WorldWideScience

Sample records for network traffic estimation

  1. Estimating Traffic and Anomaly Maps via Network Tomography

    OpenAIRE

    Mardani, Morteza; Giannakis, Georgios B.

    2014-01-01

    Mapping origin-destination (OD) network traffic is pivotal for network management and proactive security tasks. However, lack of sufficient flow-level measurements as well as potential anomalies pose major challenges towards this goal. Leveraging the spatiotemporal correlation of nominal traffic, and the sparse nature of anomalies, this paper brings forth a novel framework to map out nominal and anomalous traffic, which treats jointly important network monitoring tasks including traffic estim...

  2. Traffic volume estimation using network interpolation techniques.

    Science.gov (United States)

    2013-12-01

    Kriging method is a frequently used interpolation methodology in geography, which enables estimations of unknown values at : certain places with the considerations of distances among locations. When it is used in transportation field, network distanc...

  3. A Deep Generative Adversarial Architecture for Network-Wide Spatial-Temporal Traffic State Estimation

    OpenAIRE

    Liang, Yunyi; Cui, Zhiyong; Tian, Yu; Chen, Huimiao; Wang, Yinhai

    2018-01-01

    This study proposes a deep generative adversarial architecture (GAA) for network-wide spatial-temporal traffic state estimation. The GAA is able to combine traffic flow theory with neural networks and thus improve the accuracy of traffic state estimation. It consists of two Long Short-Term Memory Neural Networks (LSTM NNs) which capture correlation in time and space among traffic flow and traffic density. One of the LSTM NNs, called a discriminative network, aims to maximize the probability o...

  4. Networked traffic state estimation involving mixed fixed-mobile sensor data using Hamilton-Jacobi equations

    KAUST Repository

    Canepa, Edward S.

    2017-06-19

    Nowadays, traffic management has become a challenge for urban areas, which are covering larger geographic spaces and facing the generation of different kinds of traffic data. This article presents a robust traffic estimation framework for highways modeled by a system of Lighthill Whitham Richards equations that is able to assimilate different sensor data available. We first present an equivalent formulation of the problem using a Hamilton–Jacobi equation. Then, using a semi-analytic formula, we show that the model constraints resulting from the Hamilton–Jacobi equation are linear ones. We then pose the problem of estimating the traffic density given incomplete and inaccurate traffic data as a Mixed Integer Program. We then extend the density estimation framework to highway networks with any available data constraint and modeling junctions. Finally, we present a travel estimation application for a small network using real traffic measurements obtained obtained during Mobile Century traffic experiment, and comparing the results with ground truth data.

  5. Estimating Urban Traffic Patterns through Probabilistic Interconnectivity of Road Network Junctions.

    Directory of Open Access Journals (Sweden)

    Ed Manley

    Full Text Available The emergence of large, fine-grained mobility datasets offers significant opportunities for the development and application of new methodologies for transportation analysis. In this paper, the link between routing behaviour and traffic patterns in urban areas is examined, introducing a method to derive estimates of traffic patterns from a large collection of fine-grained routing data. Using this dataset, the interconnectivity between road network junctions is extracted in the form of a Markov chain. This representation encodes the probability of the successive usage of adjacent road junctions, encoding routes as flows between decision points rather than flows along road segments. This network of functional interactions is then integrated within a modified Markov chain Monte Carlo (MCMC framework, adapted for the estimation of urban traffic patterns. As part of this approach, the data-derived links between major junctions influence the movement of directed random walks executed across the network to model origin-destination journeys. The simulation process yields estimates of traffic distribution across the road network. The paper presents an implementation of the modified MCMC approach for London, United Kingdom, building an MCMC model based on a dataset of nearly 700000 minicab routes. Validation of the approach clarifies how each element of the MCMC framework contributes to junction prediction performance, and finds promising results in relation to the estimation of junction choice and minicab traffic distribution. The paper concludes by summarising the potential for the development and extension of this approach to the wider urban modelling domain.

  6. Estimation and Control of Networked Distributed Parameter Systems: Application to Traffic Flow

    KAUST Repository

    Canepa, Edward

    2016-11-01

    The management of large-scale transportation infrastructure is becoming a very complex task for the urban areas of this century which are covering bigger geographic spaces and facing the inclusion of connected and self-controlled vehicles. This new system paradigm can leverage many forms of sensing and interaction, including a high-scale mobile sensing approach. To obtain a high penetration sensing system on urban areas more practical and scalable platforms are needed, combined with estimation algorithms suitable to the computational capabilities of these platforms. The purpose of this work was to develop a transportation framework that is able to handle different kinds of sensing data (e.g., connected vehicles, loop detectors) and optimize the traffic state on a defined traffic network. The framework estimates the traffic on road networks modeled by a family of Lighthill-Whitham-Richards equations. Based on an equivalent formulation of the problem using a Hamilton-Jacobi equation and using a semi-analytic formula, I will show that the model constraints resulting from the Hamilton-Jacobi equation are linear, albeit with unknown integer variables. This general framework solve exactly a variety of problems arising in transportation networks: traffic estimation, traffic control (including robust control), cybersecurity and sensor fault detection, or privacy analysis of users in probe-based traffic monitoring systems. This framework is very flexible, fast, and yields exact results. The recent advances in sensors (GPS, inertial measurement units) and microprocessors enable the development low-cost dedicated devices for traffic sensing in cities, 5 which are highly scalable, providing a feasible solution to cover large urban areas. However, one of the main problems to address is the privacy of the users of the transportation system, the framework presented here is a viable option to guarantee the privacy of the users by design.

  7. A study of Time-varying Cost Parameter Estimation Methods in Traffic Networks for Mobile Robots

    OpenAIRE

    Das, Pragna; Xirgo, Lluís Ribas

    2015-01-01

    Industrial robust controlling systems built using automated guided vehicles (AGVs) requires planning which depends on cost parameters like time and energy of the mobile robots functioning in the system. This work addresses the problem of on-line traversal time identification and estimation for proper mobility of mobile robots on systems' traffic networks. Several filtering and estimation methods have been investigated with respect to proper identification of traversal time of arcs of systems'...

  8. Classification and Analysis of Computer Network Traffic

    DEFF Research Database (Denmark)

    Bujlow, Tomasz

    2014-01-01

    for traffic classification, which can be used for nearly real-time processing of big amounts of data using affordable CPU and memory resources. Other questions are related to methods for real-time estimation of the application Quality of Service (QoS) level based on the results obtained by the traffic......Traffic monitoring and analysis can be done for multiple different reasons: to investigate the usage of network resources, assess the performance of network applications, adjust Quality of Service (QoS) policies in the network, log the traffic to comply with the law, or create realistic models...... classifier. This thesis is focused on topics connected with traffic classification and analysis, while the work on methods for QoS assessment is limited to defining the connections with the traffic classification and proposing a general algorithm. We introduced the already known methods for traffic...

  9. A State-of-the-Art Review of the Sensor Location, Flow Observability, Estimation, and Prediction Problems in Traffic Networks

    Directory of Open Access Journals (Sweden)

    Enrique Castillo

    2015-01-01

    Full Text Available A state-of-the-art review of flow observability, estimation, and prediction problems in traffic networks is performed. Since mathematical optimization provides a general framework for all of them, an integrated approach is used to perform the analysis of these problems and consider them as different optimization problems whose data, variables, constraints, and objective functions are the main elements that characterize the problems proposed by different authors. For example, counted, scanned or “a priori” data are the most common data sources; conservation laws, flow nonnegativity, link capacity, flow definition, observation, flow propagation, and specific model requirements form the most common constraints; and least squares, likelihood, possible relative error, mean absolute relative error, and so forth constitute the bases for the objective functions or metrics. The high number of possible combinations of these elements justifies the existence of a wide collection of methods for analyzing static and dynamic situations.

  10. Estimating Emissions from Railway Traffic

    DEFF Research Database (Denmark)

    Jørgensen, Morten W.; Sorenson, Spencer C.

    1998-01-01

    Several parameters of importance for estimating emissions from railway traffic are discussed, and typical results presented. Typical emissions factors from diesel engines and electrical power generation are presented, and the effect of differences in national electrical generation sources...

  11. Estimating emissions from railway traffic

    Energy Technology Data Exchange (ETDEWEB)

    Joergensen, M.W.; Sorenson, C.

    1997-07-01

    The report discusses methods that can be used to estimate the emissions from various kinds of railway traffic. The methods are based on the estimation of the energy consumption of the train, so that comparisons can be made between electric and diesel driven trains. Typical values are given for the necessary traffic parameters, emission factors, and train loading. Detailed models for train energy consumption are presented, as well as empirically based methods using average train speed and distance between stop. (au)

  12. A sensor network architecture for urban traffic state estimation with mixed eulerian/lagrangian sensing based on distributed computing

    KAUST Repository

    Canepa, Edward S.

    2014-01-01

    This article describes a new approach to urban traffic flow sensing using decentralized traffic state estimation. Traffic sensor data is generated both by fixed traffic flow sensor nodes and by probe vehicles equipped with a short range transceiver. The data generated by these sensors is sent to a local coordinator node, that poses the problem of estimating the local state of traffic as a mixed integer linear program (MILP). The resulting optimization program is then solved by the nodes in a distributed manner, using branch-and-bound methods. An optimal amount of noise is then added to the maps before dissemination to a central database. Unlike existing probe-based traffic monitoring systems, this system does not transmit user generated location tracks nor any user presence information to a centralized server, effectively preventing privacy attacks. A simulation of the system performance on computer-generated traffic data shows that the system can be implemented with currently available technology. © 2014 Springer International Publishing Switzerland.

  13. Evaluation of traffic pollution on Moscow network

    Energy Technology Data Exchange (ETDEWEB)

    Lukanin, V.N.; Buslaev, A.P.; Yashina, M. [Moscow State Automobile and Road Technical University, MADI-TU, Mscow (Russian Federation)

    2000-07-01

    The Moscow vehicle fleet grows each year and traffic is a major source of air pollutants in Moscow. We have developed a model for air quality evaluation and management in a megalopolis in order to improve ecological parameters of vehicles. We have received estimations of traffic influence on human health. These analytical methods allow to regulate traffic flows on road network and structure of car fleet in order to minimise damage to the environment in large cities. Simulation methods are tested on traffic data of Moscow City. The purpose of the research is development of principles, modelling and experimental methods of air quality management in a large city in order to improve ecological parameters of vehicles, to regulate traffic flows on road network and structure of car fleet. (authors)

  14. Traffic measurement for big network data

    CERN Document Server

    Chen, Shigang; Xiao, Qingjun

    2017-01-01

    This book presents several compact and fast methods for online traffic measurement of big network data. It describes challenges of online traffic measurement, discusses the state of the field, and provides an overview of the potential solutions to major problems. The authors introduce the problem of per-flow size measurement for big network data and present a fast and scalable counter architecture, called Counter Tree, which leverages a two-dimensional counter sharing scheme to achieve far better memory efficiency and significantly extend estimation range. Unlike traditional approaches to cardinality estimation problems that allocate a separated data structure (called estimator) for each flow, this book takes a different design path by viewing all the flows together as a whole: each flow is allocated with a virtual estimator, and these virtual estimators share a common memory space. A framework of virtual estimators is designed to apply the idea of sharing to an array of cardinality estimation solutions, achi...

  15. Fluctuations in Urban Traffic Networks

    Science.gov (United States)

    Chen, Yu-Dong; Li, Li; Zhang, Yi; Hu, Jian-Ming; Jin, Xue-Xiang

    Urban traffic network is a typical complex system, in which movements of tremendous microscopic traffic participants (pedestrians, bicyclists and vehicles) form complicated spatial and temporal dynamics. We collected flow volumes data on the time-dependent activity of a typical urban traffic network, finding that the coupling between the average flux and the fluctuation on individual links obeys a certain scaling law, with a wide variety of scaling exponents between 1/2 and 1. These scaling phenomena can explain the interaction between the nodes' internal dynamics (i.e. queuing at intersections, car-following in driving) and changes in the external (network-wide) traffic demand (i.e. the every day increase of traffic amount during peak hours and shocking caused by traffic accidents), allowing us to further understand the mechanisms governing the transportation system's collective behavior. Multiscaling and hotspot features are observed in the traffic flow data as well. But the reason why the separated internal dynamics are comparable to the external dynamics in magnitude is still unclear and needs further investigations.

  16. Modelling traffic congestion using queuing networks

    Indian Academy of Sciences (India)

    Traffic Flow-Density diagrams are obtained using simple Jackson queuing network analysis. Such simple analytical models can be used to capture the effect of non- homogenous traffic. Keywords. Flow-density curves; uninterrupted traffic; Jackson networks. 1. Introduction. Traffic management has become very essential in ...

  17. Characterization and Modeling of Network Traffic

    DEFF Research Database (Denmark)

    Shawky, Ahmed; Bergheim, Hans; Ragnarsson, Olafur

    2011-01-01

    This paper attempts to characterize and model backbone network traffic, using a small number of statistics. In order to reduce cost and processing power associated with traffic analysis. The parameters affecting the behaviour of network traffic are investigated and the choice is that inter......-arrival time, IP addresses, port numbers and transport protocol are the only necessary parameters to model network traffic behaviour. In order to recreate this behaviour, a complex model is needed which is able to recreate traffic behaviour based on a set of statistics calculated from the parameters values....... The model investigates the traffic generation mechanisms, and grouping traffic into flows and applications....

  18. Routing strategies in traffic network and phase transition in network ...

    Indian Academy of Sciences (India)

    Routing strategy; network traffic flow; hysteretic loop; phase transition from free flow state to congestion state; scale-free network; bi-stable state; traffic dynamics. PACS Nos 89.75.Hc; 89.20.Hh; 05.10.-a; 89.75.Fb. 1. Traffic dynamics based on local routing strategy on scale-free networks. Communication networks such as ...

  19. Wireless traffic steering for green cellular networks

    CERN Document Server

    Zhang, Shan; Zhou, Sheng; Niu, Zhisheng; Shen, Xuemin (Sherman)

    2016-01-01

    This book introduces wireless traffic steering as a paradigm to realize green communication in multi-tier heterogeneous cellular networks. By matching network resources and dynamic mobile traffic demand, traffic steering helps to reduce on-grid power consumption with on-demand services provided. This book reviews existing solutions from the perspectives of energy consumption reduction and renewable energy harvesting. Specifically, it explains how traffic steering can improve energy efficiency through intelligent traffic-resource matching. Several promising traffic steering approaches for dynamic network planning and renewable energy demand-supply balancing are discussed. This book presents an energy-aware traffic steering method for networks with energy harvesting, which optimizes the traffic allocated to each cell based on the renewable energy status. Renewable energy demand-supply balancing is a key factor in energy dynamics, aimed at enhancing renewable energy sustainability to reduce on-grid energy consum...

  20. Consensus-Based Cooperative Control Based on Pollution Sensing and Traffic Information for Urban Traffic Networks

    National Research Council Canada - National Science Library

    Antonio Artuñedo; Raúl M del Toro; Rodolfo E Haber

    2017-01-01

    .... The interconnected traffic lights controller (TLC) network adapts traffic lights cycles, based on traffic and air pollution sensory information, in order to improve the performance of urban traffic networks...

  1. Traffic Management for Satellite-ATM Networks

    Science.gov (United States)

    Goyal, Rohit; Jain, Raj; Fahmy, Sonia; Vandalore, Bobby; Goyal, Mukul

    1998-01-01

    Various issues associated with "Traffic Management for Satellite-ATM Networks" are presented in viewgraph form. Specific topics include: 1) Traffic management issues for TCP/IP based data services over satellite-ATM networks; 2) Design issues for TCP/IP over ATM; 3) Optimization of the performance of TCP/IP over ATM for long delay networks; and 4) Evaluation of ATM service categories for TCP/IP traffic.

  2. Traffic incidents analysis on Slovenian motorway network

    OpenAIRE

    Jakše, Bojan

    2013-01-01

    In my bachelor thesis we were analysing traffic incidents (such as accidents, congestions, heavy snow, etc.) on Slovenian road network, specifically we focused on incidents on motorways. We were starting from database of incidents provided by Prometno-informacijski center (Traffic information center) and added information about hourly traffic at the moment of incident. We were also researching possible correlations between weather and traffic congestions and accidents as well as behaviour of ...

  3. Scaling in Computer Network Traffic

    Science.gov (United States)

    2005-01-07

    behaviour, measurement .... 29 The Self-Similar Traffic Model Fractional Gaussian Noise (fGn) and Fractional Brownian Motion (fBm) The unique...AVAILABILITY STATEMENT Approved for public release, distribution unlimited 13. SUPPLEMENTARY NOTES See also ADM001750, Wavelets and Multifractal Analysis... Multifractality Wavelet qth order moments: IE|dX(j, k)|q ∼ C 2αqj, j → 0. Estimating the LHS from data using Sq(j) = 1 nj ∑ k |dX(j, k)|q, and measure the slopes

  4. A Network Traffic Control Enhancement Approach over Bluetooth Networks

    DEFF Research Database (Denmark)

    Son, L.T.; Schiøler, Henrik; Madsen, Ole Brun

    2003-01-01

    This paper analyzes network traffic control issues in Bluetooth data networks as convex optimization problem. We formulate the problem of maximizing of total network flows and minimizing the costs of flows. An adaptive distributed network traffic control scheme is proposed as an approximated...... solution of the stated optimization problem that satisfies quality of service requirements and topologically induced constraints in Bluetooth networks, such as link capacity and node resource limitations. The proposed scheme is decentralized and complies with frequent changes of topology as well...... as capacity limitations and flow requirements in the network. Simulation shows that the performance of Bluetooth networks could be improved by applying the adaptive distributed network traffic control scheme...

  5. ROAD TRAFFIC ESTIMATION USING BLUETOOTH SENSORS

    Directory of Open Access Journals (Sweden)

    Monika N. BUGDOL

    2017-09-01

    Full Text Available The Bluetooth standard is a low-cost, very popular communication protocol offering a wide range of applications in many fields. In this paper, a novel system for road traffic estimation using Bluetooth sensors has been presented. The system consists of three main modules: filtration, statistical analysis of historical, and traffic estimation and prediction. The filtration module is responsible for the classification of road users and detecting measurements that should be removed. Traffic estimation has been performed on the basis of the data collected by Bluetooth measuring devices and information on external conditions (e.g., temperature, all of which have been gathered in the city of Bielsko-Biala (Poland. The obtained results are very promising. The smallest average relative error between the number of cars estimated by the model and the actual traffic was less than 10%.

  6. On traffic modelling in GPRS networks

    DEFF Research Database (Denmark)

    Madsen, Tatiana Kozlova; Schwefel, Hans-Peter; Prasad, Ramjee

    2005-01-01

    Optimal design and dimensioning of wireless data networks, such as GPRS, requires the knowledge of traffic characteristics of different data services. This paper presents an in-detail analysis of an IP-level traffic measurements taken in an operational GPRS network. The data measurements reported...... here are done at the Gi interface. The aim of this paper is to reveal some key statistics of GPRS data applications and to validate if the existing traffic models can adequately describe traffic volume and inter-arrival time distribution for different services. Additionally, we present a method of user...

  7. GSM Network Traffic Analysis | Ani | Nigerian Journal of Technology

    African Journals Online (AJOL)

    GSM networks are traffic intensive specifically the signaling traffic. Evolvement of effective and efficient performance management strategy requires accurate quantification of network signaling traffic volume along side with the user traffic volume. Inaccurate quantification may lead to serious network traffic congestion and ...

  8. Modeling Network Traffic in Wavelet Domain

    Directory of Open Access Journals (Sweden)

    Sheng Ma

    2004-12-01

    Full Text Available This work discovers that although network traffic has the complicated short- and long-range temporal dependence, the corresponding wavelet coefficients are no longer long-range dependent. Therefore, a "short-range" dependent process can be used to model network traffic in the wavelet domain. Both independent and Markov models are investigated. Theoretical analysis shows that the independent wavelet model is sufficiently accurate in terms of the buffer overflow probability for Fractional Gaussian Noise traffic. Any model, which captures additional correlations in the wavelet domain, only improves the performance marginally. The independent wavelet model is then used as a unified approach to model network traffic including VBR MPEG video and Ethernet data. The computational complexity is O(N for developing such wavelet models and generating synthesized traffic of length N, which is among the lowest attained.

  9. System and method for traffic signal timing estimation

    KAUST Repository

    Dumazert, Julien

    2015-12-30

    A method and system for estimating traffic signals. The method and system can include constructing trajectories of probe vehicles from GPS data emitted by the probe vehicles, estimating traffic signal cycles, combining the estimates, and computing the traffic signal timing by maximizing a scoring function based on the estimates. Estimating traffic signal cycles can be based on transition times of the probe vehicles starting after a traffic signal turns green.

  10. Occupant traffic estimation through structural vibration sensing

    Science.gov (United States)

    Pan, Shijia; Mirshekari, Mostafa; Zhang, Pei; Noh, Hae Young

    2016-04-01

    The number of people passing through different indoor areas is useful in various smart structure applications, including occupancy-based building energy/space management, marketing research, security, etc. Existing approaches to estimate occupant traffic include vision-, sound-, and radio-based (mobile) sensing methods, which have placement limitations (e.g., requirement of line-of-sight, quiet environment, carrying a device all the time). Such limitations make these direct sensing approaches difficult to deploy and maintain. An indirect approach using geophones to measure floor vibration induced by footsteps can be utilized. However, the main challenge lies in distinguishing multiple simultaneous walkers by developing features that can effectively represent the number of mixed signals and characterize the selected features under different traffic conditions. This paper presents a method to monitor multiple persons. Once the vibration signals are obtained, features are extracted to describe the overlapping vibration signals induced by multiple footsteps, which are used for occupancy traffic estimation. In particular, we focus on analysis of the efficiency and limitations of the four selected key features when used for estimating various traffic conditions. We characterize these features with signals collected from controlled impulse load tests as well as from multiple people walking through a real-world sensing area. In our experiments, the system achieves the mean estimation error of +/-0.2 people for different occupant traffic conditions (from one to four) using k-nearest neighbor classifier.

  11. Traffic Management for Next Generation Transport Networks

    DEFF Research Database (Denmark)

    Yu, Hao

    their network capacities. However, in order to provide more advanced video services than simply porting the traditional television services to the network, the service provider needs to do more than just augment the network capacity. Advanced traffic management capability is one of the relevant abilities...... slacken the steps of some network operators towards providing IPTV services. In this dissertation, the topology-based hierarchical scheduling scheme is proposed to tackle the problem addressed. The scheme simplifies the deployment process by placing an intelligent switch with centralized traffic...... management functions at the edge of the network, scheduling traffic on behalf of the other nodes. The topology-based hierarchical scheduling scheme is able to provide outstanding flow isolation due to its centralized scheduling ability, which is essential for providing IPTV services. In order to reduce...

  12. Traffic Analysis for Real-Time Communication Networks onboard Ships

    DEFF Research Database (Denmark)

    Schiøler, Henrik; Nielsen, Jens Frederik Dalsgaard; Jørgensen, N.

    1998-01-01

    The paper presents a novel method for establishing worst case estimates of queue lenghts and transmission delays in networks of interconnected segments each of ring topology as defined by the ATOMOS project for marine automation. A non probalistic model for describing traffic is introduced as well...

  13. Traffic Analysis for Real-Time Communication Networks onboard Ships

    DEFF Research Database (Denmark)

    Schiøler, Henrik; Nielsen, Jens Frederik Dalsgaard; Jørgensen, N.

    The paper presents a novel method for establishing worst case estimates of queue lenghts and transmission delays in networks of interconnected segments each of ring topology as defined by the ATOMOS project for marine automation. A non probalistic model for describing traffic is introduced as well...

  14. Detecting Target Data in Network Traffic

    Science.gov (United States)

    2017-03-01

    packets, such as unauthorized connections to services like FTP and SSH connections, as well as RDP and MSSQL. Stateful firewalls are designed to...Hashdb can also be used to analyze network traffic and embedded content in other documents. There are hashdb libraries for the Python and C...amount of data that it logs. Bro will look at to DNS traffic, HTTP requests, and if any other connections attempted to be made over FTP, SSH and other

  15. Neural network system for traffic flow management

    Science.gov (United States)

    Gilmore, John F.; Elibiary, Khalid J.; Petersson, L. E. Rickard

    1992-09-01

    Atlanta will be the home of several special events during the next five years ranging from the 1996 Olympics to the 1994 Super Bowl. When combined with the existing special events (Braves, Falcons, and Hawks games, concerts, festivals, etc.), the need to effectively manage traffic flow from surface streets to interstate highways is apparent. This paper describes a system for traffic event response and management for intelligent navigation utilizing signals (TERMINUS) developed at Georgia Tech for adaptively managing special event traffic flows in the Atlanta, Georgia area. TERMINUS (the original name given Atlanta, Georgia based upon its role as a rail line terminating center) is an intelligent surface street signal control system designed to manage traffic flow in Metro Atlanta. The system consists of three components. The first is a traffic simulation of the downtown Atlanta area around Fulton County Stadium that models the flow of traffic when a stadium event lets out. Parameters for the surrounding area include modeling for events during various times of day (such as rush hour). The second component is a computer graphics interface with the simulation that shows the traffic flows achieved based upon intelligent control system execution. The final component is the intelligent control system that manages surface street light signals based upon feedback from control sensors that dynamically adapt the intelligent controller's decision making process. The intelligent controller is a neural network model that allows TERMINUS to control the configuration of surface street signals to optimize the flow of traffic away from special events.

  16. Network origin-destination demand estimation using limited link traffic counts : strategic deployment of vehicle detectors through an integrated corridor management framework.

    Science.gov (United States)

    2009-10-15

    In typical road traffic corridors, freeway systems are generally well-equipped with traffic surveillance systems such as vehicle detector (VD) and/or closed circuit television (CCTV) systems in order to gather timely traffic information for traffic c...

  17. Competitive Traffic Assignment in Road Networks

    Directory of Open Access Journals (Sweden)

    Krylatov Alexander Y.

    2016-09-01

    Full Text Available Recently in-vehicle route guidance and information systems are rapidly developing. Such systems are expected to reduce congestion in an urban traffic area. This social benefit is believed to be reached by imposing the route choices on the network users that lead to the system optimum traffic assignment. However, guidance service could be offered by different competitive business companies. Then route choices of different mutually independent groups of users may reject traffic assignment from the system optimum state. In this paper, a game theoretic approach is shown to be very efficient to formalize competitive traffic assignment problem with various groups of users in the form of non-cooperative network game with the Nash equilibrium search. The relationships between the Wardrop’s system optimum associated with the traffic assignment problem and the Nash equilibrium associated with the competitive traffic assignment problem are investigated. Moreover, some related aspects of the Nash equilibrium and the Wardrop’s user equilibrium assignments are also discussed.

  18. Spatiotemporal Recurrent Convolutional Networks for Traffic Prediction in Transportation Networks

    Directory of Open Access Journals (Sweden)

    Haiyang Yu

    2017-06-01

    Full Text Available Predicting large-scale transportation network traffic has become an important and challenging topic in recent decades. Inspired by the domain knowledge of motion prediction, in which the future motion of an object can be predicted based on previous scenes, we propose a network grid representation method that can retain the fine-scale structure of a transportation network. Network-wide traffic speeds are converted into a series of static images and input into a novel deep architecture, namely, spatiotemporal recurrent convolutional networks (SRCNs, for traffic forecasting. The proposed SRCNs inherit the advantages of deep convolutional neural networks (DCNNs and long short-term memory (LSTM neural networks. The spatial dependencies of network-wide traffic can be captured by DCNNs, and the temporal dynamics can be learned by LSTMs. An experiment on a Beijing transportation network with 278 links demonstrates that SRCNs outperform other deep learning-based algorithms in both short-term and long-term traffic prediction.

  19. Spatiotemporal Recurrent Convolutional Networks for Traffic Prediction in Transportation Networks

    Science.gov (United States)

    Yu, Haiyang; Wu, Zhihai; Wang, Shuqin; Wang, Yunpeng; Ma, Xiaolei

    2017-01-01

    Predicting large-scale transportation network traffic has become an important and challenging topic in recent decades. Inspired by the domain knowledge of motion prediction, in which the future motion of an object can be predicted based on previous scenes, we propose a network grid representation method that can retain the fine-scale structure of a transportation network. Network-wide traffic speeds are converted into a series of static images and input into a novel deep architecture, namely, spatiotemporal recurrent convolutional networks (SRCNs), for traffic forecasting. The proposed SRCNs inherit the advantages of deep convolutional neural networks (DCNNs) and long short-term memory (LSTM) neural networks. The spatial dependencies of network-wide traffic can be captured by DCNNs, and the temporal dynamics can be learned by LSTMs. An experiment on a Beijing transportation network with 278 links demonstrates that SRCNs outperform other deep learning-based algorithms in both short-term and long-term traffic prediction. PMID:28672867

  20. Determining optimal speed limits in traffic networks

    Directory of Open Access Journals (Sweden)

    Mansour Hadji Hosseinlou

    2015-07-01

    Full Text Available Determining the speed limit of road transport systems has a significant role in the speed management of vehicles. In most cases, setting a speed limit is considered as a trade-off between reducing travel time on one hand and reducing road accidents on the other, and the two factors of vehicle fuel consumption and emission rate of air pollutants have been neglected. This paper aims to evaluate optimal speed limits in traffic networks in a way that economized societal costs are incurred. In this study, experimental and field data as well as data from simulations are used to determine how speed is related to the emission of pollutants, fuel consumption, travel time, and the number of accidents. This paper also proposes a simple model to calculate the societal costs of travel and relate them to speed. As a case study, using emission test results on cars manufactured domestically and by simulating the suburban traffic flow by Aimsun software, the total societal costs of the Shiraz-Marvdasht motorway, which is one of the most traversed routes in Iran, have been estimated. The results of the study show that from a societal perspective, the optimal speed would be 73 km/h, and from a road user perspective, it would be 82 km/h (in 2011, the average speed of the passing vehicles on that motorway was 82 km/h. The experiments in this paper were run on three different vehicles with different types of fuel. In a comparative study, the results show that the calculated speed limit is lower than the optimal speed limits in Sweden, Norway, and Australia.

  1. Analyzing Worms and Network Traffic using Compression

    OpenAIRE

    Wehner, Stephanie

    2005-01-01

    Internet worms have become a widespread threat to system and network operations. In order to fight them more efficiently, it is necessary to analyze newly discovered worms and attack patterns. This paper shows how techniques based on Kolmogorov Complexity can help in the analysis of internet worms and network traffic. Using compression, different species of worms can be clustered by type. This allows us to determine whether an unknown worm binary could in fact be a later version of an existin...

  2. Multimodale trafiknet i GIS (Multimodal Traffic Network in GIS)

    DEFF Research Database (Denmark)

    Kronbak, Jacob; Brems, Camilla Riff

    1996-01-01

    The report introduces the use of multi-modal traffic networks within a geographical Information System (GIS). The necessary theory of modelling multi-modal traffic network is reviewed and applied to the ARC/INFO GIS by an explorative example.......The report introduces the use of multi-modal traffic networks within a geographical Information System (GIS). The necessary theory of modelling multi-modal traffic network is reviewed and applied to the ARC/INFO GIS by an explorative example....

  3. Network traffic anomaly prediction using Artificial Neural Network

    Science.gov (United States)

    Ciptaningtyas, Hening Titi; Fatichah, Chastine; Sabila, Altea

    2017-03-01

    As the excessive increase of internet usage, the malicious software (malware) has also increase significantly. Malware is software developed by hacker for illegal purpose(s), such as stealing data and identity, causing computer damage, or denying service to other user[1]. Malware which attack computer or server often triggers network traffic anomaly phenomena. Based on Sophos's report[2], Indonesia is the riskiest country of malware attack and it also has high network traffic anomaly. This research uses Artificial Neural Network (ANN) to predict network traffic anomaly based on malware attack in Indonesia which is recorded by Id-SIRTII/CC (Indonesia Security Incident Response Team on Internet Infrastructure/Coordination Center). The case study is the highest malware attack (SQL injection) which has happened in three consecutive years: 2012, 2013, and 2014[4]. The data series is preprocessed first, then the network traffic anomaly is predicted using Artificial Neural Network and using two weight update algorithms: Gradient Descent and Momentum. Error of prediction is calculated using Mean Squared Error (MSE) [7]. The experimental result shows that MSE for SQL Injection is 0.03856. So, this approach can be used to predict network traffic anomaly.

  4. Dynamic traffic grooming with multigranularity traffic in WDM optical mesh networks

    Science.gov (United States)

    Huang, Jun; Zeng, Qingji; Liu, Jimin; Xiao, Pengcheng; Liu, Hua; Xiao, Shilin

    2004-04-01

    In this paper, a traffic-grooming problem for multi-granularity traffic of SDH/SONET in WDM grooming mesh networks is investigated. We propose a path select routing algorithm to solve this problem. The performances of this traffic grooming path select routing algorithm are evaluated in WDM grooming networks. Finally, we presented and compared the simulation results of this algorithm in dynamic traffic grooming WDM mesh networks with that of other algorithms.

  5. Broadband Traffic Forecasting in the Transport Network

    Directory of Open Access Journals (Sweden)

    Valentina Radojičić

    2012-07-01

    Full Text Available This paper proposes a modification of traffic forecast model generated by residential and small business (SOHO, Small Office Home Office users. The model includes forecasted values of different relevant factors and competition on broadband market. It allows forecasting the number of users for various broadband technologies and interaction impact of long-standing technologies as well as the impact of the new technology entrant on the market. All the necessary parameters are evaluated for the Serbian broadband market. The long-term forecasted results of broadband traffic are given. The analyses and evaluations performed are important inputs for the transport network resources planning.

  6. Networks and their traffic in multiplayer games

    Directory of Open Access Journals (Sweden)

    Cristian Andrés Melo López

    2016-06-01

    Full Text Available Computer games called multiplayer real-time, or (MCG are at the forefront of the use of the possibilities of the network. Research on this subject have been made for military simulations, virtual reality systems, computer support teamwork, the solutions diverge on the problems posed by MCG. With this in mind, this document provides an overview of the four issues affecting networking at the MCG. First, network resources (bandwidth, latency and computing capacity, together with the technical limits within which the MCG must operate. Second, the distribution concepts include communication architectures (peer-to-peer, client / server, server / network, and data and control architectures (centralized, distributed and reproduced .Thirdly, scalability allows the MCG to adapt to changes in parameterization resources. Finally, security is intended to fend off the traps and vandalism, which are common in online games; to check traffic, particularly these games we decided to take the massively multiplayer game League of Legends, a scene corresponding to a situation of real life in a network of ADSL access network is deployed has been simulated by using NS2 Three variants of TCP, it means SACK TCP, New Reno TCP, and TCP Vegas, have been considered for the cross traffic. The results show that TCP Vegas is able to maintain a constant speed while racing against the game traffic, since it avoids the packet loss and the delays in the tail caused by high peaks, without increasing the size of the sender window. SACK TCP and TCP New Reno, on the other hand, tend to increase continuously the sender window size, which could allow a greater loss of packages and also to cause unwanted delays for the game traffic.

  7. Scheduling Network Traffic for Grid Purposes

    DEFF Research Database (Denmark)

    Gamst, Mette

    This thesis concerns scheduling of network traffic in grid context. Grid computing consists of a number of geographically distributed computers, which work together for solving large problems. The computers are connected through a network. When scheduling job execution in grid computing, data...... transmission has so far not been taken into account. This causes stability problems, because data transmission takes time and thus causes delays to the execution plan. This thesis proposes the integration of job scheduling and network routing. The scientific contribution is based on methods from operations...

  8. Machine learning for identifying botnet network traffic

    DEFF Research Database (Denmark)

    Stevanovic, Matija; Pedersen, Jens Myrup

    2013-01-01

    . Due to promise of non-invasive and resilient detection, botnet detection based on network traffic analysis has drawn a special attention of the research community. Furthermore, many authors have turned their attention to the use of machine learning algorithms as the mean of inferring botnet......-related knowledge from the monitored traffic. This paper presents a review of contemporary botnet detection methods that use machine learning as a tool of identifying botnet-related traffic. The main goal of the paper is to provide a comprehensive overview on the field by summarizing current scientific efforts....... The contribution of the paper is three-fold. First, the paper provides a detailed insight on the existing detection methods by investigating which bot-related heuristic were assumed by the detection systems and how different machine learning techniques were adapted in order to capture botnet-related knowledge...

  9. 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.

  10. Lagrangian Multi-Class Traffic State Estimation

    NARCIS (Netherlands)

    Yuan, Y.

    2013-01-01

    Road traffic is important to everybody in the world. People travel and commute everyday. For those who travel by cars (or other types of road vehicles), traffic congestion is a daily experience. One essential goal of traffic researchers is to reduce traffic congestion and to improve the whole

  11. Network traffic model using GIPP and GIBP

    Science.gov (United States)

    Lee, Yong Duk; Van de Liefvoort, Appie; Wallace, Victor L.

    1998-10-01

    In telecommunication networks, the correlated nature of teletraffic patterns can have significant impact on queuing measures such as queue length, blocking and delay. There is, however, not yet a good general analytical description which can easily incorporate the correlation effect of the traffic, while at the same time maintaining the ease of modeling. The authors have shown elsewhere, that the covariance structures of the generalized Interrupted Poisson Process (GIPP) and the generalized Interrupted Bernoulli Process (GIBP) have an invariance property which makes them reasonably general, yet algebraically manageable, models for representing correlated network traffic. The GIPP and GIBP have a surprisingly rich sets of parameters, yet these invariance properties enable us to easily incorporate the covariance function as well as the interarrival time distribution into the model to better matchobservations. In this paper, we show an application of GIPP and GIBP for matching an analytical model to observed or experimental data.

  12. Traffic State Estimation Using Connected Vehicles and Stationary Detectors

    Directory of Open Access Journals (Sweden)

    Ellen F. Grumert

    2018-01-01

    Full Text Available Real-time traffic state estimation is of importance for efficient traffic management. This is especially the case for traffic management systems that require fast detection of changes in the traffic conditions in order to apply an effective control measure. In this paper, we propose a method for estimating the traffic state and speed and density, by using connected vehicles combined with stationary detectors. The aim is to allow fast and accurate estimation of changes in the traffic conditions. The proposed method does only require information about the speed and the position of connected vehicles and can make use of sparsely located stationary detectors to limit the dependence on the infrastructure equipment. An evaluation of the proposed method is carried out by microscopic traffic simulation. The traffic state estimated using the proposed method is compared to the true simulated traffic state. Further, the density estimates are compared to density estimates from one detector-based method, one combined method, and one connected-vehicle-based method. The results of the study show that the proposed method is a promising alternative for estimating the traffic state in traffic management applications.

  13. Forecasting of Congestion in Traffic Neural Network Modelling Using Duffing Holmes Oscillator

    Science.gov (United States)

    Mrgole, Anamarija L.; Čelan, Marko; Mesarec, Beno

    2017-10-01

    Forecasting of congestion in traffic with Neural Network is an innovative and new process of identification and detection of chaotic features in time series analysis. With the use of Duffing Holmes Oscillator, we estimate the emergence of traffic flow congestion when the traffic load on a specific section of the road and in a specific time period is close to exceeding the capacity of the road infrastructure. The orientated model is validated in six locations with a specific requirement. The paper points out the issue of importance of traffic flow forecasting and simulations for preventing or rerouting possible short term traffic flow congestions.

  14. The effects of redundancy and information manipulation on traffic networks

    OpenAIRE

    Özel, Berk; Ozel, Berk

    2014-01-01

    Traffic congestion is one of the most frequently encountered problems in real life. It is not only a scientific concern of scholars, but also an inevitable issue for most of the individuals living in urban areas. Since every driver in traffic networks tries to minimize own journey length, and volume of the traffic prevents coordination between individuals, a cooperative behavior will not be provided spontaneously in order to decrease the total cost of the network and the time spent on traffic...

