks in order to fulfill the needs of sensing applications. Optimization methods are widely used to efficiently distribute sensor nodes in the network to achieve a desired level of coverage. Most of the existing algorithms do not consider the characteristics of the real environment in the optimization process. In this paper, we propose the integration of contextual information in optimization algorithms to improve sensor network coverage. First, we investigate the implication of contextual information in sensor networks. Then, a conceptual framework for local context-aware sensor network deployment optimization method is introduced and related algorithms are presented in detail. Finally, several experiments are carried out to evaluate the validity of the proposed method. The results obtained from these experiments show the effectiveness of our approach in different contextual situations.

A probabilistic approach for optimal sensor allocation in structural health monitoring

International Nuclear Information System (INIS)

Azarbayejani, M; Reda Taha, M M; El-Osery, A I; Choi, K K

2008-01-01

Recent advances in sensor technology promote using large sensor networks to efficiently and economically monitor, identify and quantify damage in structures. In structural health monitoring (SHM) systems, the effectiveness and reliability of the sensor network are crucial to determine the optimal number and locations of sensors in SHM systems. Here, we suggest a probabilistic approach for identifying the optimal number and locations of sensors for SHM. We demonstrate a methodology to establish the probability distribution function that identifies the optimal sensor locations such that damage detection is enhanced. The approach is based on using the weights of a neural network trained from simulations using a priori knowledge about damage locations and damage severities to generate a normalized probability distribution function for optimal sensor allocation. We also demonstrate that the optimal sensor network can be related to the highest probability of detection (POD). The redundancy of the proposed sensor network is examined using a 'leave one sensor out' analysis. A prestressed concrete bridge is selected as a case study to demonstrate the effectiveness of the proposed method. The results show that the proposed approach can provide a robust design for sensor networks that are more efficient than a uniform distribution of sensors on a structure

Entropy Applications to Water Monitoring Network Design: A Review

Directory of Open Access Journals (Sweden)

Jongho Keum

2017-11-01

Full Text Available Having reliable water monitoring networks is an essential component of water resources and environmental management. A standardized process for the design of water monitoring networks does not exist with the exception of the World Meteorological Organization (WMO general guidelines about the minimum network density. While one of the major challenges in the design of optimal hydrometric networks has been establishing design objectives, information theory has been successfully adopted to network design problems by providing measures of the information content that can be deliverable from a station or a network. This review firstly summarizes the common entropy terms that have been used in water monitoring network designs. Then, this paper deals with the recent applications of the entropy concept for water monitoring network designs, which are categorized into (1 precipitation; (2 streamflow and water level; (3 water quality; and (4 soil moisture and groundwater networks. The integrated design method for multivariate monitoring networks is also covered. Despite several issues, entropy theory has been well suited to water monitoring network design. However, further work is still required to provide design standards and guidelines for operational use.

Application of SNODAS and hydrologic models to enhance entropy-based snow monitoring network design

Science.gov (United States)

Keum, Jongho; Coulibaly, Paulin; Razavi, Tara; Tapsoba, Dominique; Gobena, Adam; Weber, Frank; Pietroniro, Alain

2018-06-01

Snow has a unique characteristic in the water cycle, that is, snow falls during the entire winter season, but the discharge from snowmelt is typically delayed until the melting period and occurs in a relatively short period. Therefore, reliable observations from an optimal snow monitoring network are necessary for an efficient management of snowmelt water for flood prevention and hydropower generation. The Dual Entropy and Multiobjective Optimization is applied to design snow monitoring networks in La Grande River Basin in Québec and Columbia River Basin in British Columbia. While the networks are optimized to have the maximum amount of information with minimum redundancy based on entropy concepts, this study extends the traditional entropy applications to the hydrometric network design by introducing several improvements. First, several data quantization cases and their effects on the snow network design problems were explored. Second, the applicability the Snow Data Assimilation System (SNODAS) products as synthetic datasets of potential stations was demonstrated in the design of the snow monitoring network of the Columbia River Basin. Third, beyond finding the Pareto-optimal networks from the entropy with multi-objective optimization, the networks obtained for La Grande River Basin were further evaluated by applying three hydrologic models. The calibrated hydrologic models simulated discharges using the updated snow water equivalent data from the Pareto-optimal networks. Then, the model performances for high flows were compared to determine the best optimal network for enhanced spring runoff forecasting.

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

Performance Monitoring Techniques Supporting Cognitive Optical Networking

DEFF Research Database (Denmark)

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

2013-01-01

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...... 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....

Efficient network monitoring for large data acquisition systems

International Nuclear Information System (INIS)

Savu, D.O.; Martin, B.; Al-Shabibi, A.; Sjoen, R.; Batraneanu, S.M.; Stancu, S.N.

2012-01-01

Though constantly evolving and improving, the available network monitoring solutions have limitations when applied to the infrastructure of a high speed realtime 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 seamlessly integrates complementary data from auxiliary tools, such as NAGIOS, information services or custom databases. A number of techniques (e.g. normalization, aggregation and data caching) were used in order to improve the user interface response time. The end result is a unified monitoring interface, for fast and uniform access to system statistics, which significantly reduced the time spent by experts for ad-hoc and post-mortem analysis. (authors)

Design and optimizing factors of PACS network architecture

International Nuclear Information System (INIS)

Tao Yonghao; Miao Jingtao

2001-01-01

Objective: Exploring the design and optimizing factors of picture archiving and communication system (PACS) network architecture. Methods: Based on the PACS of shanghai first hospital to performed the measurements and tests on the requirements of network bandwidth and transmitting rate for different PACS functions and procedures respectively in static and dynamic network traffic situation, utilizing the network monitoring tools which built-in workstations and provided by Windows NT. Results: No obvious difference between switch equipment and HUB when measurements and tests implemented in static situation except route which slow down the rate markedly. In dynamic environment Switch is able to provide higher bandwidth utilizing than HUB and local system scope communication achieved faster transmitting rate than global system. Conclusion: The primary optimizing factors of PACS network architecture design include concise network topology and disassemble tremendous global traffic to multiple distributed local scope network communication to reduce the traffic of network backbone. The most important issue is guarantee essential bandwidth for diagnosis procedure of medical imaging

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

Multiobjective design of aquifer monitoring networks for optimal spatial prediction and geostatistical parameter estimation

Science.gov (United States)

Alzraiee, Ayman H.; Bau, Domenico A.; Garcia, Luis A.

2013-06-01

Effective sampling of hydrogeological systems is essential in guiding groundwater management practices. Optimal sampling of groundwater systems has previously been formulated based on the assumption that heterogeneous subsurface properties can be modeled using a geostatistical approach. Therefore, the monitoring schemes have been developed to concurrently minimize the uncertainty in the spatial distribution of systems' states and parameters, such as the hydraulic conductivity K and the hydraulic head H, and the uncertainty in the geostatistical model of system parameters using a single objective function that aggregates all objectives. However, it has been shown that the aggregation of possibly conflicting objective functions is sensitive to the adopted aggregation scheme and may lead to distorted results. In addition, the uncertainties in geostatistical parameters affect the uncertainty in the spatial prediction of K and H according to a complex nonlinear relationship, which has often been ineffectively evaluated using a first-order approximation. In this study, we propose a multiobjective optimization framework to assist the design of monitoring networks of K and H with the goal of optimizing their spatial predictions and estimating the geostatistical parameters of the K field. The framework stems from the combination of a data assimilation (DA) algorithm and a multiobjective evolutionary algorithm (MOEA). The DA algorithm is based on the ensemble Kalman filter, a Monte-Carlo-based Bayesian update scheme for nonlinear systems, which is employed to approximate the posterior uncertainty in K, H, and the geostatistical parameters of K obtained by collecting new measurements. Multiple MOEA experiments are used to investigate the trade-off among design objectives and identify the corresponding monitoring schemes. The methodology is applied to design a sampling network for a shallow unconfined groundwater system located in Rocky Ford, Colorado. Results indicate that

Software defined network inference with evolutionary optimal observation matrices

OpenAIRE

Malboubi, M; Gong, Y; Yang, Z; Wang, X; Chuah, CN; Sharma, P

2017-01-01

© 2017 Elsevier B.V. A key requirement for network management is the accurate and reliable monitoring of relevant network characteristics. In today's large-scale networks, this is a challenging task due to the scarcity of network measurement resources and the hard constraints that this imposes. This paper proposes a new framework, called SNIPER, which leverages the flexibility provided by Software-Defined Networking (SDN) to design the optimal observation or measurement matrix that can lead t...

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.

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.

Many-objective Groundwater Monitoring Network Design Using Bias-Aware Ensemble Kalman Filtering and Evolutionary Optimization

Science.gov (United States)

Kollat, J. B.; Reed, P. M.

2009-12-01

This study contributes the ASSIST (Adaptive Strategies for Sampling in Space and Time) framework for improving long-term groundwater monitoring decisions across space and time while accounting for the influences of systematic model errors (or predictive bias). The ASSIST framework combines contaminant flow-and-transport modeling, bias-aware ensemble Kalman filtering (EnKF) and many-objective evolutionary optimization. Our goal in this work is to provide decision makers with a fuller understanding of the information tradeoffs they must confront when performing long-term groundwater monitoring network design. Our many-objective analysis considers up to 6 design objectives simultaneously and consequently synthesizes prior monitoring network design methodologies into a single, flexible framework. This study demonstrates the ASSIST framework using a tracer study conducted within a physical aquifer transport experimental tank located at the University of Vermont. The tank tracer experiment was extensively sampled to provide high resolution estimates of tracer plume behavior. The simulation component of the ASSIST framework consists of stochastic ensemble flow-and-transport predictions using ParFlow coupled with the Lagrangian SLIM transport model. The ParFlow and SLIM ensemble predictions are conditioned with tracer observations using a bias-aware EnKF. The EnKF allows decision makers to enhance plume transport predictions in space and time in the presence of uncertain and biased model predictions by conditioning them on uncertain measurement data. In this initial demonstration, the position and frequency of sampling were optimized to: (i) minimize monitoring cost, (ii) maximize information provided to the EnKF, (iii) minimize failure to detect the tracer, (iv) maximize the detection of tracer flux, (v) minimize error in quantifying tracer mass, and (vi) minimize error in quantifying the moment of the tracer plume. The results demonstrate that the many-objective problem

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.

Clustering and Flow Conservation Monitoring Tool for Software Defined Networks

Directory of Open Access Journals (Sweden)

Jesús Antonio Puente Fernández

2018-04-01

Full Text Available Prediction systems present some challenges on two fronts: the relation between video quality and observed session features and on the other hand, dynamics changes on the video quality. Software Defined Networks (SDN is a new concept of network architecture that provides the separation of control plane (controller and data plane (switches in network devices. Due to the existence of the southbound interface, it is possible to deploy monitoring tools to obtain the network status and retrieve a statistics collection. Therefore, achieving the most accurate statistics depends on a strategy of monitoring and information requests of network devices. In this paper, we propose an enhanced algorithm for requesting statistics to measure the traffic flow in SDN networks. Such an algorithm is based on grouping network switches in clusters focusing on their number of ports to apply different monitoring techniques. Such grouping occurs by avoiding monitoring queries in network switches with common characteristics and then, by omitting redundant information. In this way, the present proposal decreases the number of monitoring queries to switches, improving the network traffic and preventing the switching overload. We have tested our optimization in a video streaming simulation using different types of videos. The experiments and comparison with traditional monitoring techniques demonstrate the feasibility of our proposal maintaining similar values decreasing the number of queries to the switches.

Clustering and Flow Conservation Monitoring Tool for Software Defined Networks.

Science.gov (United States)

Puente Fernández, Jesús Antonio; García Villalba, Luis Javier; Kim, Tai-Hoon

2018-04-03

Prediction systems present some challenges on two fronts: the relation between video quality and observed session features and on the other hand, dynamics changes on the video quality. Software Defined Networks (SDN) is a new concept of network architecture that provides the separation of control plane (controller) and data plane (switches) in network devices. Due to the existence of the southbound interface, it is possible to deploy monitoring tools to obtain the network status and retrieve a statistics collection. Therefore, achieving the most accurate statistics depends on a strategy of monitoring and information requests of network devices. In this paper, we propose an enhanced algorithm for requesting statistics to measure the traffic flow in SDN networks. Such an algorithm is based on grouping network switches in clusters focusing on their number of ports to apply different monitoring techniques. Such grouping occurs by avoiding monitoring queries in network switches with common characteristics and then, by omitting redundant information. In this way, the present proposal decreases the number of monitoring queries to switches, improving the network traffic and preventing the switching overload. We have tested our optimization in a video streaming simulation using different types of videos. The experiments and comparison with traditional monitoring techniques demonstrate the feasibility of our proposal maintaining similar values decreasing the number of queries to the switches.

Locations of Sampling Stations for Water Quality Monitoring in Water Distribution Networks.

Science.gov (United States)

Rathi, Shweta; Gupta, Rajesh

2014-04-01

Water quality is required to be monitored in the water distribution networks (WDNs) at salient locations to assure the safe quality of water supplied to the consumers. Such monitoring stations (MSs) provide warning against any accidental contaminations. Various objectives like demand coverage, time for detection, volume of water contaminated before detection, extent of contamination, expected population affected prior to detection, detection likelihood and others, have been independently or jointly considered in determining optimal number and location of MSs in WDNs. "Demand coverage" defined as the percentage of network demand monitored by a particular monitoring station is a simple measure to locate MSs. Several methods based on formulation of coverage matrix using pre-specified coverage criteria and optimization have been suggested. Coverage criteria is defined as some minimum percentage of total flow received at the monitoring stations that passed through any upstream node included then as covered node of the monitoring station. Number of monitoring stations increases with the increase in the value of coverage criteria. Thus, the design of monitoring station becomes subjective. A simple methodology is proposed herein which priority wise iteratively selects MSs to achieve targeted demand coverage. The proposed methodology provided the same number and location of MSs for illustrative network as an optimization method did. Further, the proposed method is simple and avoids subjectivity that could arise from the consideration of coverage criteria. The application of methodology is also shown on a WDN of Dharampeth zone (Nagpur city WDN in Maharashtra, India) having 285 nodes and 367 pipes.

Design and optimization of a ground water monitoring system using GIS and multicriteria decision analysis

Energy Technology Data Exchange (ETDEWEB)

Dutta, D.; Gupta, A.D.; Ramnarong, V.

1998-12-31

A GIS-based methodology has been developed to design a ground water monitoring system and implemented for a selected area in Mae-Klong River Basin, Thailand. A multicriteria decision-making analysis has been performed to optimize the network system based on major criteria which govern the monitoring network design such as minimization of cost of construction, reduction of kriging standard deviations, etc. The methodology developed in this study is a new approach to designing monitoring networks which can be used for any site considering site-specific aspects. It makes it possible to choose the best monitoring network from various alternatives based on the prioritization of decision factors.

Covering the Monitoring Network: A Unified Framework to Protect E-Commerce Security

Directory of Open Access Journals (Sweden)

Lirong Qiu

2017-01-01

Full Text Available Multimedia applications in smart electronic commerce (e-commerce, such as online trading and Internet marketing, always face security in storage and transmission of digital images and videos. This study addresses the problem of security in e-commerce and proposes a unified framework to analyze the security data. First, to allocate the definite security resources optimally, we build our e-commerce monitoring model as an undirected network, where a monitored node is a vertex of the graph and a connection between vertices is an undirected edge. Moreover, we aim to find a minimal cover for the monitoring network as the optimal solution of resource allocation, which is defined as the network monitoring minimization problem (NMM. This problem is proved to be NP-hard. Second, by analyzing the latent threats, we design a novel and trusted monitoring system that can integrate incident monitoring, data analysis, risk assessment, and security warnings. This system does not touch users’ privacy data. Third, we propose a sequential model-based risk assessment method, which can predict the risk according to the text semantics. Our experimental results on web scale data demonstrate that our system is flexible enough when monitoring, which also verify the effectiveness and efficiency of our system.

Serial Network Flow Monitor

Science.gov (United States)

Robinson, Julie A.; Tate-Brown, Judy M.

2009-01-01

Using a commercial software CD and minimal up-mass, SNFM monitors the Payload local area network (LAN) to analyze and troubleshoot LAN data traffic. Validating LAN traffic models may allow for faster and more reliable computer networks to sustain systems and science on future space missions. Research Summary: This experiment studies the function of the computer network onboard the ISS. On-orbit packet statistics are captured and used to validate ground based medium rate data link models and enhance the way that the local area network (LAN) is monitored. This information will allow monitoring and improvement in the data transfer capabilities of on-orbit computer networks. The Serial Network Flow Monitor (SNFM) experiment attempts to characterize the network equivalent of traffic jams on board ISS. The SNFM team is able to specifically target historical problem areas including the SAMS (Space Acceleration Measurement System) communication issues, data transmissions from the ISS to the ground teams, and multiple users on the network at the same time. By looking at how various users interact with each other on the network, conflicts can be identified and work can begin on solutions. SNFM is comprised of a commercial off the shelf software package that monitors packet traffic through the payload Ethernet LANs (local area networks) on board ISS.

Condition monitoring and thermo economic optimization of operation for a hybrid plant using artificial neural networks

Energy Technology Data Exchange (ETDEWEB)

Assadi, Mohsen; Fast, Magnus (Lund University, Dept. of Energy Sciences, Lund (Sweden))

2008-05-15

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 thermo economic optimization, on site. 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 thermo economic 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 (both measured and predicted values) in selected time intervals. 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 thermo economic optimization of e.g. maintenance. The OEMs main interest lies in investigating the possibilities of delivering ANN models, for condition monitoring, along with their new gas turbines. The project has been carried out at Lund University, Department of Energy Sciences, with support from Vaesthamnsverket AB and Siemens Industrial Turbomachinery AB. Vaesthamnsverket has 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 user interface. Siemens have contributed with expert knowledge about their SGT800 gas turbine. The implementation of the ANN models, and the accompanying user

Optimal Network-Topology Design

Science.gov (United States)

Li, Victor O. K.; Yuen, Joseph H.; Hou, Ting-Chao; Lam, Yuen Fung

1987-01-01

Candidate network designs tested for acceptability and cost. Optimal Network Topology Design computer program developed as part of study on topology design and analysis of performance of Space Station Information System (SSIS) network. Uses efficient algorithm to generate candidate network designs consisting of subsets of set of all network components, in increasing order of total costs and checks each design to see whether it forms acceptable network. Technique gives true cost-optimal network and particularly useful when network has many constraints and not too many components. Program written in PASCAL.

Toward Optimal Transport Networks

Science.gov (United States)

Alexandrov, Natalia; Kincaid, Rex K.; Vargo, Erik P.

2008-01-01

Strictly evolutionary approaches to improving the air transport system a highly complex network of interacting systems no longer suffice in the face of demand that is projected to double or triple in the near future. Thus evolutionary approaches should be augmented with active design methods. The ability to actively design, optimize and control a system presupposes the existence of predictive modeling and reasonably well-defined functional dependences between the controllable variables of the system and objective and constraint functions for optimization. Following recent advances in the studies of the effects of network topology structure on dynamics, we investigate the performance of dynamic processes on transport networks as a function of the first nontrivial eigenvalue of the network's Laplacian, which, in turn, is a function of the network s connectivity and modularity. The last two characteristics can be controlled and tuned via optimization. We consider design optimization problem formulations. We have developed a flexible simulation of network topology coupled with flows on the network for use as a platform for computational experiments.

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.

A Bayesian maximum entropy-based methodology for optimal spatiotemporal design of groundwater monitoring networks.

Science.gov (United States)

Hosseini, Marjan; Kerachian, Reza

2017-09-01

This paper presents a new methodology for analyzing the spatiotemporal variability of water table levels and redesigning a groundwater level monitoring network (GLMN) using the Bayesian Maximum Entropy (BME) technique and a multi-criteria decision-making approach based on ordered weighted averaging (OWA). The spatial sampling is determined using a hexagonal gridding pattern and a new method, which is proposed to assign a removal priority number to each pre-existing station. To design temporal sampling, a new approach is also applied to consider uncertainty caused by lack of information. In this approach, different time lag values are tested by regarding another source of information, which is simulation result of a numerical groundwater flow model. Furthermore, to incorporate the existing uncertainties in available monitoring data, the flexibility of the BME interpolation technique is taken into account in applying soft data and improving the accuracy of the calculations. To examine the methodology, it is applied to the Dehgolan plain in northwestern Iran. Based on the results, a configuration of 33 monitoring stations for a regular hexagonal grid of side length 3600 m is proposed, in which the time lag between samples is equal to 5 weeks. Since the variance estimation errors of the BME method are almost identical for redesigned and existing networks, the redesigned monitoring network is more cost-effective and efficient than the existing monitoring network with 52 stations and monthly sampling frequency.

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...

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

A case study of optimization in the decision process: Siting groundwater monitoring wells

International Nuclear Information System (INIS)

Cardwell, H.; Huff, D.; Douthitt, J.; Sale, M.

1993-12-01

Optimization is one of the tools available to assist decision makers in balancing multiple objectives and concerns. In a case study of the siting decision for groundwater monitoring wells, we look at the influence of the optimization models on the decisions made by the responsible groundwater specialist. This paper presents a multi-objective integer programming model for determining the location of monitoring wells associated with a groundwater pump-and-treat remediation. After presenting the initial optimization results, we analyze the actual decision and revise the model to incorporate elements of the problem that were later identified as important in the decision-making process. The results of a revised model are compared to the actual siting plans, the recommendations from the initial optimization runs, and the initial monitoring network proposed by the decision maker

How to Decide? Multi-Objective Early-Warning Monitoring Networks for Water Suppliers

Science.gov (United States)

Bode, Felix; Loschko, Matthias; Nowak, Wolfgang

2015-04-01

Groundwater is a resource for drinking water and hence needs to be protected from contaminations. However, many well catchments include an inventory of known and unknown risk sources, which cannot be eliminated, especially in urban regions. As a matter of risk control, all these risk sources should be monitored. A one-to-one monitoring situation for each risk source would lead to a cost explosion and is even impossible for unknown risk sources. However, smart optimization concepts could help to find promising low-cost monitoring network designs. In this work we develop a concept to plan monitoring networks using multi-objective optimization. Our considered objectives are to maximize the probability of detecting all contaminations, to enhance the early warning time before detected contaminations reach the drinking water well, and to minimize the installation and operating costs of the monitoring network. Using multi-objectives optimization, we avoid the problem of having to weight these objectives to a single objective-function. These objectives are clearly competing, and it is impossible to know their mutual trade-offs beforehand - each catchment differs in many points and it is hardly possible to transfer knowledge between geological formations and risk inventories. To make our optimization results more specific to the type of risk inventory in different catchments we do risk prioritization of all known risk sources. Due to the lack of the required data, quantitative risk ranking is impossible. Instead, we use a qualitative risk ranking to prioritize the known risk sources for monitoring. Additionally, we allow for the existence of unknown risk sources that are totally uncertain in location and in their inherent risk. Therefore, they can neither be located nor ranked. Instead, we represent them by a virtual line of risk sources surrounding the production well. We classify risk sources into four different categories: severe, medium and tolerable for known risk

Mathematical model of highways network optimization

Science.gov (United States)

Sakhapov, R. L.; Nikolaeva, R. V.; Gatiyatullin, M. H.; Makhmutov, M. M.

2017-12-01

The article deals with the issue of highways network design. Studies show that the main requirement from road transport for the road network is to ensure the realization of all the transport links served by it, with the least possible cost. The goal of optimizing the network of highways is to increase the efficiency of transport. It is necessary to take into account a large number of factors that make it difficult to quantify and qualify their impact on the road network. In this paper, we propose building an optimal variant for locating the road network on the basis of a mathematical model. The article defines the criteria for optimality and objective functions that reflect the requirements for the road network. The most fully satisfying condition for optimality is the minimization of road and transport costs. We adopted this indicator as a criterion of optimality in the economic-mathematical model of a network of highways. Studies have shown that each offset point in the optimal binding road network is associated with all other corresponding points in the directions providing the least financial costs necessary to move passengers and cargo from this point to the other corresponding points. The article presents general principles for constructing an optimal network of roads.

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.

Sampling optimization trade-offs for long-term monitoring of gamma dose rates

NARCIS (Netherlands)

Melles, S.J.; Heuvelink, G.B.M.; Twenhöfel, C.J.W.; Stöhlker, U.

2008-01-01

This paper applies a recently developed optimization method to examine the design of networks that monitor radiation under routine conditions. Annual gamma dose rates were modelled by combining regression with interpolation of the regression residuals using spatially exhaustive predictors and an

Current Status of Groundwater Monitoring Networks in Korea

OpenAIRE

Jin-Yong Lee; Kideok D. Kwon

2016-01-01

Korea has been operating groundwater monitoring systems since 1996 as the Groundwater Act enacted in 1994 enforces nationwide monitoring. Currently, there are six main groundwater monitoring networks operated by different government ministries with different purposes: National Groundwater Monitoring Network (NGMN), Groundwater Quality Monitoring Network (GQMN), Seawater Intrusion Monitoring Network (SIMN), Rural Groundwater Monitoring Network (RGMN), Subsidiary Groundwater Monitoring Network ...

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...

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.

A framework for reactive optimization in mobile ad hoc networks

DEFF Research Database (Denmark)

McClary, Dan; Syrotiuk, Violet; Kulahci, Murat

2008-01-01

We present a framework to optimize the performance of a mobile ad hoc network over a wide range of operating conditions. It includes screening experiments to quantify the parameters and interactions among parameters influential to throughput. Profile-driven regression is applied to obtain a model....... The predictive accuracy of the model is monitored and used to update the model dynamically. The results indicate the framework may be useful for the optimization of dynamic systems of high dimension....

Improved Differential Evolution Algorithm for Wireless Sensor Network Coverage Optimization

Directory of Open Access Journals (Sweden)

Xing Xu

2014-04-01

Full Text Available In order to serve for the ecological monitoring efficiency of Poyang Lake, an improved hybrid algorithm, mixed with differential evolution and particle swarm optimization, is proposed and applied to optimize the coverage problem of wireless sensor network. And then, the affect of the population size and the number of iterations on the coverage performance are both discussed and analyzed. The four kinds of statistical results about the coverage rate are obtained through lots of simulation experiments.

Current Status of Groundwater Monitoring Networks in Korea

Directory of Open Access Journals (Sweden)

Jin-Yong Lee

2016-04-01

Full Text Available Korea has been operating groundwater monitoring systems since 1996 as the Groundwater Act enacted in 1994 enforces nationwide monitoring. Currently, there are six main groundwater monitoring networks operated by different government ministries with different purposes: National Groundwater Monitoring Network (NGMN, Groundwater Quality Monitoring Network (GQMN, Seawater Intrusion Monitoring Network (SIMN, Rural Groundwater Monitoring Network (RGMN, Subsidiary Groundwater Monitoring Network (SGMN, and Drinking Water Monitoring Network (DWMN. The Networks have a total of over 3500 monitoring wells and the majority of them are now equipped with automatic data loggers and remote terminal units. Most of the monitoring data are available to the public through internet websites. These Networks have provided scientific data for designing groundwater management plans and contributed to securing the groundwater resource particularly for recent prolonged drought seasons. Each Network, however, utilizes its own well-specifications, probes, and telecommunication protocols with minimal communication with other Networks, and thus duplicate installations of monitoring wells are not uncommon among different Networks. This mini-review introduces the current regulations and the Groundwater Monitoring Networks operated in Korea and provides some suggestions to improve the sustainability of the current groundwater monitoring system in Korea.

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.

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

Energy Efficient Monitoring for Intrusion Detection in Battery-Powered Wireless Mesh Networks

KAUST Repository

Hassanzadeh, Amin

2011-07-18

Wireless Mesh Networks (WMN) are easy-to-deploy, low cost solutions for providing networking and internet services in environments with no network infrastructure, e.g., disaster areas and battlefields. Since electric power is not readily available in such environments battery-powered mesh routers, operating in an energy efficient manner, are required. To the best of our knowledge, the impact of energy efficient solutions, e.g., involving duty-cycling, on WMN intrusion detection systems, which require continuous monitoring, remains an open research problem. In this paper we propose that carefully chosen monitoring mesh nodes ensure continuous and complete detection coverage, while allowing non-monitoring mesh nodes to save energy through duty-cycling. We formulate the monitoring node selection problem as an optimization problem and propose distributed and centralized solutions for it, with different tradeoffs. Through extensive simulations and a proof-of-concept hardware/software implementation we demonstrate that our solutions extend the WMN lifetime by 8%, while ensuring, at the minimum, a 97% intrusion detection rate.

Optimal topologies for maximizing network transmission capacity

Science.gov (United States)

Chen, Zhenhao; Wu, Jiajing; Rong, Zhihai; Tse, Chi K.

2018-04-01

It has been widely demonstrated that the structure of a network is a major factor that affects its traffic dynamics. In this work, we try to identify the optimal topologies for maximizing the network transmission capacity, as well as to build a clear relationship between structural features of a network and the transmission performance in terms of traffic delivery. We propose an approach for designing optimal network topologies against traffic congestion by link rewiring and apply them on the Barabási-Albert scale-free, static scale-free and Internet Autonomous System-level networks. Furthermore, we analyze the optimized networks using complex network parameters that characterize the structure of networks, and our simulation results suggest that an optimal network for traffic transmission is more likely to have a core-periphery structure. However, assortative mixing and the rich-club phenomenon may have negative impacts on network performance. Based on the observations of the optimized networks, we propose an efficient method to improve the transmission capacity of large-scale networks.

Large Scale Environmental Monitoring through Integration of Sensor and Mesh Networks

Directory of Open Access Journals (Sweden)

Raja Jurdak

2008-11-01

Full Text Available Monitoring outdoor environments through networks of wireless sensors has received interest for collecting physical and chemical samples at high spatial and temporal scales. A central challenge to environmental monitoring applications of sensor networks is the short communication range of the sensor nodes, which increases the complexity and cost of monitoring commodities that are located in geographically spread areas. To address this issue, we propose a new communication architecture that integrates sensor networks with medium range wireless mesh networks, and provides users with an advanced web portal for managing sensed information in an integrated manner. Our architecture adopts a holistic approach targeted at improving the user experience by optimizing the system performance for handling data that originates at the sensors, traverses the mesh network, and resides at the server for user consumption. This holistic approach enables users to set high level policies that can adapt the resolution of information collected at the sensors, set the preferred performance targets for their application, and run a wide range of queries and analysis on both real-time and historical data. All system components and processes will be described in this paper.