  15. Understanding characteristics in multivariate traffic flow time series from complex network structure

    Science.gov (United States)

    Yan, Ying; Zhang, Shen; Tang, Jinjun; Wang, Xiaofei

    2017-07-01

    Discovering dynamic characteristics in traffic flow is the significant step to design effective traffic managing and controlling strategy for relieving traffic congestion in urban cities. A new method based on complex network theory is proposed to study multivariate traffic flow time series. The data were collected from loop detectors on freeway during a year. In order to construct complex network from original traffic flow, a weighted Froenius norm is adopt to estimate similarity between multivariate time series, and Principal Component Analysis is implemented to determine the weights. We discuss how to select optimal critical threshold for networks at different hour in term of cumulative probability distribution of degree. Furthermore, two statistical properties of networks: normalized network structure entropy and cumulative probability of degree, are utilized to explore hourly variation in traffic flow. The results demonstrate these two statistical quantities express similar pattern to traffic flow parameters with morning and evening peak hours. Accordingly, we detect three traffic states: trough, peak and transitional hours, according to the correlation between two aforementioned properties. The classifying results of states can actually represent hourly fluctuation in traffic flow by analyzing annual average hourly values of traffic volume, occupancy and speed in corresponding hours.

  16. Comparative study about social support network among familiar physicians and traffic officers, México

    OpenAIRE

    Aranda B., Carolina; Instituto de Investigación en Salud Ocupacional, Universidad de Guadalajara, México; Torres L., Teresa; Instituto de Investigación en Salud Ocupacional, Universidad de Guadalajara, México; Salazar E., José; Instituto de Investigación en Salud Ocupacional, Universidad de Guadalajara, México; Pando M., Manuel; Instituto de Investigación en Salud Ocupacional, Universidad de Guadalajara, México; Aldrete R., María Guadalupe; Instituto de Investigación en Salud Ocupacional, Universidad de Guadalajara, México

    2014-01-01

    The social support is the process that occurs between people that make up the social network of a subject. Actions such as listening, estimate, assess, and so on, are behaviors that occur among individuals who make up the network. The aim of this study analyze the situation of social support and social support networks on family physicians and traffic agents of a city in Mexico. 197 physicians and 875 traffic agents participated voluntarily with an informed consent. The information was collec...

  17. Routing strategies in traffic network and phase transition in network ...

    Indian Academy of Sciences (India)

    The dynamics of information traffic over scale-free networks has been investigated systematically. A series of routing strategies of data packets have been proposed, including the local routing strategy, the next-nearest-neighbour routing strategy, and the mixed routing strategy based on local static and dynamic information.

  18. Breakdown in traffic networks fundamentals of transportation science

    CERN Document Server

    Kerner, Boris S

    2017-01-01

    This book offers a detailed investigation of breakdowns in traffic and transportation networks. It shows empirically that transitions from free flow to so-called synchronized flow, initiated by local disturbances at network bottlenecks, display a nucleation-type behavior: while small disturbances in free flow decay, larger ones grow further and lead to breakdowns at the bottlenecks. Further, it discusses in detail the significance of this nucleation effect for traffic and transportation theories, and the consequences this has for future automatic driving, traffic control, dynamic traffic assignment, and optimization in traffic and transportation networks. Starting from a large volume of field traffic data collected from various sources obtained solely through measurements in real world traffic, the author develops his insights, with an emphasis less on reviewing existing methodologies, models and theories, and more on providing a detailed analysis of empirical traffic data and drawing consequences regarding t...

  19. Encapsulating Urban Traffic Rhythms into Road Networks

    Science.gov (United States)

    Wang, Junjie; Wei, Dong; He, Kun; Gong, Hang; Wang, Pu

    2014-02-01

    Using road GIS (geographical information systems) data and travel demand data for two U.S. urban areas, the dynamical driver sources of each road segment were located. A method to target road clusters closely related to urban traffic congestion was then developed to improve road network efficiency. The targeted road clusters show different spatial distributions at different times of a day, indicating that our method can encapsulate dynamical travel demand information into the road networks. As a proof of concept, when we lowered the speed limit or increased the capacity of road segments in the targeted road clusters, we found that both the number of congested roads and extra travel time were effectively reduced. In addition, the proposed modeling framework provided new insights on the optimization of transport efficiency in any infrastructure network with a specific supply and demand distribution.

  20. Network Analysis of Urban Traffic with Big Bus Data

    CERN Document Server

    Zhao, Kai

    2016-01-01

    Urban traffic analysis is crucial for traffic forecasting systems, urban planning and, more recently, various mobile and network applications. In this paper, we analyse urban traffic with network and statistical methods. Our analysis is based on one big bus dataset containing 45 million bus arrival samples in Helsinki. We mainly address following questions: 1. How can we identify the areas that cause most of the traffic in the city? 2. Why there is a urban traffic? Is bus traffic a key cause of the urban traffic? 3. How can we improve the urban traffic systems? To answer these questions, first, the betweenness is used to identify the most import areas that cause most traffics. Second, we find that bus traffic is not an important cause of urban traffic using statistical methods. We differentiate the urban traffic and the bus traffic in a city. We use bus delay as an identification of the urban traffic, and the number of bus as an identification of the bus traffic. Third, we give our solutions on how to improve...

  1. EFFECTIVE BANDWIDTH FOR SELF-SIMILAR TRAFFIC IN ATM NETWORK

    Directory of Open Access Journals (Sweden)

    Linawati Linawati

    2009-05-01

    Full Text Available This paper proposes a new approach to estimate the effective bandwidth for self-similar traffic in ATM network. In this approach we use the tail distribution of queue length based on FBM model. This approach is derived from the inequalities for Mills’ ratio. Then a comparison with Norros and Trinh&Miki schemes are analysed. The results demonstrate reasonable agreement between numerical and simulation results and between all schemes. Their bandwidth estimation tends closer for CLP improvement.

  2. Real-time network traffic classification technique for wireless local area networks based on compressed sensing

    Science.gov (United States)

    Balouchestani, Mohammadreza

    2017-05-01

    Network traffic or data traffic in a Wireless Local Area Network (WLAN) is the amount of network packets moving across a wireless network from each wireless node to another wireless node, which provide the load of sampling in a wireless network. WLAN's Network traffic is the main component for network traffic measurement, network traffic control and simulation. Traffic classification technique is an essential tool for improving the Quality of Service (QoS) in different wireless networks in the complex applications such as local area networks, wireless local area networks, wireless personal area networks, wireless metropolitan area networks, and wide area networks. Network traffic classification is also an essential component in the products for QoS control in different wireless network systems and applications. Classifying network traffic in a WLAN allows to see what kinds of traffic we have in each part of the network, organize the various kinds of network traffic in each path into different classes in each path, and generate network traffic matrix in order to Identify and organize network traffic which is an important key for improving the QoS feature. To achieve effective network traffic classification, Real-time Network Traffic Classification (RNTC) algorithm for WLANs based on Compressed Sensing (CS) is presented in this paper. The fundamental goal of this algorithm is to solve difficult wireless network management problems. The proposed architecture allows reducing False Detection Rate (FDR) to 25% and Packet Delay (PD) to 15 %. The proposed architecture is also increased 10 % accuracy of wireless transmission, which provides a good background for establishing high quality wireless local area networks.

  3. Consensus-Based Cooperative Control Based on Pollution Sensing and Traffic Information for Urban Traffic Networks

    Directory of Open Access Journals (Sweden)

    Antonio Artuñedo

    2017-04-01

    Full Text Available Nowadays many studies are being conducted to develop solutions for improving the performance of urban traffic networks. One of the main challenges is the necessary cooperation among different entities such as vehicles or infrastructure systems and how to exploit the information available through networks of sensors deployed as infrastructures for smart cities. In this work an algorithm for cooperative control of urban subsystems is proposed to provide a solution for mobility problems in cities. The interconnected traffic lights controller (TLC network adapts traffic lights cycles, based on traffic and air pollution sensory information, in order to improve the performance of urban traffic networks. The presence of air pollution in cities is not only caused by road traffic but there are other pollution sources that contribute to increase or decrease the pollution level. Due to the distributed and heterogeneous nature of the different components involved, a system of systems engineering approach is applied to design a consensus-based control algorithm. The designed control strategy contains a consensus-based component that uses the information shared in the network for reaching a consensus in the state of TLC network components. Discrete event systems specification is applied for modelling and simulation. The proposed solution is assessed by simulation studies with very promising results to deal with simultaneous responses to both pollution levels and traffic flows in urban traffic networks.

  4. Consensus-Based Cooperative Control Based on Pollution Sensing and Traffic Information for Urban Traffic Networks.

    Science.gov (United States)

    Artuñedo, Antonio; Del Toro, Raúl M; Haber, Rodolfo E

    2017-04-26

    Nowadays many studies are being conducted to develop solutions for improving the performance of urban traffic networks. One of the main challenges is the necessary cooperation among different entities such as vehicles or infrastructure systems and how to exploit the information available through networks of sensors deployed as infrastructures for smart cities. In this work an algorithm for cooperative control of urban subsystems is proposed to provide a solution for mobility problems in cities. The interconnected traffic lights controller (TLC) network adapts traffic lights cycles, based on traffic and air pollution sensory information, in order to improve the performance of urban traffic networks. The presence of air pollution in cities is not only caused by road traffic but there are other pollution sources that contribute to increase or decrease the pollution level. Due to the distributed and heterogeneous nature of the different components involved, a system of systems engineering approach is applied to design a consensus-based control algorithm. The designed control strategy contains a consensus-based component that uses the information shared in the network for reaching a consensus in the state of TLC network components. Discrete event systems specification is applied for modelling and simulation. The proposed solution is assessed by simulation studies with very promising results to deal with simultaneous responses to both pollution levels and traffic flows in urban traffic networks.

  5. Best Practices Handbook: Traffic Engineering in Range Networks

    Science.gov (United States)

    2016-03-01

    accommodate an offered load or if traffic streams are inefficiently mapped onto available resources, causing subsets of network resources to become over...access equipment and video encoding equipment. 3. A response system, consisting of protocols and access mechanisms that allow the flow of traffic ...Multiprotocol Label Switching (MPLS) that enable the predictable traffic flow across the MRTFBs. A detailed description of network elements relevant to the

  6. Small-time Scale Network Traffic Prediction Based on Complex-valued Neural Network

    Science.gov (United States)

    Yang, Bin

    2017-07-01

    Accurate models play an important role in capturing the significant characteristics of the network traffic, analyzing the network dynamic, and improving the forecasting accuracy for system dynamics. In this study, complex-valued neural network (CVNN) model is proposed to further improve the accuracy of small-time scale network traffic forecasting. Artificial bee colony (ABC) algorithm is proposed to optimize the complex-valued and real-valued parameters of CVNN model. Small-scale traffic measurements data namely the TCP traffic data is used to test the performance of CVNN model. Experimental results reveal that CVNN model forecasts the small-time scale network traffic measurement data very accurately

  7. Detecting Distributed Network Traffic Anomaly with Network-Wide Correlation Analysis

    Science.gov (United States)

    Zonglin, Li; Guangmin, Hu; Xingmiao, Yao; Dan, Yang

    2008-12-01

    Distributed network traffic anomaly refers to a traffic abnormal behavior involving many links of a network and caused by the same source (e.g., DDoS attack, worm propagation). The anomaly transiting in a single link might be unnoticeable and hard to detect, while the anomalous aggregation from many links can be prevailing, and does more harm to the networks. Aiming at the similar features of distributed traffic anomaly on many links, this paper proposes a network-wide detection method by performing anomalous correlation analysis of traffic signals' instantaneous parameters. In our method, traffic signals' instantaneous parameters are firstly computed, and their network-wide anomalous space is then extracted via traffic prediction. Finally, an anomaly is detected by a global correlation coefficient of anomalous space. Our evaluation using Abilene traffic traces demonstrates the excellent performance of this approach for distributed traffic anomaly detection.

  8. Detecting Distributed Network Traffic Anomaly with Network-Wide Correlation Analysis

    Directory of Open Access Journals (Sweden)

    Yang Dan

    2008-12-01

    Full Text Available Distributed network traffic anomaly refers to a traffic abnormal behavior involving many links of a network and caused by the same source (e.g., DDoS attack, worm propagation. The anomaly transiting in a single link might be unnoticeable and hard to detect, while the anomalous aggregation from many links can be prevailing, and does more harm to the networks. Aiming at the similar features of distributed traffic anomaly on many links, this paper proposes a network-wide detection method by performing anomalous correlation analysis of traffic signals' instantaneous parameters. In our method, traffic signals' instantaneous parameters are firstly computed, and their network-wide anomalous space is then extracted via traffic prediction. Finally, an anomaly is detected by a global correlation coefficient of anomalous space. Our evaluation using Abilene traffic traces demonstrates the excellent performance of this approach for distributed traffic anomaly detection.

  9. GIS Tools to Estimate Average Annual Daily Traffic

    Science.gov (United States)

    2012-06-01

    This project presents five tools that were created for a geographical information system to estimate Annual Average Daily : Traffic using linear regression. Three of the tools can be used to prepare spatial data for linear regression. One tool can be...

  10. An analysis of network traffic classification for botnet detection

    DEFF Research Database (Denmark)

    Stevanovic, Matija; Pedersen, Jens Myrup

    2015-01-01

    Botnets represent one of the most serious threats to the Internet security today. This paper explores how can network traffic classification be used for accurate and efficient identification of botnet network activity at local and enterprise networks. The paper examines the effectiveness of detec......Botnets represent one of the most serious threats to the Internet security today. This paper explores how can network traffic classification be used for accurate and efficient identification of botnet network activity at local and enterprise networks. The paper examines the effectiveness...

  11. Wavelength converter placement in optical networks with dynamic traffic

    DEFF Research Database (Denmark)

    Buron, Jakob Due; Ruepp, Sarah Renée; Wessing, Henrik

    2008-01-01

    We evaluate the connection provisioning performance of GMPLS-controlled wavelength routed networks under dynamic traffic load and using three different wavelength converter placement heuristics. Results show that a simple uniform placement heuristic matches the performance of complex heuristics...... under dynamic traffic assumptions....

  12. Cooperative driving in mixed traffic networks - Optimizing for performance

    NARCIS (Netherlands)

    Calvert, S.C.; Broek, T.H.A. van den; Noort, M. van

    2012-01-01

    This paper discusses a cooperative adaptive cruise control application and its effects on the traffic system. In previous work this application has been tested on the road, and traffic simulation has been used to scale up the results of the field test to larger networks and more vehicles. The

  13. Robustness of Interrelated Traffic Networks to Cascading Failures

    Science.gov (United States)

    Su, Zhen; Li, Lixiang; Peng, Haipeng; Kurths, Jürgen; Xiao, Jinghua; Yang, Yixian

    2014-06-01

    The vulnerability to real-life networks against small initial attacks has been one of outstanding challenges in the study of interrelated networks. We study cascading failures in two interrelated networks S and B composed from dependency chains and connectivity links respectively. This work proposes a realistic model for cascading failures based on the redistribution of traffic flow. We study the Barabási-Albert networks (BA) and Erdős-Rényi graphs (ER) with such structure, and found that the efficiency sharply decreases with increasing percentages of the dependency nodes for removing a node randomly. Furthermore, we study the robustness of interrelated traffic networks, especially the subway and bus network in Beijing. By analyzing different attacking strategies, we uncover that the efficiency of the city traffic system has a non-equilibrium phase transition at low capacity of the networks. This explains why the pressure of the traffic overload is relaxed by singly increasing the number of small buses during rush hours. We also found that the increment of some buses may release traffic jam caused by removing a node of the bus network randomly if the damage is limited. However, the efficiencies to transfer people flow will sharper increase when the capacity of the subway network αS > α0.

  14. Delayed Correlations in Inter-Domain Network Traffic

    OpenAIRE

    Rojkova, Viktoria; Kantardzic, Mehmed

    2007-01-01

    To observe the evolution of network traffic correlations we analyze the eigenvalue spectra and eigenvectors statistics of delayed correlation matrices of network traffic counts time series. Delayed correlation matrix D is composed of the correlations between one variable in the multivariable time series and another at a time delay \\tau . Inverse participation ratio (IPR) of eigenvectors of D deviates substantially from the IPR of eigenvectors of the equal time correlation matrix C. We relate ...

  15. Performance Modeling for Heterogeneous Wireless Networks with Multiservice Overflow Traffic

    DEFF Research Database (Denmark)

    Huang, Qian; Ko, King-Tim; Iversen, Villy Bæk

    2009-01-01

    Performance modeling is important for the purpose of developing efficient dimensioning tools for large complicated networks. But it is difficult to achieve in heterogeneous wireless networks, where different networks have different statistical characteristics in service and traffic models....... Multiservice loss analysis based on multi-dimensional Markov chain becomes intractable in these networks due to intensive computations required. This paper focuses on performance modeling for heterogeneous wireless networks based on a hierarchical overlay infrastructure. A method based on decomposition...... of the correlated traffic is used to achieve an approximate performance modeling for multiservice in hierarchical heterogeneous wireless networks with overflow traffic. The accuracy of the approximate performance obtained by our proposed modeling is verified by simulations....

  16. An Operational System for Estimating Road Traffic Information from Aerial Images

    Directory of Open Access Journals (Sweden)

    Jens Leitloff

    2014-11-01

    Full Text Available Given that ground stationary infrastructures for traffic monitoring are barely able to handle everyday traffic volumes, there is a risk that they could fail altogether in situations arising from mass events or disasters. In this work, we present an alternative approach for traffic monitoring during disaster and mass events, which is based on an airborne optical sensor system. With this system, optical image sequences are automatically examined on board an aircraft to estimate road traffic information, such as vehicle positions, velocities and driving directions. The traffic information, estimated in real time on board, is immediately downlinked to a ground station. The airborne sensor system consists of a three-head camera system, a real-time-capable GPS/INS unit, five industrial PCs and a downlink unit. The processing chain for automatic extraction of traffic information contains modules for the synchronization of image and navigation data streams, orthorectification and vehicle detection and tracking modules. The vehicle detector is based on a combination of AdaBoost and support vector machine classifiers. Vehicle tracking relies on shape-based matching operators. The processing chain is evaluated on a large number of image sequences recorded during several campaigns, and the data quality is compared to that obtained from induction loops. In summary, we can conclude that the achieved overall quality of the traffic data extracted by the airborne system is in the range of 68% and 81%. Thus, it is comparable to data obtained from stationary ground sensor networks.

  17. Algorithm for queueing networks with multi-rate traffic

    DEFF Research Database (Denmark)

    Iversen, Villy Bæk; King-Tim, Ko

    2011-01-01

    In this paper we present a new algorithm for evaluating queueing networks with multi-rate traffic. The detailed state space of a node is evaluated by explicit formulæ. We consider reversible nodes with multi-rate traffic and find the state probabilities by taking advantage of local balance. Theory...... is reversibility which implies that the arrival process and departure process are identical processes, for example state-dependent Poisson processes. This property is equivalent to reversibility. Due to product form, an open network with multi-rate traffic is easy to evaluate by convolution algorithms because...

  18. INTELLIGENT TRAFFIC-SAFETY MIRROR BY USING WIRELESS SENSOR NETWORK

    Directory of Open Access Journals (Sweden)

    Peter Danišovič

    2014-03-01

    Full Text Available This article is focused on the problematic of traffic safety, dealing with the problem of car intersections with blocked view crossing by a special wireless sensor network (WSN proposed for the traffic monitoring, concretely for vehicle’s detection at places, where it is necessary. Some ultra-low-power TI products were developed due to this reason: microcontroller MSP430F2232, 868MHz RF transceiver CC1101 and LDO voltage regulator TPS7033. The WSN consist of four network nodes supplied with the special safety lightings which serve the function of intelligent traffic safety mirror.

  19. Network-wide BGP route prediction for traffic engineering

    Science.gov (United States)

    Feamster, Nick; Rexford, Jennifer

    2002-07-01

    The Internet consists of about 13,000 Autonomous Systems (AS's) that exchange routing information using the Border Gateway Protocol (BGP). The operators of each AS must have control over the flow of traffic through their network and between neighboring AS's. However, BGP is a complicated, policy-based protocol that does not include any direct support for traffic engineering. In previous work, we have demonstrated that network operators can adapt the flow of traffic in an efficient and predictable fashion through careful adjustments to the BGP policies running on their edge routers. Nevertheless, many details of the BGP protocol and decision process make predicting the effects of these policy changes difficult. In this paper, we describe a tool that predicts traffic flow at network exit points based on the network topology, the import policy associated with each BGP session, and the routing advertisements received from neighboring AS's. We present a linear-time algorithm that computes a network-wide view of the best BGP routes for each destination prefix given a static snapshot of the network state, without simulating the complex details of BGP message passing. We describe how to construct this snapshot using the BGP routing tables and router configuration files available from operational routers. We verify the accuracy of our algorithm by applying our tool to routing and configuration data from AT&T's commercial IP network. Our route prediction techniques help support the operation of large IP backbone networks, where interdomain routing is an important aspect of traffic engineering.

  20. FPGA Based Real-time Network Traffic Analysis using Traffic Dispersion Patterns

    Energy Technology Data Exchange (ETDEWEB)

    Khan, F; Gokhale, M; Chuah, C N

    2010-03-26

    The problem of Network Traffic Classification (NTC) has attracted significant amount of interest in the research community, offering a wide range of solutions at various levels. The core challenge is in addressing high amounts of traffic diversity found in today's networks. The problem becomes more challenging if a quick detection is required as in the case of identifying malicious network behavior or new applications like peer-to-peer traffic that have potential to quickly throttle the network bandwidth or cause significant damage. Recently, Traffic Dispersion Graphs (TDGs) have been introduced as a viable candidate for NTC. The TDGs work by forming a network wide communication graphs that embed characteristic patterns of underlying network applications. However, these patterns need to be quickly evaluated for mounting real-time response against them. This paper addresses these concerns and presents a novel solution for real-time analysis of Traffic Dispersion Metrics (TDMs) in the TDGs. We evaluate the dispersion metrics of interest and present a dedicated solution on an FPGA for their analysis. We also present analytical measures and empirically evaluate operating effectiveness of our design. The mapped design on Virtex-5 device can process 7.4 million packets/second for a TDG comprising of 10k flows at very high accuracies of over 96%.

  1. Development and application of traffic accident density estimation models using kernel density estimation

    Directory of Open Access Journals (Sweden)

    Seiji Hashimoto

    2016-06-01

    Full Text Available Traffic accident frequency has been decreasing in Japan in recent years. Nevertheless, many accidents still occur on residential roads. Area-wide traffic calming measures including Zone 30, which discourages traffic by setting a speed limit of 30 km/h in residential areas, have been implemented. However, no objective implementation method has been established. Development of a model for traffic accident density estimation explained by GIS data can enable the determination of dangerous areas objectively and easily, indicating where area-wide traffic calming can be implemented preferentially. This study examined the relations between traffic accidents and city characteristics, such as population, road factors, and spatial factors. A model was developed to estimate traffic accident density. Kernel density estimation (KDE techniques were used to assess the relations efficiently. Besides, 16 models were developed by combining accident locations, accident types, and data types. By using them, the applicability of traffic accident density estimation models was examined. Results obtained using Spearman rank correlation show high coefficients between the predicted number and the actual number. The model can indicate the relative accident risk in cities. Results of this study can be used for objective determination of areas where area-wide traffic calming can be implemented preferentially, even if sufficient traffic accident data are not available.

  2. Traffic Management in ATM Networks Over Satellite Links

    Science.gov (United States)

    Goyal, Rohit; Jain, Raj; Goyal, Mukul; Fahmy, Sonia; Vandalore, Bobby; vonDeak, Thomas

    1999-01-01

    This report presents a survey of the traffic management Issues in the design and implementation of satellite Asynchronous Transfer Mode (ATM) networks. The report focuses on the efficient transport of Transmission Control Protocol (TCP) traffic over satellite ATM. First, a reference satellite ATM network architecture is presented along with an overview of the service categories available in ATM networks. A delay model for satellite networks and the major components of delay and delay variation are described. A survey of design options for TCP over Unspecified Bit Rate (UBR), Guaranteed Frame Rate (GFR) and Available Bit Rate (ABR) services in ATM is presented. The main focus is on traffic management issues. Several recommendations on the design options for efficiently carrying data services over satellite ATM networks are presented. Most of the results are based on experiments performed on Geosynchronous (GEO) latencies. Some results for Low Earth Orbits (LEO) and Medium Earth Orbit (MEO) latencies are also provided.

  3. Discrete Choice Models - Estimation of Passenger Traffic

    DEFF Research Database (Denmark)

    Sørensen, Majken Vildrik

    2003-01-01

    for data, a literature review follows. Models applied for estimation of discrete choice models are described by properties and limitations, and relations between these are established. Model types are grouped into three classes, Hybrid choice models, Tree models and Latent class models. Relations between...... for estimation of choice models). For application of the method an algorithm is provided with a case. Also for the second issue, estimation of Mixed Logit models, a method was proposed. The most commonly used approach to estimate Mixed Logit models, is to employ the Maximum Simulated Likelihood estimation (MSL...

  4. Cooperative Learning for Distributed In-Network Traffic Classification

    Science.gov (United States)

    Joseph, S. B.; Loo, H. R.; Ismail, I.; Andromeda, T.; Marsono, M. N.

    2017-04-01

    Inspired by the concept of autonomic distributed/decentralized network management schemes, we consider the issue of information exchange among distributed network nodes to network performance and promote scalability for in-network monitoring. In this paper, we propose a cooperative learning algorithm for propagation and synchronization of network information among autonomic distributed network nodes for online traffic classification. The results show that network nodes with sharing capability perform better with a higher average accuracy of 89.21% (sharing data) and 88.37% (sharing clusters) compared to 88.06% for nodes without cooperative learning capability. The overall performance indicates that cooperative learning is promising for distributed in-network traffic classification.

  5. Adaptive traffic control systems for urban networks

    Directory of Open Access Journals (Sweden)

    Radivojević Danilo

    2017-01-01

    Full Text Available Adaptive traffic control systems represent complex, but powerful tool for improvement of traffic flow conditions in locations or zones where applied. Many traffic agencies, especially those that have a large number of signalized intersections with high variability of the traffic demand, choose to apply some of the adaptive traffic control systems. However, those systems are manufactured and offered by multiple vendors (companies that are competing for the market share. Due to that fact, besides the information available from the vendors themselves, or the information from different studies conducted on different continents, very limited amount of information is available about the details how those systems are operating. The reason for that is the protecting of the intellectual property from plagiarism. The primary goal of this paper is to make a brief analysis of the functionalities, characteristics, abilities and results of the most recognized, but also less known adaptive traffic control systems to the professional public and other persons with interest in this subject.

  6. Routing of Internal MANET Traffic over External Networks

    Directory of Open Access Journals (Sweden)

    Vinh Pham

    2009-01-01

    Full Text Available Many have proposed to connect Mobile Ad Hoc Networks (MANETs to a wired backbone Internet access network. This paper demonstrates that a wired backbone network can be utilized for more than just providing access to the global Internet. Traffic between mobile nodes in the ad hoc network may also be routed via this backbone network to achieve higher throughput, and to reduce the load in the ad hoc network. This is referred to as transit routing. This paper proposes a cost metric algorithm that facilitates transit routing for some of the traffic flows between nodes in the MANET. The algorithm aims at carrying out transit routing for a flow only when it leads to improvements of the performance. The proposal is implemented and tested in the ns-2 network simulator, and the simulation results are promising.

  7. Uncovering transportation networks from traffic flux by compressed sensing

    Science.gov (United States)

    Tang, Si-Qi; Shen, Zhesi; Wang, Wen-Xu; Di, Zengru

    2015-08-01

    Transportation and communication networks are ubiquitous in nature and society. Uncovering the underlying topology as well as link weights, is fundamental to understanding traffic dynamics and designing effective control strategies to facilitate transmission efficiency. We develop a general method for reconstructing transportation networks from detectable traffic flux data using the aid of a compressed sensing algorithm. Our approach enables full reconstruction of network topology and link weights for both directed and undirected networks from relatively small amounts of data compared to the network size. The limited data requirement and certain resistance to noise allows our method to achieve real-time network reconstruction. We substantiate the effectiveness of our method through systematic numerical tests with respect to several different network structures and transmission strategies. We expect our approach to be widely applicable in a variety of transportation and communication systems.

  8. Traffic networks as information systems a viability approach

    CERN Document Server

    Aubin, Jean-Pierre

    2017-01-01

    This authored monograph covers a viability to approach to traffic management by advising to vehicles circulated on the network the velocity they should follow for satisfying global traffic conditions;. It presents an investigation of three structural innovations: The objective is to broadcast at each instant and at each position the advised celerity to vehicles, which could be read by auxiliary speedometers or used by cruise control devices. Namely, 1. Construct regulation feedback providing at each time and position advised velocities (celerities) for minimizing congestion or other requirements. 2. Taking into account traffic constraints of different type, the first one being to remain on the roads, to stop at junctions, etc. 3. Use information provided by the probe vehicles equipped with GPS to the traffic regulator; 4. Use other global traffic measures of vehicles provided by different types of sensors; These results are based on convex analysis, intertemporal optimization and viability theory as mathemati...

  9. Sensor Location Problem Optimization for Traffic Network with Different Spatial Distributions of Traffic Information.

    Science.gov (United States)

    Bao, Xu; Li, Haijian; Qin, Lingqiao; Xu, Dongwei; Ran, Bin; Rong, Jian

    2016-10-27

    To obtain adequate traffic information, the density of traffic sensors should be sufficiently high to cover the entire transportation network. However, deploying sensors densely over the entire network may not be realistic for practical applications due to the budgetary constraints of traffic management agencies. This paper describes several possible spatial distributions of traffic information credibility and proposes corresponding different sensor information credibility functions to describe these spatial distribution properties. A maximum benefit model and its simplified model are proposed to solve the traffic sensor location problem. The relationships between the benefit and the number of sensors are formulated with different sensor information credibility functions. Next, expanding models and algorithms in analytic results are performed. For each case, the maximum benefit, the optimal number and spacing of sensors are obtained and the analytic formulations of the optimal sensor locations are derived as well. Finally, a numerical example is proposed to verify the validity and availability of the proposed models for solving a network sensor location problem. The results show that the optimal number of sensors of segments with different model parameters in an entire freeway network can be calculated. Besides, it can also be concluded that the optimal sensor spacing is independent of end restrictions but dependent on the values of model parameters that represent the physical conditions of sensors and roads.

  10. A Wavelet Analysis-Based Dynamic Prediction Algorithm to Network Traffic

    Directory of Open Access Journals (Sweden)

    Meng Fan-Bo

    2016-01-01

    Full Text Available Network traffic is a significantly important parameter for network traffic engineering, while it holds highly dynamic nature in the network. Accordingly, it is difficult and impossible to directly predict traffic amount of end-to-end flows. This paper proposes a new prediction algorithm to network traffic using the wavelet analysis. Firstly, network traffic is converted into the time-frequency domain to capture time-frequency feature of network traffic. Secondly, in different frequency components, we model network traffic in the time-frequency domain. Finally, we build the prediction model about network traffic. At the same time, the corresponding prediction algorithm is presented to attain network traffic prediction. Simulation results indicates that our approach is promising.

  11. Online Incremental Learning for High Bandwidth Network Traffic Classification

    Directory of Open Access Journals (Sweden)

    H. R. Loo

    2016-01-01

    Full Text Available Data stream mining techniques are able to classify evolving data streams such as network traffic in the presence of concept drift. In order to classify high bandwidth network traffic in real-time, data stream mining classifiers need to be implemented on reconfigurable high throughput platform, such as Field Programmable Gate Array (FPGA. This paper proposes an algorithm for online network traffic classification based on the concept of incremental k-means clustering to continuously learn from both labeled and unlabeled flow instances. Two distance measures for incremental k-means (Euclidean and Manhattan distance are analyzed to measure their impact on the network traffic classification in the presence of concept drift. The experimental results on real datasets show that the proposed algorithm exhibits consistency, up to 94% average accuracy for both distance measures, even in the presence of concept drifts. The proposed incremental k-means classification using Manhattan distance can classify network traffic 3 times faster than Euclidean distance at 671 thousands flow instances per second.

  12. Traffic Adaptive MAC Protocols in Wireless Body Area Networks

    Directory of Open Access Journals (Sweden)

    Farhan Masud

    2017-01-01

    Full Text Available In Wireless Body Area Networks (WBANs, every healthcare application that is based on physical sensors is responsible for monitoring the vital signs data of patient. WBANs applications consist of heterogeneous and dynamic traffic loads. Routine patient’s observation is described as low-load traffic while an alarming situation that is unpredictable by nature is referred to as high-load traffic. This paper offers a thematic review of traffic adaptive Medium Access Control (MAC protocols in WBANs. First, we have categorized them based on their goals, methods, and metrics of evaluation. The Zigbee standard IEEE 802.15.4 and the baseline MAC IEEE 802.15.6 are also reviewed in terms of traffic adaptive approaches. Furthermore, a comparative analysis of the protocols is made and their performances are analyzed in terms of delay, packet delivery ratio (PDR, and energy consumption. The literature shows that no review work has been done on traffic adaptive MAC protocols in WBANs. This review work, therefore, could add enhancement to traffic adaptive MAC protocols and will stimulate a better way of solving the traffic adaptivity problem.

  13. Baselining Network-Wide Traffic by Time-Frequency Constrained Stable Principal Component Pursuit

    OpenAIRE

    Hu, Kai; Wang, Zhe; Yin, Baolin

    2013-01-01

    The Internet traffic analysis is important to network management,and extracting the baseline traffic patterns is especially helpful for some significant network applications.In this paper, we study on the baseline problem of the traffic matrix satisfying a refined traffic matrix decomposition model,since this model extends the assumption of the baseline traffic component to characterize its smoothness, and is more realistic than the existing traffic matrix models. We develop a novel baseline ...

  14. Bayesian estimation of traffic lane state

    Czech Academy of Sciences Publication Activity Database

    Nagy, Ivan; Kárný, Miroslav; Nedoma, Petr; Voráčová, Š.

    2003-01-01

    Roč. 17, č. 1 (2003), s. 51-65 ISSN 0890-6327 R&D Projects: GA ČR GA102/03/0049; GA AV ČR IBS1075351 Institutional research plan: CEZ:AV0Z1075907 Keywords : mixture models * estimation * Bayesian approach Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.602, year: 2003 http://library.utia.cas.cz/prace/20030021.ps

  15. Algorithm for queueing networks with multi-rate traffic

    DEFF Research Database (Denmark)

    Iversen, Villy Bæk; Ko, King-Tim

    2011-01-01

    In this paper we present a new algorithm for evaluating queueing networks with multi-rate traffic. The detailed state space of a node is evaluated by explicit formulæ. We consider reversible nodes with multi-rate traffic and find the state probabilities by taking advantage of local balance. Theory...... is reversibility which implies that the arrival process and departure process are identical processes, for example state-dependent Poisson processes. This property is equivalent to reversibility. Due to product form, an open network with multi-rate traffic is easy to evaluate by convolution algorithms because...... the nodes behave as independent nodes. For closed queueing networks with multiple servers in every node and multi-rate services we may apply multidimensional convolution algorithm to aggregate the nodes so that we end up with two nodes, the aggregated node and a single node, for which we can calculate...

  16. A Method of Urban Traffic Flow Speed Estimation Using Sparse Floating Car Data

    OpenAIRE

    WANG Xiaomeng; PENG Ling; CHI Tianhe

    2016-01-01

    The sample spatio-temporalsparsity is one of the major challenges for traffic estimation when using floating car data (FCD).Spatio-temporal characteristics of road traffic flow are analysed and applied to build a naive Bayes-based traffic estimation model which is proposed to estimate the missing traffic state of the roads which are not covered by samples. In the model, the adjacent period traffic flow speed of the target road segment is considered for the representation of the time character...

  17. A model of traffic signs recognition with convolutional neural network

    Science.gov (United States)

    Hu, Haihe; Li, Yujian; Zhang, Ting; Huo, Yi; Kuang, Wenqing

    2016-10-01

    In real traffic scenes, the quality of captured images are generally low due to some factors such as lighting conditions, and occlusion on. All of these factors are challengeable for automated recognition algorithms of traffic signs. Deep learning has provided a new way to solve this kind of problems recently. The deep network can automatically learn features from a large number of data samples and obtain an excellent recognition performance. We therefore approach this task of recognition of traffic signs as a general vision problem, with few assumptions related to road signs. We propose a model of Convolutional Neural Network (CNN) and apply the model to the task of traffic signs recognition. The proposed model adopts deep CNN as the supervised learning model, directly takes the collected traffic signs image as the input, alternates the convolutional layer and subsampling layer, and automatically extracts the features for the recognition of the traffic signs images. The proposed model includes an input layer, three convolutional layers, three subsampling layers, a fully-connected layer, and an output layer. To validate the proposed model, the experiments are implemented using the public dataset of China competition of fuzzy image processing. Experimental results show that the proposed model produces a recognition accuracy of 99.01 % on the training dataset, and yield a record of 92% on the preliminary contest within the fourth best.

  18. A First Look into SCADA Network Traffic

    NARCIS (Netherlands)

    Barbosa, R.R.R.; Sadre, R.; Pras, Aiko

    Supervisory Control and Data Acquisition (SCADA) networks are commonly deployed to aid the operation of critical infrastructures, such as water distribution facilities. These networks provide automated processes that ensure the correct functioning of these infrastructures, in a operation much

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

    DEFF Research Database (Denmark)

    Tamas-Selicean, Domitian; Pop, Paul

    2014-01-01

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

  20. Energy Saving: Scaling Network Energy Efficiency Faster than Traffic Growth

    NARCIS (Netherlands)

    Chen, Y.; Blume, O.; Gati, A.; Capone, A.; Wu, C.E.; Barth, U.; Marzetta, T.; Zhang, H.; Xu, S.

    2013-01-01

    As the mobile traffic is expected to continue its exponential growth in the near future, energy efficiency has gradually become a must criterion for wireless network design. Three fundamental questions need to be answered before the detailed design could be carried out, namely what energy efficiency

  1. Towards Mining Latent Client Identifiers from Network Traffic

    Directory of Open Access Journals (Sweden)

    Jain Sakshi

    2016-04-01

    Full Text Available Websites extensively track users via identifiers that uniquely map to client machines or user accounts. Although such tracking has desirable properties like enabling personalization and website analytics, it also raises serious concerns about online user privacy, and can potentially enable illicit surveillance by adversaries who broadly monitor network traffic.

  2. Simulation of traffic capacity of inland waterway network

    NARCIS (Netherlands)

    Chen, L.; Mou, J.; Ligteringen, H.

    2013-01-01

    The inland waterborne transportation is viewed as an economic, safe and environmentally friendly alternative to the congested road network. The traffic capacity are the critical indicator of the inland shipping performance. Actually, interacted under the complicated factors, it is challenging to

  3. Behavioral Profiling of Scada Network Traffic Using Machine Learning Algorithms

    Science.gov (United States)

    2014-03-27

    which represent potentially insecure mechanisms for authentication and authorization. 9 An example of a hacker penetrating network security at a...transport most application 35 traffic such as Lightweight Directory Access Protocol ( LDAP ), HTTP, HyperText Transfer Protocol Secure (HTTPS), POP3...Department of Homeland Security . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 DPI deep packet inspection

  4. The effects of traffic structure on application and network performance

    CERN Document Server

    Aikat, Jay; Smith, F Donelson

    2012-01-01

    Over the past three decades, the Internet's rapid growth has spurred the development of new applications in mobile computing, digital music, online video, gaming and social networks. These applications rely heavily upon various underlying network protocols and mechanisms to enable, maintain and enhance their Internet functionalityThe Effects of Traffic Structure on Application and Network Performance provides the necessary tools for maximizing the network efficiency of any Internet application, and presents ground-breaking research that will influence how these applications are built in the fu

  5. Estimates of CO2 traffic emissions from mobile concentration measurements

    Science.gov (United States)

    Maness, H. L.; Thurlow, M. E.; McDonald, B. C.; Harley, R. A.

    2015-03-01

    We present data from a new mobile system intended to aid in the design of upcoming urban CO2-monitoring networks. Our collected data include GPS probe data, video-derived traffic density, and accurate CO2 concentration measurements. The method described here is economical, scalable, and self-contained, allowing for potential future deployment in locations without existing traffic infrastructure or vehicle fleet information. Using a test data set collected on California Highway 24 over a 2 week period, we observe that on-road CO2 concentrations are elevated by a factor of 2 in congestion compared to free-flow conditions. This result is found to be consistent with a model including vehicle-induced turbulence and standard engine physics. In contrast to surface concentrations, surface emissions are found to be relatively insensitive to congestion. We next use our model for CO2 concentration together with our data to independently derive vehicle emission rate parameters. Parameters scaling the leading four emission rate terms are found to be within 25% of those expected for a typical passenger car fleet, enabling us to derive instantaneous emission rates directly from our data that compare generally favorably to predictive models presented in the literature. The present results highlight the importance of high spatial and temporal resolution traffic data for interpreting on- and near-road concentration measurements. Future work will focus on transport and the integration of mobile platforms into existing stationary network designs.

  6. Toward an optimal convolutional neural network for traffic sign recognition

    Science.gov (United States)

    Habibi Aghdam, Hamed; Jahani Heravi, Elnaz; Puig, Domenec

    2015-12-01

    Convolutional Neural Networks (CNN) beat the human performance on German Traffic Sign Benchmark competition. Both the winner and the runner-up teams trained CNNs to recognize 43 traffic signs. However, both networks are not computationally efficient since they have many free parameters and they use highly computational activation functions. In this paper, we propose a new architecture that reduces the number of the parameters 27% and 22% compared with the two networks. Furthermore, our network uses Leaky Rectified Linear Units (ReLU) as the activation function that only needs a few operations to produce the result. Specifically, compared with the hyperbolic tangent and rectified sigmoid activation functions utilized in the two networks, Leaky ReLU needs only one multiplication operation which makes it computationally much more efficient than the two other functions. Our experiments on the Gertman Traffic Sign Benchmark dataset shows 0:6% improvement on the best reported classification accuracy while it reduces the overall number of parameters 85% compared with the winner network in the competition.

  7. Routing optimization in networks based on traffic gravitational field model

    Science.gov (United States)

    Liu, Longgeng; Luo, Guangchun

    2017-04-01

    For research on the gravitational field routing mechanism on complex networks, we further analyze the gravitational effect of paths. In this study, we introduce the concept of path confidence degree to evaluate the unblocked reliability of paths that it takes the traffic state of all nodes on the path into account from the overall. On the basis of this, we propose an improved gravitational field routing protocol considering all the nodes’ gravities on the path and the path confidence degree. In order to evaluate the transmission performance of the routing strategy, an order parameter is introduced to measure the network throughput by the critical value of phase transition from a free-flow phase to a jammed phase, and the betweenness centrality is used to evaluate the transmission performance and traffic congestion of the network. Simulation results show that compared with the shortest-path routing strategy and the previous gravitational field routing strategy, the proposed algorithm improves the network throughput considerably and effectively balances the traffic load within the network, and all nodes in the network are utilized high efficiently. As long as γ ≥ α, the transmission performance can reach the maximum and remains unchanged for different α and γ, which ensures that the proposed routing protocol is high efficient and stable.

  8. [Methodologies for estimating the indirect costs of traffic accidents].

    Science.gov (United States)

    Carozzi, Soledad; Elorza, María Eugenia; Moscoso, Nebel Silvana; Ripari, Nadia Vanina

    2017-01-01

    Traffic accidents generate multiple costs to society, including those associated with the loss of productivity. However, there is no consensus about the most appropriate methodology for estimating those costs. The aim of this study was to review methods for estimating indirect costs applied in crash cost studies. A thematic review of the literature was carried out between 1995 and 2012 in PubMed with the terms cost of illness, indirect cost, road traffic injuries, productivity loss. For the assessment of costs we used the the human capital method, on the basis of the wage-income lost during the time of treatment and recovery of patients and caregivers. In the case of premature death or total disability, the discount rate was applied to obtain the present value of lost future earnings. The computed years arose by subtracting to life expectancy at birth the average age of those affected who are not incorporated into the economically active life. The interest in minimizing the problem is reflected in the evolution of the implemented methodologies. We expect that this review is useful to estimate efficiently the real indirect costs of traffic accidents.

  9. On the distribution of calls in a wireless network driven by fluid traffic

    NARCIS (Netherlands)

    Ule, Aljaz; Boucherie, Richardus J.

    2003-01-01

    This note develops a modelling approach for wireless networks driven by fluid traffic models. Introducing traffic sets that follow movement of subscribers, the wireless network with time-varying rates is transformed into a stationary network at these traffic sets, which yields that the distribution

  10. On the Distribution of CAlls in a Wireless Network driven by Fluid Traffic

    NARCIS (Netherlands)

    Ule, A.; Boucherie, R.J.

    2003-01-01

    This note develops a modelling approach for wireless networks driven by fluid traffic models. Introducing traffic sets that follow movement of subscribers, the wireless network with time-varying rates is transformed into a stationary network at these traffic sets, which yields that the distribution

  11. On the distribution of customers in a wireless network driven by fluid traffic

    NARCIS (Netherlands)

    Ule, A.; Boucherie, R.J.

    2000-01-01

    This note develops a modelling approach for wireless networks driven byfluid traffic models. Introducing traffic sets that follow movement ofsubscribers, the wireless network with time-varying rates is transformedinto a stationary network at these traffic sets, which yields that thedistribution of

  12. Generic Traffic Descriptors in Managing Service Quality in BISDN/ATM Network

    Directory of Open Access Journals (Sweden)

    Ivan Bošnjak

    2002-03-01

    Full Text Available Traffic models for multiservice broadband networks differsignificantly regarding simple analytic models applicable intelephone traffic and circuit-switch network. The paper presentsa clear analysis of standardised traffic descriptors andquality parameters of the main services in BISDNIATM. Trafficdescriptors have been associated with the basic values andconcepts developed within generic traffic theory. Part systematisationof traffic parameters has been performed as basis for formalisedgeneralised description of parameters and effectivequality management of A TM services.

  13. Efficient traffic grooming in SONET/WDM BLSR Networks

    Energy Technology Data Exchange (ETDEWEB)

    Awwal, A S; Billah, A B; Wang, B

    2004-04-02

    In this paper, we study traffic grooming in SONET/WDM BLSR networks under the uniform all-to-all traffic model with an objective to reduce total network costs (wavelength and electronic multiplexing costs), in particular, to minimize the number of ADMs while using the optimal number of wavelengths. We derive a new tighter lower bound for the number of wavelengths when the number of nodes is a multiple of 4. We show that this lower bound is achievable. All previous ADM lower bounds except perhaps that in were derived under the assumption that the magnitude of the traffic streams (r) is one unit (r = 1) with respect to the wavelength capacity granularity g. We then derive new, more general and tighter lower bounds for the number of ADMs subject to that the optimal number of wavelengths is used, and propose heuristic algorithms (circle construction algorithm and circle grooming algorithm) that try to minimize the number of ADMs while using the optimal number of wavelengths in BLSR networks. Both the bounds and algorithms are applicable to any value of r and for different wavelength granularity g. Performance evaluation shows that wherever applicable, our lower bounds are at least as good as existing bounds and are much tighter than existing ones in many cases. Our proposed heuristic grooming algorithms perform very well with traffic streams of larger magnitude. The resulting number of ADMs required is very close to the corresponding lower bounds derived in this paper.

  14. A Method of Urban Traffic Flow Speed Estimation Using Sparse Floating Car Data

    Directory of Open Access Journals (Sweden)

    WANG Xiaomeng

    2016-07-01

    Full Text Available The sample spatio-temporalsparsity is one of the major challenges for traffic estimation when using floating car data (FCD.Spatio-temporal characteristics of road traffic flow are analysed and applied to build a naive Bayes-based traffic estimation model which is proposed to estimate the missing traffic state of the roads which are not covered by samples. In the model, the adjacent period traffic flow speed of the target road segment is considered for the representation of the time characteristic. And instead of Euclidean distance and topology relationship, urban traffic flow similarity relationships are mined to quantify the interior space features of urban traffic.The result demonstrates that the method is effective for missing traffic state estimation and more precision compared to traditional methods based on topology relationship.As a conclusion, the proposed model can solve the spatio-temporal sparsity problem effectively, which has a strong practical significance for traffic application based on FCD.

  15. Traffic Rules in Electronic Financial Transactions (EFT Networks

    Directory of Open Access Journals (Sweden)

    Vedran Batoš

    2002-01-01

    Full Text Available This paper presents the traffic rules in the EFT (ElectronicFinancial Transactions networks, based on the implementationof the solution called Gold-Net developed and implementedby Euronet Worldwide Inc. Following the traffic rulesin EFT networks, out of its worldwide experience, Gold-Netevolved a comprehensive and expandable EFT network solutiondesigned to meet an institution's needs today and in the future.It is an ITM (Integrated Transaction Management solution,modular and expandable, and consists of a comprehensiveEFT software modules with ATM and POS driving capabilities.The combination of ATM management and the onlineconnection form the intercept processing control module. Asthe marketplace grows, this solution ensures that an ente1prisemay position itself for future growth and expanded service offerings.

  16. Urban Traffic Signal System Control Structural Optimization Based on Network Analysis

    Directory of Open Access Journals (Sweden)

    Li Wang

    2013-01-01

    Full Text Available Advanced urban traffic signal control systems such as SCOOT and SCATS normally coordinate traffic network using multilevel hierarchical control mechanism. In this mechanism, several key intersections will be selected from traffic signal network and the network will be divided into different control subareas. Traditionally, key intersection selection and control subareas division are executed according to dynamic traffic counts and link length between intersections, which largely rely on traffic engineers’ experience. However, it omits important inherent characteristics of traffic network topology. In this paper, we will apply network analysis approach into these two aspects for traffic system control structure optimization. Firstly, the modified C-means clustering algorithm will be proposed to assess the importance of intersections in traffic network and furthermore determine the key intersections based on three indexes instead of merely on traffic counts in traditional methods. Secondly, the improved network community discovery method will be used to give more reasonable evidence in traffic control subarea division. Finally, to test the effectiveness of network analysis approach, a hardware-in-loop simulation environment composed of regional traffic control system, microsimulation software and signal controller hardware, will be built. Both traditional method and proposed approach will be implemented on simulation test bed to evaluate traffic operation performance indexes, for example, travel time, stop times, delay and average vehicle speed. Simulation results show that the proposed network analysis approach can improve the traffic control system operation performance effectively.

  17. The wireshark field guide analyzing and troubleshooting network traffic

    CERN Document Server

    Shimonski, Robert

    2013-01-01

    The Wireshark Field Guide provides hackers, pen testers, and network administrators with practical guidance on capturing and interactively browsing computer network traffic. Wireshark is the world's foremost network protocol analyzer, with a rich feature set that includes deep inspection of hundreds of protocols, live capture, offline analysis and many other features. The Wireshark Field Guide covers the installation, configuration and use of this powerful multi-platform tool. The book give readers the hands-on skills to be more productive with Wireshark as they drill

  18. Stream Traffic Communication in Packet Switched Networks,

    Science.gov (United States)

    1977-08-01

    Currently, the interconnection of surh networks [ McKe 74a] and the standardization of protocols [Pouz 75), (Hove 76) are each of considerable interest in the...clear that failures do occur in practice. Long term monitoring of the ARPANET [ McKe 74) shows a mean time between failures (MTBF) of 431 hours for Lines...D. C.) [ McKe 74) McKenzie, A. A. Letter to S. D. Crocker. 16 Janu- ary 1974. [ McKe 74a] McKenzie, A. M. "Some Computer Network Intercon- nection

  19. Traffic Based Optimization of Spectrum Sensing in Cognitive Radio Networks

    Directory of Open Access Journals (Sweden)

    Changhua Yao

    2014-01-01

    Full Text Available We propose a more practical spectrum sensing optimization problem in cognitive radio networks (CRN, by considering the data traffic of second user (SU. Compared with most existing work, we do not assume that SU always has packets to transmit; instead, we use the actual data transmitted per second rather than the channel capacity as the achievable throughput, to reformulate the Sensing-Throughput Tradeoff problem. We mathematically analyze the problem of optimal sensing time to maximize the achievable throughput, based on the data traffic of SU. Our model is more general because the traditional Sensing-Throughput Tradeoff model can be seen as a special case of our model. We also prove that the throughput is a concave function of sensing time and there is only one optimal sensing time value which is determined by the data traffic. Simulation results show that the proposed approach outperforms existing methods.

  20. Emulation of realistic network traffic patterns on an eight-node data vortex interconnection network subsystem

    Science.gov (United States)

    Small, Benjamin A.; Shacham, Assaf; Bergman, Keren; Athikulwongse, Krit; Hawkins, Cory; Wills, D. Scott

    2004-11-01

    e demonstrate the feasibility of the data vortex interconnection network architecture for use in supercomputing by emulating realistic network traffic on an eight-node subnetwork. The evaluation workload uses memory accesses from the Barnes-Hut application in the SLPASH-2 parallel computing benchmark suite, which was extracted by using the M5 multiprocessor system simulator. We confirm that traffic is routed correctly and efficiently.

  1. Evaluation and Simulation of Common Video Conference Traffics in Communication Networks

    Directory of Open Access Journals (Sweden)

    Farhad faghani

    2014-01-01

    Full Text Available Multimedia traffics are the basic traffics in data communication networks. Especially Video conferences are the most desirable traffics in huge networks(wired, wireless, …. Traffic modeling can help us to evaluate the real networks. So, in order to have good services in data communication networks which provide multimedia services, QoS will be very important .In this research we tried to have an exact traffic model design and simulation to overcome QoS challenges. Also, we predict bandwidth by Kalman filter in Ethernet networks.

  2. Dynamic Network Traffic Flow Prediction Model based on Modified Quantum-Behaved Particle Swarm Optimization

    OpenAIRE

    Hongying Jin; Linhao Li

    2013-01-01

    This paper aims at effectively predicting the dynamic network traffic flow based on quantum-behaved particle swarm optimization algorithm. Firstly, the dynamic network traffic flow prediction problem is analyzed through formal description. Secondly, the structure of the network traffic flow prediction model is given. In this structure, Users can used a computer to start the traffic flow prediction process, and data collecting module can collect and return the data through the destination devi...

  3. Traffic sign recognition based on deep convolutional neural network

    Science.gov (United States)

    Yin, Shi-hao; Deng, Ji-cai; Zhang, Da-wei; Du, Jing-yuan

    2017-11-01

    Traffic sign recognition (TSR) is an important component of automated driving systems. It is a rather challenging task to design a high-performance classifier for the TSR system. In this paper, we propose a new method for TSR system based on deep convolutional neural network. In order to enhance the expression of the network, a novel structure (dubbed block-layer below) which combines network-in-network and residual connection is designed. Our network has 10 layers with parameters (block-layer seen as a single layer): the first seven are alternate convolutional layers and block-layers, and the remaining three are fully-connected layers. We train our TSR network on the German traffic sign recognition benchmark (GTSRB) dataset. To reduce overfitting, we perform data augmentation on the training images and employ a regularization method named "dropout". The activation function we employ in our network adopts scaled exponential linear units (SELUs), which can induce self-normalizing properties. To speed up the training, we use an efficient GPU to accelerate the convolutional operation. On the test dataset of GTSRB, we achieve the accuracy rate of 99.67%, exceeding the state-of-the-art results.

  4. Efficiency at maximum power of motor traffic on networks

    Science.gov (United States)

    Golubeva, N.; Imparato, A.

    2014-06-01

    We study motor traffic on Bethe networks subject to hard-core exclusion for both tightly coupled one-state machines and loosely coupled two-state machines that perform work against a constant load. In both cases we find an interaction-induced enhancement of the efficiency at maximum power (EMP) as compared to noninteracting motors. The EMP enhancement occurs for a wide range of network and single-motor parameters and is due to a change in the characteristic load-velocity relation caused by phase transitions in the system. Using a quantitative measure of the trade-off between the EMP enhancement and the corresponding loss in the maximum output power we identify parameter regimes where motor traffic systems operate efficiently at maximum power without a significant decrease in the maximum power output due to jamming effects.

  5. Analysis of Road Traffic Network Cascade Failures with Coupled Map Lattice Method

    Directory of Open Access Journals (Sweden)

    Yanan Zhang

    2015-01-01

    Full Text Available In recent years, there is growing literature concerning the cascading failure of network characteristics. The object of this paper is to investigate the cascade failures on road traffic network, considering the aeolotropism of road traffic network topology and road congestion dissipation in traffic flow. An improved coupled map lattice (CML model is proposed. Furthermore, in order to match the congestion dissipation, a recovery mechanism is put forward in this paper. With a real urban road traffic network in Beijing, the cascading failures are tested using different attack strategies, coupling strengths, external perturbations, and attacked road segment numbers. The impacts of different aspects on road traffic network are evaluated based on the simulation results. The findings confirmed the important roles that these characteristics played in the cascading failure propagation and dissipation on road traffic network. We hope these findings are helpful to find out the optimal road network topology and avoid cascading failure on road network.

  6. New Heuristic Algorithm for Dynamic Traffic in WDM Optical Networks

    Directory of Open Access Journals (Sweden)

    Arturo Benito Rodríguez Garcia

    2015-12-01

    Full Text Available The results and comparison of the simulation of a new heuristic algorithm called Snake One are presented. The comparison is made with three heuristic algorithms, Genetic Algorithms, Simulated Annealing, and Tabu Search, using blocking probability and network utilization as standard indicators. The simulation was made on the WDM NSFNET under dynamic traffic conditions. The results show a substantial decrease of blocking, but this causes a relative growth of network utilization. There are also load intervals at which its performance improves, decreasing the number of blocked requests.

  7. Network Traffic Prediction Based on Deep Belief Network and Spatiotemporal Compressive Sensing in Wireless Mesh Backbone Networks

    Directory of Open Access Journals (Sweden)

    Laisen Nie

    2018-01-01

    Full Text Available Wireless mesh network is prevalent for providing a decentralized access for users and other intelligent devices. Meanwhile, it can be employed as the infrastructure of the last few miles connectivity for various network applications, for example, Internet of Things (IoT and mobile networks. For a wireless mesh backbone network, it has obtained extensive attention because of its large capacity and low cost. Network traffic prediction is important for network planning and routing configurations that are implemented to improve the quality of service for users. This paper proposes a network traffic prediction method based on a deep learning architecture and the Spatiotemporal Compressive Sensing method. The proposed method first adopts discrete wavelet transform to extract the low-pass component of network traffic that describes the long-range dependence of itself. Then, a prediction model is built by learning a deep architecture based on the deep belief network from the extracted low-pass component. Otherwise, for the remaining high-pass component that expresses the gusty and irregular fluctuations of network traffic, the Spatiotemporal Compressive Sensing method is adopted to predict it. Based on the predictors of two components, we can obtain a predictor of network traffic. From the simulation, the proposed prediction method outperforms three existing methods.

  8. A Network Traffic Prediction Model Based on Quantum-Behaved Particle Swarm Optimization Algorithm and Fuzzy Wavelet Neural Network

    OpenAIRE

    Kun Zhang; Zhao Hu; Xiao-Ting Gan; Jian-Bo Fang

    2016-01-01

    Due to the fact that the fluctuation of network traffic is affected by various factors, accurate prediction of network traffic is regarded as a challenging task of the time series prediction process. For this purpose, a novel prediction method of network traffic based on QPSO algorithm and fuzzy wavelet neural network is proposed in this paper. Firstly, quantum-behaved particle swarm optimization (QPSO) was introduced. Then, the structure and operation algorithms of WFNN are presented. The pa...

  9. Ant colony optimization algorithm for signal coordination of oversaturated traffic networks.

    Science.gov (United States)

    2010-05-01

    Traffic congestion is a daily and growing problem of the modern era in mostly all major cities in the world. : Increasing traffic demand strains the existing transportation system, leading to oversaturated network : conditions, especially at peak hou...

  10. Modeling, Identification, Estimation, and Simulation of Urban Traffic Flow in Jakarta and Bandung

    Directory of Open Access Journals (Sweden)

    Herman Y. Sutarto

    2015-06-01

    Full Text Available This paper presents an overview of urban traffic flow from the perspective of system theory and stochastic control. The topics of modeling, identification, estimation and simulation techniques are evaluated and validated using actual traffic flow data from the city of Jakarta and Bandung, Indonesia, and synthetic data generated from traffic micro-simulator VISSIM. The results on particle filter (PF based state estimation and Expectation-Maximization (EM based parameter estimation (identification confirm the proposed model gives satisfactory results that capture the variation of urban traffic flow. The combination of the technique and the simulator platform assembles possibility to develop a real-time traffic light controller.  

  11. Heterogeneous delivering capability promotes traffic efficiency in complex networks

    Science.gov (United States)

    Zhu, Yan-Bo; Guan, Xiang-Min; Zhang, Xue-Jun

    2015-12-01

    Traffic is one of the most fundamental dynamical processes in networked systems. With the homogeneous delivery capability of nodes, the global dynamic routing strategy proposed by Ling et al. [Phys. Rev. E81, 016113 (2010)] adequately uses the dynamic information during the process and thus it can reach a quite high network capacity. In this paper, based on the global dynamic routing strategy, we proposed a heterogeneous delivery allocation strategy of nodes on scale-free networks with consideration of nodes degree. It is found that the network capacity as well as some other indexes reflecting transportation efficiency are further improved. Our work may be useful for the design of more efficient routing strategies in communication or transportation systems.

  12. Methods to improve traffic flow and noise exposure estimation on minor roads.

    Science.gov (United States)

    Morley, David W; Gulliver, John

    2016-09-01

    Address-level estimates of exposure to road traffic noise for epidemiological studies are dependent on obtaining data on annual average daily traffic (AADT) flows that is both accurate and with good geographical coverage. National agencies often have reliable traffic count data for major roads, but for residential areas served by minor roads, especially at national scale, such information is often not available or incomplete. Here we present a method to predict AADT at the national scale for minor roads, using a routing algorithm within a geographical information system (GIS) to rank roads by importance based on simulated journeys through the road network. From a training set of known minor road AADT, routing importance is used to predict AADT on all UK minor roads in a regression model along with the road class, urban or rural location and AADT on the nearest major road. Validation with both independent traffic counts and noise measurements show that this method gives a considerable improvement in noise prediction capability when compared to models that do not give adequate consideration to minor road variability (Spearman's rho. increases from 0.46 to 0.72). This has significance for epidemiological cohort studies attempting to link noise exposure to adverse health outcomes. Copyright © 2016 Elsevier Ltd. All rights reserved.

  13. TRAFFIC TIME SERIES FORECASTING BY FEEDFORWARD NEURAL NETWORK: A CASE STUDY BASED ON TRAFFIC DATA OF MONROE

    Directory of Open Access Journals (Sweden)

    M. Raeesi

    2014-10-01

    Full Text Available Short time prediction is one of the most important factors in intelligence transportation system (ITS. In this research, the use of feed forward neural network for traffic time-series prediction is presented. In this paper, the traffic in one direction of the road segment is predicted. The input of the neural network is the time delay data exported from the road traffic data of Monroe city. The time delay data is used for training the network. For generating the time delay data, the traffic data related to the first 300 days of 2008 is used. The performance of the feed forward neural network model is validated using the real observation data of the 301st day.

  14. A Traffic Prediction Model for Self-Adapting Routing Overlay Network in Publish/Subscribe System

    Directory of Open Access Journals (Sweden)

    Meng Chi

    2017-01-01

    Full Text Available In large-scale location-based service, an ideal situation is that self-adapting routing strategies use future traffic data as input to generate a topology which could adapt to the changing traffic well. In the paper, we propose a traffic prediction model for the broker in publish/subscribe system, which can predict the traffic of the link in future by neural network. We first introduced our traffic prediction model and then described the model integration. Finally, the experimental results show that our traffic prediction model could predict the traffic of link well.

  15. Estimating Traffic Accidents in Turkey Using Differential Evolution Algorithm

    Science.gov (United States)

    Akgüngör, Ali Payıdar; Korkmaz, Ersin

    2017-06-01

    Estimating traffic accidents play a vital role to apply road safety procedures. This study proposes Differential Evolution Algorithm (DEA) models to estimate the number of accidents in Turkey. In the model development, population (P) and the number of vehicles (N) are selected as model parameters. Three model forms, linear, exponential and semi-quadratic models, are developed using DEA with the data covering from 2000 to 2014. Developed models are statistically compared to select the best fit model. The results of the DE models show that the linear model form is suitable to estimate the number of accidents. The statistics of this form is better than other forms in terms of performance criteria which are the Mean Absolute Percentage Errors (MAPE) and the Root Mean Square Errors (RMSE). To investigate the performance of linear DE model for future estimations, a ten-year period from 2015 to 2024 is considered. The results obtained from future estimations reveal the suitability of DE method for road safety applications.

  16. A Unified Monitoring Framework for Energy Consumption and Network Traffic

    Directory of Open Access Journals (Sweden)

    Florentin Clouet

    2015-08-01

    Full Text Available Providing experimenters with deep insight about the effects of their experiments is a central feature of testbeds. In this paper, we describe Kwapi, a framework designed in the context of the Grid'5000 testbed, that unifies measurements for both energy consumption and network traffic. Because all measurements are taken at the infrastructure level (using sensors in power and network equipment, using this framework has no dependencies on the experiments themselves. Initially designed for OpenStack infrastructures, the Kwapi framework allows monitoring and reporting of energy consumption of distributed platforms. In this article, we present the extension of Kwapi to network monitoring, and outline how we overcame several challenges: scaling to a testbed the size of Grid'5000 while still providing high-frequency measurements; providing long-term loss-less storage of measurements; handling operational issues when deploying such a tool on a real infrastructure.

  17. An Architectural Concept for Intrusion Tolerance in Air Traffic Networks

    Science.gov (United States)

    Maddalon, Jeffrey M.; Miner, Paul S.

    2003-01-01

    The goal of an intrusion tolerant network is to continue to provide predictable and reliable communication in the presence of a limited num ber of compromised network components. The behavior of a compromised network component ranges from a node that no longer responds to a nod e that is under the control of a malicious entity that is actively tr ying to cause other nodes to fail. Most current data communication ne tworks do not include support for tolerating unconstrained misbehavio r of components in the network. However, the fault tolerance communit y has developed protocols that provide both predictable and reliable communication in the presence of the worst possible behavior of a limited number of nodes in the system. One may view a malicious entity in a communication network as a node that has failed and is behaving in an arbitrary manner. NASA/Langley Research Center has developed one such fault-tolerant computing platform called SPIDER (Scalable Proces sor-Independent Design for Electromagnetic Resilience). The protocols and interconnection mechanisms of SPIDER may be adapted to large-sca le, distributed communication networks such as would be required for future Air Traffic Management systems. The predictability and reliabi lity guarantees provided by the SPIDER protocols have been formally v erified. This analysis can be readily adapted to similar network stru ctures.

  18. A hybrid queuing strategy for network traffic on scale-free networks

    Science.gov (United States)

    Cai, Kai-Quan; Yu, Lu; Zhu, Yan-Bo

    2017-02-01

    In this paper, a hybrid queuing strategy (HQS) is proposed in traffic dynamics model on scale-free networks, where the delivery priority of packets in the queue is related to their distance to destination and the queue length of next jump. We compare the performance of the proposed HQS with that of the traditional first-in-first-out (FIFO) queuing strategy and the shortest-remaining-path-first (SRPF) queuing strategy proposed by Du et al. It is observed that the network traffic efficiency utilizing HQS with suitable value of parameter h can be further improved in the congestion state. Our work provides new insights for the understanding of the networked-traffic systems.

  19. Cost estimates for near-term depolyment of advanced traffic management systems. Final report

    Energy Technology Data Exchange (ETDEWEB)

    Stevens, S.S.; Chin, S.M.

    1993-02-15

    The objective of this study is to provide cost est engineering, design, installation, operation and maintenance of Advanced Traffic Management Systems (ATMS) in the largest 75 metropolitan areas in the United States. This report gives estimates for deployment costs for ATMS in the next five years, subject to the qualifications and caveats set out in following paragraphs. The report considers infrastructure components required to realize fully a functional ATMS over each of two highway networks (as discussed in the Section describing our general assumptions) under each of the four architectures identified in the MITRE Intelligent Vehicle Highway Systems (IVHS) Architecture studies. The architectures are summarized in this report in Table 2. Estimates are given for eight combinations of highway networks and architectures. We estimate that it will cost between $8.5 Billion (minimal network) and $26 Billion (augmented network) to proceed immediately with deployment of ATMS in the largest 75 metropolitan areas. Costs are given in 1992 dollars, and are not adjusted for future inflation. Our estimates are based partially on completed project costs, which have been adjusted to 1992 dollars. We assume that a particular architecture will be chosen; projected costs are broken by architecture.

  20. Effects of traffic generation patterns on the robustness of complex networks

    Science.gov (United States)

    Wu, Jiajing; Zeng, Junwen; Chen, Zhenhao; Tse, Chi K.; Chen, Bokui

    2018-02-01

    Cascading failures in communication networks with heterogeneous node functions are studied in this paper. In such networks, the traffic dynamics are highly dependent on the traffic generation patterns which are in turn determined by the locations of the hosts. The data-packet traffic model is applied to Barabási-Albert scale-free networks to study the cascading failures in such networks and to explore the effects of traffic generation patterns on network robustness. It is found that placing the hosts at high-degree nodes in a network can make the network more robust against both intentional attacks and random failures. It is also shown that the traffic generation pattern plays an important role in network design.

  1. Traffic Steering Framework for Mobile-Assisted Resource Management in Heterogeneous Networks

    DEFF Research Database (Denmark)

    Dogadaev, Anton Konstantinovich; Checko, Aleksandra; Popovska Avramova, Andrijana

    2013-01-01

    With the expected growth of mobile data traffic it is essential to manage the network resources efficiently. In order to undertake this challenge, we propose a framework for network-centric, mobile-assisted resource management, which facilitates traffic offloading from mobile network to Wi...

  2. Discovering vesicle traffic network constraints by model checking.

    Science.gov (United States)

    Shukla, Ankit; Bhattacharyya, Arnab; Kuppusamy, Lakshmanan; Srivas, Mandayam; Thattai, Mukund

    2017-01-01

    A eukaryotic cell contains multiple membrane-bound compartments. Transport vesicles move cargo between these compartments, just as trucks move cargo between warehouses. These processes are regulated by specific molecular interactions, as summarized in the Rothman-Schekman-Sudhof model of vesicle traffic. The whole structure can be represented as a transport graph: each organelle is a node, and each vesicle route is a directed edge. What constraints must such a graph satisfy, if it is to represent a biologically realizable vesicle traffic network? Graph connectedness is an informative feature: 2-connectedness is necessary and sufficient for mass balance, but stronger conditions are required to ensure correct molecular specificity. Here we use Boolean satisfiability (SAT) and model checking as a framework to discover and verify graph constraints. The poor scalability of SAT model checkers often prevents their broad application. By exploiting the special structure of the problem, we scale our model checker to vesicle traffic systems with reasonably large numbers of molecules and compartments. This allows us to test a range of hypotheses about graph connectivity, which can later be proved in full generality by other methods.

  3. Control of Networked Traffic Flow Distribution - A Stochastic Distribution System Perspective

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Hong [Pacific Northwest National Laboratory (PNNL); Aziz, H M Abdul [ORNL; Young, Stan [National Renewable Energy Laboratory (NREL); Patil, Sagar [Pacific Northwest National Laboratory (PNNL)

    2017-10-01

    Networked traffic flow is a common scenario for urban transportation, where the distribution of vehicle queues either at controlled intersections or highway segments reflect the smoothness of the traffic flow in the network. At signalized intersections, the traffic queues are controlled by traffic signal control settings and effective traffic lights control would realize both smooth traffic flow and minimize fuel consumption. Funded by the Energy Efficient Mobility Systems (EEMS) program of the Vehicle Technologies Office of the US Department of Energy, we performed a preliminary investigation on the modelling and control framework in context of urban network of signalized intersections. In specific, we developed a recursive input-output traffic queueing models. The queue formation can be modeled as a stochastic process where the number of vehicles entering each intersection is a random number. Further, we proposed a preliminary B-Spline stochastic model for a one-way single-lane corridor traffic system based on theory of stochastic distribution control.. It has been shown that the developed stochastic model would provide the optimal probability density function (PDF) of the traffic queueing length as a dynamic function of the traffic signal setting parameters. Based upon such a stochastic distribution model, we have proposed a preliminary closed loop framework on stochastic distribution control for the traffic queueing system to make the traffic queueing length PDF follow a target PDF that potentially realizes the smooth traffic flow distribution in a concerned corridor.

  4. SmartCop: Enabling Smart Traffic Violations Ticketing in Vehicular Named Data Networks

    Directory of Open Access Journals (Sweden)

    Syed Hassan Ahmed

    2016-01-01

    Full Text Available Recently, various applications for Vehicular Ad hoc Networks (VANETs have been proposed and smart traffic violation ticketing is one of them. On the other hand, the new Information-Centric Networking (ICN architectures have emerged and been investigated into VANETs, such as Vehicular Named Data Networking (VNDN. However, the existing applications in VANETs are not suitable for VNDN paradigm due to the dependency on a “named content” instead of a current “host-centric” approach. Thus, we need to design the emerging and new architectures for VNDN applications. In this paper, we propose a smart traffic violation ticketing (TVT system for VNDN, named as SmartCop, that enables a cop vehicle (CV to issue tickets for traffic violation(s to the offender(s autonomously, once they are in the transmission range of that CV. The ticket issuing delay, messaging cost, and percentage of violations detected for varying number of vehicles, violators, CVs, and vehicles speeds are estimated through simulations. In addition, we provide a road map of future research directions for enabling safe driving experience in future cars aided with VNDN technology.

  5. Dynamic traffic grooming for port number optimization in WDM optical mesh networks

    Science.gov (United States)

    Huang, Jun; Zeng, Qingji; Liu, Jimin; Xiao, Pengcheng; Liu, Hua; Xiao, Shilin

    2004-04-01

    In this paper, the objective was optimizing the port number with dynamic traffic grooming of SDH/SONET WDM mesh networks to give useful referenced data to networks design and the cost control of networks. The performances of different path select routing algorithms were evaluated in WDM grooming networks by considering traffic of different bandwidth requests. Finally, the results were presented and compared with in distributed-controlled WDM mesh networks.

  6. Radio resource management for mobile traffic offloading in heterogeneous cellular networks

    CERN Document Server

    Wu, Yuan; Huang, Jianwei; Shen, Xuemin (Sherman)

    2017-01-01

    This SpringerBrief offers two concrete design examples for traffic offloading. The first is an optimal resource allocation for small-cell based traffic offloading that aims at minimizing mobile users’ data cost. The second is an optimal resource allocation for device-to-device assisted traffic offloading that also minimizes the total energy consumption and cellular link usage (while providing an overview of the challenging issues). Both examples illustrate the importance of proper resource allocation to the success of traffic offloading, show the consequent performance advantages of executing optimal resource allocation, and present the methodologies to achieve the corresponding optimal offloading solution for traffic offloading in heterogeneous cellular networks. The authors also include an overview of heterogeneous cellular networks and explain different traffic offloading paradigms ranging from uplink traffic offloading through small cells to downlink traffic offloading via mobile device-to-device cooper...

  7. Intelligent Controlling Simulation of Traffic Flow in a Small City Network

    Science.gov (United States)

    Fouladvand, M. Ebrahim; Shaebani, M. Reza; Sadjadi, Zeinab

    2004-11-01

    We propose a two dimensional probabilistic cellular automata for the description of traffic flow in a small city network composed of two intersections. The traffic in the network is controlled by a set of traffic lights which can be operated both in fixed-time and a traffic responsive manner. Vehicular dynamics is simulated and the total delay experienced by the traffic is evaluated within specified time intervals. We investigate both decentralized and centralized traffic responsive schemes and in particular discuss the implementation of the green-wave strategy. Our investigations prove that the network delay strongly depends on the signalisation strategy. We show that in some traffic conditions, the application of the green-wave scheme may destructively lead to the increment of the global delay.

  8. A Comparison of Techniques for Reducing Unicast Traffic in HSR Networks

    Directory of Open Access Journals (Sweden)

    Nguyen Xuan Tien

    2015-10-01

    Full Text Available This paper investigates several existing techniques for reducing high-availability seamless redundancy (HSR unicast traffic in HSR networks for substation automation systems (SAS. HSR is a redundancy protocol for Ethernet networks that provides duplicate frames for separate physical paths with zero recovery time. This feature of HSR makes it very suited for real-time and mission-critical applications such as SAS systems. HSR is one of the redundancy protocols selected for SAS systems. However, the standard HSR protocol generates too much unnecessary redundant unicast traffic in connected-ring networks. This drawback degrades network performance and may cause congestion and delay. Several techniques have been proposed to reduce the redundant unicast traffic, resulting in the improvement of network performance in HSR networks. These HSR traffic reduction techniques are broadly classified into two categories based on their traffic reduction manner, including traffic filtering-based techniques and predefined path-based techniques. In this paper, we provide an overview and comparison of these HSR traffic reduction techniques found in the literature. The concepts, operational principles, network performance, advantages, and disadvantages of these techniques are investigated, summarized. We also provide a comparison of the traffic performance of these HSR traffic reduction techniques.

  9. Model for Detection and Classification of DDoS Traffic Based on Artificial Neural Network

    Directory of Open Access Journals (Sweden)

    D. Peraković

    2017-06-01

    Full Text Available Detection of DDoS (Distributed Denial of Service traffic is of great importance for the availability protection of services and other information and communication resources. The research presented in this paper shows the application of artificial neural networks in the development of detection and classification model for three types of DDoS attacks and legitimate network traffic. Simulation results of developed model showed accuracy of 95.6% in classification of pre-defined classes of traffic.

  10. An Improved ARIMA-Based Traffic Anomaly Detection Algorithm for Wireless Sensor Networks

    OpenAIRE

    Qin Yu; Lyu Jibin; Lirui Jiang

    2016-01-01

    Traffic anomaly detection is emerging as a necessary component as wireless networks gain popularity. In this paper, based on the improved Autoregressive Integrated Moving Average (ARIMA) model, we propose a traffic anomaly detection algorithm for wireless sensor networks (WSNs) which considers the particular imbalanced, nonstationary properties of the WSN traffic and the limited energy and computing capacity of the wireless sensors at the same time. We systematically analyze the characteristi...

  11. On the existence of efficient solutions to vector optimization problem of traffic flow on network

    Directory of Open Access Journals (Sweden)

    T. A. Bozhanova

    2009-09-01

    Full Text Available We studied traffic flow models in vector-valued optimization statement where the flow is controlled at the nodes of network. We considered the case when an objective mapping possesses a weakened property of upper semicontinuity and made no assumptions on the interior of the ordering cone. The sufficient conditions for the existence of efficient controls of the traffic problems are derived. The existence of efficient solutions of vector optimization problem for traffic flow on network are also proved.

  12. On the existence of efficient solutions to vector optimization problem of traffic flow on network

    OpenAIRE

    T. A. Bozhanova

    2009-01-01

    We studied traffic flow models in vector-valued optimization statement where the flow is controlled at the nodes of network. We considered the case when an objective mapping possesses a weakened property of upper semicontinuity and made no assumptions on the interior of the ordering cone. The sufficient conditions for the existence of efficient controls of the traffic problems are derived. The existence of efficient solutions of vector optimization problem for traffic flow on network are also...

  13. Traffic Engineering of Peer-Assisted Content Delivery Network with Content-Oriented Incentive Mechanism

    National Research Council Canada - National Science Library

    MAKI, Naoya; NISHIO, Takayuki; SHINKUMA, Ryoichi; MORI, Tatsuya; KAMIYAMA, Noriaki; KAWAHARA, Ryoichi; TAKAHASHI, Tatsuro

    2012-01-01

    In content services where people purchase and download large-volume contents, minimizing network traffic is crucial for the service provider and the network operator since they want to lower the cost...