Large Scale Environmental Monitoring through Integration of Sensor and Mesh Networks.

Science.gov (United States)

Jurdak, Raja; Nafaa, Abdelhamid; Barbirato, Alessio

2008-11-24

Monitoring outdoor environments through networks of wireless sensors has received interest for collecting physical and chemical samples at high spatial and temporal scales. A central challenge to environmental monitoring applications of sensor networks is the short communication range of the sensor nodes, which increases the complexity and cost of monitoring commodities that are located in geographically spread areas. To address this issue, we propose a new communication architecture that integrates sensor networks with medium range wireless mesh networks, and provides users with an advanced web portal for managing sensed information in an integrated manner. Our architecture adopts a holistic approach targeted at improving the user experience by optimizing the system performance for handling data that originates at the sensors, traverses the mesh network, and resides at the server for user consumption. This holistic approach enables users to set high level policies that can adapt the resolution of information collected at the sensors, set the preferred performance targets for their application, and run a wide range of queries and analysis on both real-time and historical data. All system components and processes will be described in this paper.

Quantized hopfield networks for reliability optimization

International Nuclear Information System (INIS)

Nourelfath, Mustapha; Nahas, Nabil

2003-01-01

The use of neural networks in the reliability optimization field is rare. This paper presents an application of a recent kind of neural networks in a reliability optimization problem for a series system with multiple-choice constraints incorporated at each subsystem, to maximize the system reliability subject to the system budget. The problem is formulated as a nonlinear binary integer programming problem and characterized as an NP-hard problem. Our design of neural network to solve efficiently this problem is based on a quantized Hopfield network. This network allows us to obtain optimal design solutions very frequently and much more quickly than others Hopfield networks

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

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.

Optimized autonomous space in-situ sensor web for volcano monitoring

Science.gov (United States)

Song, W.-Z.; Shirazi, B.; Huang, R.; Xu, M.; Peterson, N.; LaHusen, R.; Pallister, J.; Dzurisin, D.; Moran, S.; Lisowski, M.; Kedar, S.; Chien, S.; Webb, F.; Kiely, A.; Doubleday, J.; Davies, A.; Pieri, D.

2010-01-01

In response to NASA's announced requirement for Earth hazard monitoring sensor-web technology, a multidisciplinary team involving sensor-network experts (Washington State University), space scientists (JPL), and Earth scientists (USGS Cascade Volcano Observatory (CVO)), have developed a prototype of dynamic and scalable hazard monitoring sensor-web and applied it to volcano monitoring. The combined Optimized Autonomous Space In-situ Sensor-web (OASIS) has two-way communication capability between ground and space assets, uses both space and ground data for optimal allocation of limited bandwidth resources on the ground, and uses smart management of competing demands for limited space assets. It also enables scalability and seamless infusion of future space and in-situ assets into the sensor-web. The space and in-situ control components of the system are integrated such that each element is capable of autonomously tasking the other. The ground in-situ was deployed into the craters and around the flanks of Mount St. Helens in July 2009, and linked to the command and control of the Earth Observing One (EO-1) satellite. ?? 2010 IEEE.

Optimization of Emissions Sensor Networks Incorporating Tradeoffs Between Different Sensor Technologies

Science.gov (United States)

Nicholson, B.; Klise, K. A.; Laird, C. D.; Ravikumar, A. P.; Brandt, A. R.

2017-12-01

In order to comply with current and future methane emissions regulations, natural gas producers must develop emissions monitoring strategies for their facilities. In addition, regulators must develop air monitoring strategies over wide areas incorporating multiple facilities. However, in both of these cases, only a limited number of sensors can be deployed. With a wide variety of sensors to choose from in terms of cost, precision, accuracy, spatial coverage, location, orientation, and sampling frequency, it is difficult to design robust monitoring strategies for different scenarios while systematically considering the tradeoffs between different sensor technologies. In addition, the geography, weather, and other site specific conditions can have a large impact on the performance of a sensor network. In this work, we demonstrate methods for calculating optimal sensor networks. Our approach can incorporate tradeoffs between vastly different sensor technologies, optimize over typical wind conditions for a particular area, and consider different objectives such as time to detection or geographic coverage. We do this by pre-computing site specific scenarios and using them as input to a mixed-integer, stochastic programming problem that solves for a sensor network that maximizes the effectiveness of the detection program. Our methods and approach have been incorporated within an open source Python package called Chama with the goal of providing facility operators and regulators with tools for designing more effective and efficient monitoring systems. Sandia National Laboratories is a multi-mission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC., a wholly owned subsidiary of Honeywell International, Inc., for the U.S. Department of Energys National Nuclear Security Administration under contract DE-NA0003525.

SOCIAL NETWORK OPTIMIZATION A NEW METHAHEURISTIC FOR GENERAL OPTIMIZATION PROBLEMS

Directory of Open Access Journals (Sweden)

Hassan Sherafat

2017-12-01

Full Text Available In the recent years metaheuristics were studied and developed as powerful technics for hard optimization problems. Some of well-known technics in this field are: Genetic Algorithms, Tabu Search, Simulated Annealing, Ant Colony Optimization, and Swarm Intelligence, which are applied successfully to many complex optimization problems. In this paper, we introduce a new metaheuristic for solving such problems based on social networks concept, named as Social Network Optimization – SNO. We show that a wide range of np-hard optimization problems may be solved by SNO.

Optimization-based topology identification of complex networks

International Nuclear Information System (INIS)

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 synchronization-based 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. (general)

Wireless Sensor Network Optimization: Multi-Objective Paradigm.

Science.gov (United States)

Iqbal, Muhammad; Naeem, Muhammad; Anpalagan, Alagan; Ahmed, Ashfaq; Azam, Muhammad

2015-07-20

Optimization problems relating to wireless sensor network planning, design, deployment and operation often give rise to multi-objective optimization formulations where multiple desirable objectives compete with each other and the decision maker has to select one of the tradeoff solutions. These multiple objectives may or may not conflict with each other. Keeping in view the nature of the application, the sensing scenario and input/output of the problem, the type of optimization problem changes. To address different nature of optimization problems relating to wireless sensor network design, deployment, operation, planing and placement, there exist a plethora of optimization solution types. We review and analyze different desirable objectives to show whether they conflict with each other, support each other or they are design dependent. We also present a generic multi-objective optimization problem relating to wireless sensor network which consists of input variables, required output, objectives and constraints. A list of constraints is also presented to give an overview of different constraints which are considered while formulating the optimization problems in wireless sensor networks. Keeping in view the multi facet coverage of this article relating to multi-objective optimization, this will open up new avenues of research in the area of multi-objective optimization relating to wireless sensor networks.

Wireless Sensor Network Optimization: Multi-Objective Paradigm

Science.gov (United States)

Iqbal, Muhammad; Naeem, Muhammad; Anpalagan, Alagan; Ahmed, Ashfaq; Azam, Muhammad

2015-01-01

Optimization problems relating to wireless sensor network planning, design, deployment and operation often give rise to multi-objective optimization formulations where multiple desirable objectives compete with each other and the decision maker has to select one of the tradeoff solutions. These multiple objectives may or may not conflict with each other. Keeping in view the nature of the application, the sensing scenario and input/output of the problem, the type of optimization problem changes. To address different nature of optimization problems relating to wireless sensor network design, deployment, operation, planing and placement, there exist a plethora of optimization solution types. We review and analyze different desirable objectives to show whether they conflict with each other, support each other or they are design dependent. We also present a generic multi-objective optimization problem relating to wireless sensor network which consists of input variables, required output, objectives and constraints. A list of constraints is also presented to give an overview of different constraints which are considered while formulating the optimization problems in wireless sensor networks. Keeping in view the multi facet coverage of this article relating to multi-objective optimization, this will open up new avenues of research in the area of multi-objective optimization relating to wireless sensor networks. PMID:26205271

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...

Monitoring of geothermal fields by seismic networks. Guidelines and chances; Monitoring geothermaler Felder durch seismische Netzwerke. Vorgaben und Chancen

Energy Technology Data Exchange (ETDEWEB)

Barth, Andreas [Karlsruher Institut fuer Technologie (KIT), Karlsruhe (Germany). Geophysikalisches Inst.; Gaucher, Emmanuel [Karlsruher Institut fuer Technologie (KIT), Karlsruhe (Germany). Abt. Geothermie

2012-07-01

The monitoring of geothermal power plants requires seismic networks in order to quantify ground motions at the earth's surface in the case of a possible micro seismicity or to describe spatio-temporal seismicity distribution in the reservoir. The first case requires official needs. The second case may help to develop the reservoirs. An optimal configuration of the seismic network may adequate for both tasks. It also can be a chance for a long-term investment for the overall benefit.

Airborne Network Optimization with Dynamic Network Update

Science.gov (United States)

2015-03-26

source si and a target ti . For each commodity (si, ki) the commodity specifies a non- negative demand di [5]. The objective of the multi-commodity...queue predictions, and network con- gestion [15]. The implementation of the DRQC uses the Kalman filter to predict the state of the network and optimize

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.

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.

Network synchronization: optimal and pessimal scale-free topologies

International Nuclear Information System (INIS)

Donetti, Luca; Hurtado, Pablo I; Munoz, Miguel A

2008-01-01

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

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...

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.

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.

A Survey on Multimedia-Based Cross-Layer Optimization in Visual Sensor Networks

Science.gov (United States)

Costa, Daniel G.; Guedes, Luiz Affonso

2011-01-01

Visual sensor networks (VSNs) comprised of battery-operated electronic devices endowed with low-resolution cameras have expanded the applicability of a series of monitoring applications. Those types of sensors are interconnected by ad hoc error-prone wireless links, imposing stringent restrictions on available bandwidth, end-to-end delay and packet error rates. In such context, multimedia coding is required for data compression and error-resilience, also ensuring energy preservation over the path(s) toward the sink and improving the end-to-end perceptual quality of the received media. Cross-layer optimization may enhance the expected efficiency of VSNs applications, disrupting the conventional information flow of the protocol layers. When the inner characteristics of the multimedia coding techniques are exploited by cross-layer protocols and architectures, higher efficiency may be obtained in visual sensor networks. This paper surveys recent research on multimedia-based cross-layer optimization, presenting the proposed strategies and mechanisms for transmission rate adjustment, congestion control, multipath selection, energy preservation and error recovery. We note that many multimedia-based cross-layer optimization solutions have been proposed in recent years, each one bringing a wealth of contributions to visual sensor networks. PMID:22163908

Integrated Optimization of Long-Range Underwater Signal Detection, Feature Extraction, and Classification for Nuclear Treaty Monitoring

NARCIS (Netherlands)

Tuma, M.; Rorbech, V.; Prior, M.; Igel, C.

2016-01-01

We designed and jointly optimized an integrated signal processing chain for detection and classification of long-range passive-acoustic underwater signals recorded by the global geophysical monitoring network of the Comprehensive Nuclear-Test-Ban Treaty Organization. Starting at the level of raw

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.

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.

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.

Risk-based reconfiguration of safety monitoring system using dynamic Bayesian network

International Nuclear Information System (INIS)

Kohda, Takehisa; Cui Weimin

2007-01-01

To prevent an abnormal event from leading to an accident, the role of its safety monitoring system is very important. The safety monitoring system detects symptoms of an abnormal event to mitigate its effect at its early stage. As the operation time passes by, the sensor reliability decreases, which implies that the decision criteria of the safety monitoring system should be modified depending on the sensor reliability as well as the system reliability. This paper presents a framework for the decision criteria (or diagnosis logic) of the safety monitoring system. The logic can be dynamically modified based on sensor output data monitored at regular intervals to minimize the expected loss caused by two types of safety monitoring system failure events: failed-dangerous (FD) and failed-safe (FS). The former corresponds to no response under an abnormal system condition, while the latter implies a spurious activation under a normal system condition. Dynamic Bayesian network theory can be applied to modeling the entire system behavior composed of the system and its safety monitoring system. Using the estimated state probabilities, the optimal decision criterion is given to obtain the optimal diagnosis logic. An illustrative example of a three-sensor system shows the merits and characteristics of the proposed method, where the reasonable interpretation of sensor data can be obtained

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.

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.

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...

Optimizing bulk data transfers using network measurements: A practical case

International Nuclear Information System (INIS)

Ciuffoletti, A; Merola, L; Palmieri, F; Russo, G; Pardi, S

2010-01-01

In modern Data Grid infrastructures, we increasingly face the problem of providing the running applications with fast and reliable access to large data volumes, often geographically distributed across the network. As a direct consequence, the concept of replication has been adopted by the grid community to increase data availability and maximize job throughput. To be really effective, such process has to be driven by specific optimization strategies that define when and where replicas should be created or deleted on a per-site basis, and which replicas a job should use. These strategies have to take into account the available network bandwidth as a primary resource, prior to any consideration about storage or processing power. We present a novel replica management service, integrated within the Gluedomains active network monitoring architecture, designed and implemented within the centralized collective middleware framework of the SCoPE project to provide network-aware transfer services for data intensive Grid applications.

Optimal networks of future gravitational-wave telescopes

Science.gov (United States)

Raffai, Péter; Gondán, László; Heng, Ik Siong; Kelecsényi, Nándor; Logue, Josh; Márka, Zsuzsa; Márka, Szabolcs

2013-08-01

We aim to find the optimal site locations for a hypothetical network of 1-3 triangular gravitational-wave telescopes. We define the following N-telescope figures of merit (FoMs) and construct three corresponding metrics: (a) capability of reconstructing the signal polarization; (b) accuracy in source localization; and (c) accuracy in reconstructing the parameters of a standard binary source. We also define a combined metric that takes into account the three FoMs with practically equal weight. After constructing a geomap of possible telescope sites, we give the optimal 2-telescope networks for the four FoMs separately in example cases where the location of the first telescope has been predetermined. We found that based on the combined metric, placing the first telescope to Australia provides the most options for optimal site selection when extending the network with a second instrument. We suggest geographical regions where a potential second and third telescope could be placed to get optimal network performance in terms of our FoMs. Additionally, we use a similar approach to find the optimal location and orientation for the proposed LIGO-India detector within a five-detector network with Advanced LIGO (Hanford), Advanced LIGO (Livingston), Advanced Virgo, and KAGRA. We found that the FoMs do not change greatly in sites within India, though the network can suffer a significant loss in reconstructing signal polarizations if the orientation angle of an L-shaped LIGO-India is not set to the optimal value of ˜58.2°( + k × 90°) (measured counterclockwise from East to the bisector of the arms).

Wireless air monitoring network with new AMIZ-2004G dust monitors

International Nuclear Information System (INIS)

Jakowiuk, A.; Machaj, B.; Pienkos, P.; Swistowski, E.

2006-01-01

The principle of operation of the dust monitors is based on determination of dust mass deposited on air filters from known volumes of air samples. The dust mass is determined from radiation attenuation of a Pm-147 beta source. MIZA and AMIZ monitors produced in the Institute of Nuclear Chemistry and Technology, Warsaw (Poland) additionally measure relative humidity, atmospheric pressure and temperature of the air. In case the measurements are made in a few different places, direct collection of the results requires that personnel of the environment protection units has to go frequently to the monitors and collect the data. To improve the data transmission, a new version of the AMIZ-2004G monitor was developed which is equipped with a GSM modem enabling communication with a central computer. Thanks to the new construction not only a remote wireless communication with AMIZ is possible, but also a monitoring network containing a higher number of dust monitors can be made. The measuring data from all the monitors in the network can now be collected in one central computer equipped with the GSM modem and a proper acquisition program. In 2005, two such monitoring networks were put into operation

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.

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…

Improving a Radioisotope Monitoring Network for the Hydrodynamic Characterization of a Karstic Basin

Energy Technology Data Exchange (ETDEWEB)

Peralta Vital, J. L.; Gil Castillo, R.; Fleitas Esteveza, G. [Center of Radiation Protection and Hygiene (CPHR) (Cuba); Moleiro Leon, L. [Environmental Commercial Division (GAMMA) (Cuba); Dapena, C. [Institute of Isotope Geochronology and Geology (INGEIS) (Argentina); Olivera Acosta, J. [Institute of Geodesy and Astronomy (IGA) (Cuba)

2013-07-15

The paper shows the application of geomathematical tools for the design of a radioisotope monitoring network in order to characterize groundwater dynamics in a karstic basin, a very difficult task to acccomplish due to the complex physical, geographical, geologic and hydrogeological characteristics of karstic basins. The sampling frequency of the network has been optimized according to the analysis of the spectrum of variances. In order to evaluate this optimization, the geomathematical model is compared to the results of the mathematical model AQUIMPE. This model solves the flow equation of groundwater using the finite element method. The results validate the design in order to assess aquifer recharge, residence time of groundwater, vulnerability to pollution and groundwater-surface water interaction in this complex water resource. (author)

Network performance of a wireless sensor network for temperature monitoring in vineyards

DEFF Research Database (Denmark)

Liscano, Ramiro; Jacoub, John Khalil; Dersingh, Anand

2011-01-01

Wireless sensor networks (WSNs) are an emerging technology which can be used for outdoor environmental monitoring. This paper presents challenges that arose from the development and deployment of a WSN for environmental monitoring as well as network performance analysis of this network. Different...... components in our sensor network architecture are presented like the physical nodes, the sensor node code, and two messaging protocols; one for collecting sensor and network values and the other for sensor node commands. An information model for sensor nodes to support plug-and-play capabilities in sensor...... networks is also presented....

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...

Optimizing the next generation optical access networks

DEFF Research Database (Denmark)

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

2009-01-01

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...

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...

Optimal networks of future gravitational-wave telescopes

International Nuclear Information System (INIS)

Raffai, Péter; Márka, Zsuzsa; Márka, Szabolcs; Gondán, László; Kelecsényi, Nándor; Heng, Ik Siong; Logue, Josh

2013-01-01

We aim to find the optimal site locations for a hypothetical network of 1–3 triangular gravitational-wave telescopes. We define the following N-telescope figures of merit (FoMs) and construct three corresponding metrics: (a) capability of reconstructing the signal polarization; (b) accuracy in source localization; and (c) accuracy in reconstructing the parameters of a standard binary source. We also define a combined metric that takes into account the three FoMs with practically equal weight. After constructing a geomap of possible telescope sites, we give the optimal 2-telescope networks for the four FoMs separately in example cases where the location of the first telescope has been predetermined. We found that based on the combined metric, placing the first telescope to Australia provides the most options for optimal site selection when extending the network with a second instrument. We suggest geographical regions where a potential second and third telescope could be placed to get optimal network performance in terms of our FoMs. Additionally, we use a similar approach to find the optimal location and orientation for the proposed LIGO-India detector within a five-detector network with Advanced LIGO (Hanford), Advanced LIGO (Livingston), Advanced Virgo, and KAGRA. We found that the FoMs do not change greatly in sites within India, though the network can suffer a significant loss in reconstructing signal polarizations if the orientation angle of an L-shaped LIGO-India is not set to the optimal value of ∼58.2°( + k × 90°) (measured counterclockwise from East to the bisector of the arms). (paper)

Progress and lessons learned from water-quality monitoring networks

Science.gov (United States)

Myers, Donna N.; Ludtke, Amy S.

2017-01-01

Stream-quality monitoring networks in the United States were initiated and expanded after passage of successive federal water-pollution control laws from 1948 to 1972. The first networks addressed information gaps on the extent and severity of stream pollution and served as early warning systems for spills. From 1965 to 1972, monitoring networks expanded to evaluate compliance with stream standards, track emerging issues, and assess water-quality status and trends. After 1972, concerns arose regarding the ability of monitoring networks to determine if water quality was getting better or worse and why. As a result, monitoring networks adopted a hydrologic systems approach targeted to key water-quality issues, accounted for human and natural factors affecting water quality, innovated new statistical methods, and introduced geographic information systems and models that predict water quality at unmeasured locations. Despite improvements, national-scale monitoring networks have declined over time. Only about 1%, or 217, of more than 36,000 US Geological Survey monitoring sites sampled from 1975 to 2014 have been operated throughout the four decades since passage of the 1972 Clean Water Act. Efforts to sustain monitoring networks are important because these networks have collected information crucial to the description of water-quality trends over time and are providing information against which to evaluate future trends.

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.

Influence maximization in complex networks through optimal percolation

Science.gov (United States)

Morone, Flaviano; Makse, Hernán A.

2015-08-01

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, 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. Despite the vast use of heuristic strategies to identify influential spreaders, 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 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. These are topologically tagged as low-degree nodes surrounded by hierarchical coronas of hubs, and are uncovered only through the optimal collective interplay of all the influencers in the network. The present theoretical framework may hold a larger degree of universality, being applicable to other hard optimization problems exhibiting a continuous transition from a known phase.

Monitoring Churn in Wireless Networks

Science.gov (United States)

Holzer, Stephan; Pignolet, Yvonne Anne; Smula, Jasmin; Wattenhofer, Roger

Wireless networks often experience a significant amount of churn, the arrival and departure of nodes. In this paper we propose a distributed algorithm for single-hop networks that detects churn and is resilient to a worst-case adversary. The nodes of the network are notified about changes quickly, in asymptotically optimal time up to an additive logarithmic overhead. We establish a trade-off between saving energy and minimizing the delay until notification for single- and multi-channel networks.

Network optimization including gas lift and network parameters under subsurface uncertainty

Energy Technology Data Exchange (ETDEWEB)

Schulze-Riegert, R.; Baffoe, J.; Pajonk, O. [SPT Group GmbH, Hamburg (Germany); Badalov, H.; Huseynov, S. [Technische Univ. Clausthal, Clausthal-Zellerfeld (Germany). ITE; Trick, M. [SPT Group, Calgary, AB (Canada)

2013-08-01

Optimization of oil and gas field production systems poses a great challenge to field development due to complex and multiple interactions between various operational design parameters and subsurface uncertainties. Conventional analytical methods are capable of finding local optima based on single deterministic models. They are less applicable for efficiently generating alternative design scenarios in a multi-objective context. Practical implementations of robust optimization workflows integrate the evaluation of alternative design scenarios and multiple realizations of subsurface uncertainty descriptions. Production or economic performance indicators such as NPV (Net Present Value) are linked to a risk-weighted objective function definition to guide the optimization processes. This work focuses on an integrated workflow using a reservoir-network simulator coupled to an optimization framework. The work will investigate the impact of design parameters while considering the physics of the reservoir, wells, and surface facilities. Subsurface uncertainties are described by well parameters such as inflow performance. Experimental design methods are used to investigate parameter sensitivities and interactions. Optimization methods are used to find optimal design parameter combinations which improve key performance indicators of the production network system. The proposed workflow will be applied to a representative oil reservoir coupled to a network which is modelled by an integrated reservoir-network simulator. Gas-lift will be included as an explicit measure to improve production. An objective function will be formulated for the net present value of the integrated system including production revenue and facility costs. Facility and gas lift design parameters are tuned to maximize NPV. Well inflow performance uncertainties are introduced with an impact on gas lift performance. Resulting variances on NPV are identified as a risk measure for the optimized system design. A

BAKNET - Communication network for radiation monitoring devices

International Nuclear Information System (INIS)

Cohen, Y.; Wengrowicz, U.; Tirosh, D.; Barak, D.

1997-01-01

A system, based on a new concept of controlling and monitoring distributed radiation monitors, has been developed and approved at the NRCN. The system, named B AKNET Network , consists of a series of communication adapters connected to a main PC via an RS-485 communication network (see Fig. 1). The network's maximal length is 1200 meters and it enables connection of up to 128 adapters. The BAKNET adapters are designed to interface output signals of different types of stationary radiation monitors to a main PC. The BAKNET adapters' interface type includes: digital, analog, RS-232, and mixed output signals. This allows versatile interfacing of different stationary radiation monitors to the main computer. The connection to the main computer is via an RS-485 network, utilizing an identical communication protocol. The PC software, written in C ++ under MS-Windows, consists of two main programs. The first is the data collection program and the second is the Human Machine Interface (HMI). (authors)

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)

Optimal defense resource allocation in scale-free networks

Science.gov (United States)

Zhang, Xuejun; Xu, Guoqiang; Xia, Yongxiang

2018-02-01

The robustness research of networked systems has drawn widespread attention in the past decade, and one of the central topics is to protect the network from external attacks through allocating appropriate defense resource to different nodes. In this paper, we apply a specific particle swarm optimization (PSO) algorithm to optimize the defense resource allocation in scale-free networks. Results reveal that PSO based resource allocation shows a higher robustness than other resource allocation strategies such as uniform, degree-proportional, and betweenness-proportional allocation strategies. Furthermore, we find that assigning less resource to middle-degree nodes under small-scale attack while more resource to low-degree nodes under large-scale attack is conductive to improving the network robustness. Our work provides an insight into the optimal defense resource allocation pattern in scale-free networks and is helpful for designing a more robust network.

[The therapeutic drug monitoring network server of tacrolimus for Chinese renal transplant patients].

Science.gov (United States)

Deng, Chen-Hui; Zhang, Guan-Min; Bi, Shan-Shan; Zhou, Tian-Yan; Lu, Wei

2011-07-01

This study is to develop a therapeutic drug monitoring (TDM) network server of tacrolimus for Chinese renal transplant patients, which can facilitate doctor to manage patients' information and provide three levels of predictions. Database management system MySQL was employed to build and manage the database of patients and doctors' information, and hypertext mark-up language (HTML) and Java server pages (JSP) technology were employed to construct network server for database management. Based on the population pharmacokinetic model of tacrolimus for Chinese renal transplant patients, above program languages were used to construct the population prediction and subpopulation prediction modules. Based on Bayesian principle and maximization of the posterior probability function, an objective function was established, and minimized by an optimization algorithm to estimate patient's individual pharmacokinetic parameters. It is proved that the network server has the basic functions for database management and three levels of prediction to aid doctor to optimize the regimen of tacrolimus for Chinese renal transplant patients.

Practical synchronization on complex dynamical networks via optimal pinning control

Science.gov (United States)

Li, Kezan; Sun, Weigang; Small, Michael; Fu, Xinchu

2015-07-01

We consider practical synchronization on complex dynamical networks under linear feedback control designed by optimal control theory. The control goal is to minimize global synchronization error and control strength over a given finite time interval, and synchronization error at terminal time. By utilizing the Pontryagin's minimum principle, and based on a general complex dynamical network, we obtain an optimal system to achieve the control goal. The result is verified by performing some numerical simulations on Star networks, Watts-Strogatz networks, and Barabási-Albert networks. Moreover, by combining optimal control and traditional pinning control, we propose an optimal pinning control strategy which depends on the network's topological structure. Obtained results show that optimal pinning control is very effective for synchronization control in real applications.

Modeling and optimization of potable water network

Energy Technology Data Exchange (ETDEWEB)

Djebedjian, B.; Rayan, M.A. [Mansoura Univ., El-Mansoura (Egypt); Herrick, A. [Suez Canal Authority, Ismailia (Egypt)

2000-07-01

Software was developed in order to optimize the design of water distribution systems and pipe networks. While satisfying all the constraints imposed such as pipe diameter and nodal pressure, it was based on a mathematical model treating looped networks. The optimum network configuration and cost are determined considering parameters like pipe diameter, flow rate, corresponding pressure and hydraulic losses. It must be understood that minimum cost is relative to the different objective functions selected. The determination of the proper objective function often depends on the operating policies of a particular company. The solution for the optimization technique was obtained by using a non-linear technique. To solve the optimal design of network, the model was derived using the sequential unconstrained minimization technique (SUMT) of Fiacco and McCormick, which decreased the number of iterations required. The pipe diameters initially assumed were successively adjusted to correspond to the existing commercial pipe diameters. The technique was then applied to a two-loop network without pumps or valves. Fed by gravity, it comprised eight pipes, 1000 m long each. The first evaluation of the method proved satisfactory. As with other methods, it failed to find the global optimum. In the future, research efforts will be directed to the optimization of networks with pumps and reservoirs. 24 refs., 3 tabs., 1 fig.

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.

Optimal hub location in pipeline networks

Energy Technology Data Exchange (ETDEWEB)

Dott, D.R.; Wirasinghe, S.C.; Chakma, A. [Univ. of Calgary, Alberta (Canada)

1996-12-31

This paper discusses optimization strategies and techniques for the location of natural gas marketing hubs in the North American gas pipeline network. A hub is a facility at which inbound and outbound network links meet and freight is redirected towards their destinations. Common examples of hubs used in the gas pipeline industry include gas plants, interconnects and market centers. Characteristics of the gas pipeline industry which are relevant to the optimization of transportation costs using hubs are presented. Allocation techniques for solving location-allocation problems are discussed. An outline of the research in process by the authors in the field of optimal gas hub location concludes the paper.

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.

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

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.

LinkMind: Link Optimization in Swarming Mobile Sensor Networks

DEFF Research Database (Denmark)

Ngo, Trung Dung

2012-01-01

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...

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.

A data acquisition protocol for a reactive wireless sensor network monitoring application.

Science.gov (United States)

Aderohunmu, Femi A; Brunelli, Davide; Deng, Jeremiah D; Purvis, Martin K

2015-04-30

Limiting energy consumption is one of the primary aims for most real-world deployments of wireless sensor networks. Unfortunately, attempts to optimize energy efficiency are often in conflict with the demand for network reactiveness to transmit urgent messages. In this article, we propose SWIFTNET: a reactive data acquisition scheme. It is built on the synergies arising from a combination of the data reduction methods and energy-efficient data compression schemes. Particularly, it combines compressed sensing, data prediction and adaptive sampling strategies. We show how this approach dramatically reduces the amount of unnecessary data transmission in the deployment for environmental monitoring and surveillance networks. SWIFTNET targets any monitoring applications that require high reactiveness with aggressive data collection and transmission. To test the performance of this method, we present a real-world testbed for a wildfire monitoring as a use-case. The results from our in-house deployment testbed of 15 nodes have proven to be favorable. On average, over 50% communication reduction when compared with a default adaptive prediction method is achieved without any loss in accuracy. In addition, SWIFTNET is able to guarantee reactiveness by adjusting the sampling interval from 5 min up to 15 s in our application domain.