  14. Feasibility of Optical Packet Switched WDM Networks without Packet Synchronisation Under Bursty Traffic Conditions

    DEFF Research Database (Denmark)

    Fjelde, Tina; Hansen, Peter Bukhave; Kloch, Allan

    1999-01-01

    We show that complex packet synchronisation may be avoided in optical packetswitched networks. Detailed traffic analysis demonstrates that packet lossratios of 1e-10 are feasible under bursty traffic conditions for a highcapacity network consisting of asynchronously operated add-drop switch nodes...

  15. Usage of Modified Holt-Winters Method in the Anomaly Detection of Network Traffic: Case Studies

    Directory of Open Access Journals (Sweden)

    Maciej Szmit

    2012-01-01

    Full Text Available The traditional Holt-Winters method is used, among others, in behavioural analysis of network traffic for development of adaptive models for various types of traffic in sample computer networks. This paper is devoted to the application of extended versions of these models for development of predicted templates and intruder detection.

  16. Usage of Modified Holt-Winters Method in the Anomaly Detection of Network Traffic: Case Studies

    OpenAIRE

    Maciej Szmit; Anna Szmit

    2012-01-01

    The traditional Holt-Winters method is used, among others, in behavioural analysis of network traffic for development of adaptive models for various types of traffic in sample computer networks. This paper is devoted to the application of extended versions of these models for development of predicted templates and intruder detection.

  17. MULTI-LEVEL NETWORK RESILIENCE: TRAFFIC ANALYSIS, ANOMALY DETECTION AND SIMULATION

    Directory of Open Access Journals (Sweden)

    Angelos Marnerides

    2011-06-01

    Full Text Available Traffic analysis and anomaly detection have been extensively used to characterize network utilization as well as to identify abnormal network traffic such as malicious attacks. However, so far, techniques for traffic analysis and anomaly detection have been carried out independently, relying on mechanisms and algorithms either in edge or in core networks alone. In this paper we propose the notion of multi-level network resilience, in order to provide a more robust traffic analysis and anomaly detection architecture, combining mechanisms and algorithms operating in a coordinated fashion both in the edge and in the core networks. This work is motivated by the potential complementarities between the research being developed at IIT Madras and Lancaster University. In this paper we describe the current work being developed at IIT Madras and Lancaster on traffic analysis and anomaly detection, and outline the principles of a multi-level resilience architecture.

  18. Systematic Hybrid Network Scheduling for Multiple Traffic Classes with Host Timing and Phase Constraints

    Science.gov (United States)

    Varadarajan, Srivatsan (Inventor); Hall, Brendan (Inventor); Smithgall, William Todd (Inventor); Bonk, Ted (Inventor); DeLay, Benjamin F. (Inventor)

    2017-01-01

    Systems and methods for systematic hybrid network scheduling for multiple traffic classes with host timing and phase constraints are provided. In certain embodiments, a method of scheduling communications in a network comprises scheduling transmission of virtual links pertaining to a first traffic class on a global schedule to coordinate transmission of the virtual links pertaining to the first traffic class across all transmitting end stations on the global schedule; and scheduling transmission of each virtual link pertaining to a second traffic class on a local schedule of the respective transmitting end station from which each respective virtual link pertaining to the second traffic class is transmitted such that transmission of each virtual link pertaining to the second traffic class is coordinated only at the respective end station from which each respective virtual link pertaining to the second traffic class is transmitted.

  19. File Detection On Network Traffic Using Approximate Matching

    Directory of Open Access Journals (Sweden)

    Frank Breitinger

    2014-09-01

    Full Text Available In recent years, Internet technologies changed enormously and allow faster Internet connections, higher data rates and mobile usage. Hence, it is possible to send huge amounts of data / files easily which is often used by insiders or attackers to steal intellectual property. As a consequence, data leakage prevention systems (DLPS have been developed which analyze network traffic and alert in case of a data leak. Although the overall concepts of the detection techniques are known, the systems are mostly closed and commercial.Within this paper we present a new technique for network trac analysis based on approximate matching (a.k.a fuzzy hashing which is very common in digital forensics to correlate similar files. This paper demonstrates how to optimize and apply them on single network packets. Our contribution is a straightforward concept which does not need a comprehensive conguration: hash the file and store the digest in the database. Within our experiments we obtained false positive rates between 10-4 and 10-5 and an algorithm throughput of over 650 Mbit/s.

  20. Network Traffic Features for Anomaly Detection in Specific Industrial Control System Network

    Directory of Open Access Journals (Sweden)

    Matti Mantere

    2013-09-01

    Full Text Available The deterministic and restricted nature of industrial control system networks sets them apart from more open networks, such as local area networks in office environments. This improves the usability of network security, monitoring approaches that would be less feasible in more open environments. One of such approaches is machine learning based anomaly detection. Without proper customization for the special requirements of the industrial control system network environment, many existing anomaly or misuse detection systems will perform sub-optimally. A machine learning based approach could reduce the amount of manual customization required for different industrial control system networks. In this paper we analyze a possible set of features to be used in a machine learning based anomaly detection system in the real world industrial control system network environment under investigation. The network under investigation is represented by architectural drawing and results derived from network trace analysis. The network trace is captured from a live running industrial process control network and includes both control data and the data flowing between the control network and the office network. We limit the investigation to the IP traffic in the traces.

  1. Impact of Bimodal Traffic on Latency in Optical Burst Switching Networks

    Directory of Open Access Journals (Sweden)

    Yuhua Chen

    2008-01-01

    Full Text Available This paper analyzes the impact of bimodal traffic composition on latency in optical burst switching networks. In particular, it studies the performance degradation to short-length packets caused by longer packets, both of which are part of a heterogeneous traffic model. The paper defines a customer satisfaction index for each of the classes of traffic, and a composite satisfaction index. The impact of higher overall utilization of the network as well as that of the ratio of the traffic mix on each of the customer satisfaction indices is specifically addressed.

  2. Early estimate of motor vehicle traffic fatalities in 2009 : a brief statistical summary

    Science.gov (United States)

    2010-03-01

    statistical projection of traffic fatalities in 2009 shows that an estimated 33,963 people died in motor vehicle traffic crashes. This represents a decline of about 8.9 percent as compared to the 37,261 fatalities that occurred in 2008, as shown in T...

  3. Estimation of traffic recovery time for different flow regimes on freeways.

    Science.gov (United States)

    2008-06-01

    This study attempts to estimate post-incident traffic recovery time along a freeway using Monte Carlo simulation techniques. It has been found that there is a linear relationship between post-incident traffic recovery time, and incident time and traf...

  4. Estimation of Bimodal Urban Link Travel Time Distribution and Its Applications in Traffic Analysis

    Directory of Open Access Journals (Sweden)

    Yuxiong Ji

    2015-01-01

    Full Text Available Vehicles travelling on urban streets are heavily influenced by traffic signal controls, pedestrian crossings, and conflicting traffic from cross streets, which would result in bimodal travel time distributions, with one mode corresponding to travels without delays and the other travels with delays. A hierarchical Bayesian bimodal travel time model is proposed to capture the interrupted nature of urban traffic flows. The travel time distributions obtained from the proposed model are then considered to analyze traffic operations and estimate travel time distribution in real time. The advantage of the proposed bimodal model is demonstrated using empirical data, and the results are encouraging.

  5. Distance Distributions and Proximity Estimation Given Knowledge of the Heterogeneous Network Layout

    OpenAIRE

    Xenakis, Dionysis; Merakos, Lazaros; Kountouris, Marios; Passas, Nikos; Verikoukis, Christos

    2015-01-01

    Today's heterogeneous wireless network (HWN) is a collection of ubiquitous wireless networking elements (WNEs) that support diverse functional capabilities and networking purposes. In such a heterogeneous networking environment, proximity estimation will play a key role for the seamless support of emerging applications that span from the direct exchange of localized traffic between homogeneous WNEs (peer-to-peer communications) to positioning for autonomous systems using location information ...

  6. Modelling Altitude Information in Two-Dimensional Traffic Networks for Electric Mobility Simulation

    OpenAIRE

    Diogo Santos; José Pinto; Rossetti, Rosaldo J. F.; Eugénio Oliveira

    2016-01-01

    Elevation data is important for electric vehicle simulation. However, traffic simulators are often two-dimensional and do not offer the capability of modelling urban networks taking elevation into account. Specifically, SUMO - Simulation of Urban Mobility, a popular microscopic traffic simulator, relies on networks previously modelled with elevation data as to provide this information during simulations. This work tackles the problem of adding elevation data to urban network models - particul...

  7. Next generation network based carrier ethernet test bed for IPTV traffic

    DEFF Research Database (Denmark)

    Fu, Rong; Berger, Michael Stübert; Zheng, Yu

    2009-01-01

    This paper presents a Carrier Ethernet (CE) test bed based on the Next Generation Network (NGN) framework. After the concept of CE carried out by Metro Ethernet Forum (MEF), the carrier-grade Ethernet are obtaining more and more interests and being investigated as the low cost and high performance...... services of transport network to carry the IPTV traffic. This test bed is approaching to support the research on providing a high performance carrier-grade Ethernet transport network for IPTV traffic....

  8. Curve Estimation of Number of People Killed in Traffic Accidents in Turkey

    Science.gov (United States)

    Berkhan Akalin, Kadir; Karacasu, Murat; Altin, Arzu Yavuz; Ergül, Bariş

    2016-10-01

    One or more than one vehicle in motion on the highway involving death, injury and loss events which have resulted are called accidents. As a result of increasing population and traffic density, traffic accidents continue to increase and this leads to both human losses and harm to the economy. In addition, also leads to social problems. As a result of increasing population and traffic density, traffic accidents continue to increase and this leads to both human losses and harm to the economy. In addition to this, it also leads to social problems. As a result of traffic accidents, millions of people die year by year. A great majority of these accidents occur in developing countries. One of the most important tasks of transportation engineers is to reduce traffic accidents by creating a specific system. For that reason, statistical information about traffic accidents which occur in the past years should be organized by versed people. Factors affecting the traffic accidents are analyzed in various ways. In this study, modelling the number of people killed in traffic accidents in Turkey is determined. The dead people were modelled using curve fitting method with the number of people killed in traffic accidents in Turkey dataset between 1990 and 2014. It was also predicted the number of dead people by using various models for the future. It is decided that linear model is suitable for the estimates.

  9. Learning Traffic as Images: A Deep Convolutional Neural Network for Large-Scale Transportation Network Speed Prediction.

    Science.gov (United States)

    Ma, Xiaolei; Dai, Zhuang; He, Zhengbing; Ma, Jihui; Wang, Yong; Wang, Yunpeng

    2017-04-10

    This paper proposes a convolutional neural network (CNN)-based method that learns traffic as images and predicts large-scale, network-wide traffic speed with a high accuracy. Spatiotemporal traffic dynamics are converted to images describing the time and space relations of traffic flow via a two-dimensional time-space matrix. A CNN is applied to the image following two consecutive steps: abstract traffic feature extraction and network-wide traffic speed prediction. The effectiveness of the proposed method is evaluated by taking two real-world transportation networks, the second ring road and north-east transportation network in Beijing, as examples, and comparing the method with four prevailing algorithms, namely, ordinary least squares, k-nearest neighbors, artificial neural network, and random forest, and three deep learning architectures, namely, stacked autoencoder, recurrent neural network, and long-short-term memory network. The results show that the proposed method outperforms other algorithms by an average accuracy improvement of 42.91% within an acceptable execution time. The CNN can train the model in a reasonable time and, thus, is suitable for large-scale transportation networks.

  10. Traffic modeling in the integrated cellular ad hoc network system

    Science.gov (United States)

    Yamanaka, Sachiko; Shimohara, Katsunori

    2005-10-01

    We present the modeling and evaluation in the integrated cellular and ad hoc network system. The system is modeled using queueing theory and we derive some characteristic values. As regards a system model of two cells, M channels are assigned to each cell and a relay station is set in the overlapped area of two cells. New calls in cellA can be relayed to cellB if the channels in cellA are all busy and the mobile stations are in the covered area by a relay station. Handoff calls select the channels of the cell that the number of empty channels are more in the two cells. If the channels of the both cells are all busy, handoff calls can wait in a queue with the capacity Q while mobile stations are in the handoff area. However, so as not to make handoff calls possess channels prior to new calls, we manage it with the method being different from the other researches. This system is more flexible than cellular networks, the bias of traffic gets smaller and it leads to an efficient channel using. We model and evaluate our system by assuming that the dwelling time is distributed with non-exponential distribution as well as exponential one. In numerical results, we compare the characteristic values in our system with those in non-relaying system, see how the characteristic values are affected when the covered area by a relay station changes, and verify the effectiveness of our system.

  11. Neural Network for Estimating Conditional Distribution

    DEFF Research Database (Denmark)

    Schiøler, Henrik; Kulczycki, P.

    Neural networks for estimating conditional distributions and their associated quantiles are investigated in this paper. A basic network structure is developed on the basis of kernel estimation theory, and consistency is proved from a mild set of assumptions. A number of applications within...... statistcs, decision theory and signal processing are suggested, and a numerical example illustrating the capabilities of the elaborated network is given...

  12. Understanding structure of urban traffic network based on spatial-temporal correlation analysis

    Science.gov (United States)

    Yang, Yanfang; Jia, Limin; Qin, Yong; Han, Shixiu; Dong, Honghui

    2017-08-01

    Understanding the structural characteristics of urban traffic network comprehensively can provide references for improving road utilization rate and alleviating traffic congestion. This paper focuses on the spatial-temporal correlations between different pairs of traffic series and proposes a complex network-based method of constructing the urban traffic network. In the network, the nodes represent road segments, and an edge between a pair of nodes is added depending on the result of significance test for the corresponding spatial-temporal correlation. Further, a modified PageRank algorithm, named the geographical weight-based PageRank algorithm (GWPA), is proposed to analyze the spatial distribution of important segments in the road network. Finally, experiments are conducted by using three kinds of traffic series collected from the urban road network in Beijing. Experimental results show that the urban traffic networks constructed by three traffic variables all indicate both small-world and scale-free characteristics. Compared with the results of PageRank algorithm, GWPA is proved to be valid in evaluating the importance of segments and identifying the important segments with small degree.

  13. Spatio-temporal propagation of traffic jams in urban traffic networks

    OpenAIRE

    Jiang, Yinan; Kang, Rui; Li, Daqing; Guo, Shengmin; Havlin, Shlomo

    2017-01-01

    Since the first reported traffic jam about a century ago, traffic congestion has been intensively studied with various methods ranging from macroscopic to microscopic viewpoint. However, due to the population growth and fast civilization, traffic congestion has become significantly worse not only leading to economic losses, but also causes environment damages. Without understanding of jams spatio-temporal propagation behavior in a city, it is impossible to develop efficient mitigation strateg...

  14. Robust and Agile System against Fault and Anomaly Traffic in Software Defined Networks

    Directory of Open Access Journals (Sweden)

    Mihui Kim

    2017-03-01

    Full Text Available The main advantage of software defined networking (SDN is that it allows intelligent control and management of networking though programmability in real time. It enables efficient utilization of network resources through traffic engineering, and offers potential attack defense methods when abnormalities arise. However, previous studies have only identified individual solutions for respective problems, instead of finding a more global solution in real time that is capable of addressing multiple situations in network status. To cover diverse network conditions, this paper presents a comprehensive reactive system for simultaneously monitoring failures, anomalies, and attacks for high availability and reliability. We design three main modules in the SDN controller for a robust and agile defense (RAD system against network anomalies: a traffic analyzer, a traffic engineer, and a rule manager. RAD provides reactive flow rule generation to control traffic while detecting network failures, anomalies, high traffic volume (elephant flows, and attacks. The traffic analyzer identifies elephant flows, traffic anomalies, and attacks based on attack signatures and network monitoring. The traffic engineer module measures network utilization and delay in order to determine the best path for multi-dimensional routing and load balancing under any circumstances. Finally, the rule manager generates and installs a flow rule for the selected best path to control traffic. We implement the proposed RAD system based on Floodlight, an open source project for the SDN controller. We evaluate our system using simulation with and without the aforementioned RAD modules. Experimental results show that our approach is both practical and feasible, and can successfully augment an existing SDN controller in terms of agility, robustness, and efficiency, even in the face of link failures, attacks, and elephant flows.

  15. ENTVis: A Visual Analytic Tool for Entropy-Based Network Traffic Anomaly Detection.

    Science.gov (United States)

    Zhou, Fangfang; Huang, Wei; Zhao, Ying; Shi, Yang; Liang, Xing; Fan, Xiaoping

    2015-01-01

    Entropy-based traffic metrics have received substantial attention in network traffic anomaly detection because entropy can provide fine-grained metrics of traffic distribution characteristics. However, some practical issues--such as ambiguity, lack of detailed distribution information, and a large number of false positives--affect the application of entropy-based traffic anomaly detection. In this work, we introduce a visual analytic tool called ENTVis to help users understand entropy-based traffic metrics and achieve accurate traffic anomaly detection. ENTVis provides three coordinated views and rich interactions to support a coherent visual analysis on multiple perspectives: the timeline group view for perceiving situations and finding hints of anomalies, the Radviz view for clustering similar anomalies in a period, and the matrix view for understanding traffic distributions and diagnosing anomalies in detail. Several case studies have been performed to verify the usability and effectiveness of our method. A further evaluation was conducted via expert review.

  16. On the Use of Machine Learning for Identifying Botnet Network Traffic

    DEFF Research Database (Denmark)

    Stevanovic, Matija; Pedersen, Jens Myrup

    2016-01-01

    contemporary approaches use machine learning techniques for identifying malicious traffic. This paper presents a survey of contemporary botnet detection methods that rely on machine learning for identifying botnet network traffic. The paper provides a comprehensive overview on the existing scientific work thus...... contributing to the better understanding of capabilities, limitations and opportunities of using machine learning for identifying botnet traffic. Furthermore, the paper outlines possibilities for the future development of machine learning-based botnet detection systems....

  17. Freeway travel time estimation using existing fixed traffic sensors : phase 2.

    Science.gov (United States)

    2015-03-01

    Travel time, one of the most important freeway performance metrics, can be easily estimated using the : data collected from fixed traffic sensors, avoiding the need to install additional travel time data collectors. : This project is aimed at fully u...

  18. A NEURAL NETWORK BASED TRAFFIC-AWARE FORWARDING STRATEGY IN NAMED DATA NETWORKING

    Directory of Open Access Journals (Sweden)

    Parisa Bazmi

    2016-11-01

    Full Text Available Named Data Networking (NDN is a new Internet architecture which has been proposed to eliminate TCP/IP Internet architecture restrictions. This architecture is abstracting away the notion of host and working based on naming datagrams. However, one of the major challenges of NDN is supporting QoS-aware forwarding strategy so as to forward Interest packets intelligently over multiple paths based on the current network condition. In this paper, Neural Network (NN Based Traffic-aware Forwarding strategy (NNTF is introduced in order to determine an optimal path for Interest forwarding. NN is embedded in NDN routers to select next hop dynamically based on the path overload probability achieved from the NN. This solution is characterized by load balancing and QoS-awareness via monitoring the available path and forwarding data on the traffic-aware shortest path. The performance of NNTF is evaluated using ndnSIM which shows the efficiency of this scheme in terms of network QoS improvementof17.5% and 72% reduction in network delay and packet drop respectively.

  19. High-speed and high-fidelity system and method for collecting network traffic

    Science.gov (United States)

    Weigle, Eric H [Los Alamos, NM

    2010-08-24

    A system is provided for the high-speed and high-fidelity collection of network traffic. The system can collect traffic at gigabit-per-second (Gbps) speeds, scale to terabit-per-second (Tbps) speeds, and support additional functions such as real-time network intrusion detection. The present system uses a dedicated operating system for traffic collection to maximize efficiency, scalability, and performance. A scalable infrastructure and apparatus for the present system is provided by splitting the work performed on one host onto multiple hosts. The present system simultaneously addresses the issues of scalability, performance, cost, and adaptability with respect to network monitoring, collection, and other network tasks. In addition to high-speed and high-fidelity network collection, the present system provides a flexible infrastructure to perform virtually any function at high speeds such as real-time network intrusion detection and wide-area network emulation for research purposes.

  20. Exact solutions to traffic density estimation problems involving the Lighthill-Whitham-Richards traffic flow model using mixed integer programming

    KAUST Repository

    Canepa, Edward S.

    2012-09-01

    This article presents a new mixed integer programming formulation of the traffic density estimation problem in highways modeled by the Lighthill Whitham Richards equation. We first present an equivalent formulation of the problem using an Hamilton-Jacobi equation. Then, using a semi-analytic formula, we show that the model constraints resulting from the Hamilton-Jacobi equation result in linear constraints, albeit with unknown integers. We then pose the problem of estimating the density at the initial time given incomplete and inaccurate traffic data as a Mixed Integer Program. We then present a numerical implementation of the method using experimental flow and probe data obtained during Mobile Century experiment. © 2012 IEEE.

  1. Enhancing the Quality of Service for Real Time Traffic over Optical Burst Switching (OBS) Networks with Ensuring the Fairness for Other Traffics.

    Science.gov (United States)

    Al-Shargabi, Mohammed A; Shaikh, Asadullah; Ismail, Abdulsamad S

    2016-01-01

    Optical burst switching (OBS) networks have been attracting much consideration as a promising approach to build the next generation optical Internet. A solution for enhancing the Quality of Service (QoS) for high priority real time traffic over OBS with the fairness among the traffic types is absent in current OBS' QoS schemes. In this paper we present a novel Real Time Quality of Service with Fairness Ratio (RT-QoSFR) scheme that can adapt the burst assembly parameters according to the traffic QoS needs in order to enhance the real time traffic QoS requirements and to ensure the fairness for other traffic. The results show that RT-QoSFR scheme is able to fulfill the real time traffic requirements (end to end delay, and loss rate) ensuring the fairness for other traffics under various conditions such as the type of real time traffic and traffic load. RT-QoSFR can guarantee that the delay of the real time traffic packets does not exceed the maximum packets transfer delay value. Furthermore, it can reduce the real time traffic packets loss, at the same time guarantee the fairness for non real time traffic packets by determining the ratio of real time traffic inside the burst to be 50-60%, 30-40%, and 10-20% for high, normal, and low traffic loads respectively.

  2. Enhancing the Quality of Service for Real Time Traffic over Optical Burst Switching (OBS Networks with Ensuring the Fairness for Other Traffics.

    Directory of Open Access Journals (Sweden)

    Mohammed A Al-Shargabi

    Full Text Available Optical burst switching (OBS networks have been attracting much consideration as a promising approach to build the next generation optical Internet. A solution for enhancing the Quality of Service (QoS for high priority real time traffic over OBS with the fairness among the traffic types is absent in current OBS' QoS schemes. In this paper we present a novel Real Time Quality of Service with Fairness Ratio (RT-QoSFR scheme that can adapt the burst assembly parameters according to the traffic QoS needs in order to enhance the real time traffic QoS requirements and to ensure the fairness for other traffic. The results show that RT-QoSFR scheme is able to fulfill the real time traffic requirements (end to end delay, and loss rate ensuring the fairness for other traffics under various conditions such as the type of real time traffic and traffic load. RT-QoSFR can guarantee that the delay of the real time traffic packets does not exceed the maximum packets transfer delay value. Furthermore, it can reduce the real time traffic packets loss, at the same time guarantee the fairness for non real time traffic packets by determining the ratio of real time traffic inside the burst to be 50-60%, 30-40%, and 10-20% for high, normal, and low traffic loads respectively.

  3. Traffic properties for stochastic routings on scale-free networks

    CERN Document Server

    Hayashi, Yukio

    2011-01-01

    For realistic scale-free networks, we investigate the traffic properties of stochastic routing inspired by a zero-range process known in statistical physics. By parameters $\\alpha$ and $\\delta$, this model controls degree-dependent hopping of packets and forwarding of packets with higher performance at more busy nodes. Through a theoretical analysis and numerical simulations, we derive the condition for the concentration of packets at a few hubs. In particular, we show that the optimal $\\alpha$ and $\\delta$ are involved in the trade-off between a detour path for $\\alpha 0$; In the low-performance regime at a small $\\delta$, the wandering path for $\\alpha 0$ and $\\alpha < 0$ is small, neither the wandering long path with short wait trapped at nodes ($\\alpha = -1$), nor the short hopping path with long wait trapped at hubs ($\\alpha = 1$) is advisable. A uniformly random walk ($\\alpha = 0$) yields slightly better performance. We also discuss the congestion phenomena in a more complicated situation with pack...

  4. Minimal-Intrusion Traffic Monitoring And Analysis In Mission-Critical Communication Networks

    Directory of Open Access Journals (Sweden)

    Alberto Domingo Ajenjo

    2003-10-01

    Full Text Available A good knowledge of expected and actual traffic patterns is an essential tool for network planning, design and operation in deployed, mission-critical applications. This paper describes those needs, and explains the Traffic Monitoring and Analysis Platform (TMAP concept, as developed in support of NATO deployed military headquarters Communications and Information Systems. It shows how a TMAP was deployed to a real NATO exercise, to prove the concept and baseline the traffic needs per application, per user community and per time of day. Then, it analyses the obtained results and derives conclusions on how to integrate traffic monitoring and analysis platforms in future deployments.

  5. Entropy Based Analysis of DNS Query Traffic in the Campus Network

    Directory of Open Access Journals (Sweden)

    Dennis Arturo Ludeña Romaña

    2008-10-01

    Full Text Available We carried out the entropy based study on the DNS query traffic from the campus network in a university through January 1st, 2006 to March 31st, 2007. The results are summarized, as follows: (1 The source IP addresses- and query keyword-based entropies change symmetrically in the DNS query traffic from the outside of the campus network when detecting the spam bot activity on the campus network. On the other hand (2, the source IP addresses- and query keywordbased entropies change similarly each other when detecting big DNS query traffic caused by prescanning or distributed denial of service (DDoS attack from the campus network. Therefore, we can detect the spam bot and/or DDoS attack bot by only watching DNS query access traffic.

  6. Developing a New HSR Switching Node (SwitchBox for Improving Traffic Performance in HSR Networks

    Directory of Open Access Journals (Sweden)

    Nguyen Xuan Tien

    2016-01-01

    Full Text Available High availability is crucial for industrial Ethernet networks as well as Ethernet-based control systems such as automation networks and substation automation systems (SAS. Since standard Ethernet does not support fault tolerance capability, the high availability of Ethernet networks can be increased by using redundancy protocols. Various redundancy protocols for Ethernet networks have been developed and standardized, such as rapid spanning tree protocol (RSTP, media redundancy protocol (MRP, parallel redundancy protocol (PRP, high-availability seamless redundancy (HSR and others. RSTP and MRP have switchover delay drawbacks. PRP provides zero recovery time, but requires a duplicate network infrastructure. HSR operation is similar to PRP, but HSR uses a single network. However, the standard HSR protocol is mainly applied to ring-based topologies and generates excessively unnecessary redundant traffic in the network. In this paper, we develop a new switching node for the HSR protocol, called SwitchBox, which is used in HSR networks in order to support any network topology and significantly reduce redundant network traffic, including unicast, multicast and broadcast traffic, compared with standard HSR. By using the SwitchBox, HSR not only provides seamless communications with zero switchover time in case of failure, but it is also easily applied to any network topology and significantly reduces unnecessary redundant traffic in HSR networks.

  7. Traffic Control Algorithm Offering Multi-Class Fairness in PON Based Access Networks

    Science.gov (United States)

    Okumura, Yasuyuki

    This letter proposes a dynamic bandwidth allocation algorithm for access networks based PON (Passive Optical Network). It considers the mixture of transport layer protocols when responding to traffic congestion at the SNI (Service Node Interface). Simulations on a mixture of TCP (Transmission Control Protocol), and UDP (User Datagram Protocol) traffic flows show that the algorithm increases the throughput of TCP, improves the fairness between the two protocols, and solves the congestion problem at the SNI.

  8. Self-control of traffic lights and vehicle flows in urban road networks

    Science.gov (United States)

    Lämmer, Stefan; Helbing, Dirk

    2008-04-01

    Based on fluid-dynamic and many-particle (car-following) simulations of traffic flows in (urban) networks, we study the problem of coordinating incompatible traffic flows at intersections. Inspired by the observation of self-organized oscillations of pedestrian flows at bottlenecks, we propose a self-organization approach to traffic light control. The problem can be treated as a multi-agent problem with interactions between vehicles and traffic lights. Specifically, our approach assumes a priority-based control of traffic lights by the vehicle flows themselves, taking into account short-sighted anticipation of vehicle flows and platoons. The considered local interactions lead to emergent coordination patterns such as 'green waves' and achieve an efficient, decentralized traffic light control. While the proposed self-control adapts flexibly to local flow conditions and often leads to non-cyclical switching patterns with changing service sequences of different traffic flows, an almost periodic service may evolve under certain conditions and suggests the existence of a spontaneous synchronization of traffic lights despite the varying delays due to variable vehicle queues and travel times. The self-organized traffic light control is based on an optimization and a stabilization rule, each of which performs poorly at high utilizations of the road network, while their proper combination reaches a superior performance. The result is a considerable reduction not only in the average travel times, but also of their variation. Similar control approaches could be applied to the coordination of logistic and production processes.

  9. Parameter Estimation for Traffic Noise Models Using a Harmony Search Algorithm

    Directory of Open Access Journals (Sweden)

    Deok-Soon An

    2013-01-01

    Full Text Available A technique has been developed for predicting road traffic noise for environmental assessment, taking into account traffic volume as well as road surface conditions. The ASJ model (ASJ Prediction Model for Road Traffic Noise, 1999, which is based on the sound power level of the noise emitted by the interaction between the road surface and tires, employs regression models for two road surface types: dense-graded asphalt (DGA and permeable asphalt (PA. However, these models are not applicable to other types of road surfaces. Accordingly, this paper introduces a parameter estimation procedure for ASJ-based noise prediction models, utilizing a harmony search (HS algorithm. Traffic noise measurement data for four different vehicle types were used in the algorithm to determine the regression parameters for several road surface types. The parameters of the traffic noise prediction models were evaluated using another measurement set, and good agreement was observed between the predicted and measured sound power levels.

  10. Classification and Prediction of Traffic Flow Based on Real Data Using Neural Networks

    Science.gov (United States)

    Pamuła, Teresa

    2012-12-01

    This paper presents a method of classification of time series of traffic flow, on the section of the main road leading into the city of Gliwice. Video detectors recorded traffic volume data was used, covering the period of one year in 5-minute intervals - from June 2011 to May 2012. In order to classify the data a statistical analysis was performed, which resulted in the proposition of splitting the daily time series into four classes. The series were smoothed to obtain hourly flow rates. The classification was performed using neural networks with different structures and using a variable number of input data. The purpose of classification is the prediction of traffic flow rates in the afternoon basing on the morning traffic and the assessment of daily traffic volumes for a particular day of the week. The results can be utilized by intelligent urban traffic management systems.

  11. Optimization of a Traffic Control Scheme for a Post-Disaster Urban Road Network

    Directory of Open Access Journals (Sweden)

    Zengzhen Shao

    2017-12-01

    Full Text Available Traffic control of urban road networks during emergency rescues is conducive to rapid rescue in the affected areas. However, excessive control will lead to negative impacts on the normal traffic order. We propose a novel model to optimize the traffic control scheme during the post-disaster emergency rescue period named PD-TCM (post-disaster traffic control model. In this model, the vertex and edge betweenness indexes of urban road networks are introduced to evaluate the controllability of the road sections. The gravity field model is also used to adjust the travel time function of different road sections in the control and diverging domains. Experimental results demonstrate that the proposed model can obtain the optimal traffic control scheme efficiently, which gives it the ability to meet the demand of emergency rescues as well as reducing the disturbances caused by controls.

  12. Estimating Conditional Distributions by Neural Networks

    DEFF Research Database (Denmark)

    Kulczycki, P.; Schiøler, Henrik

    1998-01-01

    Neural Networks for estimating conditionaldistributions and their associated quantiles are investigated in this paper. A basic network structure is developed on the basis of kernel estimation theory, and consistency property is considered from a mild set of assumptions. A number of applications...

  13. Real time network traffic monitoring for wireless local area networks based on compressed sensing

    Science.gov (United States)

    Balouchestani, Mohammadreza

    2017-05-01

    A wireless local area network (WLAN) is an important type of wireless networks which connotes different wireless nodes in a local area network. WLANs suffer from important problems such as network load balancing, large amount of energy, and load of sampling. This paper presents a new networking traffic approach based on Compressed Sensing (CS) for improving the quality of WLANs. The proposed architecture allows reducing Data Delay Probability (DDP) to 15%, which is a good record for WLANs. The proposed architecture is increased Data Throughput (DT) to 22 % and Signal to Noise (S/N) ratio to 17 %, which provide a good background for establishing high qualified local area networks. This architecture enables continuous data acquisition and compression of WLAN's signals that are suitable for a variety of other wireless networking applications. At the transmitter side of each wireless node, an analog-CS framework is applied at the sensing step before analog to digital converter in order to generate the compressed version of the input signal. At the receiver side of wireless node, a reconstruction algorithm is applied in order to reconstruct the original signals from the compressed signals with high probability and enough accuracy. The proposed algorithm out-performs existing algorithms by achieving a good level of Quality of Service (QoS). This ability allows reducing 15 % of Bit Error Rate (BER) at each wireless node.

  14. Contribution to the Management of Traffic in Networks

    Directory of Open Access Journals (Sweden)

    Filip Chamraz

    2014-01-01

    Full Text Available The paper deals with Admission control methods (AC in IMS networks (IP multimedia subsystem as one of the elements that help ensure QoS (Quality of service. In the paper we are trying to choose the best AC method for selected IMS network to allow access to the greatest number of users. Of the large number of methods that were tested and considered good we chose two. The paper compares diffusion method and one of the measurement based method, specifically „Simple Sum“. Both methods estimate effective bandwidth to allow access for the greatest number of users/devices and allow them access to prepaid services or multimedia content.

  15. A Network Traffic Prediction Model Based on Quantum-Behaved Particle Swarm Optimization Algorithm and Fuzzy Wavelet Neural Network

    Directory of Open Access Journals (Sweden)

    Kun Zhang

    2016-01-01

    Full Text Available Due to the fact that the fluctuation of network traffic is affected by various factors, accurate prediction of network traffic is regarded as a challenging task of the time series prediction process. For this purpose, a novel prediction method of network traffic based on QPSO algorithm and fuzzy wavelet neural network is proposed in this paper. Firstly, quantum-behaved particle swarm optimization (QPSO was introduced. Then, the structure and operation algorithms of WFNN are presented. The parameters of fuzzy wavelet neural network were optimized by QPSO algorithm. Finally, the QPSO-FWNN could be used in prediction of network traffic simulation successfully and evaluate the performance of different prediction models such as BP neural network, RBF neural network, fuzzy neural network, and FWNN-GA neural network. Simulation results show that QPSO-FWNN has a better precision and stability in calculation. At the same time, the QPSO-FWNN also has better generalization ability, and it has a broad prospect on application.

  16. Estimation of Conditional Quantile using Neural Networks

    DEFF Research Database (Denmark)

    Kulczycki, P.; Schiøler, Henrik

    1999-01-01

    The problem of estimating conditional quantiles using neural networks is investigated here. A basic structure is developed using the methodology of kernel estimation, and a theory guaranteeing con-sistency on a mild set of assumptions is provided. The constructed structure constitutes a basis...... for the design of a variety of different neural networks, some of which are considered in detail. The task of estimating conditional quantiles is related to Bayes point estimation whereby a broad range of applications within engineering, economics and management can be suggested. Numerical results illustrating...... the capabilities of the elaborated neural network are also given....

  17. A Network Traffic Generator Model for Fast Network-on-Chip Simulation

    DEFF Research Database (Denmark)

    Mahadevan, Shankar; Angiolini, Frederico; Storgaard, Michael

    2005-01-01

    and effective Network-on-Chip (NoC) development and debugging environment. By capturing the type and the timestamp of communication events at the boundary of an IP core in a reference environment, the TG can subsequently emulate the core's communication behavior in different environments. Access patterns......For Systems-on-Chip (SoCs) development, a predominant part of the design time is the simulation time. Performance evaluation and design space exploration of such systems in bit- and cycle-true fashion is becoming prohibitive. We propose a traffic generation (TG) model that provides a fast...

  18. Network Traffic Generator Model for Fast Network-on-Chip Simulation

    DEFF Research Database (Denmark)

    Mahadevan, Shankar; Ang, Frederico; Olsen, Rasmus G.

    2008-01-01

    and effective Network-on-Chip (NoC) development and debugging environment. By capturing the type and the timestamp of communication events at the boundary of an IP core in a reference environment, the TG can subsequently emulate the core's communication behavior in different environments. Access patterns......For Systems-on-Chip (SoCs) development, a predominant part of the design time is the simulation time. Performance evaluation and design space exploration of such systems in bit- and cycle-true fashion is becoming prohibitive. We propose a traffic generation (TG) model that provides a fast...

  19. 4D Trajectory Estimation for Air Traffic Control Automation System Based on Hybrid System Theory

    Directory of Open Access Journals (Sweden)

    Xin-Min Tang

    2012-03-01

    Full Text Available To resolve the problem of future airspace management under great traffic flow and high density condition, 4D trajectory estimation has become one of the core technologies of the next new generation air traffic control automation system. According to the flight profile and the dynamics models of different aircraft types under different flight conditions, a hybrid system model that switches the aircraft from one flight stage to another with aircraft state changing continuously in one state is constructed. Additionally, air temperature and wind speed are used to modify aircraft true airspeed as well as ground speed, and the hybrid system evolution simulation is used to estimate aircraft 4D trajectory. The case study proves that 4D trajectory estimated through hybrid system model can image the flight dynamic states of aircraft and satisfy the needs of the planned flight altitude profile.KEY WORDSair traffic management, 4D trajectory estimation, hybrid system model, aircraft dynamic model

  20. A Survey on Urban Traffic Management System Using Wireless Sensor Networks.

    Science.gov (United States)

    Nellore, Kapileswar; Hancke, Gerhard P

    2016-01-27

    Nowadays, the number of vehicles has increased exponentially, but the bedrock capacities of roads and transportation systems have not developed in an equivalent way to efficiently cope with the number of vehicles traveling on them. Due to this, road jamming and traffic correlated pollution have increased with the associated adverse societal and financial effect on different markets worldwide. A static control system may block emergency vehicles due to traffic jams. Wireless Sensor networks (WSNs) have gained increasing attention in traffic detection and avoiding road congestion. WSNs are very trendy due to their faster transfer of information, easy installation, less maintenance, compactness and for being less expensive compared to other network options. There has been significant research on Traffic Management Systems using WSNs to avoid congestion, ensure priority for emergency vehicles and cut the Average Waiting Time (AWT) of vehicles at intersections. In recent decades, researchers have started to monitor real-time traffic using WSNs, RFIDs, ZigBee, VANETs, Bluetooth devices, cameras and infrared signals. This paper presents a survey of current urban traffic management schemes for priority-based signalling, and reducing congestion and the AWT of vehicles. The main objective of this survey is to provide a taxonomy of different traffic management schemes used for avoiding congestion. Existing urban traffic management schemes for the avoidance of congestion and providing priority to emergency vehicles are considered and set the foundation for further research.

  1. A Survey on Urban Traffic Management System Using Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Kapileswar Nellore

    2016-01-01

    Full Text Available Nowadays, the number of vehicles has increased exponentially, but the bedrock capacities of roads and transportation systems have not developed in an equivalent way to efficiently cope with the number of vehicles traveling on them. Due to this, road jamming and traffic correlated pollution have increased with the associated adverse societal and financial effect on different markets worldwide. A static control system may block emergency vehicles due to traffic jams. Wireless Sensor networks (WSNs have gained increasing attention in traffic detection and avoiding road congestion. WSNs are very trendy due to their faster transfer of information, easy installation, less maintenance, compactness and for being less expensive compared to other network options. There has been significant research on Traffic Management Systems using WSNs to avoid congestion, ensure priority for emergency vehicles and cut the Average Waiting Time (AWT of vehicles at intersections. In recent decades, researchers have started to monitor real-time traffic using WSNs, RFIDs, ZigBee, VANETs, Bluetooth devices, cameras and infrared signals. This paper presents a survey of current urban traffic management schemes for priority-based signalling, and reducing congestion and the AWT of vehicles. The main objective of this survey is to provide a taxonomy of different traffic management schemes used for avoiding congestion. Existing urban traffic management schemes for the avoidance of congestion and providing priority to emergency vehicles are considered and set the foundation for further research.

  2. Estimation of Expectable Network Quality in Wireless Mesh Networks

    OpenAIRE

    Wollenberg, Till

    2012-01-01

    Part 3: Computing in Networks; International audience; Our work aims to improve the usability of wireless mesh networks as communication layer of smart office environments. While wireless mesh networks are well-suited for this task in general, the negative impact of interference, fading, and saturation makes the communication basically opportunistic. Our goal is to develop a system which allows a short-term estimation of network quality in terms of throughput, packet loss and latency. The est...

  3. Modeling Air Traffic Management Technologies with a Queuing Network Model of the National Airspace System

    Science.gov (United States)

    Long, Dou; Lee, David; Johnson, Jesse; Gaier, Eric; Kostiuk, Peter

    1999-01-01

    This report describes an integrated model of air traffic management (ATM) tools under development in two National Aeronautics and Space Administration (NASA) programs -Terminal Area Productivity (TAP) and Advanced Air Transport Technologies (AATT). The model is made by adjusting parameters of LMINET, a queuing network model of the National Airspace System (NAS), which the Logistics Management Institute (LMI) developed for NASA. Operating LMINET with models of various combinations of TAP and AATT will give quantitative information about the effects of the tools on operations of the NAS. The costs of delays under different scenarios are calculated. An extension of Air Carrier Investment Model (ACIM) under ASAC developed by the Institute for NASA maps the technologies' impacts on NASA operations into cross-comparable benefits estimates for technologies and sets of technologies.

  4. Low Cost Wireless Network Camera Sensors for Traffic Monitoring

    Science.gov (United States)

    2012-07-01

    Many freeways and arterials in major cities in Texas are presently equipped with video detection cameras to : collect data and help in traffic/incident management. In this study, carefully controlled experiments determined : the throughput and output...

  5. Traffic Command Gesture Recognition for Virtual Urban Scenes Based on a Spatiotemporal Convolution Neural Network

    Directory of Open Access Journals (Sweden)

    Chunyong Ma

    2018-01-01

    Full Text Available Intelligent recognition of traffic police command gestures increases authenticity and interactivity in virtual urban scenes. To actualize real-time traffic gesture recognition, a novel spatiotemporal convolution neural network (ST-CNN model is presented. We utilized Kinect 2.0 to construct a traffic police command gesture skeleton (TPCGS dataset collected from 10 volunteers. Subsequently, convolution operations on the locational change of each skeletal point were performed to extract temporal features, analyze the relative positions of skeletal points, and extract spatial features. After temporal and spatial features based on the three-dimensional positional information of traffic police skeleton points were extracted, the ST-CNN model classified positional information into eight types of Chinese traffic police gestures. The test accuracy of the ST-CNN model was 96.67%. In addition, a virtual urban traffic scene in which real-time command tests were carried out was set up, and a real-time test accuracy rate of 93.0% was achieved. The proposed ST-CNN model ensured a high level of accuracy and robustness. The ST-CNN model recognized traffic command gestures, and such recognition was found to control vehicles in virtual traffic environments, which enriches the interactive mode of the virtual city scene. Traffic command gesture recognition contributes to smart city construction.

  6. Energy-aware Traffic Engineering in Hybrid SDN/IP Backbone Networks

    OpenAIRE

    Wei, Yunkai; Zhang, XiaoNing; Xie, Lei; Leng, Supeng

    2016-01-01

    Software Defined Networking (SDN) can effectively improve the performance of traffic engineering and has promising application foreground in backbone networks. Therefore, new energy saving schemes must take SDN into account, which is extremely important considering the rapidly increasing energy consumption from Telecom and ISP networks. At the same time, the introduction of SDN in a current network must be incremental in most cases, for both technical and economic reasons. During this period,...

  7. Dynamic Traffic Congestion Simulation and Dissipation Control Based on Traffic Flow Theory Model and Neural Network Data Calibration Algorithm

    OpenAIRE

    Wang, Li; Lin, Shimin; Yang, Jingfeng; Zhang, Nanfeng; Yang, Ji; Li, Yong; Zhou, Handong; Yang, Feng; Li, Zhifu

    2017-01-01

    Traffic congestion is a common problem in many countries, especially in big cities. At present, China’s urban road traffic accidents occur frequently, the occurrence frequency is high, the accident causes traffic congestion, and accidents cause traffic congestion and vice versa. The occurrence of traffic accidents usually leads to the reduction of road traffic capacity and the formation of traffic bottlenecks, causing the traffic congestion. In this paper, the formation and propagation of tra...

  8. Efficient traffic grooming with dynamic ONU grouping for multiple-OLT-based access network

    Science.gov (United States)

    Zhang, Shizong; Gu, Rentao; Ji, Yuefeng; Wang, Hongxiang

    2015-12-01

    Fast bandwidth growth urges large-scale high-density access scenarios, where the multiple Passive Optical Networking (PON) system clustered deployment can be adopted as an appropriate solution to fulfill the huge bandwidth demands, especially for a future 5G mobile network. However, the lack of interaction between different optical line terminals (OLTs) results in part of the bandwidth resources waste. To increase the bandwidth efficiency, as well as reduce bandwidth pressure at the edge of a network, we propose a centralized flexible PON architecture based on Time- and Wavelength-Division Multiplexing PON (TWDM PON). It can provide flexible affiliation for optical network units (ONUs) and different OLTs to support access network traffic localization. Specifically, a dynamic ONU grouping algorithm (DGA) is provided to obtain the minimal OLT outbound traffic. Simulation results show that DGA obtains an average 25.23% traffic gain increment under different OLT numbers within a small ONU number situation, and the traffic gain will increase dramatically with the increment of the ONU number. As the DGA can be deployed easily as an application running above the centralized control plane, the proposed architecture can be helpful to improve the network efficiency for future traffic-intensive access scenarios.

  9. The Influence of Traffic Networks on the Supply-Demand Balance of Tourism: A Case Study of Jiangsu Province, China

    Directory of Open Access Journals (Sweden)

    Tao Chen

    2014-01-01

    Full Text Available The purpose of this research is to address the impact of traffic networks on the supply-demand balance of tourism and to determine if it is necessary to incorporate the traffic flow data for nodes to determine the significant influences and impacts of traffic networks on tourism. For this purpose, a road network was established for Jiangsu province, and the topological parameters of this network and the tourism degree of coordination among each prefectural city were calculated as well. The results demonstrate that the inclusion of the spatial structure of the traffic network was not necessary for determining the supply-demand balance for tourism; thus, the collection of traffic flow data is required to perform further research. As a side result, it has been determined that the circuit routes are relatively absent from the Jiangsu traffic network, which might hinder tourism, and tourism resources are undersupplied to most prefectural cities in Jiangsu.

  10. An efficient mechanism for dynamic multicast traffic grooming in overlay IP/MPLS over WDM networks

    Science.gov (United States)

    Yu, Xiaojun; Xiao, Gaoxi; Cheng, Tee Hiang

    2014-08-01

    This paper proposes an efficient overlay multicast provisioning (OMP) mechanism for dynamic multicast traffic grooming in overlay IP/MPLS over WDM networks. To facilitate request provisioning, OMP jointly utilizes a data learning (DL) scheme on the IP/MPLS layer for logical link cost estimation, and a lightpath fragmentation (LPF) based method on the WDM layer for improving resource sharing in grooming process. Extensive simulations are carried out to evaluate the performance of OMP mechanism under different traffic loads, with either limited or unlimited port resources. Simulation results demonstrate that OMP significantly outperforms the existing methods. To evaluate the respective influences of the DL scheme and the LPF method on OMP performance, provisioning mechanisms only utilizing either the IP/MPLS layer DL scheme or the WDM layer LPF method are also devised. Comparison results show that both DL and LPF methods help improve OMP blocking performance, and contribution from the DL scheme is more significant when the fixed routing and first-fit wavelength assignment (RWA) strategy is adopted on the WDM layer. Effects of a few other factors, including definition of connection cost to be reported by the WDM layer to the IP/MPLS layer and WDM-layer routing method, on OMP performance are also evaluated.

  11. Protocol vulnerability detection based on network traffic analysis and binary reverse engineering.

    Science.gov (United States)

    Wen, Shameng; Meng, Qingkun; Feng, Chao; Tang, Chaojing

    2017-01-01

    Network protocol vulnerability detection plays an important role in many domains, including protocol security analysis, application security, and network intrusion detection. In this study, by analyzing the general fuzzing method of network protocols, we propose a novel approach that combines network traffic analysis with the binary reverse engineering method. For network traffic analysis, the block-based protocol description language is introduced to construct test scripts, while the binary reverse engineering method employs the genetic algorithm with a fitness function designed to focus on code coverage. This combination leads to a substantial improvement in fuzz testing for network protocols. We build a prototype system and use it to test several real-world network protocol implementations. The experimental results show that the proposed approach detects vulnerabilities more efficiently and effectively than general fuzzing methods such as SPIKE.

  12. Protocol vulnerability detection based on network traffic analysis and binary reverse engineering.

    Directory of Open Access Journals (Sweden)

    Shameng Wen

    Full Text Available Network protocol vulnerability detection plays an important role in many domains, including protocol security analysis, application security, and network intrusion detection. In this study, by analyzing the general fuzzing method of network protocols, we propose a novel approach that combines network traffic analysis with the binary reverse engineering method. For network traffic analysis, the block-based protocol description language is introduced to construct test scripts, while the binary reverse engineering method employs the genetic algorithm with a fitness function designed to focus on code coverage. This combination leads to a substantial improvement in fuzz testing for network protocols. We build a prototype system and use it to test several real-world network protocol implementations. The experimental results show that the proposed approach detects vulnerabilities more efficiently and effectively than general fuzzing methods such as SPIKE.

  13. A Big Network Traffic Data Fusion Approach Based on Fisher and Deep Auto-Encoder

    Directory of Open Access Journals (Sweden)

    Xiaoling Tao

    2016-03-01

    Full Text Available Data fusion is usually performed prior to classification in order to reduce the input space. These dimensionality reduction techniques help to decline the complexity of the classification model and thus improve the classification performance. The traditional supervised methods demand labeled samples, and the current network traffic data mostly is not labeled. Thereby, better learners will be built by using both labeled and unlabeled data, than using each one alone. In this paper, a novel network traffic data fusion approach based on Fisher and deep auto-encoder (DFA-F-DAE is proposed to reduce the data dimensions and the complexity of computation. The experimental results show that the DFA-F-DAE improves the generalization ability of the three classification algorithms (J48, back propagation neural network (BPNN, and support vector machine (SVM by data dimensionality reduction. We found that the DFA-F-DAE remarkably improves the efficiency of big network traffic classification.

  14. An implementation of traffic light system using multi-hop Ad hoc networks

    KAUST Repository

    Ansari, Imran Shafique

    2009-08-01

    In ad hoc networks nodes cooperate with each other to form a temporary network without the aid of any centralized administration. No wired base station or infrastructure is supported, and each host communicates via radio packets. Each host must act as a router, since routes are mostly multi-hop, due to the limited power transmission set by government agencies, (e.g. the Federal Communication Commission (FCC), which is 1 Watt in Industrial Scientific and Medical (ISM) band. The natures of wireless mobile ad hoc networks depend on batteries or other fatiguing means for their energy. A limited energy capacity may be the most significant performance constraint. Therefore, radio resource and power management is an important issue of any wireless network. In this paper, a design for traffic light system employing ad hoc networks is proposed. The traffic light system runs automatically based on signals sent through a multi-hop ad hoc network of \\'n\\' number of nodes utilizing the Token Ring protocol, which is efficient for this application from the energy prospective. The experiment consists of a graphical user interface that simulates the traffic lights and laptops (which have wireless network adapters) are used to run the graphical user interface and are responsible for setting up the ad hoc network between them. The traffic light system has been implemented utilizing A Mesh Driver (which allows for more than one wireless device to be connected simultaneously) and Java-based client-server programs. © 2009 IEEE.

  15. Estimation of Carbon Dioxide Emissions Generated by Building and Traffic in Taichung City

    Directory of Open Access Journals (Sweden)

    Chou-Tsang Chang

    2018-01-01

    Full Text Available The emissions of carbon dioxide generated by urban traffic is generally reflected by urban size. In order to discuss the traffic volume generated in developed buildings and road crossings in a single urban block, with the metropolitan area in Taichung, Taiwan as an example, this study calculates the mutual relationship between the carbon dioxide generated by the traffic volume and building development scale, in order to research energy consumption and relevance. In this research, the entire-day traffic volume of an important road crossing is subject to statistical analysis to obtain the prediction formula of total passenger car units in the main road crossing within 24 h. Then, the total CO2 emissions generated by the traffic volume in the entire year is calculated according to the investigation data of peak traffic hours within 16 blocks and the influential factors of the development scale of 95 buildings are counted. Finally, this research found that there is a passenger car unit of 4.72 generated in each square meter of land in the urban block every day, 0.99 in each square meter of floor area in the building and the average annual total CO2 emissions of each passenger car unit is 41.4 kgCO2/yr. In addition, the basic information of an integrated road system and traffic volume is used to present a readable urban traffic hot map, which can calculate a distribution map of passenger car units within one day in Taichung. This research unit can be used to forecast the development scale of various buildings in future urban blocks, in order to provide an effective approach to estimate the carbon dioxide generated by the traffic volume.

  16. NETWORK TRAFFIC FORCASTING IN INFORMATION-TELECOMMUNICATION SYSTEM OF PRYDNIPROVSK RAILWAYS BASED ON NEURO-FUZZY NETWORK

    Directory of Open Access Journals (Sweden)

    V. M. Pakhomovа

    2016-12-01

    Full Text Available Purpose. Continuous increase in network traffic in the information-telecommunication system (ITS of Prydniprovsk Railways leads to the need to determine the real-time network congestion and to control the data flows. One of the possible solutions is a method of forecasting the volume of network traffic (inbound and outbound using neural network technology that will prevent from server overload and improve the quality of services. Methodology. Analysis of current network traffic in ITS of Prydniprovsk Railways and preparation of sets: learning, test and validation ones was conducted as well as creation of neuro-fuzzy network (hybrid system in Matlab program and organization of the following phases on the appropriate sets: learning, testing, forecast adequacy analysis. Findings. For the fragment (Dnipropetrovsk – Kyiv in ITS of Prydniprovsk Railways we made a forecast (day ahead for volume of network traffic based on the hybrid system created in Matlab program; MAPE values are as follows: 6.9% for volume of inbound traffic; 7.7% for volume of outbound traffic. It was found that the average learning error of the hybrid system decreases in case of increase in: the number of inputs (from 2 to 4; the number of terms (from 2 to 5 of the input variable; learning sample power (from 20 to 100. A significant impact on the average learning error of the hybrid system is caused by the number of terms of its input variable. It was determined that the lowest value of the average learning error is provided by 4-input hybrid system, it ensures more accurate learning of the neuro-fuzzy network by the hybrid method. Originality. The work resulted in the dependences for the average hybrid system error of the network traffic volume forecasting for the fragment (Dnipropetrovsk-Kyiv in ITS Prydniprovsk Railways on: the number of its inputs, the number of input variable terms, the learning sample power for different learning methods. Practical value. Forecasting of

  17. Voice Quality Estimation in Wireless Networks

    Directory of Open Access Journals (Sweden)

    Petr Zach

    2015-01-01

    Full Text Available This article deals with the impact of Wireless (Wi-Fi networks on the perceived quality of voice services. The Quality of Service (QoS metrics must be monitored in the computer network during the voice data transmission to ensure proper voice service quality the end-user has paid for, especially in the wireless networks. In addition to the QoS, research area called Quality of Experience (QoE provides metrics and methods for quality evaluation from the end-user’s perspective. This article focuses on a QoE estimation of Voice over IP (VoIP calls in the wireless networks using network simulator. Results contribute to voice quality estimation based on characteristics of the wireless network and location of a wireless client.

  18. Development of a Software Based Firewall System for Computer Network Traffic Control

    Directory of Open Access Journals (Sweden)

    Ikhajamgbe OYAKHILOME

    2009-12-01

    Full Text Available The connection of an internal network to an external network such as Internet has made it vulnerable to attacks. One class of network attack is unauthorized penetration into network due to the openness of networks. It is possible for hackers to sum access to an internal network, this pose great danger to the network and network resources. Our objective and major concern of network design was to build a secured network, based on software firewall that ensured the integrity and confidentiality of information on the network. We studied several mechanisms to achieve this; one of such mechanism is the implementation of firewall system as a network defence. Our developed firewall has the ability to determine which network traffic should be allowed in or out of the network. Part of our studied work was also channelled towards a comprehensive study of hardware firewall security system with the aim of developing this software based firewall system. Our software firewall goes a long way in protecting an internal network from external unauthorized traffic penetration. We included an anti virus software which is lacking in most firewalls.

  19. Optimal Traffic Allocation for Multi-Stream Aggregation in Heterogeneous Networks

    DEFF Research Database (Denmark)

    Popovska Avramova, Andrijana; Iversen, Villy Bæk

    2015-01-01

    This paper investigates an optimal traffic rate allocation method for multi-stream aggregation over heterogeneous networks that deals with effective integration of two or more heterogeneous links for improved data throughput and enhanced quality of experience. The heterogeneity and the dynamic...... variations. Furthermore, services with different traffic characteristics in terms of quality of service requirements are considered. The simulation results show the advantages of our scheme with respect to efficient increase in data rate and delay performance compared to traditional schemes....

  20. Is CoV(t)-based Modeling Sufficient for Traffic Characterization in Network Links ?

    OpenAIRE

    Noirie, Ludovic; Post, Georg

    2008-01-01

    http://euronf.enst.fr/archive/164/EuroNFDeliverableDSEA641.pdf; International audience; For performance evaluation and dimensioning of packet-based networks, engineers need simple, efficient and realistic traffic models. The traffic volume on a packet link, observed at different time scales t, has previously been modeled as a stationary stochastic process based on the Coefficient of Variation CoV(t). In this paper we try to supply the missing information about the shape of the distribution fu...

  1. Bayesian estimation of the network autocorrelation model

    NARCIS (Netherlands)

    Dittrich, D.; Leenders, R.T.A.J.; Mulder, J.

    2017-01-01

    The network autocorrelation model has been extensively used by researchers interested modeling social influence effects in social networks. The most common inferential method in the model is classical maximum likelihood estimation. This approach, however, has known problems such as negative bias of

  2. A network centrality measure framework for analyzing urban traffic flow: A case study of Wuhan, China

    Science.gov (United States)

    Zhao, Shuangming; Zhao, Pengxiang; Cui, Yunfan

    2017-07-01

    In this paper, we propose an improved network centrality measure framework that takes into account both the topological characteristics and the geometric properties of a road network in order to analyze urban traffic flow in relation to different modes: intersection, road, and community, which correspond to point mode, line mode, and area mode respectively. Degree, betweenness, and PageRank centralities are selected as the analysis measures, and GPS-enabled taxi trajectory data is used to evaluate urban traffic flow. The results show that the mean value of the correlation coefficients between the modified degree, the betweenness, and the PageRank centralities and the traffic flow in all periods are higher than the mean value of the correlation coefficients between the conventional degree, the betweenness, the PageRank centralities and the traffic flow at different modes; this indicates that the modified measurements, for analyzing traffic flow, are superior to conventional centrality measurements. This study helps to shed light into the understanding of urban traffic flow in relation to different modes from the perspective of complex networks.

  3. Sensitivity Analysis of Wavelet Neural Network Model for Short-Term Traffic Volume Prediction

    Directory of Open Access Journals (Sweden)

    Jinxing Shen

    2013-01-01

    Full Text Available In order to achieve a more accurate and robust traffic volume prediction model, the sensitivity of wavelet neural network model (WNNM is analyzed in this study. Based on real loop detector data which is provided by traffic police detachment of Maanshan, WNNM is discussed with different numbers of input neurons, different number of hidden neurons, and traffic volume for different time intervals. The test results show that the performance of WNNM depends heavily on network parameters and time interval of traffic volume. In addition, the WNNM with 4 input neurons and 6 hidden neurons is the optimal predictor with more accuracy, stability, and adaptability. At the same time, a much better prediction record will be achieved with the time interval of traffic volume are 15 minutes. In addition, the optimized WNNM is compared with the widely used back-propagation neural network (BPNN. The comparison results indicated that WNNM produce much lower values of MAE, MAPE, and VAPE than BPNN, which proves that WNNM performs better on short-term traffic volume prediction.

  4. The improved degree of urban road traffic network: A case study of Xiamen, China

    Science.gov (United States)

    Wang, Shiguang; Zheng, Lili; Yu, Dexin

    2017-03-01

    The complex network theory is applied to the study of urban road traffic network topology, and we constructed a new measure to characterize an urban road network. It is inspiring to quantify the interaction more appropriately between nodes in complex networks, especially in the field of traffic. The measure takes into account properties of lanes (e.g. number of lanes, width, traffic direction). As much, it is a more comprehensive measure in comparison to previous network measures. It can be used to grasp the features of urban street network more clearly. We applied this measure to the road network in Xiamen, China. Based on a standard method from statistical physics, we examined in more detail the distribution of this new measure and found that (1) due to the limitation of space geographic attributes, traditional research conclusions acquired by using the original definition of degree to study the primal approach modeled urban street network are not very persuasive; (2) both of the direction of the network connection and the degree's odd or even classifications need to be analyzed specifically; (3) the improved degree distribution presents obvious hierarchy, and hierarchical values conform to the power-law distribution, and correlation of our new measure shows some significant segmentation of the urban road network.

  5. RESEARCH OF ENGINEERING TRAFFIC IN COMPUTER UZ NETWORK USING MPLS TE TECHNOLOGY

    Directory of Open Access Journals (Sweden)

    V. M. Pakhomovа

    2014-12-01

    Full Text Available Purpose. In railway transport of Ukraine one requires the use of computer networks of different technologies: Ethernet, Token Bus, Token Ring, FDDI and others. In combined computer networks on the railway transport it is necessary to use packet switching technology in multiprotocol networks MPLS (MultiProtocol Label Switching more effectively. They are based on the use of tags. Packet network must transmit different types of traffic with a given quality of service. The purpose of the research is development a methodology for determining the sequence of destination flows for the considered fragment of computer network of UZ. Methodology. When optimizing traffic management in MPLS networks has the important role of technology traffic engineering (Traffic Engineering, TE. The main mechanism of TE in MPLS is the use of unidirectional tunnels (MPLS TE tunnel to specify the path of the specified traffic. The mathematical model of the problem of traffic engineering in computer network of UZ technology MPLS TE was made. Computer UZ network is represented with the directed graph, their vertices are routers of computer network, and each arc simulates communication between nodes. As an optimization criterion serves the minimum value of the maximum utilization of the TE-tunnel. Findings. The six options destination flows were determined; rational sequence of flows was found, at which the maximum utilization of TE-tunnels considered a simplified fragment of a computer UZ network does not exceed 0.5. Originality. The method of solving the problem of traffic engineering in Multiprotocol network UZ technology MPLS TE was proposed; for different classes its own way is laid, depending on the bandwidth and channel loading. Practical value. Ability to determine the values of the maximum coefficient of use of TE-tunnels in computer UZ networks based on developed software model «TraffEng». The input parameters of the model: number of routers, channel capacity, the

  6. Wireless sensor networks distributed consensus estimation

    CERN Document Server

    Chen, Cailian; Guan, Xinping

    2014-01-01

    This SpringerBrief evaluates the cooperative effort of sensor nodes to accomplish high-level tasks with sensing, data processing and communication. The metrics of network-wide convergence, unbiasedness, consistency and optimality are discussed through network topology, distributed estimation algorithms and consensus strategy. Systematic analysis reveals that proper deployment of sensor nodes and a small number of low-cost relays (without sensing function) can speed up the information fusion and thus improve the estimation capability of wireless sensor networks (WSNs). This brief also investiga

  7. Trunk Reservation in Multi-service Networks with BPP Traffic

    DEFF Research Database (Denmark)

    Zheng, H.; Zhang, Qi; Iversen, Villy Bæk

    2006-01-01

    algorithm which allows for calculation of individual performance measures for each service, in particular the traffic congestion. The algorithm is numerically robust and requires a minimum of computer memory and computing time. The approximation is good when the services have equal mean service times....

  8. Integrated Control of Mixed Traffic Networks using Model Predictive Control

    NARCIS (Netherlands)

    Van den Berg, M.

    2010-01-01

    Motivation The growth of our road infrastructure cannot keep up with the growing mobility of people, and the corresponding increase in traffic demand. This results in daily congestion on the freeways. It is an illusion that the problem of congestion can be solved completely within a few years, but

  9. Traffic-aware Elastic Optical Networks to leverage Energy Savings

    DEFF Research Database (Denmark)

    Turus, Ioan; Fagertun, Anna Manolova; Dittmann, Lars

    2014-01-01

    Because of the static nature of the deployed optical networks, large energy wastage is experienced today in production networks such as Telecom networks . With power-adaptive optical interfaces and suitable grooming procedures, we propose the design of more energy efficient transport networks. Op...

  10. Design Issues for Traffic Management for the ATM UBR + Service for TCP Over Satellite Networks

    Science.gov (United States)

    Jain, Raj

    1999-01-01

    This project was a comprehensive research program for developing techniques for improving the performance of Internet protocols over Asynchronous Transfer Mode (ATM) based satellite networks. Among the service categories provided by ATM networks, the most commonly used category for data traffic is the unspecified bit rate (UBR) service. UBR allows sources to send data into the network without any feedback control. The project resulted in the numerous ATM Forum contributions and papers.

  11. Bandwidth Impacts of Localizing Peer-to-Peer IP Video Traffic in Access and Aggregation Networks

    Directory of Open Access Journals (Sweden)

    Kerpez Kenneth

    2008-01-01

    Full Text Available Abstract This paper examines the burgeoning impact of peer-to-peer (P2P traffic IP video traffic. High-quality IPTV or Internet TV has high-bandwidth requirements, and P2P IP video could severely strain broadband networks. A model for the popularity of video titles is given, showing that some titles are very popular and will often be available locally; making localized P2P attractive for video titles. The bandwidth impacts of localizing P2P video to try and keep traffic within a broadband access network area or within a broadband access aggregation network area are examined. Results indicate that such highly localized P2P video can greatly lower core bandwidth usage.

  12. Local control of traffic flows in networks: Self-organisation of phase synchronised dynamics

    Energy Technology Data Exchange (ETDEWEB)

    Laemmer, Stefan; Donner, Reik [TU Dresden, Andreas-Schubert-Str. 23, 01062 Dresden (Germany); Helbing, Dirk [ETH Zuerich, Universitaetstr. 41, 8092 Zuerich (Switzerland)

    2008-07-01

    The effective control of flows in urban traffic networks is a subject of broad economic interest. During the last years, efforts have been made to develop decentralised control strategies that take only the actual state of present traffic conditions into account. In this contribution, we introduce a permeability model for the local control of conflicting material flows on networks, which incorporates a self-organisation of the flows. The dynamics of our model is studied under different situations, with a special emphasis on the development of a phase synchronised switching behaviour at the nodes of the traffic network. In order to improve the potential applicability of our concept, we discuss how a proper demand anticipation and the definition of a priority function can be used to further optimise the performance of the presented strategy.

  13. Bandwidth Impacts of Localizing Peer-to-Peer IP Video Traffic in Access and Aggregation Networks

    Directory of Open Access Journals (Sweden)

    Kenneth Kerpez

    2008-10-01

    Full Text Available This paper examines the burgeoning impact of peer-to-peer (P2P traffic IP video traffic. High-quality IPTV or Internet TV has high-bandwidth requirements, and P2P IP video could severely strain broadband networks. A model for the popularity of video titles is given, showing that some titles are very popular and will often be available locally; making localized P2P attractive for video titles. The bandwidth impacts of localizing P2P video to try and keep traffic within a broadband access network area or within a broadband access aggregation network area are examined. Results indicate that such highly localized P2P video can greatly lower core bandwidth usage.

  14. A Novel Biobjective Risk-Based Model for Stochastic Air Traffic Network Flow Optimization Problem.

    Science.gov (United States)

    Cai, Kaiquan; Jia, Yaoguang; Zhu, Yanbo; Xiao, Mingming

    2015-01-01

    Network-wide air traffic flow management (ATFM) is an effective way to alleviate demand-capacity imbalances globally and thereafter reduce airspace congestion and flight delays. The conventional ATFM models assume the capacities of airports or airspace sectors are all predetermined. However, the capacity uncertainties due to the dynamics of convective weather may make the deterministic ATFM measures impractical. This paper investigates the stochastic air traffic network flow optimization (SATNFO) problem, which is formulated as a weighted biobjective 0-1 integer programming model. In order to evaluate the effect of capacity uncertainties on ATFM, the operational risk is modeled via probabilistic risk assessment and introduced as an extra objective in SATNFO problem. Computation experiments using real-world air traffic network data associated with simulated weather data show that presented model has far less constraints compared to stochastic model with nonanticipative constraints, which means our proposed model reduces the computation complexity.

  15. Estimation of RTT and bandwidth for congestion Control Applications in Communication Networks

    OpenAIRE

    Jacobsson, Krister; Hjalmarsson, Håkan; Möller, Niels; Johansson, Karl Henrik

    2004-01-01

    Heterogeneous communication networks with their variety of application demands, uncertain time-varying traffic load, and mixture of wired and wireless links pose several challenging problem in modeling and control. In this paper we focus on the round-trip time (RTT), which is a particularly important variable for efficient end-to-end congestion control, and on bandwidth estimation. Based on a simple aggregated model of the network, an algorithm combining a Kalman filter and a change detection...

  16. Modeling and Density Estimation of an Urban Freeway Network Based on Dynamic Graph Hybrid Automata.

    Science.gov (United States)

    Chen, Yangzhou; Guo, Yuqi; Wang, Ying

    2017-03-29

    In this paper, in order to describe complex network systems, we firstly propose a general modeling framework by combining a dynamic graph with hybrid automata and thus name it Dynamic Graph Hybrid Automata (DGHA). Then we apply this framework to model traffic flow over an urban freeway network by embedding the Cell Transmission Model (CTM) into the DGHA. With a modeling procedure, we adopt a dual digraph of road network structure to describe the road topology, use linear hybrid automata to describe multi-modes of dynamic densities in road segments and transform the nonlinear expressions of the transmitted traffic flow between two road segments into piecewise linear functions in terms of multi-mode switchings. This modeling procedure is modularized and rule-based, and thus is easily-extensible with the help of a combination algorithm for the dynamics of traffic flow. It can describe the dynamics of traffic flow over an urban freeway network with arbitrary topology structures and sizes. Next we analyze mode types and number in the model of the whole freeway network, and deduce a Piecewise Affine Linear System (PWALS) model. Furthermore, based on the PWALS model, a multi-mode switched state observer is designed to estimate the traffic densities of the freeway network, where a set of observer gain matrices are computed by using the Lyapunov function approach. As an example, we utilize the PWALS model and the corresponding switched state observer to traffic flow over Beijing third ring road. In order to clearly interpret the principle of the proposed method and avoid computational complexity, we adopt a simplified version of Beijing third ring road. Practical application for a large-scale road network will be implemented by decentralized modeling approach and distributed observer designing in the future research.

  17. Parameter estimation in channel network flow simulation

    Directory of Open Access Journals (Sweden)

    Han Longxi

    2008-03-01

    Full Text Available Simulations of water flow in channel networks require estimated values of roughness for all the individual channel segments that make up a network. When the number of individual channel segments is large, the parameter calibration workload is substantial and a high level of uncertainty in estimated roughness cannot be avoided. In this study, all the individual channel segments are graded according to the factors determining the value of roughness. It is assumed that channel segments with the same grade have the same value of roughness. Based on observed hydrological data, an optimal model for roughness estimation is built. The procedure of solving the optimal problem using the optimal model is described. In a test of its efficacy, this estimation method was applied successfully in the simulation of tidal water flow in a large complicated channel network in the lower reach of the Yangtze River in China.

  18. Modelling Altitude Information in Two-Dimensional Traffic Networks for Electric Mobility Simulation

    Directory of Open Access Journals (Sweden)

    Diogo Santos

    2016-06-01

    Full Text Available Elevation data is important for electric vehicle simulation. However, traffic simulators are often two-dimensional and do not offer the capability of modelling urban networks taking elevation into account. Specifically, SUMO - Simulation of Urban Mobility, a popular microscopic traffic simulator, relies on networks previously modelled with elevation data as to provide this information during simulations. This work tackles the problem of adding elevation data to urban network models - particularly for the case of the Porto urban network, in Portugal. With this goal in mind, a comparison between different altitude information retrieval approaches is made and a simple tool to annotate network models with altitude data is proposed. The work starts by describing the methodological approach followed during research and development, then describing and analysing its main findings. This description includes an in-depth explanation of the proposed tool. Lastly, this work reviews some related work to the subject.

  19. PLUS highway network analysis: Case of in-coming traffic burden in 2013

    Science.gov (United States)

    Asrah, Norhaidah Mohd; Djauhari, Maman Abdurachman; Mohamad, Ismail

    2017-05-01

    PLUS highway is the largest concessionary in Malaysia. The study on PLUS highway development, in order to overcome the demand for efficient road transportation, is crucial. If the highways have better interconnected network, it will help the economic activities such as trade to increase. If economic activities are increasing, the benefit will come to the people and state. In its turn, it will help the leaders to plan and conduct national development program. In this paper, network analysis approach will be used to study the in-coming traffic burden during the year of 2013. The highway network linking all the toll plazas is a dynamic network. The objective of this study is to learn and understand about highway network in terms of the in-coming traffic burden entering to each toll plazas along PLUS highway. For this purpose, the filtered network topology based on the forest of all possible minimum spanning trees is used. The in-coming traffic burden of a city is represented by the number of cars passing through the corresponding toll plaza. To interpret the filtered network, centrality measures such as degree centrality, betweenness centrality, closeness centrality, eigenvector centrality are used. An overall centrality will be proposed if those four measures are assumed to have the same role. Based on the results, some suggestions and recommendations for PLUS highway network development will be delivered to PLUS highway management.

  20. Analysis and Classification of Traffic in Wireless Sensor Network

    Science.gov (United States)

    2007-03-01

    length can be directly extracted from the Xsniffer output under the column “Len.” In the self-similarity discussion in Chapter V, two Mathcad scripts...processed through a Mathcad script as described in Chapter III to determine if the traffic is self-similar. 1. Direct Connection to Base Setup...analyzed using two Mathcad scripts for self- similarity characteristics. Variance time plots were constructed for both packet length and interarrival

  1. Communication and Networking Techniques for Traffic Safety Systems

    OpenAIRE

    Chisalita, Ioan

    2006-01-01

    Accident statistics indicate that every year a significant number of casualties and extensive property losses occur due to traffic accidents. Consequently, efforts are directed towards developing passive and active safety systems that help reduce the severity of crashes, or prevent vehicles from colliding with one another. To develop these systems, technologies such as sensor systems, computer vision and vehicular communication have been proposed. Safety vehicular communication is defined as ...

  2. Effect and Analysis of Sustainable Cell Rate using MPEG video Traffic in ATM Networks

    Directory of Open Access Journals (Sweden)

    Sakshi Kaushal

    2006-04-01

    Full Text Available The broadband networks inhibit the capability to carry multiple types of traffic – voice, video and data, but these services need to be controlled according to the traffic contract negotiated at the time of the connection to maintain desired Quality of service. Such control techniques use traffic descriptors to evaluate its performance and effectiveness. In case of Variable Bit Rate (VBR services, Peak Cell Rate (PCR and its Cell Delay Variation Tolerance (CDVTPCR are mandatory descriptors. In addition to these, ATM Forum proposed Sustainable Cell Rate (SCR and its Cell delay variation tolerance (CDVTSCR. In this paper, we evaluated the impact of specific SCR and CDVTSCR values on the Usage Parameter Control (UPC performance in case of measured MPEG traffic for improving the efficiency

  3. Application of growing hierarchical SOM for visualisation of network forensics traffic data.

    Science.gov (United States)

    Palomo, E J; North, J; Elizondo, D; Luque, R M; Watson, T

    2012-08-01

    Digital investigation methods are becoming more and more important due to the proliferation of digital crimes and crimes involving digital evidence. Network forensics is a research area that gathers evidence by collecting and analysing network traffic data logs. This analysis can be a difficult process, especially because of the high variability of these attacks and large amount of data. Therefore, software tools that can help with these digital investigations are in great demand. In this paper, a novel approach to analysing and visualising network traffic data based on growing hierarchical self-organising maps (GHSOM) is presented. The self-organising map (SOM) has been shown to be successful for the analysis of highly-dimensional input data in data mining applications as well as for data visualisation in a more intuitive and understandable manner. However, the SOM has some problems related to its static topology and its inability to represent hierarchical relationships in the input data. The GHSOM tries to overcome these limitations by generating a hierarchical architecture that is automatically determined according to the input data and reflects the inherent hierarchical relationships among them. Moreover, the proposed GHSOM has been modified to correctly treat the qualitative features that are present in the traffic data in addition to the quantitative features. Experimental results show that this approach can be very useful for a better understanding of network traffic data, making it easier to search for evidence of attacks or anomalous behaviour in a network environment. Copyright © 2012 Elsevier Ltd. All rights reserved.

  4. Predicting Traffic Flow in Local Area Networks by the Largest Lyapunov Exponent

    Directory of Open Access Journals (Sweden)

    Yan Liu

    2016-01-01

    Full Text Available The dynamics of network traffic are complex and nonlinear, and chaotic behaviors and their prediction, which play an important role in local area networks (LANs, are studied in detail, using the largest Lyapunov exponent. With the introduction of phase space reconstruction based on the time sequence, the high-dimensional traffic is projected onto the low dimension reconstructed phase space, and a reduced dynamic system is obtained from the dynamic system viewpoint. Then, a numerical method for computing the largest Lyapunov exponent of the low-dimensional dynamic system is presented. Further, the longest predictable time, which is related to chaotic behaviors in the system, is studied using the largest Lyapunov exponent, and the Wolf method is used to predict the evolution of the traffic in a local area network by both Dot and Interval predictions, and a reliable result is obtained by the presented method. As the conclusion, the results show that the largest Lyapunov exponent can be used to describe the sensitivity of the trajectory in the reconstructed phase space to the initial values. Moreover, Dot Prediction can effectively predict the flow burst. The numerical simulation also shows that the presented method is feasible and efficient for predicting the complex dynamic behaviors in LAN traffic, especially for congestion and attack in networks, which are the main two complex phenomena behaving as chaos in networks.

  5. Best response game of traffic on road network of non-signalized intersections

    Science.gov (United States)

    Yao, Wang; Jia, Ning; Zhong, Shiquan; Li, Liying

    2018-01-01

    This paper studies the traffic flow in a grid road network with non-signalized intersections. The nature of the drivers in the network is simulated such that they play an iterative snowdrift game with other drivers. A cellular automata model is applied to study the characteristics of the traffic flow and the evolution of the behaviour of the drivers during the game. The drivers use best-response as their strategy to update rules. Three major findings are revealed. First, the cooperation rate in simulation experiences staircase-shaped drop as cost to benefit ratio r increases, and cooperation rate can be derived analytically as a function of cost to benefit ratio r. Second, we find that higher cooperation rate corresponds to higher average speed, lower density and higher flow. This reveals that defectors deteriorate the efficiency of traffic on non-signalized intersections. Third, the system experiences more randomness when the density is low because the drivers will not have much opportunity to update strategy when the density is low. These findings help to show how the strategy of drivers in a traffic network evolves and how their interactions influence the overall performance of the traffic system.