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.

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

An acoustical model based monitoring network

NARCIS (Netherlands)

Wessels, P.W.; Basten, T.G.H.; Eerden, F.J.M. van der

2010-01-01

In this paper the approach for an acoustical model based monitoring network is demonstrated. This network is capable of reconstructing a noise map, based on the combination of measured sound levels and an acoustic model of the area. By pre-calculating the sound attenuation within the network the

Optimal Design of Gravitational Sewer Networks with General Cellular Automata

Directory of Open Access Journals (Sweden)

Mohammad Hadi Afshar

2014-05-01

Full Text Available In this paper, a Cellular Automata method is applied for the optimal design of sewer networks. The solution of sewer network optimization problems requires the determination of pipe diameters and average pipe cover depths, minimizing the total cost of the sewer network subject to operational constraints. In this paper, the network nodes and upstream and downstream pipe cover depths are considered as CA cells and cell states, respectively, and the links around each cell are taken into account as neighborhood. The proposed method is a general and flexible method for the optimization of sewer networks as it can be used to optimally design both gravity and pumped network due to the use of pipe nodal cover depths as the decision variables. The proposed method is tested against two  gravitational sewer networks and the  comparison of results with other methods such as  Genetic algorithm, Cellular Automata, Ant Colony Optimization Algorithm and Particle Swarm Optimization show the efficiency and effectiveness of the proposed method.

Network monitoring module of BES III system environment

International Nuclear Information System (INIS)

Song Liwen; Zhao Jingwei; Zhang Bingyun

2002-01-01

In order to meet the needs of the complicated network architecture of BES III (Beijing Spectrometer III) and make sure normal online running in the future, it is necessary to develop a multi-platforms Network Monitoring Tool which can help system administrator monitor and manage BES III network. The author provides a module that can monitor not only the traffic of switch-router's ports but also the performance status of key devices in the network environment, meanwhile it can also give warning to manager and submit the related reports. the great sense, the theory basis, the implementing method and the graph in formation of this tool will be discussed

Optimal Information Processing in Biochemical Networks

Science.gov (United States)

Wiggins, Chris

2012-02-01

A variety of experimental results over the past decades provide examples of near-optimal information processing in biological networks, including in biochemical and transcriptional regulatory networks. Computing information-theoretic quantities requires first choosing or computing the joint probability distribution describing multiple nodes in such a network --- for example, representing the probability distribution of finding an integer copy number of each of two interacting reactants or gene products while respecting the `intrinsic' small copy number noise constraining information transmission at the scale of the cell. I'll given an overview of some recent analytic and numerical work facilitating calculation of such joint distributions and the associated information, which in turn makes possible numerical optimization of information flow in models of noisy regulatory and biochemical networks. Illustrating cases include quantification of form-function relations, ideal design of regulatory cascades, and response to oscillatory driving.

Implementation of medical monitor system based on networks

Science.gov (United States)

Yu, Hui; Cao, Yuzhen; Zhang, Lixin; Ding, Mingshi

2006-11-01

In this paper, the development trend of medical monitor system is analyzed and portable trend and network function become more and more popular among all kinds of medical monitor devices. The architecture of medical network monitor system solution is provided and design and implementation details of medical monitor terminal, monitor center software, distributed medical database and two kind of medical information terminal are especially discussed. Rabbit3000 system is used in medical monitor terminal to implement security administration of data transfer on network, human-machine interface, power management and DSP interface while DSP chip TMS5402 is used in signal analysis and data compression. Distributed medical database is designed for hospital center according to DICOM information model and HL7 standard. Pocket medical information terminal based on ARM9 embedded platform is also developed to interactive with center database on networks. Two kernels based on WINCE are customized and corresponding terminal software are developed for nurse's routine care and doctor's auxiliary diagnosis. Now invention patent of the monitor terminal is approved and manufacture and clinic test plans are scheduled. Applications for invention patent are also arranged for two medical information terminals.

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.

Monitoring Malware Activity on the LAN Network

Science.gov (United States)

Skrzewski, Mirosław

Many security related organizations periodically publish current network and systems security information, with the lists of top malware programs. These lists raises the question how these threats spreads out, if the worms (the only threat with own communication abilities) are low or missing on these lists. The paper discuss the research on malware network activity, aimed to deliver the answer to the question, what is the main infection channel of modern malware, done with the usage of virtual honeypot systems on dedicated, unprotected network. Systems setup, network and systems monitoring solutions, results of over three months of network traffic and malware monitoring are presented, along with the proposed answer to our research question.

Optimal pinnate leaf-like network/matrix structure for enhanced conductive cooling

International Nuclear Information System (INIS)

Hu, Liguo; Zhou, Han; Zhu, Hanxing; Fan, Tongxiang; Zhang, Di

2015-01-01

Highlights: • We present a pinnate leaf-like network/matrix structure for conductive cooling. • We study the effect of matrix thickness on network conductive cooling performance. • Matrix thickness determines optimal distance between collection channels in network. • We determine the optimal network architecture from a global perspective. • Optimal network greatly reduces the maximum temperature difference in the network. - Abstract: Heat generated in electronic devices has to be effectively removed because excessive temperature strongly impairs their performance and reliability. Embedding a high thermal conductivity network into an electronic device is an effective method to conduct the generated heat to the outside. In this study, inspired by the pinnate leaf, we present a pinnate leaf-like network embedded in the matrix (i.e., electronic device) to cool the matrix by conduction and develop a method to construct the optimal network. In this method, we first investigate the effect of the matrix thickness on the conductive cooling performance of the network, and then optimize the network architecture from a global perspective so that to minimize the maximum temperature difference between the heat sink and the matrix. The results indicate that the matrix thickness determines the optimal distance of the neighboring collection channels in the network, which minimizes the maximum temperature difference between the matrix and the network, and that the optimal network greatly reduces the maximum temperature difference in the network. The results can serve as a design guide for efficient conductive cooling of electronic devices

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...

A one-layer recurrent neural network for constrained pseudoconvex optimization and its application for dynamic portfolio optimization.

Science.gov (United States)

Liu, Qingshan; Guo, Zhishan; Wang, Jun

2012-02-01

In this paper, a one-layer recurrent neural network is proposed for solving pseudoconvex optimization problems subject to linear equality and bound constraints. Compared with the existing neural networks for optimization (e.g., the projection neural networks), the proposed neural network is capable of solving more general pseudoconvex optimization problems with equality and bound constraints. Moreover, it is capable of solving constrained fractional programming problems as a special case. The convergence of the state variables of the proposed neural network to achieve solution optimality is guaranteed as long as the designed parameters in the model are larger than the derived lower bounds. Numerical examples with simulation results illustrate the effectiveness and characteristics of the proposed neural network. In addition, an application for dynamic portfolio optimization is discussed. Copyright © 2011 Elsevier Ltd. All rights reserved.

Optimal knockout strategies in genome-scale metabolic networks using particle swarm optimization.

Science.gov (United States)

Nair, Govind; Jungreuthmayer, Christian; Zanghellini, Jürgen

2017-02-01

Knockout strategies, particularly the concept of constrained minimal cut sets (cMCSs), are an important part of the arsenal of tools used in manipulating metabolic networks. Given a specific design, cMCSs can be calculated even in genome-scale networks. We would however like to find not only the optimal intervention strategy for a given design but the best possible design too. Our solution (PSOMCS) is to use particle swarm optimization (PSO) along with the direct calculation of cMCSs from the stoichiometric matrix to obtain optimal designs satisfying multiple objectives. To illustrate the working of PSOMCS, we apply it to a toy network. Next we show its superiority by comparing its performance against other comparable methods on a medium sized E. coli core metabolic network. PSOMCS not only finds solutions comparable to previously published results but also it is orders of magnitude faster. Finally, we use PSOMCS to predict knockouts satisfying multiple objectives in a genome-scale metabolic model of E. coli and compare it with OptKnock and RobustKnock. PSOMCS finds competitive knockout strategies and designs compared to other current methods and is in some cases significantly faster. It can be used in identifying knockouts which will force optimal desired behaviors in large and genome scale metabolic networks. It will be even more useful as larger metabolic models of industrially relevant organisms become available.

Deployment Algorithms of Wireless Sensor Networks for Near-surface Underground Oil and Gas Pipeline Monitoring

Directory of Open Access Journals (Sweden)

Hua-Ping YU

2014-07-01

Full Text Available Oil and gas pipelines are the infrastructure of national economic development. Deployment problem of wireless underground sensor networks (WUSN for oil and gas pipeline systems is a fundamental problem. This paper firstly analyzed the wireless channel characteristics and energy consumption model in near-surface underground soil, and then studied the spatial structure of oil and gas pipelines and introduced the three-layer system structure of WUSN for oil and gas pipelines monitoring. Secondly, the optimal deployment strategy in XY plane and XZ plane which were projected from three-dimensional oil and gas pipeline structure was analyzed. Thirdly, the technical framework of using kinetic energy of the fluid in pipelines to recharge sensor nodes and partition strategy for energy consumption balance based on the wireless communication technology of magnetic induction waveguide were proposed, which can effectively improve the energy performance and connectivity of the network, and provide theoretical guidance and practical basis for the monitoring of long oil and gas pipeline network, the city tap water pipe network and sewage pipe network.

Modeling and optimization of cloud-ready and content-oriented networks

CERN Document Server

Walkowiak, Krzysztof

2016-01-01

This book focuses on modeling and optimization of cloud-ready and content-oriented networks in the context of different layers and accounts for specific constraints following from protocols and technologies used in a particular layer. It addresses a wide range of additional constraints important in contemporary networks, including various types of network flows, survivability issues, multi-layer networking, and resource location. The book presents recent existing and new results in a comprehensive and cohesive way. The contents of the book are organized in five chapters, which are mostly self-contained. Chapter 1 briefly presents information on cloud computing and content-oriented services, and introduces basic notions and concepts of network modeling and optimization. Chapter 2 covers various optimization problems that arise in the context of connection-oriented networks. Chapter 3 focuses on modeling and optimization of Elastic Optical Networks. Chapter 4 is devoted to overlay networks. The book concludes w...

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.

Optimized Autonomous Space In-situ Sensor-Web for volcano monitoring

Science.gov (United States)

Song, W.-Z.; Shirazi, B.; Kedar, S.; Chien, S.; Webb, F.; Tran, D.; Davis, A.; Pieri, D.; LaHusen, R.; Pallister, J.; Dzurisin, D.; Moran, S.; Lisowski, M.

2008-01-01

In response to NASA's announced requirement for Earth hazard monitoring sensor-web technology, a multidisciplinary team involving sensor-network experts (Washington State University), space scientists (JPL), and Earth scientists (USGS Cascade Volcano Observatory (CVO)), is developing a prototype dynamic and scaleable hazard monitoring sensor-web and applying it to volcano monitoring. The combined Optimized Autonomous Space -In-situ Sensor-web (OASIS) will have two-way communication capability between ground and space assets, use both space and ground data for optimal allocation of limited power and bandwidth resources on the ground, and use smart management of competing demands for limited space assets. It will also enable scalability and seamless infusion of future space and in-situ assets into the sensor-web. The prototype will be focused on volcano hazard monitoring at Mount St. Helens, which has been active since October 2004. The system is designed to be flexible and easily configurable for many other applications as well. The primary goals of the project are: 1) integrating complementary space (i.e., Earth Observing One (EO-1) satellite) and in-situ (ground-based) elements into an interactive, autonomous sensor-web; 2) advancing sensor-web power and communication resource management technology; and 3) enabling scalability for seamless infusion of future space and in-situ assets into the sensor-web. To meet these goals, we are developing: 1) a test-bed in-situ array with smart sensor nodes capable of making autonomous data acquisition decisions; 2) efficient self-organization algorithm of sensor-web topology to support efficient data communication and command control; 3) smart bandwidth allocation algorithms in which sensor nodes autonomously determine packet priorities based on mission needs and local bandwidth information in real-time; and 4) remote network management and reprogramming tools. The space and in-situ control components of the system will be

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.

A method of network topology optimization design considering application process characteristic

Science.gov (United States)

Wang, Chunlin; Huang, Ning; Bai, Yanan; Zhang, Shuo

2018-03-01

Communication networks are designed to meet the usage requirements of users for various network applications. The current studies of network topology optimization design mainly considered network traffic, which is the result of network application operation, but not a design element of communication networks. A network application is a procedure of the usage of services by users with some demanded performance requirements, and has obvious process characteristic. In this paper, we first propose a method to optimize the design of communication network topology considering the application process characteristic. Taking the minimum network delay as objective, and the cost of network design and network connective reliability as constraints, an optimization model of network topology design is formulated, and the optimal solution of network topology design is searched by Genetic Algorithm (GA). Furthermore, we investigate the influence of network topology parameter on network delay under the background of multiple process-oriented applications, which can guide the generation of initial population and then improve the efficiency of GA. Numerical simulations show the effectiveness and validity of our proposed method. Network topology optimization design considering applications can improve the reliability of applications, and provide guidance for network builders in the early stage of network design, which is of great significance in engineering practices.

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...

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.

Distributed Multi-Commodity Network Flow Algorithm for Energy Optimal Routing in Wireless Sensor Networks.

Directory of Open Access Journals (Sweden)

J. Trdlicka

2010-12-01

Full Text Available This work proposes a distributed algorithm for energy optimal routing in a wireless sensor network. The routing problem is described as a mathematical problem by the minimum-cost multi-commodity network flow problem. Due to the separability of the problem, we use the duality theorem to derive the distributed algorithm. The algorithm computes the energy optimal routing in the network without any central node or knowledge of the whole network structure. Each node only needs to know the flow which is supposed to send or receive and the costs and capacities of the neighboring links. An evaluation of the presented algorithm on benchmarks for the energy optimal data flow routing in sensor networks with up to 100 nodes is presented.

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....

Cascade-robustness optimization of coupling preference in interconnected networks

International Nuclear Information System (INIS)

Zhang, Xue-Jun; Xu, Guo-Qiang; Zhu, Yan-Bo; Xia, Yong-Xiang

2016-01-01

Highlights: • A specific memetic algorithm was proposed to optimize coupling links. • A small toy model was investigated to examine the underlying mechanism. • The MA optimized strategy exhibits a moderate assortative pattern. • A novel coupling coefficient index was proposed to quantify coupling preference. - Abstract: Recently, the robustness of interconnected networks has attracted extensive attentions, one of which is to investigate the influence of coupling preference. In this paper, the memetic algorithm (MA) is employed to optimize the coupling links of interconnected networks. Afterwards, a comparison is made between MA optimized coupling strategy and traditional assortative, disassortative and random coupling preferences. It is found that the MA optimized coupling strategy with a moderate assortative value shows an outstanding performance against cascading failures on both synthetic scale-free interconnected networks and real-world networks. We then provide an explanation for this phenomenon from a micro-scope point of view and propose a coupling coefficient index to quantify the coupling preference. Our work is helpful for the design of robust interconnected networks.

COMBINED AND STORM SEWER NETWORK MONITORING

Directory of Open Access Journals (Sweden)

Justyna Synowiecka

2014-10-01

Full Text Available Monitoring of the drainage networks is an extremely important tool used to understand the phenomena occurring in them. In an era of urbanization and increased run-off, at the expense of natural retention in the catchment, it helps to minimize the risk of local flooding and pollution. In its scope includes measurement of the amount of rainfall, with the use of rain gauges, and their measure in the sewer network, in matter of flows and channel filling, with the help of flow meters. An indispensable part in this step is their proper calibration calibration. In addition to ongoing monitoring of the sewer system, periodic inspections by the qualified employees of Water and Sewage Company should be done. The following article reviews measurement devices, their calibration methods, as well as the phenomena that occur during operation in the sewer network. It provides a solution for monitoring and control based on the experience of the Municipal Water and Sewage Company in Wroclaw, describing common operational problems, their causes, prevention methods and a network operation walkthrough with the improve of performance indicators KPI (Key Performance Indicators according the ECB (European Benchmarking Co-operation.

Optimal neural networks for protein-structure prediction

International Nuclear Information System (INIS)

Head-Gordon, T.; Stillinger, F.H.

1993-01-01

The successful application of neural-network algorithms for prediction of protein structure is stymied by three problem areas: the sparsity of the database of known protein structures, poorly devised network architectures which make the input-output mapping opaque, and a global optimization problem in the multiple-minima space of the network variables. We present a simplified polypeptide model residing in two dimensions with only two amino-acid types, A and B, which allows the determination of the global energy structure for all possible sequences of pentamer, hexamer, and heptamer lengths. This model simplicity allows us to compile a complete structural database and to devise neural networks that reproduce the tertiary structure of all sequences with absolute accuracy and with the smallest number of network variables. These optimal networks reveal that the three problem areas are convoluted, but that thoughtful network designs can actually deconvolute these detrimental traits to provide network algorithms that genuinely impact on the ability of the network to generalize or learn the desired mappings. Furthermore, the two-dimensional polypeptide model shows sufficient chemical complexity so that transfer of neural-network technology to more realistic three-dimensional proteins is evident

Using Differential Evolution to Optimize Learning from Signals and Enhance Network Security

Energy Technology Data Exchange (ETDEWEB)

Harmer, Paul K [Air Force Institute of Technology; Temple, Michael A [Air Force Institute of Technology; Buckner, Mark A [ORNL; Farquhar, Ethan [ORNL

2011-01-01

Computer and communication network attacks are commonly orchestrated through Wireless Access Points (WAPs). This paper summarizes proof-of-concept research activity aimed at developing a physical layer Radio Frequency (RF) air monitoring capability to limit unauthorizedWAP access and mprove network security. This is done using Differential Evolution (DE) to optimize the performance of a Learning from Signals (LFS) classifier implemented with RF Distinct Native Attribute (RF-DNA) fingerprints. Performance of the resultant DE-optimized LFS classifier is demonstrated using 802.11a WiFi devices under the most challenging conditions of intra-manufacturer classification, i.e., using emissions of like-model devices that only differ in serial number. Using identical classifier input features, performance of the DE-optimized LFS classifier is assessed relative to a Multiple Discriminant Analysis / Maximum Likelihood (MDA/ML) classifier that has been used for previous demonstrations. The comparative assessment is made using both Time Domain (TD) and Spectral Domain (SD) fingerprint features. For all combinations of classifier type, feature type, and signal-to-noise ratio considered, results show that the DEoptimized LFS classifier with TD features is uperior and provides up to 20% improvement in classification accuracy with proper selection of DE parameters.

On-line plant-wide monitoring using neural networks

International Nuclear Information System (INIS)

Turkcan, E.; Ciftcioglu, O.; Eryurek, E.; Upadhyaya, B.R.

1992-06-01

The on-line signal analysis system designed for a multi-level mode operation using neural networks is described. The system is capable of monitoring the plant states by tracking different number of signals up to 32 simultaneously. The data used for this study were acquired from the Borssele Nuclear Power Plant (PWR type), and using the on-line monitoring system. An on-line plant-wide monitoring study using a multilayer neural network model is discussed in this paper. The back-propagation neural network algorithm is used for training the network. The technique assumes that each physical state of the power plant can be represented by a unique pattern of instrument readings which can be related to the condition of the plant. When disturbance occurs, the sensor readings undergo a transient, and form a different set of patterns which represent the new operational status. Diagnosing these patterns can be helpful in identifying this new state of the power plant. To this end, plant-wide monitoring with neutral networks is one of the new techniques in real-time applications. (author). 9 refs.; 5 figs

Wireless Sensor Networks for Long Distance Pipeline Monitoring

OpenAIRE

Augustine C. Azubogu; Victor E. Idigo; Schola U. Nnebe; Obinna S. Oguejiofor; Simon E.

2013-01-01

The main goal of this seminal paper is to introduce the application of Wireless Sensor Networks (WSN) in long distance infrastructure monitoring (in particular in pipeline infrastructure monitoring) – one of the on-going research projects by the Wireless Communication Research Group at the department of Electronic and Computer Engineering, Nnamdi Azikiwe University, Awka. The current sensor network architectures for monitoring long distance pipeline infrastructures are pr...

District Heating Network Design and Configuration Optimization with Genetic Algorithm

DEFF Research Database (Denmark)

Li, Hongwei; Svendsen, Svend

2013-01-01

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 it 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...

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.

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.

Research on the application of vehicle network in optimization of automobile supply supply chain

Science.gov (United States)

Jing, Xuelei; Jia, Baoxian

2017-09-01

The four key areas of the development of Internet-connected (intelligent transportation) with great potential for development,environmental monitoring, goods tracking, and the development of smart grid are the core supporting technologies of many applications. In order to improve the adaptability of data distribution, so that it can be used in urban, rural or highway and other different car networking scenarios, the study test and hypothetical test of the technical means to accurately estimate the different car network scene parameters indicators, and then different scenarios take different distribution strategies. Taking into account the limited nature of the data distribution of the Internet network data, the paper uses the idea of a customer to optimize the simulation

Network protection and insulation monitoring. Schutztechnik mit Isolationsueberwachung

Energy Technology Data Exchange (ETDEWEB)

Hofheinz, W

1983-01-01

With the increasing use of unearthed power supply networks, the selection of suitable monitoring systems has become increasingly important. By combining the unearthed power supply networks with insulation monitoring, one arrives at a protective technique with high reliability, fireproofness and accident protection. The book describes this type of network and its applications, e.g. for medical purposes. Technologies in West Germany and the USA are compared, and a historical outline is given of protective wire systems and their applications. Methods of measurement employed in insulation monitoring systems are described, and the relevant VDE regulations are cited.

Distributed Interplanetary Delay/Disruption Tolerant Network (DTN) Monitor and Control System

Science.gov (United States)

Wang, Shin-Ywan

2012-01-01

The main purpose of Distributed interplanetary Delay Tolerant Network Monitor and Control System as a DTN system network management implementation in JPL is defined to provide methods and tools that can monitor the DTN operation status, detect and resolve DTN operation failures in some automated style while either space network or some heterogeneous network is infused with DTN capability. In this paper, "DTN Monitor and Control system in Deep Space Network (DSN)" exemplifies a case how DTN Monitor and Control system can be adapted into a space network as it is DTN enabled.

Optimizing network connectivity for mobile health technologies in sub-Saharan Africa.

Science.gov (United States)

Siedner, Mark J; Lankowski, Alexander; Musinga, Derrick; Jackson, Jonathon; Muzoora, Conrad; Hunt, Peter W; Martin, Jeffrey N; Bangsberg, David R; Haberer, Jessica E

2012-01-01

Mobile health (mHealth) technologies hold incredible promise to improve healthcare delivery in resource-limited settings. Network reliability across large catchment areas can be a major challenge. We performed an analysis of network failure frequency as part of a study of real-time adherence monitoring in rural Uganda. We hypothesized that the addition of short messaging service (SMS+GPRS) to the standard cellular network modality (GPRS) would reduce network disruptions and improve transmission of data. Participants were enrolled in a study of real-time adherence monitoring in southwest Uganda. In June 2011, we began using Wisepill devices that transmit data each time the pill bottle is opened. We defined network failures as medication interruptions of >48 hours duration that were transmitted when network connectivity was re-established. During the course of the study, we upgraded devices from GPRS to GPRS+SMS compatibility. We compared network failure rates between GPRS and GPRS+SMS periods and created geospatial maps to graphically demonstrate patterns of connectivity. One hundred fifty-seven participants met inclusion criteria of seven days of SMS and seven days of SMS+GPRS observation time. Seventy-three percent were female, median age was 40 years (IQR 33-46), 39% reported >1-hour travel time to clinic and 17% had home electricity. One hundred one had GPS coordinates recorded and were included in the geospatial maps. The median number of network failures per person-month for the GPRS and GPRS+SMS modalities were 1.5 (IQR 1.0-2.2) and 0.3 (IQR 0-0.9) respectively, (mean difference 1.2, 95%CI 1.0-1.3, p-valueImprovements in network connectivity were notable throughout the region. Study costs increased by approximately $1USD per person-month. Addition of SMS to standard GPRS cellular network connectivity can significantly reduce network connection failures for mobile health applications in remote areas. Projects depending on mobile health data in resource

Regulatory Holidays and Optimal Network Expansion

NARCIS (Netherlands)

Willems, Bert; Zwart, Gijsbert

2016-01-01

We model the optimal regulation of continuous, irreversible, capacity expansion, in a model in which the regulated network firm has private information about its capacity costs, investments need to be financed out of the firm’s cash flows from selling network access and demand is stochastic. If

EMMNet: Sensor Networking for Electricity Meter Monitoring

Directory of Open Access Journals (Sweden)

Zhi-Ting Lin

2010-06-01

Full Text Available 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.

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.

A one-layer recurrent neural network for constrained nonsmooth optimization.

Science.gov (United States)

Liu, Qingshan; Wang, Jun

2011-10-01

This paper presents a novel one-layer recurrent neural network modeled by means of a differential inclusion for solving nonsmooth optimization problems, in which the number of neurons in the proposed neural network is the same as the number of decision variables of optimization problems. Compared with existing neural networks for nonsmooth optimization problems, the global convexity condition on the objective functions and constraints is relaxed, which allows the objective functions and constraints to be nonconvex. It is proven that the state variables of the proposed neural network are convergent to optimal solutions if a single design parameter in the model is larger than a derived lower bound. Numerical examples with simulation results substantiate the effectiveness and illustrate the characteristics of the proposed neural network.

Resilience-based optimal design of water distribution network

Science.gov (United States)

Suribabu, C. R.

2017-11-01

Optimal design of water distribution network is generally aimed to minimize the capital cost of the investments on tanks, pipes, pumps, and other appurtenances. Minimizing the cost of pipes is usually considered as a prime objective as its proportion in capital cost of the water distribution system project is very high. However, minimizing the capital cost of the pipeline alone may result in economical network configuration, but it may not be a promising solution in terms of resilience point of view. Resilience of the water distribution network has been considered as one of the popular surrogate measures to address ability of network to withstand failure scenarios. To improve the resiliency of the network, the pipe network optimization can be performed with two objectives, namely minimizing the capital cost as first objective and maximizing resilience measure of the configuration as secondary objective. In the present work, these two objectives are combined as single objective and optimization problem is solved by differential evolution technique. The paper illustrates the procedure for normalizing the objective functions having distinct metrics. Two of the existing resilience indices and power efficiency are considered for optimal design of water distribution network. The proposed normalized objective function is found to be efficient under weighted method of handling multi-objective water distribution design problem. The numerical results of the design indicate the importance of sizing pipe telescopically along shortest path of flow to have enhanced resiliency indices.

Bio-Mimic Optimization Strategies in Wireless Sensor Networks: A Survey

Science.gov (United States)

Adnan, Md. Akhtaruzzaman; Razzaque, Mohammd Abdur; Ahmed, Ishtiaque; Isnin, Ismail Fauzi

2014-01-01

For the past 20 years, many authors have focused their investigations on wireless sensor networks. Various issues related to wireless sensor networks such as energy minimization (optimization), compression schemes, self-organizing network algorithms, routing protocols, quality of service management, security, energy harvesting, etc., have been extensively explored. The three most important issues among these are energy efficiency, quality of service and security management. To get the best possible results in one or more of these issues in wireless sensor networks optimization is necessary. Furthermore, in number of applications (e.g., body area sensor networks, vehicular ad hoc networks) these issues might conflict and require a trade-off amongst them. Due to the high energy consumption and data processing requirements, the use of classical algorithms has historically been disregarded. In this context contemporary researchers started using bio-mimetic strategy-based optimization techniques in the field of wireless sensor networks. These techniques are diverse and involve many different optimization algorithms. As far as we know, most existing works tend to focus only on optimization of one specific issue of the three mentioned above. It is high time that these individual efforts are put into perspective and a more holistic view is taken. In this paper we take a step in that direction by presenting a survey of the literature in the area of wireless sensor network optimization concentrating especially on the three most widely used bio-mimetic algorithms, namely, particle swarm optimization, ant colony optimization and genetic algorithm. In addition, to stimulate new research and development interests in this field, open research issues, challenges and future research directions are highlighted. PMID:24368702

Bio-mimic optimization strategies in wireless sensor networks: a survey.

Science.gov (United States)

Adnan, Md Akhtaruzzaman; Abdur Razzaque, Mohammd; Ahmed, Ishtiaque; Isnin, Ismail Fauzi

2013-12-24

For the past 20 years, many authors have focused their investigations on wireless sensor networks. Various issues related to wireless sensor networks such as energy minimization (optimization), compression schemes, self-organizing network algorithms, routing protocols, quality of service management, security, energy harvesting, etc., have been extensively explored. The three most important issues among these are energy efficiency, quality of service and security management. To get the best possible results in one or more of these issues in wireless sensor networks optimization is necessary. Furthermore, in number of applications (e.g., body area sensor networks, vehicular ad hoc networks) these issues might conflict and require a trade-off amongst them. Due to the high energy consumption and data processing requirements, the use of classical algorithms has historically been disregarded. In this context contemporary researchers started using bio-mimetic strategy-based optimization techniques in the field of wireless sensor networks. These techniques are diverse and involve many different optimization algorithms. As far as we know, most existing works tend to focus only on optimization of one specific issue of the three mentioned above. It is high time that these individual efforts are put into perspective and a more holistic view is taken. In this paper we take a step in that direction by presenting a survey of the literature in the area of wireless sensor network optimization concentrating especially on the three most widely used bio-mimetic algorithms, namely, particle swarm optimization, ant colony optimization and genetic algorithm. In addition, to stimulate new research and development interests in this field, open research issues, challenges and future research directions are highlighted.