  6. Fleet size estimation for spreading operation considering road geometry, weather and traffic

    Directory of Open Access Journals (Sweden)

    Steven I-Jy Chien

    2014-02-01

    Full Text Available Extreme weather conditions(i.e. snow storm in winter time have caused significant travel disruptions and increased delay and traffic accidents. Snow plowing and salt spreading are the most common counter-measures for making our roads safer for motorists. To assist highway maintenance authorities with better planning and allocation of winter maintenance resources, this study introduces an analytical model to estimate the required number of trucks for spreading operation subjective to pre-specified service time constraints considering road geometry, weather and traffic. The complexity of the research problem lies in dealing with heterogeneous road geometry of road sections, truck capacities, spreading patterns, and traffic speeds under different weather conditions and time periods of an event. The proposed model is applied to two maintenance yards with seven road sections in New Jersey (USA, which demonstrates itself fairly practical to be implemented, considering diverse operational conditions.

  7. Self-Adapting Routing Overlay Network for Frequently Changing Application Traffic in Content-Based Publish/Subscribe System

    Directory of Open Access Journals (Sweden)

    Meng Chi

    2014-01-01

    Full Text Available In the large-scale distributed simulation area, the topology of the overlay network cannot always rapidly adapt to frequently changing application traffic to reduce the overall traffic cost. In this paper, we propose a self-adapting routing strategy for frequently changing application traffic in content-based publish/subscribe system. The strategy firstly trains the traffic information and then uses this training information to predict the application traffic in the future. Finally, the strategy reconfigures the topology of the overlay network based on this predicting information to reduce the overall traffic cost. A predicting path is also introduced in this paper to reduce the reconfiguration numbers in the process of the reconfigurations. Compared to other strategies, the experimental results show that the strategy proposed in this paper could reduce the overall traffic cost of the publish/subscribe system in less reconfigurations.

  8. Pattern Recognition and Classification of Fatal Traffic Accidents in Israel A Neural Network Approach

    DEFF Research Database (Denmark)

    Prato, Carlo Giacomo; Gitelman, Victoria; Bekhor, Shlomo

    2011-01-01

    This article provides a broad picture of fatal traffic accidents in Israel to answer an increasing need of addressing compelling problems, designing preventive measures, and targeting specific population groups with the objective of reducing the number of traffic fatalities. The analysis focuses...... on 1,793 fatal traffic accidents occurred during the period between 2003 and 2006 and applies Kohonen and feed-forward back-propagation neural networks with the objective of extracting from the data typical patterns and relevant factors. Kohonen neural networks reveal five compelling accident patterns......: (1) single-vehicle accidents of young drivers, (2) multiple-vehicle accidents between young drivers, (3) accidents involving motorcyclists or cyclists, (4) accidents where elderly pedestrians crossed in urban areas, and (5) accidents where children and teenagers cross major roads in small urban areas...

  9. A Feature Selection Method for Large-Scale Network Traffic Classification Based on Spark

    Directory of Open Access Journals (Sweden)

    Yong Wang

    2016-02-01

    Full Text Available Currently, with the rapid increasing of data scales in network traffic classifications, how to select traffic features efficiently is becoming a big challenge. Although a number of traditional feature selection methods using the Hadoop-MapReduce framework have been proposed, the execution time was still unsatisfactory with numeral iterative computations during the processing. To address this issue, an efficient feature selection method for network traffic based on a new parallel computing framework called Spark is proposed in this paper. In our approach, the complete feature set is firstly preprocessed based on Fisher score, and a sequential forward search strategy is employed for subsets. The optimal feature subset is then selected using the continuous iterations of the Spark computing framework. The implementation demonstrates that, on the precondition of keeping the classification accuracy, our method reduces the time cost of modeling and classification, and improves the execution efficiency of feature selection significantly.

  10. Integration of Body Sensor Networks and Vehicular Ad-hoc Networks for Traffic Safety

    Science.gov (United States)

    Reyes-Muñoz, Angelica; Domingo, Mari Carmen; López-Trinidad, Marco Antonio; Delgado, José Luis

    2016-01-01

    The emergence of Body Sensor Networks (BSNs) constitutes a new and fast growing trend for the development of daily routine applications. However, in the case of heterogeneous BSNs integration with Vehicular ad hoc Networks (VANETs) a large number of difficulties remain, that must be solved, especially when talking about the detection of human state factors that impair the driving of motor vehicles. The main contributions of this investigation are principally three: (1) an exhaustive review of the current mechanisms to detect four basic physiological behavior states (drowsy, drunk, driving under emotional state disorders and distracted driving) that may cause traffic accidents is presented; (2) A middleware architecture is proposed. This architecture can communicate with the car dashboard, emergency services, vehicles belonging to the VANET and road or street facilities. This architecture seeks on the one hand to improve the car driving experience of the driver and on the other hand to extend security mechanisms for the surrounding individuals; and (3) as a proof of concept, an Android real-time attention low level detection application that runs in a next-generation smartphone is developed. The application features mechanisms that allow one to measure the degree of attention of a driver on the base of her/his EEG signals, establish wireless communication links via various standard wireless means, GPRS, Bluetooth and WiFi and issue alarms of critical low driver attention levels. PMID:26784204

  11. Integration of Body Sensor Networks and Vehicular Ad-hoc Networks for Traffic Safety

    Directory of Open Access Journals (Sweden)

    Angelica Reyes-Muñoz

    2016-01-01

    Full Text Available The emergence of Body Sensor Networks (BSNs constitutes a new and fast growing trend for the development of daily routine applications. However, in the case of heterogeneous BSNs integration with Vehicular ad hoc Networks (VANETs a large number of difficulties remain, that must be solved, especially when talking about the detection of human state factors that impair the driving of motor vehicles. The main contributions of this investigation are principally three: (1 an exhaustive review of the current mechanisms to detect four basic physiological behavior states (drowsy, drunk, driving under emotional state disorders and distracted driving that may cause traffic accidents is presented; (2 A middleware architecture is proposed. This architecture can communicate with the car dashboard, emergency services, vehicles belonging to the VANET and road or street facilities. This architecture seeks on the one hand to improve the car driving experience of the driver and on the other hand to extend security mechanisms for the surrounding individuals; and (3 as a proof of concept, an Android real-time attention low level detection application that runs in a next-generation smartphone is developed. The application features mechanisms that allow one to measure the degree of attention of a driver on the base of her/his EEG signals, establish wireless communication links via various standard wireless means, GPRS, Bluetooth and WiFi and issue alarms of critical low driver attention levels.

  12. Integration of Body Sensor Networks and Vehicular Ad-hoc Networks for Traffic Safety.

    Science.gov (United States)

    Reyes-Muñoz, Angelica; Domingo, Mari Carmen; López-Trinidad, Marco Antonio; Delgado, José Luis

    2016-01-15

    The emergence of Body Sensor Networks (BSNs) constitutes a new and fast growing trend for the development of daily routine applications. However, in the case of heterogeneous BSNs integration with Vehicular ad hoc Networks (VANETs) a large number of difficulties remain, that must be solved, especially when talking about the detection of human state factors that impair the driving of motor vehicles. The main contributions of this investigation are principally three: (1) an exhaustive review of the current mechanisms to detect four basic physiological behavior states (drowsy, drunk, driving under emotional state disorders and distracted driving) that may cause traffic accidents is presented; (2) A middleware architecture is proposed. This architecture can communicate with the car dashboard, emergency services, vehicles belonging to the VANET and road or street facilities. This architecture seeks on the one hand to improve the car driving experience of the driver and on the other hand to extend security mechanisms for the surrounding individuals; and (3) as a proof of concept, an Android real-time attention low level detection application that runs in a next-generation smartphone is developed. The application features mechanisms that allow one to measure the degree of attention of a driver on the base of her/his EEG signals, establish wireless communication links via various standard wireless means, GPRS, Bluetooth and WiFi and issue alarms of critical low driver attention levels.

  13. Software defined multi-OLT passive optical network for flexible traffic allocation

    Science.gov (United States)

    Zhang, Shizong; Gu, Rentao; Ji, Yuefeng; Zhang, Jiawei; Li, Hui

    2016-10-01

    With the rapid growth of 4G mobile network and vehicular network services mobile terminal users have increasing demand on data sharing among different radio remote units (RRUs) and roadside units (RSUs). Meanwhile, commercial video-streaming, video/voice conference applications delivered through peer-to-peer (P2P) technology are still keep on stimulating the sharp increment of bandwidth demand in both business and residential subscribers. However, a significant issue is that, although wavelength division multiplexing (WDM) and orthogonal frequency division multiplexing (OFDM) technology have been proposed to fulfil the ever-increasing bandwidth demand in access network, the bandwidth of optical fiber is not unlimited due to the restriction of optical component properties and modulation/demodulation technology, and blindly increase the wavelength cannot meet the cost-sensitive characteristic of the access network. In this paper, we propose a software defined multi-OLT PON architecture to support efficient scheduling of access network traffic. By introducing software defined networking technology and wavelength selective switch into TWDM PON system in central office, multiple OLTs can be considered as a bandwidth resource pool and support flexible traffic allocation for optical network units (ONUs). Moreover, under the configuration of the control plane, ONUs have the capability of changing affiliation between different OLTs under different traffic situations, thus the inter-OLT traffic can be localized and the data exchange pressure of the core network can be released. Considering this architecture is designed to be maximum following the TWDM PON specification, the existing optical distribution network (ODN) investment can be saved and conventional EPON/GPON equipment can be compatible with the proposed architecture. What's more, based on this architecture, we propose a dynamic wavelength scheduling algorithm, which can be deployed as an application on control plane

  14. Multi Service Proxy: Mobile Web Traffic Entitlement Point in 4G Core Network

    Directory of Open Access Journals (Sweden)

    Dalibor Uhlir

    2015-05-01

    Full Text Available Core part of state-of-the-art mobile networks is composed of several standard elements like GGSN (Gateway General Packet Radio Service Support Node, SGSN (Serving GPRS Support Node, F5 or MSP (Multi Service Proxy. Each node handles network traffic from a slightly different perspective, and with various goals. In this article we will focus only on the MSP, its key features and especially on related security issues. MSP handles all HTTP traffic in the mobile network and therefore it is a suitable point for the implementation of different optimization functions, e.g. to reduce the volume of data generated by YouTube or similar HTTP-based service. This article will introduce basic features and functions of MSP as well as ways of remote access and security mechanisms of this key element in state-of-the-art mobile networks.

  15. Evaluation Study of a Wireless Multimedia Traffic-Oriented Network Model

    Science.gov (United States)

    Vasiliadis, D. C.; Rizos, G. E.; Vassilakis, C.

    2008-11-01

    In this paper, a wireless multimedia traffic-oriented network scheme over a fourth generation system (4-G) is presented and analyzed. We conducted an extensive evaluation study for various mobility configurations in order to incorporate the behavior of the IEEE 802.11b standard over a test-bed wireless multimedia network model. In this context, the Quality of Services (QoS) over this network is vital for providing a reliable high-bandwidth platform for data-intensive sources like video streaming. Therefore, the main issues concerned in terms of QoS were the metrics for bandwidth of both dropped and lost packets and their mean packet delay under various traffic conditions. Finally, we used a generic distance-vector routing protocol which was based on an implementation of Distributed Bellman-Ford algorithm. The performance of the test-bed network model has been evaluated by using the simulation environment of NS-2.

  16. Network traffic intelligence using a low interaction honeypot

    Science.gov (United States)

    Nyamugudza, Tendai; Rajasekar, Venkatesh; Sen, Prasad; Nirmala, M.; Madhu Viswanatham, V.

    2017-11-01

    Advancements in networking technology have seen more and more devices becoming connected day by day. This has given organizations capacity to extend their networks beyond their boundaries to remote offices and remote employees. However as the network grows security becomes a major challenge since the attack surface also increases. There is need to guard the network against different types of attacks like intrusion and malware through using different tools at different networking levels. This paper describes how network intelligence can be acquired through implementing a low-interaction honeypot which detects and track network intrusion. Honeypot allows an organization to interact and gather information about an attack earlier before it compromises the network. This process is important because it allows the organization to learn about future attacks of the same nature and allows them to develop counter measures. The paper further shows how honeypot-honey net based model for interruption detection system (IDS) can be used to get the best valuable information about the attacker and prevent unexpected harm to the network.

  17. Understanding the vulnerability of traffic networks by means of structured expert judgment elicitation

    NARCIS (Netherlands)

    Nogal, M.; Morales Napoles, O.; O'Connor, Alan

    2016-01-01

    There is a lack of consensus in relation to the operationality of important concepts and descriptors of traffic networks such as resilience and vulnerability. With the aim of determining a framework with mathematical sound to objectively define and delimit these concepts, the expert judgment

  18. Road safety and bicycle usage impacts of unbundling vehicular and cycle traffic in Dutch urban networks

    NARCIS (Netherlands)

    Schepers, Paul; Heinen, Eva; Methorst, Rob; Wegman, Fred

    2013-01-01

    Bicycle-motor vehicle crashes are concentrated along distributor roads where cyclists are exposed to greater volumes of high-speed motorists than they would experience on access roads. This study examined the road safety impact of network-level separation of vehicular and cycle traffic in Dutch

  19. Routing of guaranteed throughput traffic in a network-on-chip

    NARCIS (Netherlands)

    Kavaldjiev, N.K.; Smit, Gerardus Johannes Maria; Wolkotte, P.T.; Jansen, P.G.

    This paper examines the possibilities of providing throughput guarantees in a network-on-chip by appropriate traffic routing. A source routing function is used to find routes with specified throughput for the data streams in a streaming multiprocessor system-on-chip. The influence of the routing

  20. Efficient model predictive control for large-scale urban traffic networks

    NARCIS (Netherlands)

    Lin, S.

    2011-01-01

    Model Predictive Control is applied to control and coordinate large-scale urban traffic networks. However, due to the large scale or the nonlinear, non-convex nature of the on-line optimization problems solved, the MPC controllers become real-time infeasible in practice, even though the problem is

  1. Dynamic Flow Migration for Delay Constrained Traffic in Software-Defined Networks

    NARCIS (Netherlands)

    Berger, Andre; Gross, James; Danielis, Peter; Dán, György

    2017-01-01

    Various industrial control applications have stringent end-to-end latency requirements in the order of a few milliseconds. Software-defined networking (SDN) is a promising solution in order to meet these stringent requirements under varying traffic patterns, as it enables the flexible management of

  2. Downlink Performance of a Multi-Carrier MIMO System in a Bursty Traffic Cellular Network

    DEFF Research Database (Denmark)

    Nguyen, Hung Tuan; Kovacs, Istvan; Wang, Yuanye

    2011-01-01

    In this paper we analyse the downlink performance of a rank adaptive multiple input multiple output (MIMO) system in a busty traffic cellular network. A LTE-Advanced system with multiple component carriers was selected as a study case. To highlight the advantage of using MIMO techniques, we used...

  3. Report on the Dagstuhl Seminar on Visualization and Monitoring of Network Traffic

    NARCIS (Netherlands)

    Keim, Daniel A.; Pras, Aiko; Schönwälder, Jürgen; Wong, Pak Chung; Mansmann, Florian

    The Dagstuhl Seminar on Visualization and Monitoring of Network Traffic took place May 17-20, 2009 in Dagstuhl, Germany. Dagstuhl seminars promote personal interaction and open discussion of results as well as new ideas. Unlike at most conferences, the focus is not solely on the presentation of

  4. Traffic characteristics analysis in optical burst switching networks with optical label processing

    Directory of Open Access Journals (Sweden)

    Edson Moschim

    2007-03-01

    Full Text Available An analysis is carried out with burst-switching optical networks which use label processing consisting of orthogonal optical codes (OOC, considering traffic characteristics such as length/duration and arrival rate of bursts. Main results show that the use of OOC label processing influences on the decrease of burst loss probability, especially for short-lived bursts. Therefore, short bursts that would be blocked in conventional electronic processing networks are transmitted when the OOC label processing is used. Thus, an increase in the network use occurs as well as a decrease in the burst transmission latency, reaching a granularity close to packets networks.

  5. Control Policies Approaching HGI Performance in Heavy Traffic for Resource Sharing Networks

    OpenAIRE

    Budhiraja, Amarjit; Johnson, Dane

    2017-01-01

    We consider resource sharing networks of the form introduced in the work of Massouli\\'{e} and Roberts(2000) as models for Internet flows. The goal is to study the open problem, formulated in Harrison et al. (2014), of constructing simple form rate allocation policies for broad families of resource sharing networks with associated costs converging to the Hierarchical Greedy Ideal performance in the heavy traffic limit. We consider two types of cost criteria, an infinite horizon discounted cost...

  6. Deep space network software cost estimation model

    Science.gov (United States)

    Tausworthe, R. C.

    1981-01-01

    A parametric software cost estimation model prepared for Jet PRopulsion Laboratory (JPL) Deep Space Network (DSN) Data System implementation tasks is described. The resource estimation mdel modifies and combines a number of existing models. The model calibrates the task magnitude and difficulty, development environment, and software technology effects through prompted responses to a set of approximately 50 questions. Parameters in the model are adjusted to fit JPL software life-cycle statistics.

  7. 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.

  8. Hyper-Spectral Networking Concept of Operations and Future Air Traffic Management Simulations

    Science.gov (United States)

    Davis, Paul; Boisvert, Benjamin

    2017-01-01

    The NASA sponsored Hyper-Spectral Communications and Networking for Air Traffic Management (ATM) (HSCNA) project is conducting research to improve the operational efficiency of the future National Airspace System (NAS) through diverse and secure multi-band, multi-mode, and millimeter-wave (mmWave) wireless links. Worldwide growth of air transportation and the coming of unmanned aircraft systems (UAS) will increase air traffic density and complexity. Safe coordination of aircraft will require more capable technologies for communications, navigation, and surveillance (CNS). The HSCNA project will provide a foundation for technology and operational concepts to accommodate a significantly greater number of networked aircraft. This paper describes two of the HSCNA projects technical challenges. The first technical challenge is to develop a multi-band networking concept of operations (ConOps) for use in multiple phases of flight and all communication link types. This ConOps will integrate the advanced technologies explored by the HSCNA project and future operational concepts into a harmonized vision of future NAS communications and networking. The second technical challenge discussed is to conduct simulations of future ATM operations using multi-bandmulti-mode networking and technologies. Large-scale simulations will assess the impact, compared to todays system, of the new and integrated networks and technologies under future air traffic demand.

  9. Dynamic routing control in heterogeneous tactical networks with multiple traffic priorities

    Science.gov (United States)

    Fecko, Mariusz A.; Wong, Larry; Kang, Jaewong; Cichocki, Andrzej; Kaul, Vikram; Samtani, Sunil

    2012-05-01

    To efficiently use alternate paths during periods of congestion, we have devised prioritized Dynamic Routing Control Agent (pDRCA) that (1) selects best links to meet the bandwidth and delay requirements of traffic, (2) provides load-balancing and traffic prioritization when multiple topologies are available, and (3) handles changes in link quality and traffic demand, and link outages. pDRCA provides multiplatform load balancing to maximize SATCOM (both P2P and multi-point) and airborne links utilization. It influences link selection by configuring the cost metrics on a router's interface, which does not require any changes to the routing protocol itself. It supports service differentiation of multiple traffic priorities by providing more network resources to the highest priority flows. pDRCA does so by solving an optimization problem to find optimal links weights that increase throughput and decrease E2E delay; avoid congested, low quality, and long delay links; and exploit path diversity in the network. These optimal link weights are sent to the local agents to be configured on individual routers per traffic priority. The pDRCA optimization algorithm has been proven effective in improving application performance. We created a variety of different test scenarios by varying traffic profile and link behavior (stable links, varying capacity, and link outages). In the scenarios where high priority traffic experienced significant loss without pDRCA, the average loss was reduced from 49.5% to 13% and in some cases dropped to 0%. Currently, pDRCA is integrated with an open-source software router and priority queues on Linux as a component of Open Tactical Router (OTR), which is being developed by ONR DTCN program.

  10. Characterization of Background Traffic in Hybrid Network Simulation

    National Research Council Canada - National Science Library

    Lauwens, Ben; Scheers, Bart; Van de Capelle, Antoine

    2006-01-01

    .... Two approaches are common: discrete event simulation and fluid approximation. A discrete event simulation generates a huge amount of events for a full-blown battlefield communication network resulting in a very long runtime...

  11. Estimating cost of road traffic injuries in Iran using willingness to pay (WTP method.

    Directory of Open Access Journals (Sweden)

    Elaheh Ainy

    Full Text Available We aimed to use the willingness to pay (WTP method to calculate the cost of traffic injuries in Iran in 2013. We conducted a cross-sectional questionnaire-based study of 846 randomly selected road users. WTP data was collected for four scenarios for vehicle occupants, pedestrians, vehicle drivers, and motorcyclists. Final analysis was carried out using Weibull and maximum likelihood method. Mean WTP was 2,612,050 Iranian rials (IRR. Statistical value of life was estimated according to 20,408 fatalities 402,314,106,073,648 IRR (US$13,410,470,202 based on purchasing power parity at (February 27th, 2014. Injury cost was US$25,637,870,872 (based on 318,802 injured people in 2013, multiple daily traffic volume of 311, and multiple daily payment of 31,030 IRR for 250 working days. The total estimated cost of injury and death cases was 39,048,341,074$. Gross national income of Iran was, US$604,300,000,000 in 2013 and the costs of traffic injuries constituted 6·46% of gross national income. WTP was significantly associated with age, gender, monthly income, daily payment, more payment for time reduction, trip mileage, drivers and occupants from road users. The costs of traffic injuries in Iran in 2013 accounted for 6.64% of gross national income, much higher than the global average. Policymaking and resource allocation to reduce traffic-related death and injury rates have the potential to deliver a huge economic benefit.

  12. Anticipation of Traffic Demands to Guarantee QoS in IP/Optical Networks

    Directory of Open Access Journals (Sweden)

    Carolina Pinart

    2010-09-01

    Full Text Available Traffic in the Internet backbone is expected to grow above a few Tbit/s in 2020. To cope with this, operators are moving to IP/optical network architectures, where IP is the convergence layer for all services. On the other hand, the quality of service (QoS requirements of future applications encompasses the individualization of services and the assurance of stricter quality parameters such as latency, jitter or capacity. In other words, future optical networks will not only transport more IP data, but they will also have to offer differentiated QoS requirements to services. Finally, some emerging applications, e.g., grid computing, need greater flexibility in the usage of network resources, which involves establishing and releasing connections as if they were virtualized resources controlled by other elements or layers. In this context, traffic-driven lightpath provisioning and service-plane approaches arise as very interesting candidate solutions to solve the main challenges described above. This work reviews the concepts of service-oriented and self-managed networks and relates them to propose an integrated approach to assure QoS by offering flow-aware networking in the sense that traffic demands will be anticipated in a suitable way, lightpaths will be established taking into account QoS information (i.e., impairments and complex services will be decomposed into optical connections so that the above techniques can be employed to assure QoS for any service.

  13. Threshold based AntNet algorithm for dynamic traffic routing of road networks

    Directory of Open Access Journals (Sweden)

    Ayman M. Ghazy

    2012-07-01

    Full Text Available Dynamic routing algorithms play an important role in road traffic routing to avoid congestion and to direct vehicles to better routes. AntNet routing algorithms have been applied, extensively and successfully, in data communication network. However, its application for dynamic routing on road networks is still considerably limited. This paper presents a modified version of the AntNet routing algorithm, called “Threshold based AntNet”, that has the ability to efficiently utilize a priori information of dynamic traffic routing, especially, for road networks. The modification exploits the practical and pre-known information for most road traffic networks, namely, the good travel times between sources and destinations. The values of those good travel times are manipulated as threshold values. This approach has proven to conserve tracking of good routes. According to the dynamic nature of the problem, the presented approach guards the agility of rediscovering a good route. Attaining the thresholds (good reported travel times, of a given source to destination route, permits for a better utilization of the computational resources, that, leads to better accommodation for the network changes. The presented algorithm introduces a new type of ants called “check ants”. It assists in preserving good routes and, better yet, exposes and discards the degraded ones. The threshold AntNet algorithm presents a new strategy for updating the routing information, supported by the backward ants.

  14. Early estimate of motor vehicle traffic fatalities for the first half (January-June) of 2009 : a brief statistical summary

    Science.gov (United States)

    2009-10-01

    A statistical projection of traffic fatalities for the first three quarters of 2009 shows that an estimated 25,576 people died in motor vehicle traffic crashes. This represents a decline of about 7.9 percent as compared to the 27,771 fa-talities that...

  15. Early estimate of motor vehicle traffic fatalities for the first quarter (January-March) of 2009 : a brief statistical summary

    Science.gov (United States)

    2009-06-01

    A statistical projection of traffic fatalities for the first quarter of 2009 shows that an estimated 7,689 people died in motor vehicle traffic crashes. This represents a decline of about 9 percent as compared to the 8,451 fatalities that occurred in...

  16. Early estimate of motor vehicle traffic fatalities for the first half (January-June) of 2010 : a brief statistical summary

    Science.gov (United States)

    2010-09-01

    A statistical projection of traffic fatalities for the first half of : 2010 shows that an estimated 14,996 people died in motor : vehicle traffic crashes. This represents a decline of about 9.2 : percent as compared to the 16,509 fatalities that occu...

  17. Heterogeneous Cellular Networks with Spatio-Temporal Traffic: Delay Analysis and Scheduling

    OpenAIRE

    Zhong, Yi; Quek, Tony Q. S.; Ge, Xiaohu

    2016-01-01

    Emergence of new types of services has led to various traffic and diverse delay requirements in fifth generation (5G) wireless networks. Meeting diverse delay requirements is one of the most critical goals for the design of 5G wireless networks. Though the delay of point-to-point communications has been well investigated, the delay of multi-point to multi-point communications has not been thoroughly studied since it is a complicated function of all links in the network. In this work, we propo...

  18. USER EQUILIBRIUM AND SYSTEM OPTIMUM TRAFFIC ASSIGNMENTS; ISTANBUL ROAD NETWORK EXAMPLE

    Directory of Open Access Journals (Sweden)

    Banihan GÜNAY

    1996-03-01

    Full Text Available The concept of road networks and traffic flow equilibrium conditions are briefly reviewed and discussed. In order to see whether some benefits for the society (e.g. whole network by employing a System Optimum assignment approach can be achieved or not, an assessment study was carried out on the Ystanbul road network using the actual data gathered. As a result of the system optimising simulation, queuing times on the Bosphorus Bridge dropped by 12% and speed of an average car increased by 16%, compared to the results produced by the User Equilibrium assignment. Besides, the total system journey time was also reduced by about 4%.

  19. Position estimation of transceivers in communication networks

    Science.gov (United States)

    Kent, Claudia A [Pleasanton, CA; Dowla, Farid [Castro Valley, CA

    2008-06-03

    This invention provides a system and method using wireless communication interfaces coupled with statistical processing of time-of-flight data to locate by position estimation unknown wireless receivers. Such an invention can be applied in sensor network applications, such as environmental monitoring of water in the soil or chemicals in the air where the position of the network nodes is deemed critical. Moreover, the present invention can be arranged to operate in areas where a Global Positioning System (GPS) is not available, such as inside buildings, caves, and tunnels.

  20. Traffic Flow Prediction Model for Large-Scale Road Network Based on Cloud Computing

    Directory of Open Access Journals (Sweden)

    Zhaosheng Yang

    2014-01-01

    Full Text Available To increase the efficiency and precision of large-scale road network traffic flow prediction, a genetic algorithm-support vector machine (GA-SVM model based on cloud computing is proposed in this paper, which is based on the analysis of the characteristics and defects of genetic algorithm and support vector machine. In cloud computing environment, firstly, SVM parameters are optimized by the parallel genetic algorithm, and then this optimized parallel SVM model is used to predict traffic flow. On the basis of the traffic flow data of Haizhu District in Guangzhou City, the proposed model was verified and compared with the serial GA-SVM model and parallel GA-SVM model based on MPI (message passing interface. The results demonstrate that the parallel GA-SVM model based on cloud computing has higher prediction accuracy, shorter running time, and higher speedup.

  1. Noise-Assisted Concurrent Multipath Traffic Distribution in Ad Hoc Networks

    Directory of Open Access Journals (Sweden)

    Narun Asvarujanon

    2013-01-01

    Full Text Available The concept of biologically inspired networking has been introduced to tackle unpredictable and unstable situations in computer networks, especially in wireless ad hoc networks where network conditions are continuously changing, resulting in the need of robustness and adaptability of control methods. Unfortunately, existing methods often rely heavily on the detailed knowledge of each network component and the preconfigured, that is, fine-tuned, parameters. In this paper, we utilize a new concept, called attractor perturbation (AP, which enables controlling the network performance using only end-to-end information. Based on AP, we propose a concurrent multipath traffic distribution method, which aims at lowering the average end-to-end delay by only adjusting the transmission rate on each path. We demonstrate through simulations that, by utilizing the attractor perturbation relationship, the proposed method achieves a lower average end-to-end delay compared to other methods which do not take fluctuations into account.

  2. Accelerating Network Traffic Analytics Using Query-DrivenVisualization

    Energy Technology Data Exchange (ETDEWEB)

    Bethel, E. Wes; Campbell, Scott; Dart, Eli; Stockinger, Kurt; Wu,Kesheng

    2006-07-29

    Realizing operational analytics solutions where large and complex data must be analyzed in a time-critical fashion entails integrating many different types of technology. This paper focuses on an interdisciplinary combination of scientific data management and visualization/analysis technologies targeted at reducing the time required for data filtering, querying, hypothesis testing and knowledge discovery in the domain of network connection data analysis. We show that use of compressed bitmap indexing can quickly answer queries in an interactive visual data analysis application, and compare its performance with two alternatives for serial and parallel filtering/querying on 2.5 billion records worth of network connection data collected over a period of 42 weeks. Our approach to visual network connection data exploration centers on two primary factors: interactive ad-hoc and multiresolution query formulation and execution over n dimensions and visual display of then-dimensional histogram results. This combination is applied in a case study to detect a distributed network scan and to then identify the set of remote hosts participating in the attack. Our approach is sufficiently general to be applied to a diverse set of data understanding problems as well as used in conjunction with a diverse set of analysis and visualization tools.

  3. A network traffic reduction method for cooperative positioning

    NARCIS (Netherlands)

    Das, Kallol; Wymeersch, Henk

    Cooperative positioning is suitable for applications where conventional positioning fails due to lack of connectivity with a sufficient number of reference nodes. In a dense network, as the number of cooperating devices increases, the number of packet exchanges also increases proportionally. This

  4. A latency analysis for M2M and OG-like traffic patterns in different HSPA core network configurations

    Directory of Open Access Journals (Sweden)

    M. V. Popović

    2014-11-01

    Full Text Available In this paper we present an analysis intended to reveal possible impacts of core network features on latency for modelled M2M and Online Gaming traffic. Simulations were performed in a live 3G/HSPA network. Test traffic simulating multiplayer real-time games and M2M applications was generated on 10 mobile phones in parallel, sending data to a remote server. APNs with different combinations of hardware and features (proxy server, different GGSNs and firewalls, usage of Service Awareness feature were chosen. The traffic was recorded on the Gn interface in the mobile core. The goal of experiments was to evaluate any eventually significant variation of average recorded RTTs in the core part of mobile network that would clearly indicate either the impact of used APN on delay for a specific traffic pattern, or selectivity of the APN towards different traffic patterns.

  5. Diamond Networks with Bursty Traffic: Bounds on the Minimum Energy-Per-Bit

    CERN Document Server

    Shomorony, Ilan; Parvaresh, Farzad; Avestimehr, A Salman

    2012-01-01

    When data traffic in a wireless network is bursty, small amounts of data sporadically become available for transmission, at times that are unknown at the receivers, and an extra amount of energy must be spent at the transmitters to overcome this lack of synchronization between the network nodes. In practice, pre-defined header sequences are used with the purpose of synchronizing the different network nodes. However, in networks where relays must be used for communication, the overhead required for synchronizing the entire network may be very significant. In this work, we study the fundamental limits of energy-efficient communication in an asynchronous diamond network with two relays. We formalize the notion of relay synchronization by saying that a relay is synchronized if the conditional entropy of the arrival time of the source message given the received signals at the relay is small. We show that the minimum energy-per-bit for bursty traffic in diamond networks is achieved with a coding scheme where each r...

  6. Multiobjective Reinforcement Learning for Traffic Signal Control Using Vehicular Ad Hoc Network

    Directory of Open Access Journals (Sweden)

    Houli Duan

    2010-01-01

    Full Text Available We propose a new multiobjective control algorithm based on reinforcement learning for urban traffic signal control, named multi-RL. A multiagent structure is used to describe the traffic system. A vehicular ad hoc network is used for the data exchange among agents. A reinforcement learning algorithm is applied to predict the overall value of the optimization objective given vehicles' states. The policy which minimizes the cumulative value of the optimization objective is regarded as the optimal one. In order to make the method adaptive to various traffic conditions, we also introduce a multiobjective control scheme in which the optimization objective is selected adaptively to real-time traffic states. The optimization objectives include the vehicle stops, the average waiting time, and the maximum queue length of the next intersection. In addition, we also accommodate a priority control to the buses and the emergency vehicles through our model. The simulation results indicated that our algorithm could perform more efficiently than traditional traffic light control methods.

  7. Multiobjective Reinforcement Learning for Traffic Signal Control Using Vehicular Ad Hoc Network

    Science.gov (United States)

    Houli, Duan; Zhiheng, Li; Yi, Zhang

    2010-12-01

    We propose a new multiobjective control algorithm based on reinforcement learning for urban traffic signal control, named multi-RL. A multiagent structure is used to describe the traffic system. A vehicular ad hoc network is used for the data exchange among agents. A reinforcement learning algorithm is applied to predict the overall value of the optimization objective given vehicles' states. The policy which minimizes the cumulative value of the optimization objective is regarded as the optimal one. In order to make the method adaptive to various traffic conditions, we also introduce a multiobjective control scheme in which the optimization objective is selected adaptively to real-time traffic states. The optimization objectives include the vehicle stops, the average waiting time, and the maximum queue length of the next intersection. In addition, we also accommodate a priority control to the buses and the emergency vehicles through our model. The simulation results indicated that our algorithm could perform more efficiently than traditional traffic light control methods.

  8. Integrated coding-aware intra-ONU scheduling for passive optical networks with inter-ONU traffic

    Science.gov (United States)

    Li, Yan; Dai, Shifang; Wu, Weiwei

    2016-12-01

    Recently, with the soaring of traffic among optical network units (ONUs), network coding (NC) is becoming an appealing technique for improving the performance of passive optical networks (PONs) with such inter-ONU traffic. However, in the existed NC-based PONs, NC can only be implemented by buffering inter-ONU traffic at the optical line terminal (OLT) to wait for the establishment of coding condition, such passive uncertain waiting severely limits the effect of NC technique. In this paper, we will study integrated coding-aware intra-ONU scheduling in which the scheduling of inter-ONU traffic within each ONU will be undertaken by the OLT to actively facilitate the forming of coding inter-ONU traffic based on the global inter-ONU traffic distribution, and then the performance of PONs with inter-ONU traffic can be significantly improved. We firstly design two report message patterns and an inter-ONU traffic transmission framework as the basis for the integrated coding-aware intra-ONU scheduling. Three specific scheduling strategies are then proposed for adapting diverse global inter-ONU traffic distributions. The effectiveness of the work is finally evaluated by both theoretical analysis and simulations.

  9. Integration of a network aware traffic generation device into a computer network emulation platform

    CSIR Research Space (South Africa)

    Von Solms, S

    2014-07-01

    Full Text Available Flexible, open source network emulation tools can provide network researchers with significant benefits regarding network behaviour and performance. The evaluation of these networks can benefit greatly from the integration of realistic, network...

  10. Prediction of road traffic death rate using neural networks optimised by genetic algorithm.

    Science.gov (United States)

    Jafari, Seyed Ali; Jahandideh, Sepideh; Jahandideh, Mina; Asadabadi, Ebrahim Barzegari

    2015-01-01

    Road traffic injuries (RTIs) are realised as a main cause of public health problems at global, regional and national levels. Therefore, prediction of road traffic death rate will be helpful in its management. Based on this fact, we used an artificial neural network model optimised through Genetic algorithm to predict mortality. In this study, a five-fold cross-validation procedure on a data set containing total of 178 countries was used to verify the performance of models. The best-fit model was selected according to the root mean square errors (RMSE). Genetic algorithm, as a powerful model which has not been introduced in prediction of mortality to this extent in previous studies, showed high performance. The lowest RMSE obtained was 0.0808. Such satisfactory results could be attributed to the use of Genetic algorithm as a powerful optimiser which selects the best input feature set to be fed into the neural networks. Seven factors have been known as the most effective factors on the road traffic mortality rate by high accuracy. The gained results displayed that our model is very promising and may play a useful role in developing a better method for assessing the influence of road traffic mortality risk factors.

  11. Position Estimation of Transceivers in Communication Networks

    Energy Technology Data Exchange (ETDEWEB)

    Dowla, F; Kent, C

    2004-01-20

    With rapid developments in wireless sensor networks, there is a growing need for transceiver position estimation independent of GPS, which may not be available in indoor networks. Our approach is to use range estimates from time-of-flight (TOF) measurements, a technique well suited to large bandwidth physical links, such as in ultra-wideband (UWB) systems. In our UWB systems, pulse duration less than 200 psecs can easily be resolved to less than a foot. Assuming an encoded UWB physical layer, we first test positioning accuracy using simulations. We are interested in sensitivity to range errors and the required number of ranging nodes, and we show that in a high-precision environment, such as UWB, the optimal number of transmitters is four. Four transmitters with {+-}20ft. range error can locate a receiver to within one or two feet. We then implement these algorithms on an 802.11 wireless network and demonstrate the ability to locate a network access point to approximately 20 feet.

  12. Traffic Dimensioning and Performance Modeling of 4G LTE Networks

    Science.gov (United States)

    Ouyang, Ye

    2011-01-01

    Rapid changes in mobile techniques have always been evolutionary, and the deployment of 4G Long Term Evolution (LTE) networks will be the same. It will be another transition from Third Generation (3G) to Fourth Generation (4G) over a period of several years, as is the case still with the transition from Second Generation (2G) to 3G. As a result,…

  13. Design and Implementation of Real-Time Vehicular Camera for Driver Assistance and Traffic Congestion Estimation

    Directory of Open Access Journals (Sweden)

    Sanghyun Son

    2015-08-01

    Full Text Available As society has developed, the number of vehicles has increased and road conditions have become complicated, increasing the risk of crashes. Therefore, a service that provides safe vehicle control and various types of information to the driver is urgently needed. In this study, we designed and implemented a real-time traffic information system and a smart camera device for smart driver assistance systems. We selected a commercial device for the smart driver assistance systems, and applied a computer vision algorithm to perform image recognition. For application to the dynamic region of interest, dynamic frame skip methods were implemented to perform parallel processing in order to enable real-time operation. In addition, we designed and implemented a model to estimate congestion by analyzing traffic information. The performance of the proposed method was evaluated using images of a real road environment. We found that the processing time improved by 15.4 times when all the proposed methods were applied in the application. Further, we found experimentally that there was little or no change in the recognition accuracy when the proposed method was applied. Using the traffic congestion estimation model, we also found that the average error rate of the proposed model was 5.3%.

  14. Design and Implementation of Real-Time Vehicular Camera for Driver Assistance and Traffic Congestion Estimation

    Science.gov (United States)

    Son, Sanghyun; Baek, Yunju

    2015-01-01

    As society has developed, the number of vehicles has increased and road conditions have become complicated, increasing the risk of crashes. Therefore, a service that provides safe vehicle control and various types of information to the driver is urgently needed. In this study, we designed and implemented a real-time traffic information system and a smart camera device for smart driver assistance systems. We selected a commercial device for the smart driver assistance systems, and applied a computer vision algorithm to perform image recognition. For application to the dynamic region of interest, dynamic frame skip methods were implemented to perform parallel processing in order to enable real-time operation. In addition, we designed and implemented a model to estimate congestion by analyzing traffic information. The performance of the proposed method was evaluated using images of a real road environment. We found that the processing time improved by 15.4 times when all the proposed methods were applied in the application. Further, we found experimentally that there was little or no change in the recognition accuracy when the proposed method was applied. Using the traffic congestion estimation model, we also found that the average error rate of the proposed model was 5.3%. PMID:26295230

  15. Comparison between genetic algorithm and self organizing map to detect botnet network traffic

    Science.gov (United States)

    Yugandhara Prabhakar, Shinde; Parganiha, Pratishtha; Madhu Viswanatham, V.; Nirmala, M.