Identifying uncertainty of the mean of some water quality variables along water quality monitoring network of Bahr El Baqar drain

Directory of Open Access Journals (Sweden)

Hussein G. Karaman

2013-10-01

Full Text Available Assigning objectives to the environmental monitoring network is the pillar of the design to these kinds of networks. Conflicting network objectives may affect the adequacy of the design in terms of sampling frequency and the spatial distribution of the monitoring stations which in turn affect the accuracy of the data and the information extracted. The first step in resolving this problem is to identify the uncertainty inherent in the network as the result of the vagueness of the design objective. Entropy has been utilized and adopted over the past decades to identify uncertainty in similar water data sets. Therefore it is used to identify the uncertainties inherent in the water quality monitoring network of Bahr El-Baqar drain located in the Eastern Delta. Toward investigating the applicability of the Entropy methodology, comprehensive analysis at the selected drain as well as their data sets is carried out. Furthermore, the uncertainty calculated by the entropy function will be presented by the means of the geographical information system to give the decision maker a global view to these uncertainties and to open the door to other researchers to find out innovative approaches to lower these uncertainties reaching optimal monitoring network in terms of the spatial distribution of the monitoring stations.

Network monitoring in the Tier2 site in Prague

International Nuclear Information System (INIS)

Eliáš, Marek; Fiala, Lukáš; Horký, Jirí; Chudoba, Jirí; Kouba, Tomáš; Kundrát, Jan; Švec, Jan

2011-01-01

Network monitoring provides different types of view on the network traffic. It's output enables computing centre staff to make qualified decisions about changes in the organization of computing centre network and to spot possible problems. In this paper we present network monitoring framework used at Tier-2 in Prague in Institute of Physics (FZU). The framework consists of standard software and custom tools. We discuss our system for hardware failures detection using syslog logging and Nagios active checks, bandwidth monitoring of physical links and analysis of NetFlow exports from Cisco routers. We present tool for automatic detection of network layout based on SNMP. This tool also records topology changes into SVN repository. Adapted weathermap4rrd is used to visualize recorded data to get fast overview showing current bandwidth usage of links in network.

Small cell networks deployment, management, and optimization

CERN Document Server

Claussen, Holger; Ho, Lester; Razavi, Rouzbeh; Kucera, Stepan

2018-01-01

Small Cell Networks: Deployment, Management, and Optimization addresses key problems of the cellular network evolution towards HetNets. It focuses on the latest developments in heterogeneous and small cell networks, as well as their deployment, operation, and maintenance. It also covers the full spectrum of the topic, from academic, research, and business to the practice of HetNets in a coherent manner. Additionally, it provides complete and practical guidelines to vendors and operators interested in deploying small cells. The first comprehensive book written by well-known researchers and engineers from Nokia Bell Labs, Small Cell Networks begins with an introduction to the subject--offering chapters on capacity scaling and key requirements of future networks. It then moves on to sections on coverage and capacity optimization, and interference management. From there, the book covers mobility management, energy efficiency, and small cell deployment, ending with a section devoted to future trends and applicat...

On the Optimization of a Probabilistic Data Aggregation Framework for Energy Efficiency in Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Stella Kafetzoglou

2015-08-01

Full Text Available 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.

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.

Optimization of Pipe Networks

DEFF Research Database (Denmark)

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

1991-01-01

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...

Monitoring and optimization of ATLAS Tier 2 center GoeGrid

CERN Document Server

AUTHOR|(INSPIRE)INSPIRE-00219638; Quadt, Arnulf; 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...

Topologically determined optimal stochastic resonance responses of spatially embedded networks

International Nuclear Information System (INIS)

Gosak, Marko; Marhl, Marko; Korosak, Dean

2011-01-01

We have analyzed the stochastic resonance phenomenon on spatial networks of bistable and excitable oscillators, which are connected according to their location and the amplitude of external forcing. By smoothly altering the network topology from a scale-free (SF) network with dominating long-range connections to a network where principally only adjacent oscillators are connected, we reveal that besides an optimal noise intensity, there is also a most favorable interaction topology at which the best correlation between the response of the network and the imposed weak external forcing is achieved. For various distributions of the amplitudes of external forcing, the optimal topology is always found in the intermediate regime between the highly heterogeneous SF network and the strong geometric regime. Our findings thus indicate that a suitable number of hubs and with that an optimal ratio between short- and long-range connections is necessary in order to obtain the best global response of a spatial network. Furthermore, we link the existence of the optimal interaction topology to a critical point indicating the transition from a long-range interactions-dominated network to a more lattice-like network structure.

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.

Simultaneous optimization of water and heat exchange networks

Energy Technology Data Exchange (ETDEWEB)

Chen, Zhiyou; Hou, Yanlong; Li, Xiaoduan; Wang, Jingtao [Tianjin University, Tianjin (China)

2014-04-15

This paper focuses on the simultaneous optimization of the heat-integrated water allocation networks. A mathematic model is established to illustrate the modified state-space representation of this problem. An easy logical method is employed to help identify the streams of hot or cold ones. In this model, the water exchange networks (WEN), heat exchange networks (HEN), and the interactions between the WEN and HEN combine together as one unity. Thus, the whole network can be solved at one time, which enhances the possibility to get a global optimal result. Examples from the literature and a PVC plant are analyzed to illustrate the accuracy and applicability of this method.

Establishing an air pollution monitoring network for intra-urban population exposure assessment : a location-allocation approach

Energy Technology Data Exchange (ETDEWEB)

Kanaroglou, P.S. [McMaster Univ., Hamilton, ON (Canada). School of Geography and Geology; Jerrett, M.; Beckerman, B.; Arain, M.A. [McMaster Univ., Hamilton, ON (Canada). School of Geography and Geology]|[McMaster Univ., Hamilton, ON (Canada). McMaster Inst. of Environment and Health; Morrison, J. [Carleton Univ., Ottawa, ON (Canada). School of Computer Science; Gilbert, N.L. [Health Canada, Ottawa, ON (Canada). Air Health Effects Div; Brook, J.R. [Meteorological Service of Canada, Toronto, ON (Canada)

2004-10-01

A study was conducted to assess the relation between traffic-generated air pollution and health reactions ranging from childhood asthma to mortality from lung cancer. In particular, it developed a formal method of optimally locating a dense network of air pollution monitoring stations in order to derive an exposure assessment model based on the data obtained from the monitoring stations and related land use, population and biophysical information. The method for determining the locations of 100 nitrogen dioxide monitors in Toronto, Ontario focused on land use, transportation infrastructure and the distribution of at-risk populations. The exposure assessment produced reasonable estimates at the intra-urban scale. This method for locating air pollution monitors effectively maximizes sampling coverage in relation to important socio-demographic characteristics and likely pollution variability. The location-allocation approach integrates many variables into the demand surface to reconfigure a monitoring network and is especially useful for measuring traffic pollutants with fine-scale spatial variability. The method also shows great promise for improving the assessment of exposure to ambient air pollution in epidemiologic studies. 19 refs., 3 tabs., 4 figs.

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

Radiation monitoring network of the Czech Republic

International Nuclear Information System (INIS)

Kuca, P.; Novak, L.; Rulik, P.; Tecl, J.

2003-01-01

The Radiation Monitoring Network (RMN) of the Czech Republic was established after the Chernobyl accident in 1986 and it is developed all the time. It is co-ordinated by the State Office for Nuclear Safety in co-operation with the National Radiation Protection Institute. Czech RMN consists of the several sub-networks, which include selected or all permanent parts of RMN. The sub-networks are following: the Early Warning Network (EWN), the TLD Territorial Network, the Network of the Measuring Sites of Air Contamination, the Network of Laboratories Equipped with Gamma-spectrometric and Radiochemical Analytical Instrumentation, the Ground and Airborne Mobile Groups. The Laboratory of Monitoring of Internal Contamination and the information system (IS) are a significant part of RMN, too. The data of RMN resulting from monitoring are transferred to the central database of CRMN, processed by the information system (IS). They are used in normal and emergency situations for an evaluation of radiation situation and for preparation of recommendations for protection of the public and the environment. In 2002 any extraordinary radioactivity in the environment was not detected and also none of the measuring points recorded any exceeding of established investigation levels. In components of environment and also in human beings a very low activity of 137 Cs was still measurable, that had been released into environment after the Chernobyl accident and by the nuclear weapon tests in sixties of the last century. (authors)

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

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...... series. The overall objective s are to improve training by application of second-order methods and to improve generalization ability by architecture optimization accomplished by pruning. The major topics covered in the thesis are: 1. The problem of training recurrent networks is analyzed from a numerical...... of solution obtained as well as computation time required. 3. A theoretical definition of the generalization error for recurrent networks is provided. This definition justifies a commonly adopted approach for estimating generalization ability. 4. The viability of pruning recurrent networks by the Optimal...

Compensatory Analysis and Optimization for MADM for Heterogeneous Wireless Network Selection

Directory of Open Access Journals (Sweden)

Jian Zhou

2016-01-01

Full Text Available In the next-generation heterogeneous wireless networks, a mobile terminal with a multi-interface may have network access from different service providers using various technologies. In spite of this heterogeneity, seamless intersystem mobility is a mandatory requirement. One of the major challenges for seamless mobility is the creation of a network selection scheme, which is for users that select an optimal network with best comprehensive performance between different types of networks. However, the optimal network may be not the most reasonable one due to compensation of MADM (Multiple Attribute Decision Making, and the network is called pseudo-optimal network. This paper conducts a performance evaluation of a number of widely used MADM-based methods for network selection that aim to keep the mobile users always best connected anywhere and anytime, where subjective weight and objective weight are all considered. The performance analysis shows that the selection scheme based on MEW (weighted multiplicative method and combination weight can better avoid accessing pseudo-optimal network for balancing network load and reducing ping-pong effect in comparison with three other MADM solutions.

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.

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.

Optimization in a Networked Economy

Directory of Open Access Journals (Sweden)

Ahmet Sekreter

2017-10-01

Full Text Available An age of network has been living for the last decades. The information technologies have been used by hundreds of millions of users. These technologies are enabling to connect businesses and economic activities. One of the characteristics of the networked economy is the amount of data that produced due to the interlinking of firms, individuals, processes by businesses, and economic activities. Another issue with the networked economy is the complexity of the data. Extraction of the knowledge from the networked economy has challenges by the traditional approach since data is large scale, second decentralized, and third they connect many heterogeneous agents. The challenges can be overcome by the new optimization methods including human element or the social interactions with technological infrastructure.

A Distributed Approach to Continuous Monitoring of Constrained k-Nearest Neighbor Queries in Road Networks

Directory of Open Access Journals (Sweden)

Hyung-Ju Cho

2012-01-01

Full Text Available Given two positive parameters k and r, a constrained k-nearest neighbor (CkNN query returns the k closest objects within a network distance r of the query location in road networks. In terms of the scalability of monitoring these CkNN queries, existing solutions based on central processing at a server suffer from a sudden and sharp rise in server load as well as messaging cost as the number of queries increases. In this paper, we propose a distributed and scalable scheme called DAEMON for the continuous monitoring of CkNN queries in road networks. Our query processing is distributed among clients (query objects and server. Specifically, the server evaluates CkNN queries issued at intersections of road segments, retrieves the objects on the road segments between neighboring intersections, and sends responses to the query objects. Finally, each client makes its own query result using this server response. As a result, our distributed scheme achieves close-to-optimal communication costs and scales well to large numbers of monitoring queries. Exhaustive experimental results demonstrate that our scheme substantially outperforms its competitor in terms of query processing time and messaging cost.

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

Optimal satisfaction degree in energy harvesting cognitive radio networks

International Nuclear Information System (INIS)

Li Zan; Liu Bo-Yang; Si Jiang-Bo; Zhou Fu-Hui

2015-01-01

A cognitive radio (CR) network with energy harvesting (EH) is considered to improve both spectrum efficiency and energy efficiency. A hidden Markov model (HMM) is used to characterize the imperfect spectrum sensing process. In order to maximize the whole satisfaction degree (WSD) of the cognitive radio network, a tradeoff between the average throughput of the secondary user (SU) and the interference to the primary user (PU) is analyzed. We formulate the satisfaction degree optimization problem as a mixed integer nonlinear programming (MINLP) problem. The satisfaction degree optimization problem is solved by using differential evolution (DE) algorithm. The proposed optimization problem allows the network to adaptively achieve the optimal solution based on its required quality of service (Qos). Numerical results are given to verify our analysis. (paper)

Synchronization-optimized networks for coupled nearly identical ...

Indian Academy of Sciences (India)

From the stability criteria of the MSF, we construct optimal networks ... of intense research in physical, biological, chemical, technological and social sci- ..... In figure 3a, a sample of initial network of 32 coupled nearly identical Rössler oscilla-.

Optimal unemployment insurance with monitoring and sanctions

NARCIS (Netherlands)

Boone, J.; Fredriksson, P.; Holmlund, B.; van Ours, J.C.

2007-01-01

This article analyses the design of optimal unemployment insurance in a search equilibrium framework where search effort among the unemployed is not perfectly observable. We examine to what extent the optimal policy involves monitoring of search effort and benefit sanctions if observed search is

Optical Network Virtualisation Using Multitechnology Monitoring and SDN-Enabled Optical Transceiver

Science.gov (United States)

Ou, Yanni; Davis, Matthew; Aguado, Alejandro; Meng, Fanchao; Nejabati, Reza; Simeonidou, Dimitra

2018-05-01

We introduce the real-time multi-technology transport layer monitoring to facilitate the coordinated virtualisation of optical and Ethernet networks supported by optical virtualise-able transceivers (V-BVT). A monitoring and network resource configuration scheme is proposed to include the hardware monitoring in both Ethernet and Optical layers. The scheme depicts the data and control interactions among multiple network layers under the software defined network (SDN) background, as well as the application that analyses the monitored data obtained from the database. We also present a re-configuration algorithm to adaptively modify the composition of virtual optical networks based on two criteria. The proposed monitoring scheme is experimentally demonstrated with OpenFlow (OF) extensions for a holistic (re-)configuration across both layers in Ethernet switches and V-BVTs.

Vibration monitoring with artificial neural networks

International Nuclear Information System (INIS)

Alguindigue, I.

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 network 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 from operating machinery. Two neural networks algorithms were used in our project: the Recirculation algorithm for data compression and the Backpropagation algorithm to perform the actual classification of the patterns. 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 to date are very encouraging

Neural network for nonsmooth pseudoconvex optimization with general convex constraints.

Science.gov (United States)

Bian, Wei; Ma, Litao; Qin, Sitian; Xue, Xiaoping

2018-05-01

In this paper, a one-layer recurrent neural network is proposed for solving a class of nonsmooth, pseudoconvex optimization problems with general convex constraints. Based on the smoothing method, we construct a new regularization function, which does not depend on any information of the feasible region. Thanks to the special structure of the regularization function, we prove the global existence, uniqueness and "slow solution" character of the state of the proposed neural network. Moreover, the state solution of the proposed network is proved to be convergent to the feasible region in finite time and to the optimal solution set of the related optimization problem subsequently. In particular, the convergence of the state to an exact optimal solution is also considered in this paper. Numerical examples with simulation results are given to show the efficiency and good characteristics of the proposed network. In addition, some preliminary theoretical analysis and application of the proposed network for a wider class of dynamic portfolio optimization are included. Copyright © 2018 Elsevier Ltd. All rights reserved.

Bi and tri-objective optimization in the deterministic network interdiction problem

International Nuclear Information System (INIS)

Rocco S, Claudio M.; Emmanuel Ramirez-Marquez, Jose; Salazar A, Daniel E.

2010-01-01

Solution approaches to the deterministic network interdiction problem have previously been developed for optimizing a single figure-of-merit of the network configuration (i.e. flow that can be transmitted between a source node and a sink node for a fixed network design) under constraints related to limited amount of resources available to interdict network links. These approaches work under the assumption that: (1) nominal capacity of each link is completely reduced when interdicted and (2) there is a single criterion to optimize. This paper presents a newly developed evolutionary algorithm that for the first time allows solving multi-objective optimization models for the design of network interdiction strategies that take into account a variety of figures-of-merit. The algorithm provides an approximation to the optimal Pareto frontier using: (a) techniques in Monte Carlo simulation to generate potential network interdiction strategies, (b) graph theory to analyze strategies' maximum source-sink flow and (c) an evolutionary search that is driven by the probability that a link will belong to the optimal Pareto set. Examples for different sizes of networks and network behavior are used throughout the paper to illustrate and validate the approach.

Optimal Quantum Spatial Search on Random Temporal Networks

Science.gov (United States)

Chakraborty, Shantanav; Novo, Leonardo; Di Giorgio, Serena; Omar, Yasser

2017-12-01

To investigate the performance of quantum information tasks on networks whose topology changes in time, we study the spatial search algorithm by continuous time quantum walk to find a marked node on a random temporal network. We consider a network of n nodes constituted by a time-ordered sequence of Erdös-Rényi random graphs G (n ,p ), where p is the probability that any two given nodes are connected: After every time interval τ , a new graph G (n ,p ) replaces the previous one. We prove analytically that, for any given p , there is always a range of values of τ for which the running time of the algorithm is optimal, i.e., O (√{n }), even when search on the individual static graphs constituting the temporal network is suboptimal. On the other hand, there are regimes of τ where the algorithm is suboptimal even when each of the underlying static graphs are sufficiently connected to perform optimal search on them. From this first study of quantum spatial search on a time-dependent network, it emerges that the nontrivial interplay between temporality and connectivity is key to the algorithmic performance. Moreover, our work can be extended to establish high-fidelity qubit transfer between any two nodes of the network. Overall, our findings show that one can exploit temporality to achieve optimal quantum information tasks on dynamical random networks.

Optimal Quantum Spatial Search on Random Temporal Networks.

Science.gov (United States)

Chakraborty, Shantanav; Novo, Leonardo; Di Giorgio, Serena; Omar, Yasser

2017-12-01

To investigate the performance of quantum information tasks on networks whose topology changes in time, we study the spatial search algorithm by continuous time quantum walk to find a marked node on a random temporal network. We consider a network of n nodes constituted by a time-ordered sequence of Erdös-Rényi random graphs G(n,p), where p is the probability that any two given nodes are connected: After every time interval τ, a new graph G(n,p) replaces the previous one. We prove analytically that, for any given p, there is always a range of values of τ for which the running time of the algorithm is optimal, i.e., O(sqrt[n]), even when search on the individual static graphs constituting the temporal network is suboptimal. On the other hand, there are regimes of τ where the algorithm is suboptimal even when each of the underlying static graphs are sufficiently connected to perform optimal search on them. From this first study of quantum spatial search on a time-dependent network, it emerges that the nontrivial interplay between temporality and connectivity is key to the algorithmic performance. Moreover, our work can be extended to establish high-fidelity qubit transfer between any two nodes of the network. Overall, our findings show that one can exploit temporality to achieve optimal quantum information tasks on dynamical random networks.

Optimized Charging Scheduling with Single Mobile Charger for Wireless Rechargeable Sensor Networks

Directory of Open Access Journals (Sweden)

Qihua Wang

2017-11-01

Full Text Available Due to the rapid development of wireless charging technology, the recharging issue in wireless rechargeable sensor network (WRSN has been a popular research problem in the past few years. The weakness of previous work is that charging route planning is not reasonable. In this work, a dynamic optimal scheduling scheme aiming to maximize the vacation time ratio of a single mobile changer for WRSN is proposed. In the proposed scheme, the wireless sensor network is divided into several sub-networks according to the initial topology of deployed sensor networks. After comprehensive analysis of energy states, working state and constraints for different sensor nodes in WRSN, we transform the optimized charging path problem of the whole network into the local optimization problem of the sub networks. The optimized charging path with respect to dynamic network topology in each sub-network is obtained by solving an optimization problem, and the lifetime of the deployed wireless sensor network can be prolonged. Simulation results show that the proposed scheme has good and reliable performance for a small wireless rechargeable sensor network.

NLP model and stochastic multi-start optimization approach for heat exchanger networks

International Nuclear Information System (INIS)

Núñez-Serna, Rosa I.; Zamora, Juan M.

2016-01-01

Highlights: • An NLP model for the optimal design of heat exchanger networks is proposed. • The NLP model is developed from a stage-wise grid diagram representation. • A two-phase stochastic multi-start optimization methodology is utilized. • Improved network designs are obtained with different heat load distributions. • Structural changes and reductions in the number of heat exchangers are produced. - Abstract: Heat exchanger network synthesis methodologies frequently identify good network structures, which nevertheless, might be accompanied by suboptimal values of design variables. The objective of this work is to develop a nonlinear programming (NLP) model and an optimization approach that aim at identifying the best values for intermediate temperatures, sub-stream flow rate fractions, heat loads and areas for a given heat exchanger network topology. The NLP model that minimizes the total annual cost of the network is constructed based on a stage-wise grid diagram representation. To improve the possibilities of obtaining global optimal designs, a two-phase stochastic multi-start optimization algorithm is utilized for the solution of the developed model. The effectiveness of the proposed optimization approach is illustrated with the optimization of two network designs proposed in the literature for two well-known benchmark problems. Results show that from the addressed base network topologies it is possible to achieve improved network designs, with redistributions in exchanger heat loads that lead to reductions in total annual costs. The results also show that the optimization of a given network design sometimes leads to structural simplifications and reductions in the total number of heat exchangers of the network, thereby exposing alternative viable network topologies initially not anticipated.

NRC TLD Direct Radiation Monitoring Network

International Nuclear Information System (INIS)

Struckmeyer, R.; McNamara, N.

1992-06-01

The US Nuclear Regulatory Commission (NRC) Direct Radiation Monitoring Network is operated by the NRC in cooperation with participating states to provide continuous measurement of the ambient radiation levels around licensed NRC facilities, primarily power reactors. Ambient radiation levels result from naturally occurring radionuclides present in the soil, cosmic radiation constantly bombarding the earth from outer space, and the contribution, if any, from the monitored facilities and other man-made sources. The Network is intended to measure radiation levels during routine facility operations and to establish background radiation levels used to assess the radiological impact of an unusual condition, such as an accident. This report presents the radiation levels measured around all facilities in the Network for the first quarter of 1992. All radiation measurements are made using small, passive detectors called thermoluminescent dosimeters (TLDs), which provide a quantitative measurement of the radiation levels in the area in which they are placed. Each site is monitored by arranging approximately 40 to 50 TLD stations in two concentric rings extending to about five miles from the facility. All TLD stations are outside the site boundary of the facility

Reconnecting Stochastic Methods With Hydrogeological Applications: A Utilitarian Uncertainty Analysis and Risk Assessment Approach for the Design of Optimal Monitoring Networks

Science.gov (United States)

Bode, Felix; Ferré, Ty; Zigelli, Niklas; Emmert, Martin; Nowak, Wolfgang

2018-03-01

Collaboration between academics and practitioners promotes knowledge transfer between research and industry, with both sides benefiting greatly. However, academic approaches are often not feasible given real-world limits on time, cost and data availability, especially for risk and uncertainty analyses. Although the need for uncertainty quantification and risk assessment are clear, there are few published studies examining how scientific methods can be used in practice. In this work, we introduce possible strategies for transferring and communicating academic approaches to real-world applications, countering the current disconnect between increasingly sophisticated academic methods and methods that work and are accepted in practice. We analyze a collaboration between academics and water suppliers in Germany who wanted to design optimal groundwater monitoring networks for drinking-water well catchments. Our key conclusions are: to prefer multiobjective over single-objective optimization; to replace Monte-Carlo analyses by scenario methods; and to replace data-hungry quantitative risk assessment by easy-to-communicate qualitative methods. For improved communication, it is critical to set up common glossaries of terms to avoid misunderstandings, use striking visualization to communicate key concepts, and jointly and continually revisit the project objectives. Ultimately, these approaches and recommendations are simple and utilitarian enough to be transferred directly to other practical water resource related problems.

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...

Optimisation of groundwater level monitoring networks using geostatistical modelling based on the Spartan family variogram and a genetic algorithm method

Science.gov (United States)

Parasyris, Antonios E.; Spanoudaki, Katerina; Kampanis, Nikolaos A.

2016-04-01

Groundwater level monitoring networks provide essential information for water resources management, especially in areas with significant groundwater exploitation for agricultural and domestic use. Given the high maintenance costs of these networks, development of tools, which can be used by regulators for efficient network design is essential. In this work, a monitoring network optimisation tool is presented. The network optimisation tool couples geostatistical modelling based on the Spartan family variogram with a genetic algorithm method and is applied to Mires basin in Crete, Greece, an area of high socioeconomic and agricultural interest, which suffers from groundwater overexploitation leading to a dramatic decrease of groundwater levels. The purpose of the optimisation tool is to determine which wells to exclude from the monitoring network because they add little or no beneficial information to groundwater level mapping of the area. Unlike previous relevant investigations, the network optimisation tool presented here uses Ordinary Kriging with the recently-established non-differentiable Spartan variogram for groundwater level mapping, which, based on a previous geostatistical study in the area leads to optimal groundwater level mapping. Seventy boreholes operate in the area for groundwater abstraction and water level monitoring. The Spartan variogram gives overall the most accurate groundwater level estimates followed closely by the power-law model. The geostatistical model is coupled to an integer genetic algorithm method programmed in MATLAB 2015a. The algorithm is used to find the set of wells whose removal leads to the minimum error between the original water level mapping using all the available wells in the network and the groundwater level mapping using the reduced well network (error is defined as the 2-norm of the difference between the original mapping matrix with 70 wells and the mapping matrix of the reduced well network). The solution to the

Recurrent neural network for non-smooth convex optimization problems with application to the identification of genetic regulatory networks.

Science.gov (United States)

Cheng, Long; Hou, Zeng-Guang; Lin, Yingzi; Tan, Min; Zhang, Wenjun Chris; Wu, Fang-Xiang

2011-05-01

A recurrent neural network is proposed for solving the non-smooth convex optimization problem with the convex inequality and linear equality constraints. Since the objective function and inequality constraints may not be smooth, the Clarke's generalized gradients of the objective function and inequality constraints are employed to describe the dynamics of the proposed neural network. It is proved that the equilibrium point set of the proposed neural network is equivalent to the optimal solution of the original optimization problem by using the Lagrangian saddle-point theorem. Under weak conditions, the proposed neural network is proved to be stable, and the state of the neural network is convergent to one of its equilibrium points. Compared with the existing neural network models for non-smooth optimization problems, the proposed neural network can deal with a larger class of constraints and is not based on the penalty method. Finally, the proposed neural network is used to solve the identification problem of genetic regulatory networks, which can be transformed into a non-smooth convex optimization problem. The simulation results show the satisfactory identification accuracy, which demonstrates the effectiveness and efficiency of the proposed approach.

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

PARTICLE SWARM OPTIMIZATION (PSO FOR TRAINING OPTIMIZATION ON CONVOLUTIONAL NEURAL NETWORK (CNN

Directory of Open Access Journals (Sweden)

Arie Rachmad Syulistyo

2016-02-01

Full Text Available Neural network attracts plenty of researchers lately. Substantial number of renowned universities have developed neural network for various both academically and industrially applications. Neural network shows considerable performance on various purposes. Nevertheless, for complex applications, neural network’s accuracy significantly deteriorates. To tackle the aforementioned drawback, lot of researches had been undertaken on the improvement of the standard neural network. One of the most promising modifications on standard neural network for complex applications is deep learning method. In this paper, we proposed the utilization of Particle Swarm Optimization (PSO in Convolutional Neural Networks (CNNs, which is one of the basic methods in deep learning. The use of PSO on the training process aims to optimize the results of the solution vectors on CNN in order to improve the recognition accuracy. The data used in this research is handwritten digit from MNIST. The experiments exhibited that the accuracy can be attained in 4 epoch is 95.08%. This result was better than the conventional CNN and DBN.  The execution time was also almost similar to the conventional CNN. Therefore, the proposed method was a promising method.

Optimization of rainfall networks using information entropy and temporal variability analysis

Science.gov (United States)

Wang, Wenqi; Wang, Dong; Singh, Vijay P.; Wang, Yuankun; Wu, Jichun; Wang, Lachun; Zou, Xinqing; Liu, Jiufu; Zou, Ying; He, Ruimin

2018-04-01

Rainfall networks are the most direct sources of precipitation data and their optimization and evaluation are essential and important. Information entropy can not only represent the uncertainty of rainfall distribution but can also reflect the correlation and information transmission between rainfall stations. Using entropy this study performs optimization of rainfall networks that are of similar size located in two big cities in China, Shanghai (in Yangtze River basin) and Xi'an (in Yellow River basin), with respect to temporal variability analysis. Through an easy-to-implement greedy ranking algorithm based on the criterion called, Maximum Information Minimum Redundancy (MIMR), stations of the networks in the two areas (each area is further divided into two subareas) are ranked during sliding inter-annual series and under different meteorological conditions. It is found that observation series with different starting days affect the ranking, alluding to the temporal variability during network evaluation. We propose a dynamic network evaluation framework for considering temporal variability, which ranks stations under different starting days with a fixed time window (1-year, 2-year, and 5-year). Therefore, we can identify rainfall stations which are temporarily of importance or redundancy and provide some useful suggestions for decision makers. The proposed framework can serve as a supplement for the primary MIMR optimization approach. In addition, during different periods (wet season or dry season) the optimal network from MIMR exhibits differences in entropy values and the optimal network from wet season tended to produce higher entropy values. Differences in spatial distribution of the optimal networks suggest that optimizing the rainfall network for changing meteorological conditions may be more recommended.

A One-Layer Recurrent Neural Network for Constrained Complex-Variable Convex Optimization.

Science.gov (United States)

Qin, Sitian; Feng, Jiqiang; Song, Jiahui; Wen, Xingnan; Xu, Chen

2018-03-01

In this paper, based on calculus and penalty method, a one-layer recurrent neural network is proposed for solving constrained complex-variable convex optimization. It is proved that for any initial point from a given domain, the state of the proposed neural network reaches the feasible region in finite time and converges to an optimal solution of the constrained complex-variable convex optimization finally. In contrast to existing neural networks for complex-variable convex optimization, the proposed neural network has a lower model complexity and better convergence. Some numerical examples and application are presented to substantiate the effectiveness of the proposed neural network.

Optimization of a Time-Lapse Gravity Network for Carbon Sequestration

Science.gov (United States)

Appriou, D.; Strickland, C. E.; Ruprecht Yonkofski, C. M.

2017-12-01

The objective of this study is to evaluate what could be a comprehensive and optimal state of the art gravity monitoring network that would meet the UIC class VI regulation and insure that 90% of the CO2 injected remain underground. Time-lapse gravity surveys have a long history of effective applications of monitoring temporal density changes in the subsurface. For decades, gravity measurements have been used for a wide range of applications. The interest of time-lapse gravity surveys for monitoring carbon sequestration sites started recently. The success of their deployment in such sites depends upon a combination of favorable conditions, such as the reservoir geometry, depth, thickness, density change over time induced by the CO2 injection and the location of the instrument. In most cases, the density changes induced by the CO2 plume in the subsurface are not detectable from the surface but the use of borehole gravimeters can provide excellent results. In the framework of the National Assessment and Risk Partnership (NRAP) funded by the Department of Energy, the evaluation of the effectiveness of the gravity monitoring of a CO2 storage site has been assessed using multiple synthetic scenarios implemented on a community model developed for the Kimberlina site (e.g., fault leakage scenarios, borehole leakage). The Kimberlina carbon sequestration project was a pilot project located in southern San Joaquin Valley, California, aimed to safely inject 250,000 t CO2/yr for four years. Although the project was cancelled in 2012, the site characterization efforts resulted in the development of a geologic model. In this study, we present the results of the time-lapse gravity monitoring applied on different multiphase flow and reactive transport models developed by Lawrence Berkeley National Laboratory (i.e., no leakage, permeable fault zone, wellbore leakage). Our monitoring approach considers an ideal network, consisting of multiple vertical and horizontal instrumented

Algorithms for finding optimal paths in network games with p players

Directory of Open Access Journals (Sweden)

R. Boliac

1997-08-01

Full Text Available We study the problem of finding optimal paths in network games with p players. Some polynomial-time algorithms for finding optimal paths and optimal by Nash strategies of the players in network games with p players are proposed.

Design and optimization of all-optical networks

Science.gov (United States)

Xiao, Gaoxi

1999-10-01

In this thesis, we present our research results on the design and optimization of all-optical networks. We divide our results into the following four parts: 1.In the first part, we consider broadcast-and-select networks. In our research, we propose an alternative and cheaper network configuration to hide the tuning time. In addition, we derive lower bounds on the optimal schedule lengths and prove that they are tighter than the best existing bounds. 2.In the second part, we consider all-optical wide area networks. We propose a set of algorithms for allocating a given number of WCs to the nodes. We adopt a simulation-based optimization approach, in which we collect utilization statistics of WCs from computer simulation and then perform optimization to allocate the WCs. Therefore, our algorithms are widely applicable and they are not restricted to any particular model and assumption. We have conducted extensive computer simulation on regular and irregular networks under both uniform and non-uniform traffic. We see that our method can get nearly the same performance as that of full wavelength conversion by using a much smaller number of WCs. Compared with the best existing method, the results show that our algorithms can significantly reduce (1)the overall blocking probability (i.e., better mean quality of service) and (2)the maximum of the blocking probabilities experienced at all the source nodes (i.e., better fairness). Equivalently, for a given performance requirement on blocking probability, our algorithms can significantly reduce the number of WCs required. 3.In the third part, we design and optimize the physical topology of all-optical wide area networks. We show that the design problem is NP-complete and we propose a heuristic algorithm called two-stage cut saturation algorithm for this problem. Simulation results show that (1)the proposed algorithm can efficiently design networks with low cost and high utilization, and (2)if wavelength converters are

Optimal Power Allocation Algorithm for Radar Network Systems Based on Low Probability of Intercept Optimization(in English

Directory of Open Access Journals (Sweden)

Shi Chen-guang

2014-08-01

Full Text Available A novel optimal power allocation algorithm for radar network systems is proposed for Low Probability of Intercept (LPI technology in modern electronic warfare. The algorithm is based on the LPI optimization. First, the Schleher intercept factor for a radar network is derived, and then the Schleher intercept factor is minimized by optimizing the transmission power allocation among netted radars in the network to guarantee target-tracking performance. Furthermore, the Nonlinear Programming Genetic Algorithm (NPGA is used to solve the resulting nonconvex, nonlinear, and constrained optimization problem. Numerical simulation results show the effectiveness of the proposed algorithm.

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.

Radiation monitoring network of the Slovak Hydrometeorological Institute

International Nuclear Information System (INIS)

Melicherova, T.

2005-01-01

In 2000 Centre of Partial monitoring system 'Radioactivity of environment' was established on Slovak Hydrometeorology Institute (SHMI). Radiation monitoring network is one part of Radiation monitoring network of the Slovak Republic. At present SHMI operates in its monitoring network 23 detectors GammaTracer fy Genitron, one mobile detector and one stan by detector. All active detectors are placed in the professional meteorological stations in the selected parts of Slovakia. First one of these detectors was installed in 1999 and they replaced former type of detector (FAG). Last two detectors were installed in 2002. Detector GammaTracer has range of measurement from 20 nSv/h to 10 Sv/h. The detectors are calibrated every 2 years in the Slovak Institute of Metrology in compliance with the calibration plan. SHMI operates 4 aerosol monitors in Hurbanovo, Lucenec, Stropkov and Liesek. Filter 8 from these monitors are analysed in the Institute of Public Health (Cs-137, Be-7). On the base of bilateral agreement between the Austrian Ministry of Agriculture, Forestry, Environment and Water-Management and the Slovak Ministry of Environment Austrian side gave into the ownership of the Slovak side an automatic aerosol monitor AMS-02 including container and weather station. This monitor was installed in meteorological station Jaslovske Bohunice on 4-th October 2001. The Slovak Ministry of Environment provides the Austrian Ministry of Agriculture, Forestry, Environment and Water-Management with the readings of this monitor, free of charge, for at least 3 years and vice versa, the Austrian side gives the readings of the Austrian aerosol monitors to the Slovak Ministry of Environment free of charge. At present national monitoring center in Bratislava-Koliba is connected via ISDN line with Jaslovske Bohunice and Austrian center providing the data exchange. Radiation data (dose rate in the unit nSv/h) are collected via the Institute network to the MSS (message switch system) in the

OPTIMIZING RADIOLOGICAL MONITOR SITING OVER THE CONTINENTAL U.S

International Nuclear Information System (INIS)

Chen, K; Robert Buckley, R; Robert Kurzeja, R; Lance Osteen, L; Saleem Salaymeh, S

2007-01-01

The US Environmental Protection Agency (EPA) is installing a network of sensors in the US to monitor background radiation and elevated radiation levels expected from a possible nuclear incident. The network (RadNet) of 180 fixed sensors is intended to provide a basic estimate of the radiation level throughout the US and enhanced accuracy near population centers. This report discusses one of the objective methods for locating these monitors based on criteria outlined by the EPA. The analysis employs a representative climatology of incident scenarios that includes 50 release locations, four seasons and four times of the day. This climatology was calculated from 5,600 simulations generated with NOAA-ARL's HYSPLIT Lagrangian trajectory model. The method treats the release plumes as targets and monitors are located to maximize the number of plumes detected with the network. Weighting schemes based on detection only, dose-weighted detection and population-dose weighted detection were evaluated. The result shows that most of the monitors are located around the population centers, as expected. However, there are monitors quite uniformly distributed around the less populated areas. The monitors at the populated areas will provide early warning to protect the general public, and the monitors spread across the country will provide valuable data for modelers to estimate the extent and the transport of the radioactive contamination

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.

Environmental monitoring networks in Spain; Redes de vigilancia radiologica ambiental en Espana

Energy Technology Data Exchange (ETDEWEB)

Luque Heredia, S.; Martin Matarranz, J. L.; Marugan Tovar, I.; Rey del Castillo, C.; Salas Collantes, R.; Sterling Carmona, A.; Ramos Salvador, L. M.

2011-07-01

Environmental monitoring in Spain is carried out by several networks with different objectives and scope, a monitoring network in the vicinity of nuclear facilities and radioactive nuclear fuel cycle and various monitoring networks nationally funded and managed by agencies public. The aim of this paper is to present a summary of all monitoring networks, including a series of figures with the stations that are, their geographical distribution and the programs in them.

Brocade: Optimal flow placement in SDN networks

CERN Multimedia

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.

Optimized Neural Network for Fault Diagnosis and Classification

International Nuclear Information System (INIS)

Elaraby, S.M.

2005-01-01

This paper presents a developed and implemented toolbox for optimizing neural network structure of fault diagnosis and classification. Evolutionary algorithm based on hierarchical genetic algorithm structure is used for optimization. The simplest feed-forward neural network architecture is selected. Developed toolbox has friendly user interface. Multiple solutions are generated. The performance and applicability of the proposed toolbox is verified with benchmark data patterns and accident diagnosis of Egyptian Second research reactor (ETRR-2)

Optimal Control of Interdependent Epidemics in Complex Networks

OpenAIRE

Chen, Juntao; Zhang, Rui; Zhu, Quanyan

2017-01-01

Optimal control of interdependent epidemics spreading over complex networks is a critical issue. We first establish a framework to capture the coupling between two epidemics, and then analyze the system's equilibrium states by categorizing them into three classes, and deriving their stability conditions. The designed control strategy globally optimizes the trade-off between the control cost and the severity of epidemics in the network. A gradient descent algorithm based on a fixed point itera...

ANZA Seismic Network- From Monitoring to Science

Science.gov (United States)

Vernon, F.; Eakin, J.; Martynov, V.; Newman, R.; Offield, G.; Hindley, A.; Astiz, L.

2007-05-01

The ANZA Seismic Network (http:eqinfo.ucsd.edu) utilizes broadband and strong motion sensors with 24-bit dataloggers combined with real-time telemetry to monitor local and regional seismicity in southernmost California. The ANZA network provides real-time data to the IRIS DMC, California Integrated Seismic Network (CISN), other regional networks, and the Advanced National Seismic System (ANSS), in addition to providing near real-time information and monitoring to the greater San Diego community. Twelve high dynamic range broadband and strong motion sensors adjacent to the San Jacinto Fault zone contribute data for earthquake source studies and continue the monitoring of the seismic activity of the San Jacinto fault initiated 24 years ago. Five additional stations are located in the San Diego region with one more station on San Clemente Island. The ANZA network uses the advance wireless networking capabilities of the NSF High Performance Wireless Research and Education Network (http:hpwren.ucsd.edu) to provide the communication infrastructure for the real-time telemetry of Anza seismic stations. The ANZA network uses the Antelope data acquisition software. The combination of high quality hardware, communications, and software allow for an annual network uptime in excess of 99.5% with a median annual station real-time data return rate of 99.3%. Approximately 90,000 events, dominantly local sources but including regional and teleseismic events, comprise the ANZA network waveform database. All waveform data and event data are managed using the Datascope relational database. The ANZA network data has been used in a variety of scientific research including detailed structure of the San Jacinto Fault Zone, earthquake source physics, spatial and temporal studies of aftershocks, array studies of teleseismic body waves, and array studies on the source of microseisms. To augment the location, detection, and high frequency observations of the seismic source spectrum from local

A one-layer recurrent neural network for constrained nonconvex optimization.

Science.gov (United States)

Li, Guocheng; Yan, Zheng; Wang, Jun

2015-01-01

In this paper, a one-layer recurrent neural network is proposed for solving nonconvex optimization problems subject to general inequality constraints, designed based on an exact penalty function method. It is proved herein that any neuron state of the proposed neural network is convergent to the feasible region in finite time and stays there thereafter, provided that the penalty parameter is sufficiently large. The lower bounds of the penalty parameter and convergence time are also estimated. In addition, any neural state of the proposed neural network is convergent to its equilibrium point set which satisfies the Karush-Kuhn-Tucker conditions of the optimization problem. Moreover, the equilibrium point set is equivalent to the optimal solution to the nonconvex optimization problem if the objective function and constraints satisfy given conditions. Four numerical examples are provided to illustrate the performances of the proposed neural network.

DRO: domain-based route optimization scheme for nested mobile networks

Directory of Open Access Journals (Sweden)

Chuang Ming-Chin

2011-01-01

Full Text Available Abstract The network mobility (NEMO basic support protocol is designed to support NEMO management, and to ensure communication continuity between nodes in mobile networks. However, in nested mobile networks, NEMO suffers from the pinball routing problem, which results in long packet transmission delays. To solve the problem, we propose a domain-based route optimization (DRO scheme that incorporates a domain-based network architecture and ad hoc routing protocols for route optimization. DRO also improves the intra-domain handoff performance, reduces the convergence time during route optimization, and avoids the out-of-sequence packet problem. A detailed performance analysis and simulations were conducted to evaluate the scheme. The results demonstrate that DRO outperforms existing mechanisms in terms of packet transmission delay (i.e., better route-optimization, intra-domain handoff latency, convergence time, and packet tunneling overhead.

Design of a particulate-monitoring network for the Y-12 plant

International Nuclear Information System (INIS)

Hougland, E.S.; Oakes, T.W.; Underwood, J.N.

1982-01-01

An Air Quality Monitoring Network Design (AQMND) with multiple objectives is being developed for the Y-12 Plant production facilities. The objectives are: Y-12 facility surveillance; monitoring the transport of Y-12 generated airborne effluents towards either the Oak Ridge National Laboratory or the developed region of the City of Oak Ridge; and monitoring population exposure in residential areas close to the Y-12 Plant. A two step design process was carried out, using the Air Quality Monitor Network Design Model (AQMND) previously used for the Oak Ridge National Laboratory network. In the first step of the design we used existing air quality monitor locations, subjectively designated locations, and grid intersections as a set of potential monitor sites. The priority sites from the first step (modified to account for terrain and accessibility), and subjectively designated sites, were used as the potential monitor sites for the second step of the process which produced the final design recommendations for the monitor network

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.

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)

Development of a method of robust rain gauge network optimization based on intensity-duration-frequency results

Directory of Open Access Journals (Sweden)

A. Chebbi

2013-10-01

Full Text Available Based on rainfall intensity-duration-frequency (IDF curves, fitted in several locations of a given area, a robust optimization approach is proposed to identify the best locations to install new rain gauges. The advantage of robust optimization is that the resulting design solutions yield networks which behave acceptably under hydrological variability. Robust optimization can overcome the problem of selecting representative rainfall events when building the optimization process. This paper reports an original approach based on Montana IDF model parameters. The latter are assumed to be geostatistical variables, and their spatial interdependence is taken into account through the adoption of cross-variograms in the kriging process. The problem of optimally locating a fixed number of new monitoring stations based on an existing rain gauge network is addressed. The objective function is based on the mean spatial kriging variance and rainfall variogram structure using a variance-reduction method. Hydrological variability was taken into account by considering and implementing several return periods to define the robust objective function. Variance minimization is performed using a simulated annealing algorithm. In addition, knowledge of the time horizon is needed for the computation of the robust objective function. A short- and a long-term horizon were studied, and optimal networks are identified for each. The method developed is applied to north Tunisia (area = 21 000 km2. Data inputs for the variogram analysis were IDF curves provided by the hydrological bureau and available for 14 tipping bucket type rain gauges. The recording period was from 1962 to 2001, depending on the station. The study concerns an imaginary network augmentation based on the network configuration in 1973, which is a very significant year in Tunisia because there was an exceptional regional flood event in March 1973. This network consisted of 13 stations and did not meet World

A wireless sensor network design and evaluation for large structural strain field monitoring

International Nuclear Information System (INIS)

Qiu, Zixue; Wu, Jian; Yuan, Shenfang

2011-01-01

Structural strain changes under external environmental or mechanical loads are the main monitoring parameters in structural health monitoring or mechanical property tests. This paper presents a wireless sensor network designed for monitoring large structural strain field variation. First of all, a precision strain sensor node is designed for multi-channel strain gauge signal conditioning and wireless monitoring. In order to establish a synchronous strain data acquisition network, the cluster-star network synchronization method is designed in detail. To verify the functionality of the designed wireless network for strain field monitoring capability, a multi-point network evaluation system is developed for an experimental aluminum plate structure for load variation monitoring. Based on the precision wireless strain nodes, the wireless data acquisition network is deployed to synchronously gather, process and transmit strain gauge signals and monitor results under concentrated loads. This paper shows the efficiency of the wireless sensor network for large structural strain field monitoring

RadNet Radiological Air Monitoring Network

International Nuclear Information System (INIS)

Scott Telofski, J.; Askren, D.R.; Petko, Ch.M.; Fraass, R.G.

2010-01-01

The United States Environmental Protection Agency operates a national environmental radiation monitoring program called RadNet. RadNet monitors airborne particulates, precipitation, milk, and drinking water for radiation levels. The primary purpose of the original program in the 1950's and 1960's was to collect and analyze samples in various media to assess the effects of radioactive fallout from above-ground nuclear weapon testing. As above-ground testing diminished in the 1970's, the program, especially the air network, became critical in evaluating effects of other types of nuclear incidents, such as the nuclear reactor accident at Chernobyl, as well as monitoring trends in environmental radioactive contamination. The value of rapid data collection subsequent to such incidents led to the consideration of developing air monitors with radiation detectors and telecommunication equipment for real-time radiation measurement. The strengthened United States homeland security posture after 2001 led to production and installation of the current real-time RadNet air monitors. There are now 118 stationary, continuously operating air monitoring stations and 40 mobile air monitors for site specific monitoring. The stationary air monitors include radiation detectors, meteorological sensors, a high-volume air sampler, and communication devices for hourly data transfers. When unusual levels are detected, scientists download a full sodium iodide detector spectrum for analysis. The real-time data collected by RadNet stationary systems permit rapid identification and quantification of airborne nuclides with sufficient sensitivity to provide critical information to help determine protective actions. The data also may help to rapidly refine long-range radioactive plume models and estimate exposure to the population. This paper provides an overview of the airborne particulate monitoring conducted during above-ground nuclear weapon testing, summarizes the uses of data from the program

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.

Modeling and optimization of an electric power distribution network ...

African Journals Online (AJOL)

Modeling and optimization of an electric power distribution network planning system using ... of the network was modelled with non-linear mathematical expressions. ... given feasible locations, re-conductoring of existing feeders in the network, ...

Optimal control of epidemic information dissemination over networks.

Science.gov (United States)

Chen, Pin-Yu; Cheng, Shin-Ming; Chen, Kwang-Cheng

2014-12-01

Information dissemination control is of crucial importance to facilitate reliable and efficient data delivery, especially in networks consisting of time-varying links or heterogeneous links. Since the abstraction of information dissemination much resembles the spread of epidemics, epidemic models are utilized to characterize the collective dynamics of information dissemination over networks. From a systematic point of view, we aim to explore the optimal control policy for information dissemination given that the control capability is a function of its distribution time, which is a more realistic model in many applications. The main contributions of this paper are to provide an analytically tractable model for information dissemination over networks, to solve the optimal control signal distribution time for minimizing the accumulated network cost via dynamic programming, and to establish a parametric plug-in model for information dissemination control. In particular, we evaluate its performance in mobile and generalized social networks as typical examples.

Traffic Congestion Evaluation and Signal Control Optimization Based on Wireless Sensor Networks: Model and Algorithms

Directory of Open Access Journals (Sweden)

Wei Zhang

2012-01-01

Full Text Available This paper presents the model and algorithms for traffic flow data monitoring and optimal traffic light control based on wireless sensor networks. Given the scenario that sensor nodes are sparsely deployed along the segments between signalized intersections, an analytical model is built using continuum traffic equation and develops the method to estimate traffic parameter with the scattered sensor data. Based on the traffic data and principle of traffic congestion formation, we introduce the congestion factor which can be used to evaluate the real-time traffic congestion status along the segment and to predict the subcritical state of traffic jams. The result is expected to support the timing phase optimization of traffic light control for the purpose of avoiding traffic congestion before its formation. We simulate the traffic monitoring based on the Mobile Century dataset and analyze the performance of traffic light control on VISSIM platform when congestion factor is introduced into the signal timing optimization model. The simulation result shows that this method can improve the spatial-temporal resolution of traffic data monitoring and evaluate traffic congestion status with high precision. It is helpful to remarkably alleviate urban traffic congestion and decrease the average traffic delays and maximum queue length.

A Wildlife Monitoring System Based on Wireless Image Sensor Networks

Directory of Open Access Journals (Sweden)

Junguo Zhang

2014-10-01

Full Text Available Survival and development of wildlife sustains the balance and stability of the entire ecosystem. Wildlife monitoring can provide lots of information such as wildlife species, quantity, habits, quality of life and habitat conditions, to help researchers grasp the status and dynamics of wildlife resources, and to provide basis for the effective protection, sustainable use, and scientific management of wildlife resources. Wildlife monitoring is the foundation of wildlife protection and management. Wireless Sensor Networks (WSN technology has become the most popular technology in the field of information. With advance of the CMOS image sensor technology, wireless sensor networks combined with image sensors, namely Wireless Image Sensor Networks (WISN technology, has emerged as an alternative in monitoring applications. Monitoring wildlife is one of its most promising applications. In this paper, system architecture of the wildlife monitoring system based on the wireless image sensor networks was presented to overcome the shortcomings of the traditional monitoring methods. Specifically, some key issues including design of wireless image sensor nodes and software process design have been studied and presented. A self-powered rotatable wireless infrared image sensor node based on ARM and an aggregation node designed for large amounts of data were developed. In addition, their corresponding software was designed. The proposed system is able to monitor wildlife accurately, automatically, and remotely in all-weather condition, which lays foundations for applications of wireless image sensor networks in wildlife monitoring.

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

Intercontinental Multi-Domain Monitoring for the LHC Optical Private Network

CERN Multimedia

CERN. Geneva

2012-01-01

The Large Hadron Collider (LHC) is currently running at CERN in Geneva, Switzerland. Physicists are using LHC to recreate the conditions just after the Big Bang, by colliding two beams of particles and heavy ions head-on at very high energy. The project is expected to generate 27 TB of raw data per day, plus 10 TB of "event summary data". This data is sent out from CERN to eleven Tier 1 academic institutions in Europe, Asia, and North America using a multi-gigabits Optical Private Network (OPN), the LHCOPN. Network monitoring on such complex network architecture to ensure robust and reliable operation is of crucial importance. The chosen approach for monitoring the OPN is based on the perfSONAR MDM framework (http://perfsonar.geant.net), which is designed for multi-domain monitoring environments. perfSONAR (www.perfsonar.net) is an infrastructure for performance monitoring data exchange between networks, making it easier to solve performance problems occurring between network measurement points interconne...

Development of a Wireless Sensor Network for Individual Monitoring of Panels in a Photovoltaic Plant

Directory of Open Access Journals (Sweden)

Miguel J. Prieto

2014-01-01

Full Text Available With photovoltaic (PV systems proliferating in the last few years due to the high prices of fossil fuels and pollution issues, among others, it is extremely important to monitor the efficiency of these plants and optimize the energy production process. This will also result in improvements related to the maintenance and security of the installation. In order to do so, the main parameters in the plant must be continuously monitored so that the appropriate actions can be carried out. This monitoring should not only be carried out at a global level, but also at panel-level, so that a better understanding of what is actually happening in the PV plant can be obtained. This paper presents a system based on a wireless sensor network (WSN that includes all the components required for such monitoring as well as a power supply obtaining the energy required by the sensors from the photovoltaic panels. The system proposed succeeds in identifying all the nodes in the network and provides real-time monitoring while tracking efficiency, features, failures and weaknesses from a single cell up to the whole infrastructure. Thus, the decision-making process is simplified, which contributes to reducing failures, wastes and, consequently, costs.

Development of a wireless sensor network for individual monitoring of panels in a photovoltaic plant.

Science.gov (United States)

Prieto, Miguel J; Pernía, Alberto M; Nuño, Fernando; Díaz, Juan; Villegas, Pedro J

2014-01-30

With photovoltaic (PV) systems proliferating in the last few years due to the high prices of fossil fuels and pollution issues, among others, it is extremely important to monitor the efficiency of these plants and optimize the energy production process. This will also result in improvements related to the maintenance and security of the installation. In order to do so, the main parameters in the plant must be continuously monitored so that the appropriate actions can be carried out. This monitoring should not only be carried out at a global level, but also at panel-level, so that a better understanding of what is actually happening in the PV plant can be obtained. This paper presents a system based on a wireless sensor network (WSN) that includes all the components required for such monitoring as well as a power supply obtaining the energy required by the sensors from the photovoltaic panels. The system proposed succeeds in identifying all the nodes in the network and provides real-time monitoring while tracking efficiency, features, failures and weaknesses from a single cell up to the whole infrastructure. Thus, the decision-making process is simplified, which contributes to reducing failures, wastes and, consequently, costs.

Chaotic Hopfield Neural Network Swarm Optimization and Its Application

Directory of Open Access Journals (Sweden)

Yanxia Sun

2013-01-01

Full Text Available A new neural network based optimization algorithm is proposed. The presented model is a discrete-time, continuous-state Hopfield neural network and the states of the model are updated synchronously. The proposed algorithm combines the advantages of traditional PSO, chaos and Hopfield neural networks: particles learn from their own experience and the experiences of surrounding particles, their search behavior is ergodic, and convergence of the swarm is guaranteed. The effectiveness of the proposed approach is demonstrated using simulations and typical optimization problems.

Wide area network monitoring system for HEP experiments at Fermilab

International Nuclear Information System (INIS)

Grigoriev, Maxim; Fermilab; Cottrell, Les; Logg, Connie; SLAC

2004-01-01

Large, distributed High Energy Physics (HEP) collaborations, such as D0, CDF and US-CMS, depend on stable and robust network paths between major world research centres. The evolving emphasis on data and compute Grids increases the reliance on network performance. Fermilab's experimental groups and network support personnel identified a critical need for WAN monitoring to ensure the quality and efficient utilization of such network paths. This has led to the development of the Network Monitoring system we will present in this paper. The system evolved from the IEPM-BW project, started at SLAC three years ago. At Fermilab this system has developed into a fully functional infrastructure with bi-directional active network probes and path characterizations. It is based on the Iperf achievable throughput tool, Ping and Synack to test ICMP/TCP connectivity. It uses Pipechar and Traceroute to test, compare and report hop-by-hop network path characterization. It also measures real file transfer performance by BBFTP and GridFTP. The Monitoring system has an extensive web-interface and all the data is available through standalone SOAP web services or by a MonaLISA client. Also in this paper we will present a case study of network path asymmetry and abnormal performance between FNAL and SDSC, which was discovered and resolved by utilizing the Network Monitoring system

Wide Area Network Monitoring System for HEP Experiments at Fermilab

International Nuclear Information System (INIS)

Grigoriev, M.

2004-01-01

Large, distributed High Energy Physics (HEP) collaborations, such as D0, CDF and US-CMS, depend on stable and robust network paths between major world research centres. The evolving emphasis on data and compute Grids increases the reliance on network performance. Fermilab's experimental groups and network support personnel identified a critical need for WAN monitoring to ensure the quality and efficient utilization of such network paths. This has led to the development of the Network Monitoring system we will present in this paper. The system evolved from the IEPM-BW project, started at SLAC three years ago. At Fermilab this system has developed into a fully functional infrastructure with bi-directional active network probes and path characterizations. It is based on the Iperf achievable throughput tool, Ping and Synack to test ICMP/TCP connectivity. It uses Pipechar and Traceroute to test, compare and report hop-by-hop network path characterization. It also measures real file transfer performance by BBFTP and GridFTP. The Monitoring system has an extensive web-interface and all the data is available through standalone SOAP web services or by a MonaLISA client. Also in this paper we will present a case study of network path asymmetry and abnormal performance between FNAL and SDSC, which was discovered and resolved by utilizing the Network Monitoring system

Wide Area Network Monitoring System for HEP Experiments at Fermilab

Energy Technology Data Exchange (ETDEWEB)

Grigoriev, M.

2004-11-23

Large, distributed High Energy Physics (HEP) collaborations, such as D0, CDF and US-CMS, depend on stable and robust network paths between major world research centres. The evolving emphasis on data and compute Grids increases the reliance on network performance. Fermilab's experimental groups and network support personnel identified a critical need for WAN monitoring to ensure the quality and efficient utilization of such network paths. This has led to the development of the Network Monitoring system we will present in this paper. The system evolved from the IEPM-BW project, started at SLAC three years ago. At Fermilab this system has developed into a fully functional infrastructure with bi-directional active network probes and path characterizations. It is based on the Iperf achievable throughput tool, Ping and Synack to test ICMP/TCP connectivity. It uses Pipechar and Traceroute to test, compare and report hop-by-hop network path characterization. It also measures real file transfer performance by BBFTP and GridFTP. The Monitoring system has an extensive web-interface and all the data is available through standalone SOAP web services or by a MonaLISA client. Also in this paper we will present a case study of network path asymmetry and abnormal performance between FNAL and SDSC, which was discovered and resolved by utilizing the Network Monitoring system.

NRC TLD Direct Radiation Monitoring Network

International Nuclear Information System (INIS)

Struckmeyer, R.

1994-03-01

This report presents the results of the NRC Direct Radiation Monitoring Network for the fourth quarter of 1993. It provides the ambient radiation levels measured in the vicinity of 75 sites throughout the United States. In addition, it describes the equipment used, monitoring station selection criteria, characterization of the dosimeter response, calibration procedures, statistical methods, intercomparison, and quality assurance program

NRC TLD Direct Radiation Monitoring Network

International Nuclear Information System (INIS)

Struckmeyer, R.; McNamara, N.

1993-03-01

This report present the results of the NRC Direct Radiation Monitoring Network for the fourth quarter of 1992. It provides the ambient radiation levels measured in the vicinity of 75 sites throughout the United States. In addition, it describes the equipment used, monitoring station selection criteria, characterization of the dosimeter response, calibration procedures, statistical methods, intercomparison, and quality assurance program

Optimal placement of distributed generation in distribution networks ...