    2017-11-01

    In Cyber Security world the botnet attacks are increasing. To detect botnet is a challenging task. Botnet is a group of computers connected in a coordinated fashion to do malicious activities. Many techniques have been developed and used to detect and prevent botnet traffic and the attacks. In this paper, a comparative study is done on Genetic Algorithm (GA) and Self Organizing Map (SOM) to detect the botnet network traffic. Both are soft computing techniques and used in this paper as data analytics system. GA is based on natural evolution process and SOM is an Artificial Neural Network type, uses unsupervised learning techniques. SOM uses neurons and classifies the data according to the neurons. Sample of KDD99 dataset is used as input to GA and SOM.

  16. Game theoretic analysis of congestion, safety and security networks, air traffic and emergency departments

    CERN Document Server

    Zhuang, Jun

    2015-01-01

    Maximizing reader insights into the roles of intelligent agents in networks, air traffic and emergency departments, this volume focuses on congestion in systems where safety and security are at stake, devoting special attention to applying game theoretic analysis of congestion to: protocols in wired and wireless networks; power generation, air transportation and emergency department overcrowding. Reviewing exhaustively the key recent research into the interactions between game theory, excessive crowding, and safety and security elements, this book establishes a new research angle by illustrating linkages between the different research approaches and serves to lay the foundations for subsequent analysis. Congestion (excessive crowding) is defined in this work as all kinds of flows; e.g., road/sea/air traffic, people, data, information, water, electricity, and organisms. Analyzing systems where congestion occurs – which may be in parallel, series, interlinked, or interdependent, with flows one way or both way...

  17. CIPP: a versatile analytical model for VBR traffic in ATM networks

    Science.gov (United States)

    Manivasakan, R.; Desai, U. B.; Karandikar, Abhay

    1999-08-01

    Correlated Interarrival time Process (CIPP) has been proposed, for modeling both the composite arrival process of packets in broadband networks and the individual source modeling. The CIPP--a generalization of the Poisson process- - is a stationary counting process and is parameterized by a correlation parameter `p' which represents the degree of correlation in adjacent interarrivals in addition to `(lambda) ' the intensity of the process. In this paper, we present the performance modeling of VBR video traffic in ATM networks, using CIPP/M/1 queue. We first give the expressions for stationary distributions for CIPP/M/1 queue. The, we derive the queuing measures of interest. We simulate a queue with smoothed VBR video trace data as input (with exponential services) to compare with the theoretical measures derived above. Experimental results show that the CIPP/M/1 queue, models well with ATM multiplexer performance with the real world VBR video traffic input.

  18. A model to identify urban traffic congestion hotspots in complex networks

    CERN Document Server

    Solé-Ribalta, Albert; Arenas, Alex

    2016-01-01

    The rapid growth of population in urban areas is jeopardizing the mobility and air quality worldwide. One of the most notable problems arising is that of traffic congestion. With the advent of technologies able to sense real-time data about cities, and its public distribution for analysis, we are in place to forecast scenarios valuable for improvement and control. Here, we propose an idealized model, based on the critical phenomena arising in complex networks, that allows to analytically predict congestion hotspots in urban environments. Results on real cities' road networks, considering, in some experiments, real-traffic data, show that the proposed model is capable of identifying susceptible junctions that might becomes hotspots if mobility demand increases.

  19. INCITE: Edge-based Traffic Processing and Inference for High-Performance Networks

    Energy Technology Data Exchange (ETDEWEB)

    Baraniuk, Richard G.; Feng, Wu-chun; Cottrell, Les; Knightly, Edward; Nowak, Robert; Riedi, Rolf

    2005-06-20

    The INCITE (InterNet Control and Inference Tools at the Edge) Project developed on-line tools to characterize and map host and network performance as a function of space, time, application, protocol, and service. In addition to their utility for trouble-shooting problems, these tools will enable a new breed of applications and operating systems that are network aware and resource aware. Launching from the foundation provided our recent leading-edge research on network measurement, multifractal signal analysis, multiscale random fields, and quality of service, our effort consisted of three closely integrated research thrusts that directly attack several key networking challenges of DOE's SciDAC program. These are: Thrust 1, Multiscale traffic analysis and modeling techniques; Thrust 2, Inference and control algorithms for network paths, links, and routers, and Thrust 3, Data collection tools.

  20. An Efficient Tabu Search DSA Algorithm for Heterogeneous Traffic in Cellular Networks

    OpenAIRE

    Kamal, Hany; Coupechoux, Marceau; Godlewski, Philippe

    2010-01-01

    International audience; In this paper, we propose and analyze a TS (Tabu Search) algorithm for DSA (Dynamic Spectrum Access) in cellular networks. We consider a scenario where cellular operators share a common access band, and we focus on the strategy of one operator providing packet services to the end-users. We consider a soft interference requirement for the algorithm's design that suits the packet traffic context. The operator's objective is to maximize its reward while taking into accoun...

  1. Using bayesian model to estimate the cost of traffic injuries in Iran in 2013.

    Science.gov (United States)

    Ainy, Elaheh; Soori, Hamid; Ganjali, Mojtaba; Bahadorimonfared, Ayad

    2017-01-01

    A significant social and economic burden inflicts by road traffic injuries (RTIs). We aimed to use Bayesian model, to present the precise method, and to estimate the cost of RTIs in Iran in 2013. In a cross-sectional study on costs resulting from traffic injuries, 846 people per road user were randomly selected and investigated during 3 months (1(st) September-1(st) December) in 2013. The research questionnaire was prepared based on the standard for willingness to pay (WTP) method considering perceived risks, especially in Iran. Data were collected along with four scenarios for occupants, pedestrians, vehicle drivers, and motorcyclists. Inclusion criterion was having at least high school education and being in the age range of 18-65 years old; risk perception was an important factor to the study and measured by visual tool. Samples who did not have risk perception were excluded from the study. Main outcome measure was cost estimation of traffic injuries using WTP method. Mean WTP was 2,612,050 internal rate of return (IRR) among these road users. Statistical value of life was estimated according to 20,408 death cases 402,314,106,073,648 IRR, equivalent to 13,410,470,202$ based on the dollar free market rate of 30,000 IRR (purchase power parity). In sum, injury and death cases came to 1,171,450,232,238,648 IRR equivalents to 39,048,341,074$. Moreover, in 2013, costs of traffic accident constituted 6.46% of gross national income, which was 604,300,000,000$. WTP had a significant relationship with age, middle and high income, daily payment to injury reduction, more payment to time reduction, trip mileage, private cars drivers, bus, minibus vehicles, and occupants (P < 0.01). Costs of traffic injuries included noticeable portion of gross national income. If policy-making and resource allocation are made based on the scientific pieces of evidence, an enormous amount of capital can be saved through reducing death and injury rates.

  2. 77 FR 3544 - Meeting and Webinar on the Active Traffic and Demand Management and Intelligent Network Flow...

    Science.gov (United States)

    2012-01-24

    ... Management and Intelligent Network Flow Optimization Operational Concepts; Notice of Public Meeting AGENCY... Traffic and Demand Management (ADTM) and Intelligent Network Flow Optimization (INFLO) operational... transportation network. Issued in Washington, DC, on the 18th day of January 2012. John Augustine, Managing...

  3. Admission Control for Multiservices Traffic in Hierarchical Mobile IPv6 Networks by Using Fuzzy Inference System

    Directory of Open Access Journals (Sweden)

    Jung-Shyr Wu

    2012-01-01

    Full Text Available CAC (Call Admission Control plays a significant role in providing QoS (Quality of Service in mobile wireless networks. In addition to much research that focuses on modified Mobile IP to get better efficient handover performance, CAC should be introduced to Mobile IP-based network to guarantee the QoS for users. In this paper, we propose a CAC scheme which incorporates multiple traffic types and adjusts the admission threshold dynamically using fuzzy control logic to achieve better usage of resources. The method can provide QoS in Mobile IPv6 networks with few modifications on MAP (Mobility Anchor Point functionality and slight change in BU (Binding Update message formats. According to the simulation results, the proposed scheme presents good performance of voice and video traffic at the expenses of poor performance on data traffic. It is evident that these CAC schemes can reduce the probability of the handoff dropping and the cell overload and limit the probability of the new call blocking.

  4. Model establishing and performance analysis of service stratum traffic in the integrated sensing network

    Science.gov (United States)

    Ge, Zhiqun; Wang, Ying; Zhang, Xiaolu; Zheng, Yu; Zhao, Xinqun; Sun, Xiaohan

    2017-01-01

    We propose a time-division hybrid-user data flow model scheme based on semi-Markov state-transition algorithm for multiclass business and service in Integrated Sensing Network (ISN). Two typical flow models, visual sense and auditory sense service models, are set up due to the real situation of service stratum traffic, respectively. The experimental system based on the Asynchronous Optical Packet Switching (AOPS) network simulation platform is established for the feasibility of the proposed data flow model. The results show that the proposed models achieve reasonable packet loss rate and delay time in the case of different business and service levels.

  5. A multiclass vehicular dynamic traffic flow model for main roads and dedicated lanes/roads of multimodal transport network

    Energy Technology Data Exchange (ETDEWEB)

    Sossoe, K.S., E-mail: kwami.sossoe@irt-systemx.fr [TECHNOLOGICAL RESEARCH INSTITUTE SYSTEMX (France); Lebacque, J-P., E-mail: jean-patrick.lebacque@ifsttar.fr [UPE/IFSTTAR-COSYS-GRETTIA (France)

    2015-03-10

    We present in this paper a model of vehicular traffic flow for a multimodal transportation road network. We introduce the notion of class of vehicles to refer to vehicles of different transport modes. Our model describes the traffic on highways (which may contain several lanes) and network transit for pubic transportation. The model is drafted with Eulerian and Lagrangian coordinates and uses a Logit model to describe the traffic assignment of our multiclass vehicular flow description on shared roads. The paper also discusses traffic streams on dedicated lanes for specific class of vehicles with event-based traffic laws. An Euler-Lagrangian-remap scheme is introduced to numerically approximate the model’s flow equations.

  6. Estimation of Road Traffic Mortality in Kurdistan Province, Iran, During 2004-2009, Using Capture-Recapture Method

    Directory of Open Access Journals (Sweden)

    Lida Gorgin

    2016-04-01

    Full Text Available Background: To reduce traffic injuries in the country, health professionals should have accurate estimates of road traffic deaths. Multiple and sometimes inconsistent statistics presented by organizations in charge create high degree of uncertainty for planners and decision makers. To achieve an accurate estimate, several methods are available. Of them, capture-recapture method seems to be an appropriate and affordable method regarding the reliability of the data sources. This study aimed to estimate the number of road traffic deaths in Kurdistan Province during 2004-2009, using capture-recapture method and based on 2 sources of data obtained from Death Registration System and Forensic Medicine Department. Materials and Methods: All deaths due to road traffic accidents in Kurdistan Province were extracted during 2004-2009. These deaths were legally registered in Death Registration System and Forensic Medicine Department. Shared cases among these 2 sources were identified based on full name, age, gender, and date of death and finally the accurate number of deaths was calculated using the correct volume formula. Results: During study period, Forensic Medicine Department of the province had registered about 3289 cases of road traffic mortalities and Death Registration System had registered 3771 cases of death resulting from road traffic accidents. Using capture-recapture method, the number of deaths in the same years was estimated as 5726 people (5818-5634:CI95%. The proportion of mortality registered in the Death Registration System and Forensic Medicine Department of the province to the total estimated deaths were 65.8% and 57.4%, respectively and both systems together covered 85.4% of road traffic deaths, i.e. under-reporting of about 832 people. Conclusion: The results of the present study indicate that none of 2 sources of Forensic Medicine Department and Death Registration System, per se or both, fully covered road traffic mortalities and

  7. Report on the Dagstuhl Seminar on Visualization and Monitoring of Network Traffic

    Energy Technology Data Exchange (ETDEWEB)

    Keim, Daniel; Pras, Aiko; Schonwalder, Jurgen; Wong, Pak C.; Mansmann, Florian

    2011-01-26

    The Dagstuhl Seminar on Visualization and Monitoring of Network Traffic [1] took place May 17-20, 2009 in Dagstuhl, Germany. Dagstuhl seminars promote personal interaction and open discussion of results as well as new ideas. Unlike at most conferences, the focus is not solely on the presentation of established results but to equal parts on results, ideas, sketches, and open problems. The aim of this particular seminar was to bring together experts from the information visualization community and the networking community in order to discuss the state of the art of monitoring and visualization of network traffic. People from the different research communities involved jointly organized the seminar. The co-chairs of the seminar from the networking community were Aiko Pras (University of Twente) and Jürgen Schönwälder (Jacobs University Bremen). The co-chairs from the visualization community were Daniel A. Keim (University of Konstanz) and Pak Chung Wong (Pacific Northwest National Lab). Florian Mansmann (University of Konstanz) helped with producing this report. The seminar was organized and supported by Schloss Dagstuhl and the EC IST-EMANICS Network of Excellence [1].

  8. Determination of network origin-destination matrices using partial link traffic counts and virtual sensor information in an integrated corridor management framework.

    Science.gov (United States)

    2014-04-01

    Trip origin-destination (O-D) demand matrices are critical components in transportation network : modeling, and provide essential information on trip distributions and corresponding spatiotemporal : traffic patterns in traffic zones in vehicular netw...

  9. A comparison of traffic estimates of nocturnal flying animals using radar, thermal imaging, and acoustic recording.

    Science.gov (United States)

    Horton, Kyle G; Shriver, W Gregory; Buler, Jeffrey J

    2015-03-01

    There are several remote-sensing tools readily available for the study of nocturnally flying animals (e.g., migrating birds), each possessing unique measurement biases. We used three tools (weather surveillance radar, thermal infrared camera, and acoustic recorder) to measure temporal and spatial patterns of nocturnal traffic estimates of flying animals during the spring and fall of 2011 and 2012 in Lewes, Delaware, USA. Our objective was to compare measures among different technologies to better understand their animal detection biases. For radar and thermal imaging, the greatest observed traffic rate tended to occur at, or shortly after, evening twilight, whereas for the acoustic recorder, peak bird flight-calling activity was observed just prior to morning twilight. Comparing traffic rates during the night for all seasons, we found that mean nightly correlations between acoustics and the other two tools were weakly correlated (thermal infrared camera and acoustics, r = 0.004 ± 0.04 SE, n = 100 nights; radar and acoustics, r = 0.14 ± 0.04 SE, n = 101 nights), but highly variable on an individual nightly basis (range = -0.84 to 0.92, range = -0.73 to 0.94). The mean nightly correlations between traffic rates estimated by radar and by thermal infrared camera during the night were more strongly positively correlated (r = 0.39 ± 0.04 SE, n = 125 nights), but also were highly variable for individual nights (range = -0.76 to 0.98). Through comparison with radar data among numerous height intervals, we determined that flying animal height above the ground influenced thermal imaging positively and flight call detections negatively. Moreover, thermal imaging detections decreased with the presence of cloud cover and increased with mean ground flight speed of animals, whereas acoustic detections showed no relationship with cloud cover presence but did decrease with increased flight speed. We found sampling methods to be positively correlated when comparing mean nightly

  10. A wireless sensor network for urban traffic characterization and trend monitoring.

    Science.gov (United States)

    Fernández-Lozano, J J; Martín-Guzmán, Miguel; Martín-Ávila, Juan; García-Cerezo, A

    2015-10-15

    Sustainable mobility requires a better management of the available infrastructure resources. To achieve this goal, it is necessary to obtain accurate data about road usage, in particular in urban areas. Although a variety of sensor alternates for urban traffic exist, they usually require extensive investments in the form of construction works for installation, processing means, etc. Wireless Sensor Networks (WSN) are an alternative to acquire urban traffic data, allowing for flexible, easy deployment. Together with the use of the appropriate sensors, like Bluetooth identification, and associate processing, WSN can provide the means to obtain in real time data like the origin-destination matrix, a key tool for trend monitoring which previously required weeks or months to be completed. This paper presents a system based on WSN designed to characterize urban traffic, particularly traffic trend monitoring through the calculation of the origin-destination matrix in real time by using Bluetooth identification. Additional sensors are also available integrated in different types of nodes. Experiments in real conditions have been performed, both for separate sensors (Bluetooth, ultrasound and laser), and for the whole system, showing the feasibility of this approach.

  11. Time-delay neural network for audio monitoring of road traffic and vehicle classification

    Science.gov (United States)

    Nooralahiyan, Amir Y.; Lopez, Louis; Mckewon, Denis; Ahmadi, Masoud

    1997-02-01

    The aim of this research is to investigate the feasibility of developing a cost effective traffic monitoring detector for the purpose of reliable on-line vehicle classification to aid traffic management systems. The detector used was a directional microphone connected to a DAT recorder. The digital signal was preprocessed by LPC (Linear Predictive Coding) parameter conversion based on autocorrelation analysis. A Time Delay Neural Network (TDNN) was chosen to classify individual travelling vehicles based on their speed-independent acoustic signature. The network was trained and tested with real data for four types of vehicles. The paper provides a description of the TDNN architecture and training algorithm and an overview of the LPC pre-processing and feature extraction technique as applied to audio monitoring of road traffic. The performance of TDNN vehicle classification, convergence and accuracy for the training patterns are fully illustrated. In generalizing to a limited number of test patterns available, 100% accuracy in classification was achieved. The net was also robust to changes in the starting position of the acoustic waveforms with 86% accuracy for the same test data set.

  12. Optimized Virtual Machine Placement with Traffic-Aware Balancing in Data Center Networks

    Directory of Open Access Journals (Sweden)

    Tao Chen

    2016-01-01

    Full Text Available Virtualization has been an efficient method to fully utilize computing resources such as servers. The way of placing virtual machines (VMs among a large pool of servers greatly affects the performance of data center networks (DCNs. As network resources have become a main bottleneck of the performance of DCNs, we concentrate on VM placement with Traffic-Aware Balancing to evenly utilize the links in DCNs. In this paper, we first proposed a Virtual Machine Placement Problem with Traffic-Aware Balancing (VMPPTB and then proved it to be NP-hard and designed a Longest Processing Time Based Placement algorithm (LPTBP algorithm to solve it. To take advantage of the communication locality, we proposed Locality-Aware Virtual Machine Placement Problem with Traffic-Aware Balancing (LVMPPTB, which is a multiobjective optimization problem of simultaneously minimizing the maximum number of VM partitions of requests and minimizing the maximum bandwidth occupancy on uplinks of Top of Rack (ToR switches. We also proved it to be NP-hard and designed a heuristic algorithm (Least-Load First Based Placement algorithm, LLBP algorithm to solve it. Through extensive simulations, the proposed heuristic algorithm is proven to significantly balance the bandwidth occupancy on uplinks of ToR switches, while keeping the number of VM partitions of each request small enough.

  13. Estimation of gaseous real-world traffic emissions downstream a motorway

    Science.gov (United States)

    Kohler, M.; Corsmeier, U.; Vogt, U.; Vogel, B.

    The consequences of air pollution scenarios caused by road traffic or the impact of exhaust gas reduction techniques are estimated by emission models. To ensure the quality of model results, it is necessary to evaluate the used emission factors under real-world conditions. Therefore, the Institut für Meteorologie und Klimaforschung (IMK) of the Forschungszentrum Karlsruhe initiated the field campaign BAB II (BundesAutoBahn, Federal motorway). The campaign was conducted in May 2001 with the objective of measuring the traffic emissions at a motorway section and to compare them to modelled emissions. Based on experiences during a precursor campaign (BAB I, 1997), a symmetric experimental set-up was installed which allowed measurements up- and downwind of a motorway nearby Heidelberg, Germany. This paper focuses on the determination of source intensities and emission factors for CO and NO x, whereas other papers in this issue handle VOC and particulate matter. First the basic approach of BAB II measurements up- and downwind of a motorway was approved, showing that it is possible to detect the plume originating from traffic emissions. A case study during a traffic jam illustrates that driving patterns have a strong impact on the emissions and therefore a detailed traffic census is required to obtain reliable emission calculations. Two different strategies were used: (i) long-time measurements during the whole campaign to obtain vertical profiles each 30 min and (ii) measurements during eight special operation periods (SOP) in a higher temporal resolution of 5 min, using instrumentation in elevators. It could be shown that even at a distance of 60-80 m from the motorway the structure of the plume is still inhomogeneous, and concentration changes within short times. The inhomogeneity of the plume not only affects the temporal scale, the spatial scale is also influenced and frequently concentration maxima in higher altitudes are observed. Mean source intensities of 9.5 kg

  14. DECISION WITH ARTIFICIAL NEURAL NETWORKS IN DISCRETE EVENT SIMULATION MODELS ON A TRAFFIC SYSTEM

    Directory of Open Access Journals (Sweden)

    Marília Gonçalves Dutra da Silva

    2016-04-01

    Full Text Available ABSTRACT This work aims to demonstrate the use of a mechanism to be applied in the development of the discrete-event simulation models that perform decision operations through the implementation of an artificial neural network. Actions that involve complex operations performed by a human agent in a process, for example, are often modeled in simplified form with the usual mechanisms of simulation software. Therefore, it was chosen a traffic system controlled by a traffic officer with a flow of vehicles and pedestrians to demonstrate the proposed solution. From a module built in simulation software itself, it was possible to connect the algorithm for intelligent decision to the simulation model. The results showed that the model elaborated responded as expected when it was submitted to actions, which required different decisions to maintain the operation of the system with changes in the flow of people and vehicles.

  15. Performance Evaluation of IEEE 802.11ah Networks With High-Throughput Bidirectional Traffic.

    Science.gov (United States)

    Šljivo, Amina; Kerkhove, Dwight; Tian, Le; Famaey, Jeroen; Munteanu, Adrian; Moerman, Ingrid; Hoebeke, Jeroen; De Poorter, Eli

    2018-01-23

    So far, existing sub-GHz wireless communication technologies focused on low-bandwidth, long-range communication with large numbers of constrained devices. Although these characteristics are fine for many Internet of Things (IoT) applications, more demanding application requirements could not be met and legacy Internet technologies such as Transmission Control Protocol/Internet Protocol (TCP/IP) could not be used. This has changed with the advent of the new IEEE 802.11ah Wi-Fi standard, which is much more suitable for reliable bidirectional communication and high-throughput applications over a wide area (up to 1 km). The standard offers great possibilities for network performance optimization through a number of physical- and link-layer configurable features. However, given that the optimal configuration parameters depend on traffic patterns, the standard does not dictate how to determine them. Such a large number of configuration options can lead to sub-optimal or even incorrect configurations. Therefore, we investigated how two key mechanisms, Restricted Access Window (RAW) grouping and Traffic Indication Map (TIM) segmentation, influence scalability, throughput, latency and energy efficiency in the presence of bidirectional TCP/IP traffic. We considered both high-throughput video streaming traffic and large-scale reliable sensing traffic and investigated TCP behavior in both scenarios when the link layer introduces long delays. This article presents the relations between attainable throughput per station and attainable number of stations, as well as the influence of RAW, TIM and TCP parameters on both. We found that up to 20 continuously streaming IP-cameras can be reliably connected via IEEE 802.11ah with a maximum average data rate of 160 kbps, whereas 10 IP-cameras can achieve average data rates of up to 255 kbps over 200 m. Up to 6960 stations transmitting every 60 s can be connected over 1 km with no lost packets. The presented results enable the fine tuning

  16. A Novel Architecture for Adaptive Traffic Control in Network on Chip using Code Division Multiple Access Technique

    OpenAIRE

    Fatemeh. Dehghani; Shahram. Darooei

    2016-01-01

    Network on chip has emerged as a long-term and effective method in Multiprocessor System-on-Chip communications in order to overcome the bottleneck in bus based communication architectures. Efficiency and performance of network on chip is so dependent on the architecture and structure of the network. In this paper a new structure and architecture for adaptive traffic control in network on chip using Code Division Multiple Access technique is presented. To solve the problem of synchronous acce...

  17. The performance evaluation of a new neural network based traffic management scheme for a satellite communication network

    Science.gov (United States)

    Ansari, Nirwan; Liu, Dequan

    1991-01-01

    A neural-network-based traffic management scheme for a satellite communication network is described. The scheme consists of two levels of management. The front end of the scheme is a derivation of Kohonen's self-organization model to configure maps for the satellite communication network dynamically. The model consists of three stages. The first stage is the pattern recognition task, in which an exemplar map that best meets the current network requirements is selected. The second stage is the analysis of the discrepancy between the chosen exemplar map and the state of the network, and the adaptive modification of the chosen exemplar map to conform closely to the network requirement (input data pattern) by means of Kohonen's self-organization. On the basis of certain performance criteria, whether a new map is generated to replace the original chosen map is decided in the third stage. A state-dependent routing algorithm, which arranges the incoming call to some proper path, is used to make the network more efficient and to lower the call block rate. Simulation results demonstrate that the scheme, which combines self-organization and the state-dependent routing mechanism, provides better performance in terms of call block rate than schemes that only have either the self-organization mechanism or the routing mechanism.

  18. A Space-Time Network-Based Modeling Framework for Dynamic Unmanned Aerial Vehicle Routing in Traffic Incident Monitoring Applications

    Directory of Open Access Journals (Sweden)

    Jisheng Zhang

    2015-06-01

    Full Text Available It is essential for transportation management centers to equip and manage a network of fixed and mobile sensors in order to quickly detect traffic incidents and further monitor the related impact areas, especially for high-impact accidents with dramatic traffic congestion propagation. As emerging small Unmanned Aerial Vehicles (UAVs start to have a more flexible regulation environment, it is critically important to fully explore the potential for of using UAVs for monitoring recurring and non-recurring traffic conditions and special events on transportation networks. This paper presents a space-time network- based modeling framework for integrated fixed and mobile sensor networks, in order to provide a rapid and systematic road traffic monitoring mechanism. By constructing a discretized space-time network to characterize not only the speed for UAVs but also the time-sensitive impact areas of traffic congestion, we formulate the problem as a linear integer programming model to minimize the detection delay cost and operational cost, subject to feasible flying route constraints. A Lagrangian relaxation solution framework is developed to decompose the original complex problem into a series of computationally efficient time-dependent and least cost path finding sub-problems. Several examples are used to demonstrate the results of proposed models in UAVs’ route planning for small and medium-scale networks.

  19. TCP with source traffic shaping (TCP-STS): an approach for network congestion reduction

    Science.gov (United States)

    Elaywe, Ali H.; Kamal, Ahmed E.

    2002-07-01

    The Transmission Control Protocol (TCP), provides flow control functions which are based on the window mechanism. Packet losses are detected by various mechanisms, such as timeouts and duplicate acknowledgements, and are then recovered from using different techniques. A problem that arises with the use of window based mechanisms is that the availability of a large number of credits at the source may cause a source to flood the network with back-to-back packets, which may drive the network into congestion, especially if multiple sources become active at the same time. In this paper we propose a new approach for congestion reduction. The approach works by shaping the traffic at the TCP source, such that the basic TCP flow control mechanism is still preserved, but the packet transmissions are spaced in time in order to prevent a sudden surge of traffic from overflowing the routers' buffers. Simulation results show that this technique can result in an improved network performance, in terms of reduced mean delay, delay variance, and packet dropping ratio.

  20. Prediction of Ship Traffic Flow Based on BP Neural Network and Markov Model

    Directory of Open Access Journals (Sweden)

    Lv Pengfei

    2016-01-01

    Full Text Available This paper discusses the distribution regularity of ship arrival and departure and the method of prediction of ship traffic flow. Depict the frequency histograms of ships arriving to port every day and fit the curve of the frequency histograms with a variety of distribution density function by using the mathematical statistic methods based on the samples of ship-to-port statistics of Fangcheng port nearly a year. By the chi-square testing: the fitting with Negative Binomial distribution and t-Location Scale distribution are superior to normal distribution and Logistic distribution in the branch channel; the fitting with Logistic distribution is superior to normal distribution, Negative Binomial distribution and t-Location Scale distribution in main channel. Build the BP neural network and Markov model based on BP neural network model to forecast ship traffic flow of Fangcheng port. The new prediction model is superior to BP neural network model by comparing the relative residuals of predictive value, which means the new model can improve the prediction accuracy.

  1. Can Green Traffic Policies Affect Air Quality? Evidence from A Difference-in-Difference Estimation in China

    Directory of Open Access Journals (Sweden)

    Lu-Yi Qiu

    2017-06-01

    Full Text Available Air pollution has been a serious challenge for human sustainable development. Researches show that emissions from the transport sector have been found to be a main source of air pollution in cities. Governments have implemented numerous green traffic policies to mitigate harmful emissions. However, the problem as to whether the green traffic policies are effective, and the extent to which the policies affect air quality remain unknown. This paper is the first attempt to apply a difference-in-difference method to investigate how a specific green traffic policy (in our case, the green traffic pilot cities program affects air quality. The estimates show that the pilot program is associated with consistent reductions in annual concentration of pollutants. In pilot cities of China, the annual concentration of SO 2 , NO 2 and PM 10 decrease by 10.71 percent, 11.26 percent and 9.85 percent, respectively, after the implementation of the green traffic pilot cities program. The results show that the green traffic pilot has a noticeable improvement on air quality of the pilot cities, implying that government intervention has a positive influence on pollution prevention in the transport sector. Moreover, the green traffic system construction can be popularized in other cities to mitigate air pollution.

  2. Application of radial basis neural network for state estimation of ...

    African Journals Online (AJOL)

    user

    An original application of radial basis function (RBF) neural network for power system state estimation is proposed in this paper. The property of massive parallelism of neural networks is employed for this. The application of RBF neural network for state estimation is investigated by testing its applicability on a IEEE 14 bus ...

  3. Temporal Classification Error Compensation of Convolutional Neural Network for Traffic Sign Recognition

    Science.gov (United States)

    Yoon, Seungjong; Kim, Eungtae

    2017-02-01

    In this paper, we propose the method that classifies the traffic signs by using Convolutional Neural Network(CNN) and compensates the error rate of CNN using the temporal correlation between adjacent successive frames. Instead of applying a conventional CNN architecture with more layers, Temporal Classification Error Compensation(TCEC) is proposed to improve the error rate in the architecture which has less nodes and layers than a conventional CNN. Experimental results show that the complexity of the proposed method could be reduced by 50% compared with that of the conventional CNN with same layers, and the error rate could be improved by about 3%.

  4. A Practical Method for Multilevel Classification and Accounting of Traffic in Computer Networks

    DEFF Research Database (Denmark)

    Bujlow, Tomasz; Pedersen, Jens Myrup

    the service provider (as Facebook, YouTube, or Google). Furthermore, Deep Packet Inspection (DPI), which seems to be the most accurate technique, in addition to the extensive needs for resources, often cannot be used by ISPs in their networks due to privacy or legal reasons. Techniques based on Machine......, SSH, and Telnet. Within each application group we identify a number of behaviors -- for example, for HTTP, we selected file transfer, web browsing, web radio, and unknown. Our system built based on the method provides also traffic accounting and it was tested on 2 datasets. The classification results...

  5. Adaptive EWMA Method Based on Abnormal Network Traffic for LDoS Attacks

    Directory of Open Access Journals (Sweden)

    Dan Tang

    2014-01-01

    Full Text Available The low-rate denial of service (LDoS attacks reduce network services capabilities by periodically sending high intensity pulse data flows. For their concealed performance, it is more difficult for traditional DoS detection methods to detect LDoS attacks; at the same time the accuracy of the current detection methods for LDoS attacks is relatively low. As the fact that LDoS attacks led to abnormal distribution of the ACK traffic, LDoS attacks can be detected by analyzing the distribution characteristics of ACK traffic. Then traditional EWMA algorithm which can smooth the accidental error while being the same as the exceptional mutation may cause some misjudgment; therefore a new LDoS detection method based on adaptive EWMA (AEWMA algorithm is proposed. The AEWMA algorithm which uses an adaptive weighting function instead of the constant weighting of EWMA algorithm can smooth the accidental error and retain the exceptional mutation. So AEWMA method is more beneficial than EWMA method for analyzing and measuring the abnormal distribution of ACK traffic. The NS2 simulations show that AEWMA method can detect LDoS attacks effectively and has a low false negative rate and a false positive rate. Based on DARPA99 datasets, experiment results show that AEWMA method is more efficient than EWMA method.

  6. Alternative method of highway traffic safety analysis for developing countries using delphi technique and Bayesian network.

    Science.gov (United States)

    Mbakwe, Anthony C; Saka, Anthony A; Choi, Keechoo; Lee, Young-Jae

    2016-08-01

    Highway traffic accidents all over the world result in more than 1.3 million fatalities annually. An alarming number of these fatalities occurs in developing countries. There are many risk factors that are associated with frequent accidents, heavy loss of lives, and property damage in developing countries. Unfortunately, poor record keeping practices are very difficult obstacle to overcome in striving to obtain a near accurate casualty and safety data. In light of the fact that there are numerous accident causes, any attempts to curb the escalating death and injury rates in developing countries must include the identification of the primary accident causes. This paper, therefore, seeks to show that the Delphi Technique is a suitable alternative method that can be exploited in generating highway traffic accident data through which the major accident causes can be identified. In order to authenticate the technique used, Korea, a country that underwent similar problems when it was in its early stages of development in addition to the availability of excellent highway safety records in its database, is chosen and utilized for this purpose. Validation of the methodology confirms the technique is suitable for application in developing countries. Furthermore, the Delphi Technique, in combination with the Bayesian Network Model, is utilized in modeling highway traffic accidents and forecasting accident rates in the countries of research. Copyright © 2016 Elsevier Ltd. All rights reserved.

  7. Achieving Passive Localization with Traffic Light Schedules in Urban Road Sensor Networks

    Directory of Open Access Journals (Sweden)

    Qiang Niu

    2016-10-01

    Full Text Available Localization is crucial for the monitoring applications of cities, such as road monitoring, environment surveillance, vehicle tracking, etc. In urban road sensor networks, sensors are often sparely deployed due to the hardware cost. Under this sparse deployment, sensors cannot communicate with each other via ranging hardware or one-hop connectivity, rendering the existing localization solutions ineffective. To address this issue, this paper proposes a novel Traffic Lights Schedule-based localization algorithm (TLS, which is built on the fact that vehicles move through the intersection with a known traffic light schedule. We can first obtain the law by binary vehicle detection time stamps and describe the law as a matrix, called a detection matrix. At the same time, we can also use the known traffic light information to construct the matrices, which can be formed as a collection called a known matrix collection. The detection matrix is then matched in the known matrix collection for identifying where sensors are located on urban roads. We evaluate our algorithm by extensive simulation. The results show that the localization accuracy of intersection sensors can reach more than 90%. In addition, we compare it with a state-of-the-art algorithm and prove that it has a wider operational region.

  8. Combination Adaptive Traffic Algorithm and Coordinated Sleeping in Wireless Sensor Network

    Directory of Open Access Journals (Sweden)

    M. Udin Harun Al Rasyid

    2014-12-01

    Full Text Available Wireless sensor network (WSN uses a battery as its primary power source, so that WSN will be limited to battery power for long operations. The WSN should be able to save the energy consumption in order to operate in a long time.WSN has the potential to be the future of wireless communications solutions. WSN are small but has a variety of functions that can help human life. WSN has the wide variety of sensors and can communicate quickly making it easier for people to obtain information accurately and quickly. In this study, we combine adaptive traffic algorithms and coordinated sleeping as power‐efficient WSN solution. We compared the performance of our proposed ideas combination adaptive traffic and coordinated sleeping algorithm with non‐adaptive scheme. From the simulation results, our proposed idea has good‐quality data transmission and more efficient in energy consumption, but it has higher delay than that of non‐adaptive scheme. Keywords:WSN,adaptive traffic,coordinated sleeping,beacon order,superframe order.

  9. Visualizing Network Traffic to Understand the Performance of Massively Parallel Simulations

    KAUST Repository

    Landge, A. G.

    2012-12-01

    The performance of massively parallel applications is often heavily impacted by the cost of communication among compute nodes. However, determining how to best use the network is a formidable task, made challenging by the ever increasing size and complexity of modern supercomputers. This paper applies visualization techniques to aid parallel application developers in understanding the network activity by enabling a detailed exploration of the flow of packets through the hardware interconnect. In order to visualize this large and complex data, we employ two linked views of the hardware network. The first is a 2D view, that represents the network structure as one of several simplified planar projections. This view is designed to allow a user to easily identify trends and patterns in the network traffic. The second is a 3D view that augments the 2D view by preserving the physical network topology and providing a context that is familiar to the application developers. Using the massively parallel multi-physics code pF3D as a case study, we demonstrate that our tool provides valuable insight that we use to explain and optimize pF3D-s performance on an IBM Blue Gene/P system. © 1995-2012 IEEE.

  10. Network-Wide Traffic Anomaly Detection and Localization Based on Robust Multivariate Probabilistic Calibration Model

    Directory of Open Access Journals (Sweden)

    Yuchong Li

    2015-01-01

    Full Text Available Network anomaly detection and localization are of great significance to network security. Compared with the traditional methods of host computer, single link and single path, the network-wide anomaly detection approaches have distinctive advantages with respect to detection precision and range. However, when facing the actual problems of noise interference or data loss, the network-wide anomaly detection approaches also suffer significant performance reduction or may even become unavailable. Besides, researches on anomaly localization are rare. In order to solve the mentioned problems, this paper presents a robust multivariate probabilistic calibration model for network-wide anomaly detection and localization. It applies the latent variable probability theory with multivariate t-distribution to establish the normal traffic model. Not only does the algorithm implement network anomaly detection by judging whether the sample’s Mahalanobis distance exceeds the threshold, but also it locates anomalies by contribution analysis. Both theoretical analysis and experimental results demonstrate its robustness and wider use. The algorithm is applicable when dealing with both data integrity and loss. It also has a stronger resistance over noise interference and lower sensitivity to the change of parameters, all of which indicate its performance stability.

  11. Determination of conditions for reliability of travel parameters estimation in a network using “floating” cars

    Science.gov (United States)

    Kocherga, Victor; Topilin, Ivan; Volodina, Marina

    2017-10-01

    Based on the analysis of the experimental data the article reveals that if in the area under study a travel length is more than 7 km (about 20 minutes of movement), it becomes possible to obtain stable relationships between the specific parameters of traffic in the network. A further increase in the duration of observations does not cause a change in the trip parameters and the value of the correlation ratio for the model. The corresponding results are achieved with a constant cruising of five “floating” cars in the area under study. Moreover, it is proved that reliable results of estimating the traffic parameters on the network are obtained both for fixed traffic routes of “floating” cars and for randomly choosing routes.

  12. Cybersecurity and Network Forensics: Analysis of Malicious Traffic towards a Honeynet with Deep Packet Inspection

    Directory of Open Access Journals (Sweden)

    Gabriel Arquelau Pimenta Rodrigues

    2017-10-01

    Full Text Available Any network connected to the Internet is subject to cyber attacks. Strong security measures, forensic tools, and investigators contribute together to detect and mitigate those attacks, reducing the damages and enabling reestablishing the network to its normal operation, thus increasing the cybersecurity of the networked environment. This paper addresses the use of a forensic approach with Deep Packet Inspection to detect anomalies in the network traffic. As cyber attacks may occur on any layer of the TCP/IP networking model, Deep Packet Inspection is an effective way to reveal suspicious content in the headers or the payloads in any packet processing layer, excepting of course situations where the payload is encrypted. Although being efficient, this technique still faces big challenges. The contributions of this paper rely on the association of Deep Packet Inspection with forensics analysis to evaluate different attacks towards a Honeynet operating in a network laboratory at the University of Brasilia. In this perspective, this work could identify and map the content and behavior of attacks such as the Mirai botnet and brute-force attacks targeting various different network services. Obtained results demonstrate the behavior of automated attacks (such as worms and bots and non-automated attacks (brute-force conducted with different tools. The data collected and analyzed is then used to generate statistics of used usernames and passwords, IP and services distribution, among other elements. This paper also discusses the importance of network forensics and Chain of Custody procedures to conduct investigations and shows the effectiveness of the mentioned techniques in evaluating different attacks in networks.