African Journals Online (AJOL)

This paper proposes the application of Particle Swarm Optimization (PSO) technique to find the optimal size and optimum location for the placement of DG in the radial distribution networks for active power compensation by reduction in real power losses and enhancement in voltage profile. In the first segment, the optimal ...

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

Deterministic network interdiction optimization via an evolutionary approach

International Nuclear Information System (INIS)

Rocco S, Claudio M.; Ramirez-Marquez, Jose Emmanuel

2009-01-01

This paper introduces an evolutionary optimization approach that can be readily applied to solve deterministic network interdiction problems. The network interdiction problem solved considers the minimization of the maximum flow that can be transmitted between a source node and a sink node for a fixed network design when there is a limited amount of resources available to interdict network links. Furthermore, the model assumes that the nominal capacity of each network link and the cost associated with their interdiction can change from link to link. For this problem, the solution approach developed is based on three steps that use: (1) Monte Carlo simulation, to generate potential network interdiction strategies, (2) Ford-Fulkerson algorithm for maximum s-t flow, to analyze strategies' maximum source-sink flow and, (3) an evolutionary optimization technique to define, in probabilistic terms, how likely a link is to appear in the final interdiction strategy. Examples for different sizes of networks and network behavior are used throughout the paper to illustrate the approach. In terms of computational effort, the results illustrate that solutions are obtained from a significantly restricted solution search space. Finally, the authors discuss the need for a reliability perspective to network interdiction, so that solutions developed address more realistic scenarios of such problem

Sonification of network traffic flow for monitoring and situational awareness

Science.gov (United States)

2018-01-01

Maintaining situational awareness of what is happening within a computer network is challenging, not only because the behaviour happens within machines, but also because data traffic speeds and volumes are beyond human ability to process. Visualisation techniques are widely used to present information about network traffic dynamics. Although they provide operators with an overall view and specific information about particular traffic or attacks on the network, they often still fail to represent the events in an understandable way. Also, because they require visual attention they are not well suited to continuous monitoring scenarios in which network administrators must carry out other tasks. Here we present SoNSTAR (Sonification of Networks for SiTuational AwaReness), a real-time sonification system for monitoring computer networks to support network administrators’ situational awareness. SoNSTAR provides an auditory representation of all the TCP/IP traffic within a network based on the different traffic flows between between network hosts. A user study showed that SoNSTAR raises situational awareness levels by enabling operators to understand network behaviour and with the benefit of lower workload demands (as measured by the NASA TLX method) than visual techniques. SoNSTAR identifies network traffic features by inspecting the status flags of TCP/IP packet headers. Combinations of these features define particular traffic events which are mapped to recorded sounds to generate a soundscape that represents the real-time status of the network traffic environment. The sequence, timing, and loudness of the different sounds allow the network to be monitored and anomalous behaviour to be detected without the need to continuously watch a monitor screen. PMID:29672543

Sonification of network traffic flow for monitoring and situational awareness.

Science.gov (United States)

Debashi, Mohamed; Vickers, Paul

2018-01-01

Maintaining situational awareness of what is happening within a computer network is challenging, not only because the behaviour happens within machines, but also because data traffic speeds and volumes are beyond human ability to process. Visualisation techniques are widely used to present information about network traffic dynamics. Although they provide operators with an overall view and specific information about particular traffic or attacks on the network, they often still fail to represent the events in an understandable way. Also, because they require visual attention they are not well suited to continuous monitoring scenarios in which network administrators must carry out other tasks. Here we present SoNSTAR (Sonification of Networks for SiTuational AwaReness), a real-time sonification system for monitoring computer networks to support network administrators' situational awareness. SoNSTAR provides an auditory representation of all the TCP/IP traffic within a network based on the different traffic flows between between network hosts. A user study showed that SoNSTAR raises situational awareness levels by enabling operators to understand network behaviour and with the benefit of lower workload demands (as measured by the NASA TLX method) than visual techniques. SoNSTAR identifies network traffic features by inspecting the status flags of TCP/IP packet headers. Combinations of these features define particular traffic events which are mapped to recorded sounds to generate a soundscape that represents the real-time status of the network traffic environment. The sequence, timing, and loudness of the different sounds allow the network to be monitored and anomalous behaviour to be detected without the need to continuously watch a monitor screen.

Establishing a Multi-spatial Wireless Sensor Network to Monitor Nitrate Concentrations in Soil Moisture

Science.gov (United States)

Haux, E.; Busek, N.; Park, Y.; Estrin, D.; Harmon, T. C.

2004-12-01

The use of reclaimed wastewater for irrigation in agriculture can be a significant source of nutrients, in particular nitrogen species, but its use raises concern for groundwater, riparian, and water quality. A 'smart' technology would have the ability to measure wastewater nutrients as they enter the irrigation system, monitor their transport in situ and optimally control inputs with little human intervention, all in real-time. Soil heterogeneity and economic issues require, however, a balance between cost and the spatial and temporal scales of the monitoring effort. Therefore, a wireless and embedded sensor network, deployed in the soil vertically across the horizon, is capable of collecting, processing, and transmitting sensor data. The network consists of several networked nodes or 'pylons', each outfitted with an array of sensors measuring humidity, temperature, precipitation, soil moisture, and aqueous nitrate concentrations. Individual sensor arrays are controlled by a MICA2 mote (Crossbow Technology Inc., San Jose, CA) programmed with TinyOS (University of California, Berkeley, CA) and a Stargate (Crossbow Technology Inc., San Jose, CA) base-station capable of GPRS for data transmission. Results are reported for the construction and testing of a prototypical pylon at the benchtop and in the field.

Optimizing an estuarine water quality monitoring program through an entropy-based hierarchical spatiotemporal Bayesian framework

Science.gov (United States)

Alameddine, Ibrahim; Karmakar, Subhankar; Qian, Song S.; Paerl, Hans W.; Reckhow, Kenneth H.

2013-10-01

The total maximum daily load program aims to monitor more than 40,000 standard violations in around 20,000 impaired water bodies across the United States. Given resource limitations, future monitoring efforts have to be hedged against the uncertainties in the monitored system, while taking into account existing knowledge. In that respect, we have developed a hierarchical spatiotemporal Bayesian model that can be used to optimize an existing monitoring network by retaining stations that provide the maximum amount of information, while identifying locations that would benefit from the addition of new stations. The model assumes the water quality parameters are adequately described by a joint matrix normal distribution. The adopted approach allows for a reduction in redundancies, while emphasizing information richness rather than data richness. The developed approach incorporates the concept of entropy to account for the associated uncertainties. Three different entropy-based criteria are adopted: total system entropy, chlorophyll-a standard violation entropy, and dissolved oxygen standard violation entropy. A multiple attribute decision making framework is adopted to integrate the competing design criteria and to generate a single optimal design. The approach is implemented on the water quality monitoring system of the Neuse River Estuary in North Carolina, USA. The model results indicate that the high priority monitoring areas identified by the total system entropy and the dissolved oxygen violation entropy criteria are largely coincident. The monitoring design based on the chlorophyll-a standard violation entropy proved to be less informative, given the low probabilities of violating the water quality standard in the estuary.

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...... (MMAE) approach to the data resulted in the highest classification success rate, due to the use of precise forth-order mathematical models which relate the feed offer to the pitch angle of the neck. This thesis shows that wireless sensor networks can be successfully employed to monitor the behavior...

Synchrony-optimized networks of non-identical Kuramoto oscillators

International Nuclear Information System (INIS)

Brede, Markus

2008-01-01

In this Letter we discuss a method for generating synchrony-optimized coupling architectures of Kuramoto oscillators with a heterogeneous distribution of native frequencies. The method allows us to relate the properties of the coupling network to its synchronizability. These relations were previously only established from a linear stability analysis of the identical oscillator case. We further demonstrate that the heterogeneity in the oscillator population produces heterogeneity in the optimal coupling network as well. Two rules for enhancing the synchronizability of a given network by a suitable placement of oscillators are given: (i) native frequencies of adjacent oscillators must be anti-correlated and (ii) frequency magnitudes should positively correlate with the degree of the node they are placed at

A Cross-Layer Wireless Sensor Network Energy-Efficient Communication Protocol for Real-Time Monitoring of the Long-Distance Electric Transmission Lines

Directory of Open Access Journals (Sweden)

Jun Yu

2015-01-01

Full Text Available Optimization of energy consumption in Wireless Sensor Network (WSN nodes has become a critical link that constrains the engineering application of the smart grid due to the fact that the smart grid is characterized by long-distance transmission in a special environment. The paper proposes a linear hierarchical network topological structure specific to WSN energy conservation in environmental monitoring of the long-distance electric transmission lines in the smart grid. Based on the topological structural characteristics and optimization of network layers, the paper also proposes a Topological Structure be Layered Configurations (TSLC routing algorithm to improve the quality of WSN data transmission performance. Coprocessing of the network layer and the media access control (MAC layer is achieved by using the cross-layer design method, accessing the status for the nodes in the network layer and obtaining the status of the network nodes of the MAC layer. It efficiently saves the energy of the whole network, improves the quality of the network service performance, and prolongs the life cycle of the network.

A quantitative method for groundwater surveillance monitoring network design at the Hanford Site

International Nuclear Information System (INIS)

Meyer, P.D.

1993-12-01

As part of the Environmental Surveillance Program at the Hanford Site, mandated by the US Department of Energy, hundreds of groundwater wells are sampled each year, with each sample typically analyzed for a variety of constituents. The groundwater sampling program must satisfy several broad objectives. These objectives include an integrated assessment of the condition of groundwater and the identification and quantification of existing, emerging, or potential groundwater problems. Several quantitative network desip objectives are proposed and a mathematical optimization model is developed from these objectives. The model attempts to find minimum cost network alternatives that maximize the amount of information generated by the network. Information is measured both by the rats of change with respect to time of the contaminant concentration and the uncertainty in contaminant concentration. In an application to tritium monitoring at the Hanford Site, both information measures were derived from historical data using time series analysis

Connection with seismic networks and construction of real time earthquake monitoring system

Energy Technology Data Exchange (ETDEWEB)

Chi, Heon Cheol; Lee, H. I.; Shin, I. C.; Lim, I. S.; Park, J. H.; Lee, B. K.; Whee, K. H.; Cho, C. S. [Korea Atomic Energy Research Institute, Taejon (Korea, Republic of)

2000-12-15

It is natural to use the nuclear power plant seismic network which have been operated by KEPRI(Korea Electric Power Research Institute) and local seismic network by KIGAM(Korea Institute of Geology, Mining and Material). The real time earthquake monitoring system is composed with monitoring module and data base module. Data base module plays role of seismic data storage and classification and the other, monitoring module represents the status of acceleration in the nuclear power plant area. This research placed the target on the first, networking the KIN's seismic monitoring system with KIGAM and KEPRI seismic network and the second, construction the KIN's Independent earthquake monitoring system.

Connection with seismic networks and construction of real time earthquake monitoring system

International Nuclear Information System (INIS)

Chi, Heon Cheol; Lee, H. I.; Shin, I. C.; Lim, I. S.; Park, J. H.; Lee, B. K.; Whee, K. H.; Cho, C. S.

2000-12-01

It is natural to use the nuclear power plant seismic network which have been operated by KEPRI(Korea Electric Power Research Institute) and local seismic network by KIGAM(Korea Institute of Geology, Mining and Material). The real time earthquake monitoring system is composed with monitoring module and data base module. Data base module plays role of seismic data storage and classification and the other, monitoring module represents the status of acceleration in the nuclear power plant area. This research placed the target on the first, networking the KIN's seismic monitoring system with KIGAM and KEPRI seismic network and the second, construction the KIN's Independent earthquake monitoring system

Optimization and Control of Communication Networks

OpenAIRE

Chiang, Mung; Low, Steven

2005-01-01

Recently, there has been a surge in research activities that utilize the power of recent developments in nonlinear optimization to tackle a wide scope of work in the analysis and design of communication systems, touching every layer of the layered network architecture, and resulting in both intellectual and practical impacts significantly beyond the earlier frameworks. These research activities are driven by both new demands in the areas of communications and networking, and n...

NRC TLD Direct Radiation Monitoring Network

International Nuclear Information System (INIS)

Struckmeyer, R.; McNamara, N.

1991-04-01

This report presents the results of the NRC [Nuclear Regulatory Commission] Direct Radiation Monitoring Network for the fourth quarter of 1990. It provides the ambient radiation levels measured in the vicinity of 75 sites throughout the United States. In addition, it describes the equipment used, monitoring station selection criteria, characterization of the dosimeter response, calibration procedures, statistical methods, intercomparison, and quality assurance program. 3 figs., 4 tabs

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.

Optimal satisfaction degree in energy harvesting cognitive radio networks

Science.gov (United States)

Li, Zan; Liu, Bo-Yang; Si, Jiang-Bo; Zhou, Fu-Hui

2015-12-01

A cognitive radio (CR) network with energy harvesting (EH) is considered to improve both spectrum efficiency and energy efficiency. A hidden Markov model (HMM) is used to characterize the imperfect spectrum sensing process. In order to maximize the whole satisfaction degree (WSD) of the cognitive radio network, a tradeoff between the average throughput of the secondary user (SU) and the interference to the primary user (PU) is analyzed. We formulate the satisfaction degree optimization problem as a mixed integer nonlinear programming (MINLP) problem. The satisfaction degree optimization problem is solved by using differential evolution (DE) algorithm. The proposed optimization problem allows the network to adaptively achieve the optimal solution based on its required quality of service (Qos). Numerical results are given to verify our analysis. Project supported by the National Natural Science Foundation of China (Grant No. 61301179), the Doctorial Programs Foundation of the Ministry of Education of China (Grant No. 20110203110011), and the 111 Project (Grant No. B08038).

Optimal Joint Liability Lending and with Costly Peer Monitoring

NARCIS (Netherlands)

Carli, Francesco; 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

PSO-Optimized Hopfield Neural Network-Based Multipath Routing for Mobile Ad-hoc Networks

Directory of Open Access Journals (Sweden)

Mansour Sheikhan

2012-06-01

Full Text Available Mobile ad-hoc network (MANET is a dynamic collection of mobile computers without the need for any existing infrastructure. Nodes in a MANET act as hosts and routers. Designing of robust routing algorithms for MANETs is a challenging task. Disjoint multipath routing protocols address this problem and increase the reliability, security and lifetime of network. However, selecting an optimal multipath is an NP-complete problem. In this paper, Hopfield neural network (HNN which its parameters are optimized by particle swarm optimization (PSO algorithm is proposed as multipath routing algorithm. Link expiration time (LET between each two nodes is used as the link reliability estimation metric. This approach can find either node-disjoint or link-disjoint paths in singlephase route discovery. Simulation results confirm that PSO-HNN routing algorithm has better performance as compared to backup path set selection algorithm (BPSA in terms of the path set reliability and number of paths in the set.

Geo mathematic tools for the design of a radioisotopes monitoring network in order to modelling the groundwater dynamics processes and hydrodynamic management

International Nuclear Information System (INIS)

Peralta, J.L.; Gil, R.; Leyva, D.; Molerio, L.F.; Pin, M.

2004-01-01

The present paper, shows the application of geo mathematic tools [Mangin,1981; Molerio,1997] for the design of a radioisotopes monitoring network in order to modelling the groundwater dynamics processes and hydrodynamic management of a Karstic Basin (Almendares-Vento watershed), which is very difficult to evaluate due to the physical-geographical, geologic and hydrogeological characteristics. The Almendares Vento watershed (AVW) is close to the Jaruco-Aguacate watershed, with a similar hydrogeologic and geologic structure, therefore similar result must be expected. In the AVW case is necessary to identify, with more precision, the water propagation limits of the stratified layers according to the waters transit times, recharges and dynamics aquifers, residence time, groundwater contamination and the groundwater-surface water interaction due to the dam placed on the basin. The paper allowed the identification of a monitoring points network, taking into account, between other statistical approaches, the good correlation, the high memory effect, etc. According to the analysis of the variances spectral, have been obtained and optimized the sampling frequency of the network points in the Basin. Besides, it have been identified the necessities to include the detailed evaluation of a specific point of the network in the hydrodynamic study (Vento watershed). In order to evaluate the optimization of the designed monitoring network, the geo mathematic study developed was compared with the results of the mathematical model AQUIMPE, the final result showed the validation of the obtained design. The results of the work allow the best monitoring of the parameters in order to determine the aquifer recharge, residence times, the vulnerability to the waters contamination and the groundwater-surface water interaction

Method of optimization onboard communication network

Science.gov (United States)

Platoshin, G. A.; Selvesuk, N. I.; Semenov, M. E.; Novikov, V. M.

2018-02-01

In this article the optimization levels of onboard communication network (OCN) are proposed. We defined the basic parameters, which are necessary for the evaluation and comparison of modern OCN, we identified also a set of initial data for possible modeling of the OCN. We also proposed a mathematical technique for implementing the OCN optimization procedure. This technique is based on the principles and ideas of binary programming. It is shown that the binary programming technique allows to obtain an inherently optimal solution for the avionics tasks. An example of the proposed approach implementation to the problem of devices assignment in OCN is considered.

Wireless visual sensor network resource allocation using cross-layer optimization

Science.gov (United States)

Bentley, Elizabeth S.; Matyjas, John D.; Medley, Michael J.; Kondi, Lisimachos P.

2009-01-01

In this paper, we propose an approach to manage network resources for a Direct Sequence Code Division Multiple Access (DS-CDMA) visual sensor network where nodes monitor scenes with varying levels of motion. It uses cross-layer optimization across the physical layer, the link layer and the application layer. Our technique simultaneously assigns a source coding rate, a channel coding rate, and a power level to all nodes in the network based on one of two criteria that maximize the quality of video of the entire network as a whole, subject to a constraint on the total chip rate. One criterion results in the minimal average end-to-end distortion amongst all nodes, while the other criterion minimizes the maximum distortion of the network. Our approach allows one to determine the capacity of the visual sensor network based on the number of nodes and the quality of video that must be transmitted. For bandwidth-limited applications, one can also determine the minimum bandwidth needed to accommodate a number of nodes with a specific target chip rate. Video captured by a sensor node camera is encoded and decoded using the H.264 video codec by a centralized control unit at the network layer. To reduce the computational complexity of the solution, Universal Rate-Distortion Characteristics (URDCs) are obtained experimentally to relate bit error probabilities to the distortion of corrupted video. Bit error rates are found first by using Viterbi's upper bounds on the bit error probability and second, by simulating nodes transmitting data spread by Total Square Correlation (TSC) codes over a Rayleigh-faded DS-CDMA channel and receiving that data using Auxiliary Vector (AV) filtering.

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) r...

Stochastic network interdiction optimization via capacitated network reliability modeling and probabilistic solution discovery

International Nuclear Information System (INIS)

Ramirez-Marquez, Jose Emmanuel; Rocco S, Claudio M.

2009-01-01

This paper introduces an evolutionary optimization approach that can be readily applied to solve stochastic network interdiction problems (SNIP). The network interdiction problem solved considers the minimization of the cost associated with an interdiction strategy such that the maximum flow that can be transmitted between a source node and a sink node for a fixed network design is greater than or equal to a given reliability requirement. Furthermore, the model assumes that the nominal capacity of each network link and the cost associated with their interdiction can change from link to link and that such interdiction has a probability of being successful. This version of the SNIP is for the first time modeled as a capacitated network reliability problem allowing for the implementation of computation and solution techniques previously unavailable. The solution process is based on an evolutionary algorithm that implements: (1) Monte-Carlo simulation, to generate potential network interdiction strategies, (2) capacitated network reliability techniques to analyze strategies' source-sink flow reliability and, (3) an evolutionary optimization technique to define, in probabilistic terms, how likely a link is to appear in the final interdiction strategy. Examples for different sizes of networks are used throughout the paper to illustrate the approach

Global Optimization for Transport Network Expansion and Signal Setting

OpenAIRE

Liu, Haoxiang; Wang, David Z. W.; Yue, Hao

2015-01-01

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 pr...

A Jackson network model and threshold policy for joint optimization of energy and delay in multi-hop wireless networks

KAUST Repository

Xia, Li; Shihada, Basem

2014-01-01

This paper studies the joint optimization problem of energy and delay in a multi-hop wireless network. The optimization variables are the transmission rates, which are adjustable according to the packet queueing length in the buffer. The optimization goal is to minimize the energy consumption of energy-critical nodes and the packet transmission delay throughout the network. In this paper, we aim at understanding the well-known decentralized algorithms which are threshold based from a different research angle. By using a simplified network model, we show that we can adopt the semi-open Jackson network model and study this optimization problem in closed form. This simplified network model further allows us to establish some significant optimality properties. We prove that the system performance is monotonic with respect to (w.r.t.) the transmission rate. We also prove that the threshold-type policy is optimal, i.e., when the number of packets in the buffer is larger than a threshold, transmit with the maximal rate (power); otherwise, no transmission. With these optimality properties, we develop a heuristic algorithm to iteratively find the optimal threshold. Finally, we conduct some simulation experiments to demonstrate the main idea of this paper.

A Jackson network model and threshold policy for joint optimization of energy and delay in multi-hop wireless networks

KAUST Repository

Xia, Li

2014-11-20

This paper studies the joint optimization problem of energy and delay in a multi-hop wireless network. The optimization variables are the transmission rates, which are adjustable according to the packet queueing length in the buffer. The optimization goal is to minimize the energy consumption of energy-critical nodes and the packet transmission delay throughout the network. In this paper, we aim at understanding the well-known decentralized algorithms which are threshold based from a different research angle. By using a simplified network model, we show that we can adopt the semi-open Jackson network model and study this optimization problem in closed form. This simplified network model further allows us to establish some significant optimality properties. We prove that the system performance is monotonic with respect to (w.r.t.) the transmission rate. We also prove that the threshold-type policy is optimal, i.e., when the number of packets in the buffer is larger than a threshold, transmit with the maximal rate (power); otherwise, no transmission. With these optimality properties, we develop a heuristic algorithm to iteratively find the optimal threshold. Finally, we conduct some simulation experiments to demonstrate the main idea of this paper.

QoS and energy aware cooperative routing protocol for wildfire monitoring wireless sensor networks.

Science.gov (United States)

Maalej, Mohamed; Cherif, Sofiane; Besbes, Hichem

2013-01-01

Wireless sensor networks (WSN) are presented as proper solution for wildfire monitoring. However, this application requires a design of WSN taking into account the network lifetime and the shadowing effect generated by the trees in the forest environment. Cooperative communication is a promising solution for WSN which uses, at each hop, the resources of multiple nodes to transmit its data. Thus, by sharing resources between nodes, the transmission quality is enhanced. In this paper, we use the technique of reinforcement learning by opponent modeling, optimizing a cooperative communication protocol based on RSSI and node energy consumption in a competitive context (RSSI/energy-CC), that is, an energy and quality-of-service aware-based cooperative communication routing protocol. Simulation results show that the proposed algorithm performs well in terms of network lifetime, packet delay, and energy consumption.

Research on robust optimization of emergency logistics network considering the time dependence characteristic

Science.gov (United States)

WANG, Qingrong; ZHU, Changfeng; LI, Ying; ZHANG, Zhengkun

2017-06-01

Considering the time dependence of emergency logistic network and complexity of the environment that the network exists in, in this paper the time dependent network optimization theory and robust discrete optimization theory are combined, and the emergency logistics dynamic network optimization model with characteristics of robustness is built to maximize the timeliness of emergency logistics. On this basis, considering the complexity of dynamic network and the time dependence of edge weight, an improved ant colony algorithm is proposed to realize the coupling of the optimization algorithm and the network time dependence and robustness. Finally, a case study has been carried out in order to testify validity of this robustness optimization model and its algorithm, and the value of different regulation factors was analyzed considering the importance of the value of the control factor in solving the optimal path. Analysis results show that this model and its algorithm above-mentioned have good timeliness and strong robustness.

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.

On Optimal Policies for Network-Coded Cooperation

DEFF Research Database (Denmark)

Khamfroush, Hana; Roetter, Daniel Enrique Lucani; Pahlevani, Peyman

2015-01-01

Network-coded cooperative communication (NC-CC) has been proposed and evaluated as a powerful technology that can provide a better quality of service in the next-generation wireless systems, e.g., D2D communications. Previous contributions have focused on performance evaluation of NC-CC scenarios...... rather than searching for optimal policies that can minimize the total cost of reliable packet transmission. We break from this trend by initially analyzing the optimal design of NC-CC for a wireless network with one source, two receivers, and half-duplex erasure channels. The problem is modeled...... as a special case of Markov decision process (MDP), which is called stochastic shortest path (SSP), and is solved for any field size, arbitrary number of packets, and arbitrary erasure probabilities of the channels. The proposed MDP solution results in an optimal transmission policy per time slot, and we use...

Localization of multilayer networks by optimized single-layer rewiring.

Science.gov (United States)

Jalan, Sarika; Pradhan, Priodyuti

2018-04-01

We study localization properties of principal eigenvectors (PEVs) of multilayer networks (MNs). Starting with a multilayer network corresponding to a delocalized PEV, we rewire the network edges using an optimization technique such that the PEV of the rewired multilayer network becomes more localized. The framework allows us to scrutinize structural and spectral properties of the networks at various localization points during the rewiring process. We show that rewiring only one layer is enough to attain a MN having a highly localized PEV. Our investigation reveals that a single edge rewiring of the optimized MN can lead to the complete delocalization of a highly localized PEV. This sensitivity in the localization behavior of PEVs is accompanied with the second largest eigenvalue lying very close to the largest one. This observation opens an avenue to gain a deeper insight into the origin of PEV localization of networks. Furthermore, analysis of multilayer networks constructed using real-world social and biological data shows that the localization properties of these real-world multilayer networks are in good agreement with the simulation results for the model multilayer network. This paper is relevant to applications that require understanding propagation of perturbation in multilayer networks.

Multi-Objective Design Of Optimal Greenhouse Gas Observation Networks

Science.gov (United States)

Lucas, D. D.; Bergmann, D. J.; Cameron-Smith, P. J.; Gard, E.; Guilderson, T. P.; Rotman, D.; Stolaroff, J. K.

2010-12-01

One of the primary scientific functions of a Greenhouse Gas Information System (GHGIS) is to infer GHG source emission rates and their uncertainties by combining measurements from an observational network with atmospheric transport modeling. Certain features of the observational networks that serve as inputs to a GHGIS --for example, sampling location and frequency-- can greatly impact the accuracy of the retrieved GHG emissions. Observation System Simulation Experiments (OSSEs) provide a framework to characterize emission uncertainties associated with a given network configuration. By minimizing these uncertainties, OSSEs can be used to determine optimal sampling strategies. Designing a real-world GHGIS observing network, however, will involve multiple, conflicting objectives; there will be trade-offs between sampling density, coverage and measurement costs. To address these issues, we have added multi-objective optimization capabilities to OSSEs. We demonstrate these capabilities by quantifying the trade-offs between retrieval error and measurement costs for a prototype GHGIS, and deriving GHG observing networks that are Pareto optimal. [LLNL-ABS-452333: This work performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

Intercomparisons in the radiation monitoring network of the Czech Republic

Energy Technology Data Exchange (ETDEWEB)

Tuckova, S; Malatova, I [National Radiation Protection Inst., Prague (Czech Republic); Drabova, D [State Office for Nuclear Safety, Prague (Czech Republic)

1996-12-31

In Czech Republic, altogether 11 laboratories, equipped by semiconductor gamma spectrometry supply regularly to the Centre of Radiation Monitoring Network the measured data about the radionuclide activity concentration in different environmental samples, participating thus in monitoring of radiation situation in the country. The Center of Radiation Monitoring Network of Czech Republic periodically organizes through its reference laboratories interlaboratory comparison tests ensuring thus quality of the measurements within the radiation monitoring network. A ring intercomparison test was organized in 1994. The piece of steel rather highly contaminated by {sup 60}Co was used. In the intercomparison test 1994-1995 of pulverized concrete breeze-block containing fly ash with natural radionuclides were used. Results of this measurement is given as an example (authors).

Monitoring of composite structures using a network of integrated PVDF film transducers

International Nuclear Information System (INIS)

Guzmán, Enrique; Cugnoni, Joël; Gmür, Thomas

2015-01-01

Aiming to reduce costs, polyvinylidene difluoride (PVDF) film patches are an emerging alternative to more classic piezoelectric technologies, like ceramic patches, as transducers to measure local deformation in many structural applications. This choice is supported by advantages such as the low weight and mechanical flexibility of PVDF, making this polymer suitable for embedding inside full scale polymer based composite structures. Piezoelectric transducer patches can be used as actuators to dynamically excite full-scale composite structures, and as sensors to measure the strain. The main objective of this paper is to verify that the PVDF transducers can provide exploitable signals in the context of structural health monitoring. In order to do so, two aspects of the design of transducer network are investigated: the optimization of the sensor network, for which the effective independence method is proposed, and the use of operational modal analysis (OMA), since it is a simple method to extract the natural frequencies of a structure from a time series. The results of the analysis are compared to a reference set issued from experimental modal analysis (EMA), a simple, well-known, classic method, which is carried out using accelerometers and an impact hammer. By statistical means, it is shown that there is no significant difference between the two methods, and an optimized PVDF transducer network combined with OMA can perform the dynamic analysis of a structure as well as a classic EMA setup would do. This leads the way to the use of low-cost PVDF embedded transducer networks for robust composite material characterization. (paper)

Quality management status of national radiation environmental monitoring network and strategy for development

International Nuclear Information System (INIS)

Huang Renjie; Zhang Rongsuo; Ni Shiying; Shen Gang

2009-01-01

During the period of 10th five-year plan, MEP has constructed a national radiation environmental monitoring network. In the running of the network, quality management on monitoring data is of vital importance. So all the members of the radiation environmental monitoring network are required to ensure the quality of monitoring method, equipment, reagent,quality of personnel, data processing and information management and so on. Thus the monitoring result would be typical and accuracy in science. The article introduced in detail the quality management status of the National Radiation Environmental Monitoring Network and put forward the strategy for development from the institutionalized and large-scale point of view of radioactive environmental monitoring work. (authors)

A network security situation prediction model based on wavelet neural network with optimized parameters

Directory of Open Access Journals (Sweden)

Haibo Zhang

2016-08-01

Full Text Available The security incidents ion networks are sudden and uncertain, it is very hard to precisely predict the network security situation by traditional methods. In order to improve the prediction accuracy of the network security situation, we build a network security situation prediction model based on Wavelet Neural Network (WNN with optimized parameters by the Improved Niche Genetic Algorithm (INGA. The proposed model adopts WNN which has strong nonlinear ability and fault-tolerance performance. Also, the parameters for WNN are optimized through the adaptive genetic algorithm (GA so that WNN searches more effectively. Considering the problem that the adaptive GA converges slowly and easily turns to the premature problem, we introduce a novel niche technology with a dynamic fuzzy clustering and elimination mechanism to solve the premature convergence of the GA. Our final simulation results show that the proposed INGA-WNN prediction model is more reliable and effective, and it achieves faster convergence-speed and higher prediction accuracy than the Genetic Algorithm-Wavelet Neural Network (GA-WNN, Genetic Algorithm-Back Propagation Neural Network (GA-BPNN and WNN.

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

Monitoring long-term ecological changes through the Ecological Monitoring and Assessment Network: science-based and policy relevant.

Science.gov (United States)

Vaughan, H; Brydges, T; Fenech, A; Lumb, A

2001-01-01

Ecological monitoring and its associated research programs have often provided answers to various environmental management issues. In the face of changing environmental conditions, ecological monitoring provides decision-makers with reliable information as they grapple with maintaining a sustainable economy and healthy environment. The Ecological Monitoring and Assessment Network (EMAN) is a national ecological monitoring network consisting of (1) about 100 case study sites across the country characterized by long-term multi-disciplinary environmental work conducted by a multitude of agencies (142 partners and counting); (2) a variety of less comprehensive yet more extensive monitoring sites; (3) a network where core monitoring variables of ecosystem change are measured; and (4) geo-referenced environmental observations. Environment Canada is the co-ordinating partner for the network through the EMAN Co-ordinating Office. EMAN's mission is to focus a scientifically-sound, policy-relevant ecosystem monitoring and research network based on (a) stabilizing a network of case-study sites operated by a variety of partners, and (b) developing a number of cooperative dispersed monitoring initiatives in order to deliver unique and needed goods and services. These goods and services include: (1) an efficient and cost-effective early warning system which detects, describes and reports on changes in Canadian ecosystems at a national or ecozone scale; and (2) cross-disciplinary and cross-jurisdictional assessments of ecosystem status, trends and processes. The early warning system and assessments of ecosystem status, trends and processes provide Environment Canada and partner organizations with timely information that facilitates increasingly adaptive policies and priority setting. Canadians are also informed of changes and trends occurring in Canadian ecosystems and, as a result, are better able to make decisions related to conservation and sustainability.

Statistical process control using optimized neural networks: a case study.

Science.gov (United States)

Addeh, Jalil; Ebrahimzadeh, Ata; Azarbad, Milad; Ranaee, Vahid

2014-09-01

The most common statistical process control (SPC) tools employed for monitoring process changes are control charts. A control chart demonstrates that the process has altered by generating an out-of-control signal. This study investigates the design of an accurate system for the control chart patterns (CCPs) recognition in two aspects. First, an efficient system is introduced that includes two main modules: feature extraction module and classifier module. In the feature extraction module, a proper set of shape features and statistical feature are proposed as the efficient characteristics of the patterns. In the classifier module, several neural networks, such as multilayer perceptron, probabilistic neural network and radial basis function are investigated. Based on an experimental study, the best classifier is chosen in order to recognize the CCPs. Second, a hybrid heuristic recognition system is introduced based on cuckoo optimization algorithm (COA) algorithm to improve the generalization performance of the classifier. The simulation results show that the proposed algorithm has high recognition accuracy. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

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...

Optimization of controllability and robustness of complex networks by edge directionality

Science.gov (United States)

Liang, Man; Jin, Suoqin; Wang, Dingjie; Zou, Xiufen

2016-09-01

Recently, controllability of complex networks has attracted enormous attention in various fields of science and engineering. How to optimize structural controllability has also become a significant issue. Previous studies have shown that an appropriate directional assignment can improve structural controllability; however, the evolution of the structural controllability of complex networks under attacks and cascading has always been ignored. To address this problem, this study proposes a new edge orientation method (NEOM) based on residual degree that changes the link direction while conserving topology and directionality. By comparing the results with those of previous methods in two random graph models and several realistic networks, our proposed approach is demonstrated to be an effective and competitive method for improving the structural controllability of complex networks. Moreover, numerical simulations show that our method is near-optimal in optimizing structural controllability. Strikingly, compared to the original network, our method maintains the structural controllability of the network under attacks and cascading, indicating that the NEOM can also enhance the robustness of controllability of networks. These results alter the view of the nature of controllability in complex networks, change the understanding of structural controllability and affect the design of network models to control such networks.

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

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...

Initial Results of a New Mobile Spectrum Occupancy Monitoring Network

NARCIS (Netherlands)

van Bloem, J.W.H.; Schiphorst, Roelof; Slump, Cornelis H.

2010-01-01

In this paper we present results of the new monitoring network for spectrum governance. The network is based on the RFeye system of CRFS where the data is collected employing mobile monitoring vehicles. The measurement data, obtained from a frequency sweep between 10 MHz and 6 GHz, is further

A probabilistic computational framework for bridge network optimal maintenance scheduling

International Nuclear Information System (INIS)

Bocchini, Paolo; Frangopol, Dan M.

2011-01-01

This paper presents a probabilistic computational framework for the Pareto optimization of the preventive maintenance applications to bridges of a highway transportation network. The bridge characteristics are represented by their uncertain reliability index profiles. The in/out of service states of the bridges are simulated taking into account their correlation structure. Multi-objective Genetic Algorithms have been chosen as numerical tool for the solution of the optimization problem. The design variables of the optimization are the preventive maintenance schedules of all the bridges of the network. The two conflicting objectives are the minimization of the total present maintenance cost and the maximization of the network performance indicator. The final result is the Pareto front of optimal solutions among which the managers should chose, depending on engineering and economical factors. A numerical example illustrates the application of the proposed approach.

A two-layer recurrent neural network for nonsmooth convex optimization problems.

Science.gov (United States)

Qin, Sitian; Xue, Xiaoping

2015-06-01

In this paper, a two-layer recurrent neural network is proposed to solve the nonsmooth convex optimization problem subject to convex inequality and linear equality constraints. Compared with existing neural network models, the proposed neural network has a low model complexity and avoids penalty parameters. It is proved that from any initial point, the state of the proposed neural network reaches the equality feasible region in finite time and stays there thereafter. Moreover, the state is unique if the initial point lies in the equality feasible region. The equilibrium point set of the proposed neural network is proved to be equivalent to the Karush-Kuhn-Tucker optimality set of the original optimization problem. It is further proved that the equilibrium point of the proposed neural network is stable in the sense of Lyapunov. Moreover, from any initial point, the state is proved to be convergent to an equilibrium point of the proposed neural network. Finally, as applications, the proposed neural network is used to solve nonlinear convex programming with linear constraints and L1 -norm minimization problems.

The central monitoring station of Indian Environmental Radiation Monitoring Network (IERMON): the architecture and functions

International Nuclear Information System (INIS)

Garg, Saurabh; Ratheesh, M.P.; Mukundan, T.; Patel, M.D.; Nair, C.K.G.; Puranik, V.D.

2010-01-01

The Indian Environmental Radiation Monitoring Network (IERMON) is being established across the country by the Bhabha Atomic Research Centre, Mumbai. The network consists of stations with automated systems for environmental radiation monitoring with online data communication facility. Currently about 100 stations are operational and additional 500 stations are expected to be installed by March, 2012. The network is established with different objectives, the main objective being the detection and reporting of any nuclear emergency anywhere in the country. The central monitoring station of the network is established in Mumbai. This paper describes the architecture and functions of IERMON Central Station. The Central Station consists of server room for online data collection from remote stations and maintenance of databases for various applications; central monitoring room for user interaction with database and IERMON website maintenance and development room for the development of new applications. The functions of IERMON Central Station include detection and reporting of nuclear emergency, maintenance of remote stations, enhancement of public awareness on environmental radiation through public display systems and website, etc. The details on system layout and data protocols can be found in the paper. (author)

An Embedded Wireless Sensor Network with Wireless Power Transmission Capability for the Structural Health Monitoring of Reinforced Concrete Structures.

Science.gov (United States)

Gallucci, Luca; Menna, Costantino; Angrisani, Leopoldo; Asprone, Domenico; Moriello, Rosario Schiano Lo; Bonavolontà, Francesco; Fabbrocino, Francesco

2017-11-07

Maintenance strategies based on structural health monitoring can provide effective support in the optimization of scheduled repair of existing structures, thus enabling their lifetime to be extended. With specific regard to reinforced concrete (RC) structures, the state of the art seems to still be lacking an efficient and cost-effective technique capable of monitoring material properties continuously over the lifetime of a structure. Current solutions can typically only measure the required mechanical variables in an indirect, but economic, manner, or directly, but expensively. Moreover, most of the proposed solutions can only be implemented by means of manual activation, making the monitoring very inefficient and then poorly supported. This paper proposes a structural health monitoring system based on a wireless sensor network (WSN) that enables the automatic monitoring of a complete structure. The network includes wireless distributed sensors embedded in the structure itself, and follows the monitoring-based maintenance (MBM) approach, with its ABCDE paradigm, namely: accuracy, benefit, compactness, durability, and easiness of operations. The system is structured in a node level and has a network architecture that enables all the node data to converge in a central unit. Human control is completely unnecessary until the periodic evaluation of the collected data. Several tests are conducted in order to characterize the system from a metrological point of view and assess its performance and effectiveness in real RC conditions.

An Embedded Wireless Sensor Network with Wireless Power Transmission Capability for the Structural Health Monitoring of Reinforced Concrete Structures

Directory of Open Access Journals (Sweden)

Luca Gallucci

2017-11-01

Full Text Available Maintenance strategies based on structural health monitoring can provide effective support in the optimization of scheduled repair of existing structures, thus enabling their lifetime to be extended. With specific regard to reinforced concrete (RC structures, the state of the art seems to still be lacking an efficient and cost-effective technique capable of monitoring material properties continuously over the lifetime of a structure. Current solutions can typically only measure the required mechanical variables in an indirect, but economic, manner, or directly, but expensively. Moreover, most of the proposed solutions can only be implemented by means of manual activation, making the monitoring very inefficient and then poorly supported. This paper proposes a structural health monitoring system based on a wireless sensor network (WSN that enables the automatic monitoring of a complete structure. The network includes wireless distributed sensors embedded in the structure itself, and follows the monitoring-based maintenance (MBM approach, with its ABCDE paradigm, namely: accuracy, benefit, compactness, durability, and easiness of operations. The system is structured in a node level and has a network architecture that enables all the node data to converge in a central unit. Human control is completely unnecessary until the periodic evaluation of the collected data. Several tests are conducted in order to characterize the system from a metrological point of view and assess its performance and effectiveness in real RC conditions.

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.  

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.

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......, a generic model to represent the processing steps, and appropriate optimization tools. A special software interface has been created to automate the steps in the methodology workflow, allow the transfer of data between tools and obtain the mathematical representation of the problem as required...

Sewer Networks Optimization by Particle Swarm Optimization with Abilities of Fly-Back Mechanism and Harmony Memory

Directory of Open Access Journals (Sweden)

محسن نفیسی

2014-10-01

Full Text Available Lack of an efficient sewer network in urban areas threatens public health and may give rise to contagious diseases. Various optimization methods have been developed for use in designing sewers networks in response to a number of requirements such as the high costs of constructing sewer networks, financial limitations, the presence of both discrete and continuous decision variables, and the nonlinear time complexity of such design problems. In this study, the particle swarm optimization algorithm (PSO with the capability of “fly-back” mechanism equipped with the harmony search (HPSO is used for the optimization of sewers network designs. The objective function consists of minimizing the excavation and embedding costs of commercial pipes. The fly-back mechanism and the harmony memory method are used to prevent leaving out variables from the feasible space of the problem in an attempt to enhance model efficiency. Model constraints are satisfied at two levels, which leads to the desirable convergence of the PSO algorithm as compared to the conventional penalty methods in alternative evolutionary algorithms. In order to determine the admissible decision variables, the Manning equation is used as a hydraulic model. The performance of the proposed algorithm is shown by presenting two examples of sewer networks. Compared to the PSO algorithm used in sewer network optimization models, the proposed model exhibits a tangible improvement in cost reduction and a higher computational stability.

Performance improvement of optical CDMA networks with stochastic artificial bee colony optimization technique

Science.gov (United States)

Panda, Satyasen

2018-05-01

This paper proposes a modified artificial bee colony optimization (ABC) algorithm based on levy flight swarm intelligence referred as artificial bee colony levy flight stochastic walk (ABC-LFSW) optimization for optical code division multiple access (OCDMA) network. The ABC-LFSW algorithm is used to solve asset assignment problem based on signal to noise ratio (SNR) optimization in OCDM networks with quality of service constraints. The proposed optimization using ABC-LFSW algorithm provides methods for minimizing various noises and interferences, regulating the transmitted power and optimizing the network design for improving the power efficiency of the optical code path (OCP) from source node to destination node. In this regard, an optical system model is proposed for improving the network performance with optimized input parameters. The detailed discussion and simulation results based on transmitted power allocation and power efficiency of OCPs are included. The experimental results prove the superiority of the proposed network in terms of power efficiency and spectral efficiency in comparison to networks without any power allocation approach.

Quality assurance of gamma spectrometry in monitoring network of CSFR

International Nuclear Information System (INIS)

Malatova, I.; Drabova, D.; Bucina, I.

2004-01-01

On the basis of the Chernobyl experience the Czechoslovak government decided in July 1986 to set up Czechoslovak Monitoring Network and to assign the Centre of Radiation Hygiene of the Institute of Hygiene and Epidemiology to be its headquarters (Centre of Czechoslovak Monitoring Network). The requirements for emergency monitoring are stated in the document The principles of Monitoring for Protection of Public Health in case of a Radiation Accident approved by the Czechoslovak government in April 1987. Assignments of components of the Network, equipment and technical support required, aims of their activities and chronological order of their activation are stated in the document Requirements on Monitoring, Setting up and Equipment of the Czechoslovak Monitoring Network drawn up by the Centre and approved by the Czechoslovak Governmental Commission for Coordination of the Measures in Case of a Radiation Accident in April 1988. It should be noted, however, that basic principles of environmental monitoring aimed at obtaining the complete information of radiation situation, discharges and releases of radionuclides both during the normal operation and in case of an accident were worked on since putting the first PWR-type NPP in Czechoslovakia into operation in 1979. In March 1986 the Instruction for emergency monitoring was approved by the commission. The existence of this instruction and corresponding professional, technical and organizational preparedness of organizations departments responsible for monitoring manifested its positive impact especially in the situation after the Chernobyl accident. This fact refers especially to institutions of hygienic service and nuclear power engineering. National and international experience gained after the Chernobyl accident led to some elaboration in the organization of monitoring and to more precise definition of its conception

Environmental monitoring network for India

Science.gov (United States)

P.V. Sundareshwar; R. Murtugudde; G. Srinivasan; S. Singh; K.J. Ramesh; R. Ramesh; S.B. Verma; D. Agarwal; D. Baldocchi; C.K. Baru; K.K. Baruah; G.R. Chowdhury; V.K. Dadhwal; C.B.S. Dutt; J. Fuentes; Prabhat Gupta; W.W. Hardgrove; M. Howard; C.S. Jha; S. Lal; W.K. Michener; A.P. Mitra; J.T. Morris; R.R. Myneni; M. Naja; R. Nemani; R. Purvaja; S. Raha; S.K. Santhana Vanan; M. Sharma; A. Subramaniam; R. Sukumar; R.R. Twilley; P.R. Zimmerman

2007-01-01

Understanding the consequences of global environmental change and its mitigation will require an integrated global effort of comprehensive long-term data collection, synthesis, and action (1). The last decade has seen a dramatic global increase in the number of networked monitoring sites. For example, FLUXNET is a global collection of >300 micrometeorological...

Evaluation of water resources monitoring networks: study applied to surface waters in the Macaé River Basin

Directory of Open Access Journals (Sweden)

Carolina Cloris Lopes Benassuly

2012-04-01

Full Text Available Knowledge of hydrological phenomena is required in water resources monitoring, in order to structure the water management, focusing on ensuring its multiple uses while allowing that resource´s control and conservation. The effectiveness of monitoring depends on adequate information systems design and proper operation conditions. Data acquisition, treatment and analysis are vital for establishing management strategies, thus monitoring systems and networks shall be conceived according to their main objectives, and be optimized in terms of location of data stations. The generated data shall also model hydrological behavior of the studied basin, so that data interpolation can be applied to the whole basin. The present work aimed to join concepts and methods that guide the structuring of hydrologic monitoring networks of surface waters. For evaluating historical series characteristics as well as work stations redundancy, the entropy method was used. The Macaé River Basin’s importance is related to the public and industrial uses of water in the region that is responsible for more than 80% of Brazilian oil and gas production, what justifies the relevance of the research made. This study concluded that despite of its relatively short extension, the Macaé River Basin should have higher monitoring network density, in order to provide more reliable management data. It also depicted the high relevancy of stations located in its upper course.

Optimization of municipal pressure pumping station layout and sewage pipe network design

Science.gov (United States)

Tian, Jiandong; Cheng, Jilin; Gong, Yi

2018-03-01

Accelerated urbanization places extraordinary demands on sewer networks; thus optimization research to improve the design of these systems has practical significance. In this article, a subsystem nonlinear programming model is developed to optimize pumping station layout and sewage pipe network design. The subsystem model is expanded into a large-scale complex nonlinear programming system model to find the minimum total annual cost of the pumping station and network of all pipe segments. A comparative analysis is conducted using the sewage network in Taizhou City, China, as an example. The proposed method demonstrated that significant cost savings could have been realized if the studied system had been optimized using the techniques described in this article. Therefore, the method has practical value for optimizing urban sewage projects and provides a reference for theoretical research on optimization of urban drainage pumping station layouts.

Study on network traffic forecast model of SVR optimized by GAFSA

International Nuclear Information System (INIS)

Liu, Yuan; Wang, RuiXue

2016-01-01

There are some problems, such as low precision, on existing network traffic forecast model. In accordance with these problems, this paper proposed the network traffic forecast model of support vector regression (SVR) algorithm optimized by global artificial fish swarm algorithm (GAFSA). GAFSA constitutes an improvement of artificial fish swarm algorithm, which is a swarm intelligence optimization algorithm with a significant effect of optimization. The optimum training parameters used for SVR could be calculated by optimizing chosen parameters, which would make the forecast more accurate. With the optimum training parameters searched by GAFSA algorithm, a model of network traffic forecast, which greatly solved problems of great errors in SVR improved by others intelligent algorithms, could be built with the forecast result approaching stability and the increased forecast precision. The simulation shows that, compared with other models (e.g. GA-SVR, CPSO-SVR), the forecast results of GAFSA-SVR network traffic forecast model is more stable with the precision improved to more than 89%, which plays an important role on instructing network control behavior and analyzing security situation.

Feed Forward Neural Network and Optimal Control Problem with Control and State Constraints

Science.gov (United States)

Kmet', Tibor; Kmet'ová, Mária

2009-09-01

A feed forward neural network based optimal control synthesis is presented for solving optimal control problems with control and state constraints. The paper extends adaptive critic neural network architecture proposed by [5] to the optimal control problems with control and state constraints. The optimal control problem is transcribed into a nonlinear programming problem which is implemented with adaptive critic neural network. The proposed simulation method is illustrated by the optimal control problem of nitrogen transformation cycle model. Results show that adaptive critic based systematic approach holds promise for obtaining the optimal control with control and state constraints.

Autonomous smart sensor network for full-scale structural health monitoring

Science.gov (United States)

Rice, Jennifer A.; Mechitov, Kirill A.; Spencer, B. F., Jr.; Agha, Gul A.

2010-04-01

The demands of aging infrastructure require effective methods for structural monitoring and maintenance. Wireless smart sensor networks offer the ability to enhance structural health monitoring (SHM) practices through the utilization of onboard computation to achieve distributed data management. Such an approach is scalable to the large number of sensor nodes required for high-fidelity modal analysis and damage detection. While smart sensor technology is not new, the number of full-scale SHM applications has been limited. This slow progress is due, in part, to the complex network management issues that arise when moving from a laboratory setting to a full-scale monitoring implementation. This paper presents flexible network management software that enables continuous and autonomous operation of wireless smart sensor networks for full-scale SHM applications. The software components combine sleep/wake cycling for enhanced power management with threshold detection for triggering network wide tasks, such as synchronized sensing or decentralized modal analysis, during periods of critical structural response.

Wireless Sensor Network Based Subsurface Contaminant Plume Monitoring

Science.gov (United States)

2012-04-16

Sensor Network (WSN) to monitor contaminant plume movement in naturally heterogeneous subsurface formations to advance the sensor networking based...time to assess the source and predict future plume behavior. This proof-of-concept research aimed at demonstrating the use of an intelligent Wireless

Optimizing the Energy and Throughput of a Water-Quality Monitoring System.

Science.gov (United States)

Olatinwo, Segun O; Joubert, Trudi-H

2018-04-13

This work presents a new approach to the maximization of energy and throughput in a wireless sensor network (WSN), with the intention of applying the approach to water-quality monitoring. Water-quality monitoring using WSN technology has become an interesting research area. Energy scarcity is a critical issue that plagues the widespread deployment of WSN systems. Different power supplies, harvesting energy from sustainable sources, have been explored. However, when energy-efficient models are not put in place, energy harvesting based WSN systems may experience an unstable energy supply, resulting in an interruption in communication, and low system throughput. To alleviate these problems, this paper presents the joint maximization of the energy harvested by sensor nodes and their information-transmission rate using a sum-throughput technique. A wireless information and power transfer (WIPT) method is considered by harvesting energy from dedicated radio frequency sources. Due to the doubly near-far condition that confronts WIPT systems, a new WIPT system is proposed to improve the fairness of resource utilization in the network. Numerical simulation results are presented to validate the mathematical formulations for the optimization problem, which maximize the energy harvested and the overall throughput rate. Defining the performance metrics of achievable throughput and fairness in resource sharing, the proposed WIPT system outperforms an existing state-of-the-art WIPT system, with the comparison based on numerical simulations of both systems. The improved energy efficiency of the proposed WIPT system contributes to addressing the problem of energy scarcity.

Complex fluid network optimization and control integrative design based on nonlinear dynamic model

International Nuclear Information System (INIS)

Sui, Jinxue; Yang, Li; Hu, Yunan

2016-01-01

In view of distribution according to complex fluid network’s needs, this paper proposed one optimization computation method of the nonlinear programming mathematical model based on genetic algorithm. The simulation result shows that the overall energy consumption of the optimized fluid network has a decrease obviously. The control model of the fluid network is established based on nonlinear dynamics. We design the control law based on feedback linearization, take the optimal value by genetic algorithm as the simulation data, can also solve the branch resistance under the optimal value. These resistances can provide technical support and reference for fluid network design and construction, so can realize complex fluid network optimization and control integration design.

Radiation monitoring network in Poland

International Nuclear Information System (INIS)

Grabowski, D.; Kurowski, W.; Muszynski, W.; Rubel, B.; Smagala, G.; Swietochowska, J.

2001-01-01

In Poland the radioactive contamination of the environment and food has been controlled since the early sixties by the Service for Measurements of Radioactive Contamination (SPSP). The service comprises a network of measuring stations and the Centre of Radioactive Contamination Measurements (COPSP). Actually, there are 100 measurement stations. The main task of such station is systematic measurement of radioactivity level in samples of environment components and food. Nine stations of SPSP acting within meteorological stations, ten stations of low level air radioactivity measurements (Aerosols Sampling Stations-500) and eleven permanent monitoring stations (PMS) form the radiation monitoring warning system in Poland. (author)

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.

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.

A one-layer recurrent neural network for constrained nonsmooth invex optimization.

Science.gov (United States)

Li, Guocheng; Yan, Zheng; Wang, Jun

2014-02-01

Invexity is an important notion in nonconvex optimization. In this paper, a one-layer recurrent neural network is proposed for solving constrained nonsmooth invex optimization problems, designed based on an exact penalty function method. It is proved herein that any state of the proposed neural network is globally convergent to the optimal solution set of constrained invex optimization problems, with a sufficiently large penalty parameter. In addition, any neural state is globally convergent to the unique optimal solution, provided that the objective function and constraint functions are pseudoconvex. Moreover, any neural state is globally convergent to the feasible region in finite time and stays there thereafter. The lower bounds of the penalty parameter and convergence time are also estimated. Two numerical examples are provided to illustrate the performances of the proposed neural network. Copyright © 2013 Elsevier Ltd. All rights reserved.

Ensemble Entropy for Monitoring Network Design

Directory of Open Access Journals (Sweden)

Leonardo Alfonso

2014-03-01

Full Text Available Information-theory provides, among others, conceptual methods to quantify the amount of information contained in single random variables and methods to quantify the amount of information contained and shared among two or more variables. Although these concepts have been successfully applied in hydrology and other fields, the evaluation of these quantities is sensitive to different assumptions in the estimation of probabilities. An example is the histogram bin size used to estimate probabilities to calculate Information Theory quantities via frequency methods. The present research aims at introducing a method to take into consideration the uncertainty coming from these parameters in the evaluation of the North Sea’s water level network. The main idea is that the entropy of a random variable can be represented as a probability distribution of possible values, instead of entropy being a deterministic value. The method consists of solving multiple scenarios of Multi-Objective Optimization Problem in which information content is maximized and redundancy is minimized. Results include probabilistic analysis of the chosen parameters on the resulting family of Pareto fronts, providing additional criteria on the selection of the final set of monitoring points.

Identification of Homogeneous Stations for Quality Monitoring Network of Mashhad Aquifer Based on Nitrate Pollution

Directory of Open Access Journals (Sweden)

Moslem Akbarzadeh

2017-01-01

, we could identify homogenous wells in terms of nitrate pollution index variability based on entropy clustering, which would be an important and effective step in Mashhad aquifer monitoring and evaluation of its quality. Also, in order to evaluate and optimize the monitoring network, it could be emphasized on network optimization necessity and approach selection. Accordingly, less monitoring network clusters lead more homogeneous. Therefore the optimization approach will be justified from increasing to decreasing. In this case the monitoring costs, including drilling, equipment, sampling, maintenance and laboratory analysis, also reduce.

Risk-based optimization of pipe inspections in large underground networks with imprecise information

International Nuclear Information System (INIS)

Mancuso, A.; Compare, M.; Salo, A.; Zio, E.; Laakso, T.

2016-01-01

In this paper, we present a novel risk-based methodology for optimizing the inspections of large underground infrastructure networks in the presence of incomplete information about the network features and parameters. The methodology employs Multi Attribute Value Theory to assess the risk of each pipe in the network, whereafter the optimal inspection campaign is built with Portfolio Decision Analysis (PDA). Specifically, Robust Portfolio Modeling (RPM) is employed to identify Pareto-optimal portfolios of pipe inspections. The proposed methodology is illustrated by reporting a real case study on the large-scale maintenance optimization of the sewerage network in Espoo, Finland. - Highlights: • Risk-based approach to optimize pipe inspections on large underground networks. • Reasonable computational effort to select efficient inspection portfolios. • Possibility to accommodate imprecise expert information. • Feasibility of the approach shown by Espoo water system case study.

Optimal network structure to induce the maximal small-world effect

International Nuclear Information System (INIS)

Zhang Zheng-Zhen; Xu Wen-Jun; Lin Jia-Ru; Zeng Shang-You

2014-01-01

In this paper, the general efficiency, which is the average of the global efficiency and the local efficiency, is defined to measure the communication efficiency of a network. The increasing ratio of the general efficiency of a small-world network relative to that of the corresponding regular network is used to measure the small-world effect quantitatively. The more considerable the small-world effect, the higher the general efficiency of a network with a certain cost is. It is shown that the small-world effect increases monotonically with the increase of the vertex number. The optimal rewiring probability to induce the best small-world effect is approximately 0.02 and the optimal average connection probability decreases monotonically with the increase of the vertex number. Therefore, the optimal network structure to induce the maximal small-world effect is the structure with the large vertex number (> 500), the small rewiring probability (≍ 0.02) and the small average connection probability (< 0.1). Many previous research results support our results. (interdisciplinary physics and related areas of science and technology)

NRC TLD Direct Radiation Monitoring Network

International Nuclear Information System (INIS)

Struckmeyer, R.; McNamara, N.

1991-12-01

This report provides the status and results of the NRC Thermoluminescent Dosimeter (TLD) Direct Radiation Monitoring Network. It presents the radiation levels measured in the vicinity of NRC licensed facilities throughout the country for the third quarter of 1991

RECOVERY ACT - Robust Optimization for Connectivity and Flows in Dynamic Complex Networks

Energy Technology Data Exchange (ETDEWEB)

Balasundaram, Balabhaskar [Oklahoma State Univ., Stillwater, OK (United States); Butenko, Sergiy [Texas A & M Univ., College Station, TX (United States); Boginski, Vladimir [Univ. of Florida, Gainesville, FL (United States); Uryasev, Stan [Univ. of Florida, Gainesville, FL (United States)

2013-12-25

The goal of this project was to study robust connectivity and flow patterns of complex multi-scale systems modeled as networks. Networks provide effective ways to study global, system level properties, as well as local, multi-scale interactions at a component level. Numerous applications from power systems, telecommunication, transportation, biology, social science, and other areas have benefited from novel network-based models and their analysis. Modeling and optimization techniques that employ appropriate measures of risk for identifying robust clusters and resilient network designs in networks subject to uncertain failures were investigated in this collaborative multi-university project. In many practical situations one has to deal with uncertainties associated with possible failures of network components, thereby affecting the overall efficiency and performance of the system (e.g., every node/connection has a probability of partial or complete failure). Some extreme examples include power grid component failures, airline hub failures due to weather, or freeway closures due to emergencies. These are also situations in which people, materials, or other resources need to be managed efficiently. Important practical examples include rerouting flow through power grids, adjusting flight plans, and identifying routes for emergency services and supplies, in the event network elements fail unexpectedly. Solutions that are robust under uncertainty, in addition to being economically efficient, are needed. This project has led to the development of novel models and methodologies that can tackle the optimization problems arising in such situations. A number of new concepts, which have not been previously applied in this setting, were investigated in the framework of the project. The results can potentially help decision-makers to better control and identify robust or risk-averse decisions in such situations. Formulations and optimal solutions of the considered problems need

Hybrid Swarm Intelligence Optimization Approach for Optimal Data Storage Position Identification in Wireless Sensor Networks

Science.gov (United States)

Mohanasundaram, Ranganathan; Periasamy, Pappampalayam Sanmugam

2015-01-01

The current high profile debate with regard to data storage and its growth have become strategic task in the world of networking. It mainly depends on the sensor nodes called producers, base stations, and also the consumers (users and sensor nodes) to retrieve and use the data. The main concern dealt here is to find an optimal data storage position in wireless sensor networks. The works that have been carried out earlier did not utilize swarm intelligence based optimization approaches to find the optimal data storage positions. To achieve this goal, an efficient swam intelligence approach is used to choose suitable positions for a storage node. Thus, hybrid particle swarm optimization algorithm has been used to find the suitable positions for storage nodes while the total energy cost of data transmission is minimized. Clustering-based distributed data storage is utilized to solve clustering problem using fuzzy-C-means algorithm. This research work also considers the data rates and locations of multiple producers and consumers to find optimal data storage positions. The algorithm is implemented in a network simulator and the experimental results show that the proposed clustering and swarm intelligence based ODS strategy is more effective than the earlier approaches. PMID:25734182

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...

Radiation monitoring network of the Czech Republic

International Nuclear Information System (INIS)

Drabova, D.; Prouza, Z.; Malatova, I.; Bucina, I.

1996-01-01

Radiation Monitoring Network of the Czech Republic (RMN) was established after the Chernobyl accident. It consists of technical centers, laboratories and monitoring groups of State Office for Nuclear Safety, National Radiation Protection Institute, nuclear power plants, hydrometeorological service, army and Civil Defense, research institutes and other institutions. The structure of RMN, its basic components and responsible institutions are described. (author)

Pareto evolution of gene networks: an algorithm to optimize multiple fitness objectives

International Nuclear Information System (INIS)

Warmflash, Aryeh; Siggia, Eric D; Francois, Paul

2012-01-01

The computational evolution of gene networks functions like a forward genetic screen to generate, without preconceptions, all networks that can be assembled from a defined list of parts to implement a given function. Frequently networks are subject to multiple design criteria that cannot all be optimized simultaneously. To explore how these tradeoffs interact with evolution, we implement Pareto optimization in the context of gene network evolution. In response to a temporal pulse of a signal, we evolve networks whose output turns on slowly after the pulse begins, and shuts down rapidly when the pulse terminates. The best performing networks under our conditions do not fall into categories such as feed forward and negative feedback that also encode the input–output relation we used for selection. Pareto evolution can more efficiently search the space of networks than optimization based on a single ad hoc combination of the design criteria. (paper)

Pareto evolution of gene networks: an algorithm to optimize multiple fitness objectives.

Science.gov (United States)

Warmflash, Aryeh; Francois, Paul; Siggia, Eric D

2012-10-01

The computational evolution of gene networks functions like a forward genetic screen to generate, without preconceptions, all networks that can be assembled from a defined list of parts to implement a given function. Frequently networks are subject to multiple design criteria that cannot all be optimized simultaneously. To explore how these tradeoffs interact with evolution, we implement Pareto optimization in the context of gene network evolution. In response to a temporal pulse of a signal, we evolve networks whose output turns on slowly after the pulse begins, and shuts down rapidly when the pulse terminates. The best performing networks under our conditions do not fall into categories such as feed forward and negative feedback that also encode the input-output relation we used for selection. Pareto evolution can more efficiently search the space of networks than optimization based on a single ad hoc combination of the design criteria.

Self-Configuration and Self-Optimization Process in Heterogeneous Wireless Networks

Directory of Open Access Journals (Sweden)

Eduardo Camponogara

2010-12-01

Full Text Available Self-organization in Wireless Mesh Networks (WMN is an emergent research area, which is becoming important due to the increasing number of nodes in a network. Consequently, the manual configuration of nodes is either impossible or highly costly. So it is desirable for the nodes to be able to configure themselves. In this paper, we propose an alternative architecture for self-organization of WMN based on Optimized Link State Routing Protocol (OLSR and the ad hoc on demand distance vector (AODV routing protocols as well as using the technology of software agents. We argue that the proposed self-optimization and self-configuration modules increase the throughput of network, reduces delay transmission and network load, decreases the traffic of HELLO messages according to network’s scalability. By simulation analysis, we conclude that the self-optimization and self-configuration mechanisms can significantly improve the performance of OLSR and AODV protocols in comparison to the baseline protocols analyzed.

Self-Configuration and Self-Optimization Process in Heterogeneous Wireless Networks

Science.gov (United States)

Guardalben, Lucas; Villalba, Luis Javier García; Buiati, Fábio; Sobral, João Bosco Mangueira; Camponogara, Eduardo

2011-01-01

Self-organization in Wireless Mesh Networks (WMN) is an emergent research area, which is becoming important due to the increasing number of nodes in a network. Consequently, the manual configuration of nodes is either impossible or highly costly. So it is desirable for the nodes to be able to configure themselves. In this paper, we propose an alternative architecture for self-organization of WMN based on Optimized Link State Routing Protocol (OLSR) and the ad hoc on demand distance vector (AODV) routing protocols as well as using the technology of software agents. We argue that the proposed self-optimization and self-configuration modules increase the throughput of network, reduces delay transmission and network load, decreases the traffic of HELLO messages according to network’s scalability. By simulation analysis, we conclude that the self-optimization and self-configuration mechanisms can significantly improve the performance of OLSR and AODV protocols in comparison to the baseline protocols analyzed. PMID:22346584

Application of Neural Network Optimized by Mind Evolutionary Computation in Building Energy Prediction

Science.gov (United States)

Song, Chen; Zhong-Cheng, Wu; Hong, Lv

2018-03-01

Building Energy forecasting plays an important role in energy management and plan. Using mind evolutionary algorithm to find the optimal network weights and threshold, to optimize the BP neural network, can overcome the problem of the BP neural network into a local minimum point. The optimized network is used for time series prediction, and the same month forecast, to get two predictive values. Then two kinds of predictive values are put into neural network, to get the final forecast value. The effectiveness of the method was verified by experiment with the energy value of three buildings in Hefei.

Computation of optimal transport and related hedging problems via penalization and neural networks

OpenAIRE

Eckstein, Stephan; Kupper, Michael

2018-01-01

This paper presents a widely applicable approach to solving (multi-marginal, martingale) optimal transport and related problems via neural networks. The core idea is to penalize the optimization problem in its dual formulation and reduce it to a finite dimensional one which corresponds to optimizing a neural network with smooth objective function. We present numerical examples from optimal transport, martingale optimal transport, portfolio optimization under uncertainty and generative adversa...

Modification of GNPS environment radiation monitoring network system

International Nuclear Information System (INIS)

Jiang Lili; Cao Chunsheng

1999-01-01

GNPS Environment Radiation Continuous Monitoring System (KRS), the only real time on-line system of site radiation monitoring, was put into service in 1993 prior to the first loading the the plant. It is revealed through several years of operation that this system has some deficiencies such as inadequate real time monitoring means, no figure and diagram display function on the central computer, high failures, frequent failure warning signals, thus making the availability of the system at a low level. In recent years, with the rapid development of computer network technology and increasingly strict requirements on the NPP environment protection raised by the government and public, KRS modification had become necessary and urgent. In 1996, GNPS carried out modification work on the measuring geometry condition of γ radiation monitoring sub-station and lightening protection. To enhance the functions of real time monitoring and data auto-processing, further modification of the system was made in 1998, including the update of the software and hardware of KRS central processor, set-up of system computer local network and database. In this way, the system availability and monitoring quality are greatly improved and effective monitoring and analysis means are provided for gaseous release during normal operation and under accident condition

Optimization of investments in gas networks

International Nuclear Information System (INIS)

Andre, J.

2010-09-01

The natural gas networks require very important investments to cope with a still growing demand and to satisfy the new regulatory constraints. The gas market deregulation imposed to the gas network operators, first, transparency rules of a natural monopoly to justify their costs and ultimately their tariffs, and, second, market fluidity objectives in order to facilitate access for competition to the end-users. These major investments are the main reasons for the use of optimization techniques aiming at reducing the costs. Due to the discrete choices (investment location, limited choice of additional capacities, timing) crossed with physical non linear constraints (flow/pressures relations in the pipe or operating ranges of compressors), the programs to solve are Large Mixed Non Linear Programs (MINLP). As these types of programs are known to be hard to solve exactly in polynomial times (NP-hard), advanced optimization methods have to be implemented to obtain realistic results. The objectives of this thesis are threefold. First, one states several investment problems modeling of natural gas networks from industrial world motivations. Second, one identifies the most suitable methods and algorithms to the formulated problems. Third, one exposes the main advantages and drawbacks of these methods with the help of numerical applications on real cases. (author)

AS Migration and Optimization of the Power Integrated Data Network

Science.gov (United States)

Zhou, Junjie; Ke, Yue

2018-03-01

In the transformation process of data integration network, the impact on the business has always been the most important reference factor to measure the quality of network transformation. With the importance of the data network carrying business, we must put forward specific design proposals during the transformation, and conduct a large number of demonstration and practice to ensure that the transformation program meets the requirements of the enterprise data network. This paper mainly demonstrates the scheme of over-migrating point-to-point access equipment in the reconstruction project of power data comprehensive network to migrate the BGP autonomous domain to the specified domain defined in the industrial standard, and to smooth the intranet OSPF protocol Migration into ISIS agreement. Through the optimization design, eventually making electric power data network performance was improved on traffic forwarding, traffic forwarding path optimized, extensibility, get larger, lower risk of potential loop, the network stability was improved, and operational cost savings, etc.

A New Mechanism for Network Monitoring and Shielding in Wireless LAN

Directory of Open Access Journals (Sweden)

Jiujun Cheng

2014-01-01

Full Text Available Wireless LAN (WLAN technology is developing rapidly with the help of wireless communication technology and social demand. During the development of WLAN, the security is more and more important, and wireless monitoring and shielding are of prime importance for network security. In this paper, we have explored various security issues of IEEE 802.11 based wireless network and analyzed numerous problems in implementing the wireless monitoring and shielding system. We identify the challenges which monitoring and shielding system needs to be aware of, and then provide a feasible mechanism to avoid those challenges. We implemented an actual wireless LAN monitoring and shielding system on Maemo operating system to monitor wireless network data stream efficiently and solve the security problems of mobile users. More importantly, the system analyzes wireless network protocols efficiently and flexibly, reveals rich information of the IEEE 802.11 protocol such as traffic distribution and different IP connections, and graphically displays later. Moreover, the system running results show that the system has the capability to work stably, and accurately and analyze the wireless protocols efficiently.

Nuclear reactors project optimization based on neural network and genetic algorithm

International Nuclear Information System (INIS)

Pereira, Claudio M.N.A.; Schirru, Roberto; Martinez, Aquilino S.

1997-01-01

This work presents a prototype of a system for nuclear reactor core design optimization based on genetic algorithms and artificial neural networks. A neural network is modeled and trained in order to predict the flux and the neutron multiplication factor values based in the enrichment, network pitch and cladding thickness, with average error less than 2%. The values predicted by the neural network are used by a genetic algorithm in this heuristic search, guided by an objective function that rewards the high flux values and penalizes multiplication factors far from the required value. Associating the quick prediction - that may substitute the reactor physics calculation code - with the global optimization capacity of the genetic algorithm, it was obtained a quick and effective system for nuclear reactor core design optimization. (author). 11 refs., 8 figs., 3 tabs

A One-Layer Recurrent Neural Network for Real-Time Portfolio Optimization With Probability Criterion.

Science.gov (United States)

Liu, Qingshan; Dang, Chuangyin; Huang, Tingwen

2013-02-01

This paper presents a decision-making model described by a recurrent neural network for dynamic portfolio optimization. The portfolio-optimization problem is first converted into a constrained fractional programming problem. Since the objective function in the programming problem is not convex, the traditional optimization techniques are no longer applicable for solving this problem. Fortunately, the objective function in the fractional programming is pseudoconvex on the feasible region. It leads to a one-layer recurrent neural network modeled by means of a discontinuous dynamic system. To ensure the optimal solutions for portfolio optimization, the convergence of the proposed neural network is analyzed and proved. In fact, the neural network guarantees to get the optimal solutions for portfolio-investment advice if some mild conditions are satisfied. A numerical example with simulation results substantiates the effectiveness and illustrates the characteristics of the proposed neural network.

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).

Improved Artificial Fish Algorithm for Parameters Optimization of PID Neural Network

OpenAIRE

Jing Wang; Yourui Huang

2013-01-01

In order to solve problems such as initial weights are difficult to be determined, training results are easy to trap in local minima in optimization process of PID neural network parameters by traditional BP algorithm, this paper proposed a new method based on improved artificial fish algorithm for parameters optimization of PID neural network. This improved artificial fish algorithm uses a composite adaptive artificial fish algorithm based on optimal artificial fish and nearest artificial fi...

Optimal design of cluster-based ad-hoc networks using probabilistic solution discovery

International Nuclear Information System (INIS)

Cook, Jason L.; Ramirez-Marquez, Jose Emmanuel

2009-01-01

The reliability of ad-hoc networks is gaining popularity in two areas: as a topic of academic interest and as a key performance parameter for defense systems employing this type of network. The ad-hoc network is dynamic and scalable and these descriptions are what attract its users. However, these descriptions are also synonymous for undefined and unpredictable when considering the impacts to the reliability of the system. The configuration of an ad-hoc network changes continuously and this fact implies that no single mathematical expression or graphical depiction can describe the system reliability-wise. Previous research has used mobility and stochastic models to address this challenge successfully. In this paper, the authors leverage the stochastic approach and build upon it a probabilistic solution discovery (PSD) algorithm to optimize the topology for a cluster-based mobile ad-hoc wireless network (MAWN). Specifically, the membership of nodes within the back-bone network or networks will be assigned in such as way as to maximize reliability subject to a constraint on cost. The constraint may also be considered as a non-monetary cost, such as weight, volume, power, or the like. When a cost is assigned to each component, a maximum cost threshold is assigned to the network, and the method is run; the result is an optimized allocation of the radios enabling back-bone network(s) to provide the most reliable network possible without exceeding the allowable cost. The method is intended for use directly as part of the architectural design process of a cluster-based MAWN to efficiently determine an optimal or near-optimal design solution. It is capable of optimizing the topology based upon all-terminal reliability (ATR), all-operating terminal reliability (AoTR), or two-terminal reliability (2TR)

OPTIMAL CONFIGURATION OF A COMMAND AND CONTROL NETWORK: BALANCING PERFORMANCE AND RECONFIGURATION CONSTRAINTS

Energy Technology Data Exchange (ETDEWEB)

L. DOWELL

1999-07-01

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.

Optimal Allocation of Generalized Power Sources in Distribution Network Based on Multi-Objective Particle Swarm Optimization Algorithm

Directory of Open Access Journals (Sweden)

Li Ran

2017-01-01

Full Text Available Optimal allocation of generalized power sources in distribution network is researched. A simple index of voltage stability is put forward. Considering the investment and operation benefit, the stability of voltage and the pollution emissions of generalized power sources in distribution network, a multi-objective optimization planning model is established. A multi-objective particle swarm optimization algorithm is proposed to solve the optimal model. In order to improve the global search ability, the strategies of fast non-dominated sorting, elitism and crowding distance are adopted in this algorithm. Finally, tested the model and algorithm by IEEE-33 node system to find the best configuration of GP, the computed result shows that with the generalized power reasonable access to the active distribution network, the investment benefit and the voltage stability of the system is improved, and the proposed algorithm has better global search capability.

A Global Network Alignment Method Using Discrete Particle Swarm Optimization.

Science.gov (United States)

Huang, Jiaxiang; Gong, Maoguo; Ma, Lijia

2016-10-19

Molecular interactions data increase exponentially with the advance of biotechnology. This makes it possible and necessary to comparatively analyse the different data at a network level. Global network alignment is an important network comparison approach to identify conserved subnetworks and get insight into evolutionary relationship across species. Network alignment which is analogous to subgraph isomorphism is known to be an NP-hard problem. In this paper, we introduce a novel heuristic Particle-Swarm-Optimization based Network Aligner (PSONA), which optimizes a weighted global alignment model considering both protein sequence similarity and interaction conservations. The particle statuses and status updating rules are redefined in a discrete form by using permutation. A seed-and-extend strategy is employed to guide the searching for the superior alignment. The proposed initialization method "seeds" matches with high sequence similarity into the alignment, which guarantees the functional coherence of the mapping nodes. A greedy local search method is designed as the "extension" procedure to iteratively optimize the edge conservations. PSONA is compared with several state-of-art methods on ten network pairs combined by five species. The experimental results demonstrate that the proposed aligner can map the proteins with high functional coherence and can be used as a booster to effectively refine the well-studied aligners.

COMBINED AND STORM SEWER NETWORK MONITORING

OpenAIRE

Justyna Synowiecka; Ewa Burszta-Adamiak; Tomasz Konieczny; Paweł Malinowski

2014-01-01

Monitoring of the drainage networks is an extremely important tool used to understand the phenomena occurring in them. In an era of urbanization and increased run-off, at the expense of natural retention in the catchment, it helps to minimize the risk of local flooding and pollution. In its scope includes measurement of the amount of rainfall, with the use of rain gauges, and their measure in the sewer network, in matter of flows and channel filling, with the help of flow meters. An indispens...

A proposal of optimal sampling design using a modularity strategy

Science.gov (United States)

Simone, A.; Giustolisi, O.; Laucelli, D. B.

2016-08-01

In real water distribution networks (WDNs) are present thousands nodes and optimal placement of pressure and flow observations is a relevant issue for different management tasks. The planning of pressure observations in terms of spatial distribution and number is named sampling design and it was faced considering model calibration. Nowadays, the design of system monitoring is a relevant issue for water utilities e.g., in order to manage background leakages, to detect anomalies and bursts, to guarantee service quality, etc. In recent years, the optimal location of flow observations related to design of optimal district metering areas (DMAs) and leakage management purposes has been faced considering optimal network segmentation and the modularity index using a multiobjective strategy. Optimal network segmentation is the basis to identify network modules by means of optimal conceptual cuts, which are the candidate locations of closed gates or flow meters creating the DMAs. Starting from the WDN-oriented modularity index, as a metric for WDN segmentation, this paper proposes a new way to perform the sampling design, i.e., the optimal location of pressure meters, using newly developed sampling-oriented modularity index. The strategy optimizes the pressure monitoring system mainly based on network topology and weights assigned to pipes according to the specific technical tasks. A multiobjective optimization minimizes the cost of pressure meters while maximizing the sampling-oriented modularity index. The methodology is presented and discussed using the Apulian and Exnet networks.

Implementation and Analysis of a Wireless Sensor Network-Based Pet Location Monitoring System for Domestic Scenarios.

Science.gov (United States)

Aguirre, Erik; Lopez-Iturri, Peio; Azpilicueta, Leyre; Astrain, José Javier; Villadangos, Jesús; Santesteban, Daniel; Falcone, Francisco

2016-08-30

The flexibility of new age wireless networks and the variety of sensors to measure a high number of variables, lead to new scenarios where anything can be monitored by small electronic devices, thereby implementing Wireless Sensor Networks (WSN). Thanks to ZigBee, RFID or WiFi networks the precise location of humans or animals as well as some biological parameters can be known in real-time. However, since wireless sensors must be attached to biological tissues and they are highly dispersive, propagation of electromagnetic waves must be studied to deploy an efficient and well-working network. The main goal of this work is to study the influence of wireless channel limitations in the operation of a specific pet monitoring system, validated at physical channel as well as at functional level. In this sense, radio wave propagation produced by ZigBee devices operating at the ISM 2.4 GHz band is studied through an in-house developed 3D Ray Launching simulation tool, in order to analyze coverage/capacity relations for the optimal system selection as well as deployment strategy in terms of number of transceivers and location. Furthermore, a simplified dog model is developed for simulation code, considering not only its morphology but also its dielectric properties. Relevant wireless channel information such as power distribution, power delay profile and delay spread graphs are obtained providing an extensive wireless channel analysis. A functional dog monitoring system is presented, operating over the implemented ZigBee network and providing real time information to Android based devices. The proposed system can be scaled in order to consider different types of domestic pets as well as new user based functionalities.

Implementation and Analysis of a Wireless Sensor Network-Based Pet Location Monitoring System for Domestic Scenarios

Directory of Open Access Journals (Sweden)

Erik Aguirre

2016-08-01

Full Text Available The flexibility of new age wireless networks and the variety of sensors to measure a high number of variables, lead to new scenarios where anything can be monitored by small electronic devices, thereby implementing Wireless Sensor Networks (WSN. Thanks to ZigBee, RFID or WiFi networks the precise location of humans or animals as well as some biological parameters can be known in real-time. However, since wireless sensors must be attached to biological tissues and they are highly dispersive, propagation of electromagnetic waves must be studied to deploy an efficient and well-working network. The main goal of this work is to study the influence of wireless channel limitations in the operation of a specific pet monitoring system, validated at physical channel as well as at functional level. In this sense, radio wave propagation produced by ZigBee devices operating at the ISM 2.4 GHz band is studied through an in-house developed 3D Ray Launching simulation tool, in order to analyze coverage/capacity relations for the optimal system selection as well as deployment strategy in terms of number of transceivers and location. Furthermore, a simplified dog model is developed for simulation code, considering not only its morphology but also its dielectric properties. Relevant wireless channel information such as power distribution, power delay profile and delay spread graphs are obtained providing an extensive wireless channel analysis. A functional dog monitoring system is presented, operating over the implemented ZigBee network and providing real time information to Android based devices. The proposed system can be scaled in order to consider different types of domestic pets as well as new user based functionalities.

Realization of Intelligent Household Appliance Wireless Monitoring Network Based on LEACH Protocol

Directory of Open Access Journals (Sweden)

Weilong ZHOU

2014-06-01

Full Text Available The intelligent household appliance wireless monitoring network can real-time monitor the apparent power and power factor of various household appliances in different indoor regions, and can realize the real-time monitoring on the household appliance working status and performance. The household appliance wireless monitoring network based on LEACH protocol is designed in the paper. Firstly, the basic idea of LEACH routing algorithm is proposed. Aiming at the node-distribution feature of intelligent home, the selection of cluster head in the routing algorithm and the data transmission method at the stable communication phase is modified. Moreover, the hardware circuit of power acquisition and power factor measurement is designed. The realization of wireless monitoring network based on CC2530 is described, each module and the whole system were conducted the on-line debugging. Finally, the system is proved to meet the practical requirement through the networking test.

Near-Optimal Resource Allocation in Cooperative Cellular Networks Using Genetic Algorithms

OpenAIRE

Luo, Zihan; Armour, Simon; McGeehan, Joe

2015-01-01

This paper shows how a genetic algorithm can be used as a method of obtaining the near-optimal solution of the resource block scheduling problem in a cooperative cellular network. An exhaustive search is initially implementedto guarantee that the optimal result, in terms of maximizing the bandwidth efficiency of the overall network, is found, and then the genetic algorithm with the properly selected termination conditions is used in the same network. The simulation results show that the genet...

Data-Driven Handover Optimization in Next Generation Mobile Communication Networks

Directory of Open Access Journals (Sweden)

Po-Chiang Lin

2016-01-01

Full Text Available Network densification is regarded as one of the important ingredients to increase capacity for next generation mobile communication networks. However, it also leads to mobility problems since users are more likely to hand over to another cell in dense or even ultradense mobile communication networks. Therefore, supporting seamless and robust connectivity through such networks becomes a very important issue. In this paper, we investigate handover (HO optimization in next generation mobile communication networks. We propose a data-driven handover optimization (DHO approach, which aims to mitigate mobility problems including too-late HO, too-early HO, HO to wrong cell, ping-pong HO, and unnecessary HO. The key performance indicator (KPI is defined as the weighted average of the ratios of these mobility problems. The DHO approach collects data from the mobile communication measurement results and provides a model to estimate the relationship between the KPI and features from the collected dataset. Based on the model, the handover parameters, including the handover margin and time-to-trigger, are optimized to minimize the KPI. Simulation results show that the proposed DHO approach could effectively mitigate mobility problems.

Optimal scheduling for distribution network with redox flow battery storage

International Nuclear Information System (INIS)

Hosseina, Majid; Bathaee, Seyed Mohammad Taghi

2016-01-01

Highlights: • A novel method for optimal scheduling of storages in radial network is presented. • Peak shaving and load leveling are the main objectives. • Vanadium redox flow battery is considered as the energy storage unit. • Real data is used for simulation. - Abstract: There are many advantages to utilize storages in electric power system. Peak shaving, load leveling, load frequency control, integration of renewable, energy trading and spinning reserve are the most important of them. Batteries, especially redox flow batteries, are one of the appropriate storages for utilization in distribution network. This paper presents a novel, heuristic and practical method for optimal scheduling in distribution network with flow battery storage. This heuristic method is more suitable for scheduling and operation of distribution networks which require installation of storages. Peak shaving and load leveling is considered as the main objective in this paper. Several indices are presented in this paper for determine the place of storages and also scheduling for optimal use of energy in them. Simulations of this paper are based on real information of distribution network substation that located in Semnan, Iran.

A One-Layer Recurrent Neural Network for Pseudoconvex Optimization Problems With Equality and Inequality Constraints.

Science.gov (United States)

Qin, Sitian; Yang, Xiudong; Xue, Xiaoping; Song, Jiahui

2017-10-01

Pseudoconvex optimization problem, as an important nonconvex optimization problem, plays an important role in scientific and engineering applications. In this paper, a recurrent one-layer neural network is proposed for solving the pseudoconvex optimization problem with equality and inequality constraints. It is proved that from any initial state, the state of the proposed neural network reaches the feasible region in finite time and stays there thereafter. It is also proved that the state of the proposed neural network is convergent to an optimal solution of the related problem. Compared with the related existing recurrent neural networks for the pseudoconvex optimization problems, the proposed neural network in this paper does not need the penalty parameters and has a better convergence. Meanwhile, the proposed neural network is used to solve three nonsmooth optimization problems, and we make some detailed comparisons with the known related conclusions. In the end, some numerical examples are provided to illustrate the effectiveness of the performance of the proposed neural network.

Optimization of in-vivo monitoring program for radiation emergency response

Energy Technology Data Exchange (ETDEWEB)

Ha, Wi Ho; Kim, Jong Kyung [Dept. of Nuclear Engineering, Hanyang University, Seoul (Korea, Republic of)

2016-12-15

In case of radiation emergencies, internal exposure monitoring for the members of public will be required to confirm internal contamination of each individual. In-vivo monitoring technique using portable gamma spectrometer can be easily applied for internal exposure monitoring in the vicinity of the on-site area. In this study, minimum detectable doses (MDDs) for '1'3'4Cs, {sup 137}Cs, and {sup 131}I were calculated adjusting minimum detectable activities (MDAs) from 50 to 1,000 Bq to find out the optimal in-vivo counting condition. DCAL software was used to derive retention fraction of Cs and I isotopes in the whole body and thyroid, respectively. A minimum detectable level was determined to set committed effective dose of 0.1 mSv for emergency response. We found that MDDs at each MDA increased along with the elapsed time. 1,000 Bq for {sup 134}Cs and {sup 137}Cs, and 100 Bq for {sup 131}I were suggested as optimal MDAs to provide in-vivo monitoring service in case of radiation emergencies. In-vivo monitoring program for emergency response should be designed to achieve the optimal MDA suggested from the present work. We expect that a reduction of counting time compared with routine monitoring program can achieve the high throughput system in case of radiation emergencies.

A mathematical model for optimization of an integrated network logistic design

Directory of Open Access Journals (Sweden)

Lida Tafaghodi

2011-10-01

Full Text Available In this study, the integrated forward/reverse logistics network is investigated, and a capacitated multi-stage, multi-product logistics network design is proposed by formulating a generalized logistics network problem into a mixed-integer nonlinear programming model (MINLP for minimizing the total cost of the closed-loop supply chain network. Moreover, the proposed model is solved by using optimization solver, which provides the decisions related to the facility location problem, optimum quantity of shipped product, and facility capacity. Numerical results show the power of the proposed MINLP model to avoid th sub-optimality caused by separate design of forward and reverse logistics networks and to handle various transportation modes and periodic demand.

Nuclear power plant monitoring using real-time learning neural network

International Nuclear Information System (INIS)

Nabeshima, Kunihiko; Tuerkcan, E.; Ciftcioglu, O.

1994-01-01

In the present research, artificial neural network (ANN) with real-time adaptive learning is developed for the plant wide monitoring of Borssele Nuclear Power Plant (NPP). Adaptive ANN learning capability is integrated to the monitoring system so that robust and sensitive on-line monitoring is achieved in real-time environment. The major advantages provided by ANN are that system modelling is formed by means of measurement information obtained from a multi-output process system, explicit modelling is not required and the modelling is not restricted to linear systems. Also ANN can respond very fast to anomalous operational conditions. The real-time ANN learning methodology with adaptive real-time monitoring capability is described below for the wide-range and plant-wide data from an operating nuclear power plant. The layered neural network with error backpropagation algorithm for learning has three layers. The network type is auto-associative, inputs and outputs are exactly the same, using 12 plant signals. (author)