  13. Advancing interconnect density for spiking neural network hardware implementations using traffic-aware adaptive network-on-chip routers.

    Science.gov (United States)

    Carrillo, Snaider; Harkin, Jim; McDaid, Liam; Pande, Sandeep; Cawley, Seamus; McGinley, Brian; Morgan, Fearghal

    2012-09-01

    The brain is highly efficient in how it processes information and tolerates faults. Arguably, the basic processing units are neurons and synapses that are interconnected in a complex pattern. Computer scientists and engineers aim to harness this efficiency and build artificial neural systems that can emulate the key information processing principles of the brain. However, existing approaches cannot provide the dense interconnect for the billions of neurons and synapses that are required. Recently a reconfigurable and biologically inspired paradigm based on network-on-chip (NoC) and spiking neural networks (SNNs) has been proposed as a new method of realising an efficient, robust computing platform. However, the use of the NoC as an interconnection fabric for large-scale SNNs demands a good trade-off between scalability, throughput, neuron/synapse ratio and power consumption. This paper presents a novel traffic-aware, adaptive NoC router, which forms part of a proposed embedded mixed-signal SNN architecture called EMBRACE (EMulating Biologically-inspiRed ArChitectures in hardwarE). The proposed adaptive NoC router provides the inter-neuron connectivity for EMBRACE, maintaining router communication and avoiding dropped router packets by adapting to router traffic congestion. Results are presented on throughput, power and area performance analysis of the adaptive router using a 90 nm CMOS technology which outperforms existing NoCs in this domain. The adaptive behaviour of the router is also verified on a Stratix II FPGA implementation of a 4 × 2 router array with real-time traffic congestion. The presented results demonstrate the feasibility of using the proposed adaptive NoC router within the EMBRACE architecture to realise large-scale SNNs on embedded hardware. Copyright © 2012 Elsevier Ltd. All rights reserved.

  14. Modeling and Simulation of Road Traffic Noise Using Artificial Neural Network and Regression.

    Science.gov (United States)

    Honarmand, M; Mousavi, S M

    2014-04-01

    Modeling and simulation of noise pollution has been done in a large city, where the population is over 2 millions. Two models of artificial neural network and regression were developed to predict in-city road traffic noise pollution with using the data of noise measurements and vehicle counts at three points of the city for a period of 12 hours. The MATLAB and DATAFIT softwares were used for simulation. The predicted results of noise level were compared with the measured noise levels in three stations. The values of normalized bias, sum of squared errors, mean of squared errors, root mean of squared errors, and squared correlation coefficient calculated for each model show the results of two models are suitable, and the predictions of artificial neural network are closer to the experimental data.

  15. Reliable Path Selection Problem in Uncertain Traffic Network after Natural Disaster

    Directory of Open Access Journals (Sweden)

    Jing Wang

    2013-01-01

    Full Text Available After natural disaster, especially for large-scale disasters and affected areas, vast relief materials are often needed. In the meantime, the traffic networks are always of uncertainty because of the disaster. In this paper, we assume that the edges in the network are either connected or blocked, and the connection probability of each edge is known. In order to ensure the arrival of these supplies at the affected areas, it is important to select a reliable path. A reliable path selection model is formulated, and two algorithms for solving this model are presented. Then, adjustable reliable path selection model is proposed when the edge of the selected reliable path is broken. And the corresponding algorithms are shown to be efficient both theoretically and numerically.

  16. Improved network convergence and quality of service by strict priority queuing of routing traffic

    Science.gov (United States)

    Balandin, Sergey; Heiner, Andreas P.

    2002-07-01

    During the transient period after a link failure the network cannot guarantee the agreed service levels to user data. This is due to the fact that forwarding tables in the network are inconsistent. Moreover, link states can inadvertently be advertised wrong due to protocol time outs, which may result in persistent route flaps. Reducing the probability of wrongly advertised link states, and the time during which the forwarding tables are inconsistent, is therefore of eminent importance to provide consistent and high level QoS to user data. By queuing routing traffic in a queue with strict priority over all other (data) queues, i.e. assigning the highest priority in a Differentiated Services model, we were able to reduce the probability of routing data loss to almost zero, and reduce flooding times almost to their theoretical limit. The quality of service provided to user traffic was considerable higher than without the proposed modification. The scheme is independent of the routing protocol, and can be used with most differentiated service models. It is compatible with the current OSPF standard, and can be used in conjunction with other improvements in the protocol with similar objectives.

  17. Energy-Saving Traffic Scheduling in Hybrid Software Defined Wireless Rechargeable Sensor Networks.

    Science.gov (United States)

    Wei, Yunkai; Ma, Xiaohui; Yang, Ning; Chen, Yijin

    2017-09-15

    Software Defined Wireless Rechargeable Sensor Networks (SDWRSNs) are an inexorable trend for Wireless Sensor Networks (WSNs), including Wireless Rechargeable Sensor Network (WRSNs). However, the traditional network devices cannot be completely substituted in the short term. Hybrid SDWRSNs, where software defined devices and traditional devices coexist, will last for a long time. Hybrid SDWRSNs bring new challenges as well as opportunities for energy saving issues, which is still a key problem considering that the wireless chargers are also exhaustible, especially in some rigid environment out of the main supply. Numerous energy saving schemes for WSNs, or even some works for WRSNs, are no longer suitable for the new features of hybrid SDWRSNs. To solve this problem, this paper puts forward an Energy-saving Traffic Scheduling (ETS) algorithm. The ETS algorithm adequately considers the new characters in hybrid SDWRSNs, and takes advantage of the Software Defined Networking (SDN) controller's direct control ability on SDN nodes and indirect control ability on normal nodes. The simulation results show that, comparing with traditional Minimum Transmission Energy (MTE) protocol, ETS can substantially improve the energy efficiency in hybrid SDWRSNs for up to 20-40% while ensuring feasible data delay.

  18. Energy-Saving Traffic Scheduling in Hybrid Software Defined Wireless Rechargeable Sensor Networks

    Directory of Open Access Journals (Sweden)

    Yunkai Wei

    2017-09-01

    Full Text Available Software Defined Wireless Rechargeable Sensor Networks (SDWRSNs are an inexorable trend for Wireless Sensor Networks (WSNs, including Wireless Rechargeable Sensor Network (WRSNs. However, the traditional network devices cannot be completely substituted in the short term. Hybrid SDWRSNs, where software defined devices and traditional devices coexist, will last for a long time. Hybrid SDWRSNs bring new challenges as well as opportunities for energy saving issues, which is still a key problem considering that the wireless chargers are also exhaustible, especially in some rigid environment out of the main supply. Numerous energy saving schemes for WSNs, or even some works for WRSNs, are no longer suitable for the new features of hybrid SDWRSNs. To solve this problem, this paper puts forward an Energy-saving Traffic Scheduling (ETS algorithm. The ETS algorithm adequately considers the new characters in hybrid SDWRSNs, and takes advantage of the Software Defined Networking (SDN controller’s direct control ability on SDN nodes and indirect control ability on normal nodes. The simulation results show that, comparing with traditional Minimum Transmission Energy (MTE protocol, ETS can substantially improve the energy efficiency in hybrid SDWRSNs for up to 20–40% while ensuring feasible data delay.

  19. Energy-Saving Traffic Scheduling in Hybrid Software Defined Wireless Rechargeable Sensor Networks

    Science.gov (United States)

    Wei, Yunkai; Ma, Xiaohui; Yang, Ning; Chen, Yijin

    2017-01-01

    Software Defined Wireless Rechargeable Sensor Networks (SDWRSNs) are an inexorable trend for Wireless Sensor Networks (WSNs), including Wireless Rechargeable Sensor Network (WRSNs). However, the traditional network devices cannot be completely substituted in the short term. Hybrid SDWRSNs, where software defined devices and traditional devices coexist, will last for a long time. Hybrid SDWRSNs bring new challenges as well as opportunities for energy saving issues, which is still a key problem considering that the wireless chargers are also exhaustible, especially in some rigid environment out of the main supply. Numerous energy saving schemes for WSNs, or even some works for WRSNs, are no longer suitable for the new features of hybrid SDWRSNs. To solve this problem, this paper puts forward an Energy-saving Traffic Scheduling (ETS) algorithm. The ETS algorithm adequately considers the new characters in hybrid SDWRSNs, and takes advantage of the Software Defined Networking (SDN) controller’s direct control ability on SDN nodes and indirect control ability on normal nodes. The simulation results show that, comparing with traditional Minimum Transmission Energy (MTE) protocol, ETS can substantially improve the energy efficiency in hybrid SDWRSNs for up to 20–40% while ensuring feasible data delay. PMID:28914816

  20. Effective link quality estimation as a means to improved end-to-end packet delivery in high traffic mobile ad hoc networks☆

    Directory of Open Access Journals (Sweden)

    Syed Rehan Afzal

    2017-08-01

    Full Text Available Accurate link quality estimation is a fundamental building block in quality aware multi hop routing. In an inherently lossy, unreliable and dynamic medium such as wireless, the task of accurate estimation becomes very challenging. Over the years ETX has been widely used as a reliable link quality estimation metric. However, more recently it has been established that under heavy traffic loads ETX performance gets significantly worse. We examine the ETX metric's behavior in detail with respect to the MAC layer and UDP data; and identify the causes of its unreliability. Motivated by the observations made in our analysis, we present the design and implementation of our link quality measurement metric xDDR – a variation of ETX. This article extends xDDR to support network mobility. Our experiments show that xDDR substantially outperforms minimum hop count, ETX and HETX in terms of end-to-end packet delivery ratio in static as well as mobile scenarios.

  1. Deep neural network for traffic sign recognition systems: An analysis of spatial transformers and stochastic optimisation methods.

    Science.gov (United States)

    Arcos-García, Álvaro; Álvarez-García, Juan A; Soria-Morillo, Luis M

    2018-01-31

    This paper presents a Deep Learning approach for traffic sign recognition systems. Several classification experiments are conducted over publicly available traffic sign datasets from Germany and Belgium using a Deep Neural Network which comprises Convolutional layers and Spatial Transformer Networks. Such trials are built to measure the impact of diverse factors with the end goal of designing a Convolutional Neural Network that can improve the state-of-the-art of traffic sign classification task. First, different adaptive and non-adaptive stochastic gradient descent optimisation algorithms such as SGD, SGD-Nesterov, RMSprop and Adam are evaluated. Subsequently, multiple combinations of Spatial Transformer Networks placed at distinct positions within the main neural network are analysed. The recognition rate of the proposed Convolutional Neural Network reports an accuracy of 99.71% in the German Traffic Sign Recognition Benchmark, outperforming previous state-of-the-art methods and also being more efficient in terms of memory requirements. Copyright © 2018 Elsevier Ltd. All rights reserved.

  2. Cyber-Threat Assessment for the Air Traffic Management System: A Network Controls Approach

    Science.gov (United States)

    Roy, Sandip; Sridhar, Banavar

    2016-01-01

    Air transportation networks are being disrupted with increasing frequency by failures in their cyber- (computing, communication, control) systems. Whether these cyber- failures arise due to deliberate attacks or incidental errors, they can have far-reaching impact on the performance of the air traffic control and management systems. For instance, a computer failure in the Washington DC Air Route Traffic Control Center (ZDC) on August 15, 2015, caused nearly complete closure of the Centers airspace for several hours. This closure had a propagative impact across the United States National Airspace System, causing changed congestion patterns and requiring placement of a suite of traffic management initiatives to address the capacity reduction and congestion. A snapshot of traffic on that day clearly shows the closure of the ZDC airspace and the resulting congestion at its boundary, which required augmented traffic management at multiple locations. Cyber- events also have important ramifications for private stakeholders, particularly the airlines. During the last few months, computer-system issues have caused several airlines fleets to be grounded for significant periods of time: these include United Airlines (twice), LOT Polish Airlines, and American Airlines. Delays and regional stoppages due to cyber- events are even more common, and may have myriad causes (e.g., failure of the Department of Homeland Security systems needed for security check of passengers, see [3]). The growing frequency of cyber- disruptions in the air transportation system reflects a much broader trend in the modern society: cyber- failures and threats are becoming increasingly pervasive, varied, and impactful. In consequence, an intense effort is underway to develop secure and resilient cyber- systems that can protect against, detect, and remove threats, see e.g. and its many citations. The outcomes of this wide effort on cyber- security are applicable to the air transportation infrastructure

  3. Improving Sample Estimate Reliability and Validity with Linked Ego Networks

    CERN Document Server

    Lu, Xin

    2012-01-01

    Respondent-driven sampling (RDS) is currently widely used in public health, especially for the study of hard-to-access populations such as injecting drug users and men who have sex with men. The method works like a snowball sample but can, given that some assumptions are met, generate unbiased population estimates. However, recent studies have shown that traditional RDS estimators are likely to generate large variance and estimate error. To improve the performance of traditional estimators, we propose a method to generate estimates with ego network data collected by RDS. By simulating RDS processes on an empirical human social network with known population characteristics, we have shown that the precision of estimates on the composition of network link types is greatly improved with ego network data. The proposed estimator for population characteristics shows superior advantage over traditional RDS estimators, and most importantly, the new method exhibits strong robustness to the recruitment preference of res...

  4. Energy-Saving Mechanism in WDM/TDM-PON Based on Upstream Network Traffic

    Directory of Open Access Journals (Sweden)

    Paola Garfias

    2014-08-01

    Full Text Available One of the main challenges of Passive Optical Networks (PONs is the resource (bandwidth and wavelength management. Since it has been shown that access networks consume a significant part of the overall energy of the telecom networks, the resource management schemes should also consider energy minimization strategies. To sustain the increased bandwidth demand of emerging applications in the access section of the network, it is expected that next generation optical access networks will adopt the wavelength division/time division multiplexing (WDM/TDM technique to increase PONs capacity. Compared with traditional PONs, the architecture of a WDM/TDM-PON requires more transceivers/receivers, hence they are expected to consume more energy. In this paper, we focus on the energy minimization in WDM/TDM-PONs and we propose an energy-efficient Dynamic Bandwidth and Wavelength Allocation mechanism whose objective is to turn off, whenever possible, the unnecessary upstream traffic receivers at the Optical Line Terminal (OLT. We evaluate our mechanism in different scenarios and show that the proper use of upstream channels leads to relevant energy savings. Our proposed energy-saving mechanism is able to save energy at the OLT while maintaining the introduced penalties in terms of packet delay and cycle time within an acceptable range. We might highlight the benefits of our proposal as a mechanism that maximizes the channel utilization. Detailed implementation of the proposed algorithm is presented, and simulation results are reported to quantify energy savings and effects on network performance on different network scenarios.

  5. Building national estimates of the burden of road traffic injuries in developing countries from all available data sources: Iran.

    Science.gov (United States)

    Bhalla, K; Naghavi, M; Shahraz, S; Bartels, D; Murray, C J L

    2009-06-01

    To use a range of existing information sources to develop a national snapshot of the burden of road traffic injuries in one developing country-Iran. The distribution of deaths was estimated by using data from the national death registration system, hospital admissions and outpatient visits from a time-limited hospital registry in 12 of 30 provinces, and injuries that received no institutional care using the 2000 demographic and health survey. Results were extrapolated to national annual incidence of health burden differentiated by age, sex, external cause, nature of injuries and institutional care. In 2005, 30,721 Iranians died annually in road traffic crashes and over one million were injured. The death rate (44 per 100,000) is the highest of any country in the world for which reliable estimates are available. Road traffic injuries are the third leading cause of death in Iran. While young adults are at high risk in non-fatal crashes, the elderly have the highest total death rates, largely due to pedestrian crashes. While car occupants lead the death count, motorized two-wheeler riders dominate hospital admissions, outpatient visits and health burden. Reliable estimates of the burden of road traffic injuries are an essential input for rational priority setting. Most low income countries are unlikely to have national injury surveillance systems for several decades. Thus national estimates of the burden of injuries should be built by collating information from all existing information sources by appropriately correcting for source specific shortcomings.

  6. Estimate of physical sequelae in victims of road traffic accidents hospitalized in the Public Health System.

    Science.gov (United States)

    Andrade, Silvânia Suely Caribé de Araújo; Jorge, Maria Helena Prado de Mello

    2016-03-01

    To describe the profile of the victims of road accidents presenting physical sequelae, according to the criteria established by researchers and analyze the trends in hospitalization for this cause in Brazil, from 2000 to 2013. An ecological time-series study was performed using the data from the Hospital Information System of the National Health System (SUS). Trends in hospitalization were estimated using Prais-Winstein regression. During this period, a total of 1,747,191 hospitalizations for traffic accidents were registered; 410,448 were victims with physical sequelae. About 77.7% of them were male subjects, 26.5% belonged to the age group of 20 - 29 years, 46.4% lived in Southeast Brazil, 44.0% were pedestrians, and 31.1% were motorcyclists. In total, 51,189 cases were "confirmed" sequelae (12.5%), and pedestrians accounted for 43.8% of cases. There were 359,259 hospitalizations for the diagnosis of "possible" sequelae, and motorcyclists accounted for 43.3% of these cases. There was a trend of stability for all the patients with confirmed and possible sequelae, but there was a significant rise in hospitalization rates owing to confirmed sequelae among the men in North and Central-West regions. The hospitalizations associated with physical sequelae were responsible for about one-fourth of the hospitalizations in the Hospital Information System in the studied period. Most events involved men, young adults, residents in Southeast Brazil, and pedestrians. Hospitalization rates for traffic accidents associated with physical sequelae were stable in Brazil and regions, but a significant increase was observed for confirmed sequelae among men in the North and Central-West regions.

  7. An Interference-Aware Traffic-Priority-Based Link Scheduling Algorithm for Interference Mitigation in Multiple Wireless Body Area Networks

    Directory of Open Access Journals (Sweden)

    Thien T. T. Le

    2016-12-01

    Full Text Available Currently, wireless body area networks (WBANs are effectively used for health monitoring services. However, in cases where WBANs are densely deployed, interference among WBANs can cause serious degradation of network performance and reliability. Inter-WBAN interference can be reduced by scheduling the communication links of interfering WBANs. In this paper, we propose an interference-aware traffic-priority-based link scheduling (ITLS algorithm to overcome inter-WBAN interference in densely deployed WBANs. First, we model a network with multiple WBANs as an interference graph where node-level interference and traffic priority are taken into account. Second, we formulate link scheduling for multiple WBANs as an optimization model where the objective is to maximize the throughput of the entire network while ensuring the traffic priority of sensor nodes. Finally, we propose the ITLS algorithm for multiple WBANs on the basis of the optimization model. High spatial reuse is also achieved in the proposed ITLS algorithm. The proposed ITLS achieves high spatial reuse while considering traffic priority, packet length, and the number of interfered sensor nodes. Our simulation results show that the proposed ITLS significantly increases spatial reuse and network throughput with lower delay by mitigating inter-WBAN interference.

  8. Bayesian Forecasting of WWW Traffic on the Time Varying Poisson Model

    OpenAIRE

    Koizumi, Daiki; Matsushima, Toshiyasu; Hirasawa, Shigeichi

    2009-01-01

    Traffic forecasting from past observed traffic data with small calculation complexity is one of important problems for planning of servers and networks. Focusing on World Wide Web (WWW) traffic as fundamental investigation, this paper would deal with Bayesian forecasting of network traffic on the time varying Poisson model from a viewpoint from statistical decision theory. Under this model, we would show that the estimated forecasting value is obtained by simple arithmetic calculation and exp...

  9. Market driven network neutrality and the fallacies of internet traffic quality regulation

    OpenAIRE

    Knieps, Günter

    2011-01-01

    In the U.S. paying for priority arrangements between Internet access service providers and Internet application providers to favor some traffic over other traf-fic is considered unreasonable discrimination. In Europe the focus is on mini-mum traffic quality requirements. It can be shown that neither market power nor universal service arguments can justify traffic quality regulation. In particular, heterogeneous demand for traffic quality for delay sensitive versus delay insen-sitive applicati...

  10. Mapping Neural Network Derived from the Parzen Window Estimator

    DEFF Research Database (Denmark)

    Schiøler, Henrik; Hartmann, U.

    1992-01-01

    The article presents a general theoretical basis for the construction of mapping neural networks. The theory is based on the Parzen Window estimator for......The article presents a general theoretical basis for the construction of mapping neural networks. The theory is based on the Parzen Window estimator for...

  11. Receiver Based Traffic Control Mechanism to Protect Low Capacity Network in Infrastructure Based Wireless Mesh Network

    Science.gov (United States)

    Gilani, Syed Sherjeel Ahmad; Zubair, Muhammad; Khan, Zeeshan Shafi

    Infrastructure-based Wireless Mesh Networks are emerging as an affordable, robust, flexible and scalable technology. With the advent of Wireless Mesh Networks (WMNs) the dream of connecting multiple technology based networks seems to come true. A fully secure WMN is still a challenge for the researchers. In infrastructure-based WMNs almost all types of existing Wireless Networks like Wi-Fi, Cellular, WiMAX, and Sensor etc can be connected through Wireless Mesh Routers (WMRs). This situation can lead to a security problem. Some nodes can be part of the network with high processing power, large memory and least energy issues while others may belong to a network having low processing power, small memory and serious energy limitations. The later type of the nodes is very much vulnerable to targeted attacks. In our research we have suggested to set some rules on the WMR to mitigate these kinds of targeted flooding attacks. The WMR will then share those set of rules with other WMRs for Effective Utilization of Resources.

  12. An ELM-Based Approach for Estimating Train Dwell Time in Urban Rail Traffic

    Directory of Open Access Journals (Sweden)

    Wen-jun Chu

    2015-01-01

    Full Text Available Dwell time estimation plays an important role in the operation of urban rail system. On this specific problem, a range of models based on either polynomial regression or microsimulation have been proposed. However, the generalization performance of polynomial regression models is limited and the accuracy of existing microsimulation models is unstable. In this paper, a new dwell time estimation model based on extreme learning machine (ELM is proposed. The underlying factors that may affect urban rail dwell time are analyzed first. Then, the relationships among different factors are extracted and modeled by ELM neural networks, on basis of which an overall estimation model is proposed. At last, a set of observed data from Beijing subway is used to illustrate the proposed method and verify its overall performance.

  13. Distributed Estimation and Control for Robotic Networks

    NARCIS (Netherlands)

    Simonetto, A.

    2012-01-01

    Mobile robots that communicate and cooperate to achieve a common task have been the subject of an increasing research interest in recent years. These possibly heterogeneous groups of robots communicate locally via a communication network and therefore are usually referred to as robotic networks.

  14. On-Chip SDM Switching for Unicast, Multicast and Traffic Grooming in Data Center Networks

    DEFF Research Database (Denmark)

    Kamchevska, Valerija; Ding, Yunhong; Dalgaard, Kjeld

    2017-01-01

    This paper reports on the use of a novel photonic integrated circuit that facilitates multicast and grooming in an optical data center architecture. The circuit allows for on-chip spatial multiplexing and demultiplexing as well as fiber core switching. Using this device, we experimentally verify...... that multicast and/or grooming can be successfully performed along the full range of output ports, for different group size and different power ratio. Moreover, we experimentally demonstrate SDM transmission and 5 Tbit/s switching using the on-chip fiber switch with integrated fan-in/fan-out devices and achieve...... errorfree performance (BER≤10-9) for a network scenario including simultaneous unicast/multicast switching and traffic grooming....

  15. Impact of the traffic load on performance of an alternative LTE railway communication network

    DEFF Research Database (Denmark)

    Sniady, Aleksander; Soler, José

    2013-01-01

    obstructing railway operations at big train stations and junctions. Hence, other technologies, such as Long Term Evolution (LTE), need to be considered as an alternative to GSM-R. The goal of this paper is to demonstrate the capacity increase that railways can expect, from the introduction of LTE as internal...... communication infrastructure supporting railway signaling. This work is based on OPNET realistic network simulations, which show the relation between the traffic load (the number of trains transmitting and receiving data in an LTE cell) and the delay performance of the European Train Control System (ETCS......) signaling, which is one of the essential railway communication services. Results of the simulations demonstrate that LTE can solve the urgent capacity problem faced by railways currently deploying GSM-R....

  16. Path sets size, model specification, or model estimation: Which one matters most in predicting stochastic user equilibrium traffic flow?

    OpenAIRE

    Haghani, Milad; Shahhoseini, Zahra; Sarvi, Majid

    2016-01-01

    This study aims to make an objective comparative analysis between the relative significance of three crucial modelling aspects involved in the probabilistic analysis of transport networks. The first question to address is the extent to which the size of generated path sets can affect the prediction of the static flow in the path-based traffic assignment paradigm. The importance of this question arises from the fact that the need to generate a large quantity of paths may be perceived by analys...

  17. Estimation of global network statistics from incomplete data.

    Directory of Open Access Journals (Sweden)

    Catherine A Bliss

    Full Text Available Complex networks underlie an enormous variety of social, biological, physical, and virtual systems. A profound complication for the science of complex networks is that in most cases, observing all nodes and all network interactions is impossible. Previous work addressing the impacts of partial network data is surprisingly limited, focuses primarily on missing nodes, and suggests that network statistics derived from subsampled data are not suitable estimators for the same network statistics describing the overall network topology. We generate scaling methods to predict true network statistics, including the degree distribution, from only partial knowledge of nodes, links, or weights. Our methods are transparent and do not assume a known generating process for the network, thus enabling prediction of network statistics for a wide variety of applications. We validate analytical results on four simulated network classes and empirical data sets of various sizes. We perform subsampling experiments by varying proportions of sampled data and demonstrate that our scaling methods can provide very good estimates of true network statistics while acknowledging limits. Lastly, we apply our techniques to a set of rich and evolving large-scale social networks, Twitter reply networks. Based on 100 million tweets, we use our scaling techniques to propose a statistical characterization of the Twitter Interactome from September 2008 to November 2008. Our treatment allows us to find support for Dunbar's hypothesis in detecting an upper threshold for the number of active social contacts that individuals maintain over the course of one week.

  18. A cost-effective traffic data collection system based on the iDEN mobile telecommunication network.

    Science.gov (United States)

    2008-10-01

    This report describes a cost-effective data collection system for Caltrans 170 traffic signal : controller. The data collection system is based on TCP/IP communication over existing : low-cost mobile communication networks and Motorola iDEN1 mobile...

  19. Estimating impact on clover-grass yield caused by traffic intensities

    DEFF Research Database (Denmark)

    Jørgensen, Rasmus Nyholm; Sørensen, Claus Grøn; Green, Ole

    2009-01-01

    Traffic intensities have a significant influence on a range of crop and soil parameters (Hamza & Anderson, 2005; Raper, 2005). For grass and especially clover, the yield response is negative as a function of traffic intensity (e.g. Frost, 1988).  During the growing season, conventional grass-clov...

  20. Distributed fusion estimation for sensor networks with communication constraints

    CERN Document Server

    Zhang, Wen-An; Song, Haiyu; Yu, Li

    2016-01-01

    This book systematically presents energy-efficient robust fusion estimation methods to achieve thorough and comprehensive results in the context of network-based fusion estimation. It summarizes recent findings on fusion estimation with communication constraints; several novel energy-efficient and robust design methods for dealing with energy constraints and network-induced uncertainties are presented, such as delays, packet losses, and asynchronous information... All the results are presented as algorithms, which are convenient for practical applications.

  1. A Study of Video Teleconferencing Traffic on a TCP/IP Network

    National Research Council Canada - National Science Library

    Carvey, Harlan

    1997-01-01

    ... of traffic generated by a video teleconferencing application. This information is useful in formulating accurate models to support the various classes of traffic that will dominate the broadband ISDN (B-ISDN or ATM...

  2. Traffic data collection and anonymous vehicle detection using wireless sensor networks : research summary.

    Science.gov (United States)

    2012-05-01

    Problem: : Most Intelligent Transportation System (ITS) applications require distributed : acquisition of various traffic metrics such as traffic speed, volume, and density. : The existing measurement technologies, such as inductive loops, infrared, ...

  3. Traffic data collection and anonymous vehicle detection using wireless sensor networks.

    Science.gov (United States)

    2012-05-01

    New traffic sensing devices based on wireless sensing technologies were designed and tested. Such devices encompass a cost-effective, battery-free, and energy self-sustained architecture for real-time traffic measurement over distributed points in a ...

  4. An Intelligent Traffic Flow Control System Based on Radio Frequency Identification and Wireless Sensor Networks

    National Research Council Canada - National Science Library

    Chao, Kuei-Hsiang; Chen, Pi-Yun

    2014-01-01

    This study primarily focuses on the use of radio frequency identification (RFID) as a form of traffic flow detection, which transmits collected information related to traffic flow directly to a control system through an RS232 interface...

  5. Estimating the causes of traffic accidents using logistic regression and discriminant analysis.

    Science.gov (United States)

    Karacasu, Murat; Ergül, Barış; Altin Yavuz, Arzu

    2014-01-01

    Factors that affect traffic accidents have been analysed in various ways. In this study, we use the methods of logistic regression and discriminant analysis to determine the damages due to injury and non-injury accidents in the Eskisehir Province. Data were obtained from the accident reports of the General Directorate of Security in Eskisehir; 2552 traffic accidents between January and December 2009 were investigated regarding whether they resulted in injury. According to the results, the effects of traffic accidents were reflected in the variables. These results provide a wealth of information that may aid future measures toward the prevention of undesired results.

  6. Timing analysis of rate-constrained traffic in TTEthernet using network calculus

    DEFF Research Database (Denmark)

    Zhao, Luxi; Pop, Paul; Li, Qiao

    2017-01-01

    calculus (NC) to determine the worst-case end-to-end delays of RC traffic in TTEthernet. The main contribution of this paper is capturing the effects of all the integration policies on the latency bounds of RC traffic using NC, and the consideration of relative frame offsets of TT traffic to reduce...

  7. Network Structure and Biased Variance Estimation in Respondent Driven Sampling.

    Directory of Open Access Journals (Sweden)

    Ashton M Verdery

    Full Text Available This paper explores bias in the estimation of sampling variance in Respondent Driven Sampling (RDS. Prior methodological work on RDS has focused on its problematic assumptions and the biases and inefficiencies of its estimators of the population mean. Nonetheless, researchers have given only slight attention to the topic of estimating sampling variance in RDS, despite the importance of variance estimation for the construction of confidence intervals and hypothesis tests. In this paper, we show that the estimators of RDS sampling variance rely on a critical assumption that the network is First Order Markov (FOM with respect to the dependent variable of interest. We demonstrate, through intuitive examples, mathematical generalizations, and computational experiments that current RDS variance estimators will always underestimate the population sampling variance of RDS in empirical networks that do not conform to the FOM assumption. Analysis of 215 observed university and school networks from Facebook and Add Health indicates that the FOM assumption is violated in every empirical network we analyze, and that these violations lead to substantially biased RDS estimators of sampling variance. We propose and test two alternative variance estimators that show some promise for reducing biases, but which also illustrate the limits of estimating sampling variance with only partial information on the underlying population social network.

  8. Network Structure and Biased Variance Estimation in Respondent Driven Sampling.

    Science.gov (United States)

    Verdery, Ashton M; Mouw, Ted; Bauldry, Shawn; Mucha, Peter J

    2015-01-01

    This paper explores bias in the estimation of sampling variance in Respondent Driven Sampling (RDS). Prior methodological work on RDS has focused on its problematic assumptions and the biases and inefficiencies of its estimators of the population mean. Nonetheless, researchers have given only slight attention to the topic of estimating sampling variance in RDS, despite the importance of variance estimation for the construction of confidence intervals and hypothesis tests. In this paper, we show that the estimators of RDS sampling variance rely on a critical assumption that the network is First Order Markov (FOM) with respect to the dependent variable of interest. We demonstrate, through intuitive examples, mathematical generalizations, and computational experiments that current RDS variance estimators will always underestimate the population sampling variance of RDS in empirical networks that do not conform to the FOM assumption. Analysis of 215 observed university and school networks from Facebook and Add Health indicates that the FOM assumption is violated in every empirical network we analyze, and that these violations lead to substantially biased RDS estimators of sampling variance. We propose and test two alternative variance estimators that show some promise for reducing biases, but which also illustrate the limits of estimating sampling variance with only partial information on the underlying population social network.

  9. ESTIMATION OF PV MODULE SURFACE TEMPERATURE USING ARTIFICIAL NEURAL NETWORKS

    Directory of Open Access Journals (Sweden)

    Can Coskun

    2016-12-01

    Full Text Available This study aimed to use the artificial neural network (ANN method to estimate the surface temperature of a photovoltaic (PV panel. Using the experimentally obtained PV data, the accuracy of the ANN model was evaluated. To train the artificial neural network (ANN, outer temperature solar radiation and wind speed values were inputs and surface temperature was an output. The ANN was used to estimate PV panel surface temperature. Using the Levenberg-Marquardt (LM algorithm the feed forward artificial neural network was trained. Two back propagation type ANN algorithms were used and their performance was compared with the estimate from the LM algorithm. To train the artificial neural network, experimental data were used for two thirds with the remaining third used for testing. Additionally scaled conjugate gradient (SCG back propagation and resilient back propagation (RB type ANN algorithms were used for comparison with the LM algorithm. The performances of these three types of artificial neural network were compared and mean error rates of between 0.005962 and 0.012177% were obtained. The best estimate was produced by the LM algorithm. Estimation of PV surface temperature with artificial neural networks provides better results than conventional correlation methods. This study showed that artificial neural networks may be effectively used to estimate PV surface temperature.

  10. Modelling and Implementation of QoS in Wireless Sensor Networks: A Multiconstrained Traffic Engineering Model

    Directory of Open Access Journals (Sweden)

    Bagula AntoineB

    2010-01-01

    Full Text Available This paper revisits the problem of Quality of Service (QoS provisioning to assess the relevance of using multipath routing to improve the reliability and packet delivery in wireless sensor networks while maintaining lower power consumption levels. Building upon a previous benchmark, we propose a traffic engineering model that relies on delay, reliability, and energy-constrained paths to achieve faster, reliable, and energy-efficient transmission of the information routed by a wireless sensor network. As a step forward into the implementation of the proposed QoS model, we describe the initial steps of its packet forwarding protocol and highlight the tradeoff between the complexity of the model and the ease of implementation. Using simulation, we demonstrate the relative efficiency of our proposed model compared to single path routing, disjoint path routing, and the previously proposed benchmarks. The results reveal that by achieving a good tradeoff between delay minimization, reliability maximization, and path set selection, our model outperforms the other models in terms of energy consumption and quality of paths used to route the information.

  11. Traffic Adaptive Synchronized Cluster Based MAC Protocol for Cognitive Radio Ad Hoc Network

    Directory of Open Access Journals (Sweden)

    Sultana Sahelee

    2017-01-01

    Full Text Available In wireless communication, Cognitive Radio Network (CRN is the contemporary research area to improve efficiency and spectrum utilization. It is structured with both licensed users and unlicensed users. In CRN, unlicensed users also called Cognitive Radio (CR users are permitted to utilize the free/idle of licensed channels without harmful interference to licensed users. However, accessing idle channels is the big challenging issue due to licensed users’ activities. A large number of cluster based MAC protocol have been proposed to solve this issue. In this paper, we have come up with a Traffic Adaptive Synchronized Cluster Based MAC Protocol for Cognitive Radio Ad Hoc Network, with the target of creating cluster structure more vigorous to the licensed users’ channel re-occupancy actions, maximize throughput, and minimize switching delay, so that CR users be able to use the idle spectrum more efficiently. In our protocol, clusters are formed according to Cluster Identification Channel (CIC and inter-communication is completed without gateway nodes. Finally, we have analysed and implemented our protocol through simulation and it provides better performance in terms of different performance metrics.

  12. CROSS LAYERED HYBRID TRANSPORT LAYER PROTOCOL APPROACH TO ENHANCE NETWORK UTILISATION FOR VIDEO TRAFFIC

    Directory of Open Access Journals (Sweden)

    Matilda.S

    2010-03-01

    Full Text Available Video data transfer is the major traffic in today’s Internet. With the emerging need for anytime anywhere communication, applications transmitting video is gaining momentum. Real Time Protocol is the primary standard for transfer of video data, as; it requires timely delivery and can tolerate loss of packets. Streaming is the method used for delivering video content from the source server to the user. But this has many drawbacks: a It sends only the amount of data equivalent to the streaming encoded rate to the client irrespective of the available bandwidth in the path. Hence the links are underutilized; b It utilizes the link for the entire period of transfer and hence the link is not available to service other new clients. Thus as the number of clients increases, the network performance decreases. In this work, the advantages and disadvantages of the combination of different protocols in the application layer and transport layer are analyzed. The significant characteristics of each of these protocols are utilized and a combination of protocols for improving the network performance is arrived at, while retaining the QoS of video transmission.

  13. Selfish routing equilibrium in stochastic traffic network: A probability-dominant description.

    Science.gov (United States)

    Zhang, Wenyi; He, Zhengbing; Guan, Wei; Ma, Rui

    2017-01-01

    This paper suggests a probability-dominant user equilibrium (PdUE) model to describe the selfish routing equilibrium in a stochastic traffic network. At PdUE, travel demands are only assigned to the most dominant routes in the same origin-destination pair. A probability-dominant rerouting dynamic model is proposed to explain the behavioral mechanism of PdUE. To facilitate applications, the logit formula of PdUE is developed, of which a well-designed route set is not indispensable and the equivalent varitional inequality formation is simple. Two routing strategies, i.e., the probability-dominant strategy (PDS) and the dominant probability strategy (DPS), are discussed through a hypothetical experiment. It is found that, whether out of insurance or striving for perfection, PDS is a better choice than DPS. For more general cases, the conducted numerical tests lead to the same conclusion. These imply that PdUE (rather than the conventional stochastic user equilibrium) is a desirable selfish routing equilibrium for a stochastic network, given that the probability distributions of travel time are available to travelers.

  14. Selfish routing equilibrium in stochastic traffic network: A probability-dominant description

    Science.gov (United States)

    Zhang, Wenyi; Guan, Wei; Ma, Rui

    2017-01-01

    This paper suggests a probability-dominant user equilibrium (PdUE) model to describe the selfish routing equilibrium in a stochastic traffic network. At PdUE, travel demands are only assigned to the most dominant routes in the same origin-destination pair. A probability-dominant rerouting dynamic model is proposed to explain the behavioral mechanism of PdUE. To facilitate applications, the logit formula of PdUE is developed, of which a well-designed route set is not indispensable and the equivalent varitional inequality formation is simple. Two routing strategies, i.e., the probability-dominant strategy (PDS) and the dominant probability strategy (DPS), are discussed through a hypothetical experiment. It is found that, whether out of insurance or striving for perfection, PDS is a better choice than DPS. For more general cases, the conducted numerical tests lead to the same conclusion. These imply that PdUE (rather than the conventional stochastic user equilibrium) is a desirable selfish routing equilibrium for a stochastic network, given that the probability distributions of travel time are available to travelers. PMID:28829834

  15. Evaluation of origin-destination matrix estimation techniques to support aspects of traffic modeling.

    Science.gov (United States)

    2014-05-01

    Travel demand forecasting models are used to predict future traffic volumes to evaluate : roadway improvement alternatives. Each of the metropolitan planning organizations (MPO) in : Alabama maintains a travel demand model to support planning efforts...

  16. The Comparison of a Roundabout Traffic Delay Estimation between SUMO and IHCM 1997 on Roundabout

    Directory of Open Access Journals (Sweden)

    Tina Andriyana

    2015-06-01

    The result showed the traffic delay in observation data is higher than delay in SUMO result and IHCM 1997 calculation. The statistical results showed that the traffic delay of SUMO, and IHCM 1997 have no similarities to the observation. Furthermore, from the linear regression result, only SUMO result has the highest value for determination coefficient (R2 compared to IHCM 1997 as shown in the West and South arms for SUMO result in the morning measurement. It means SUMO more representatives the observation compared to IHCM 1997. It is occurred because SUMO is developed in Europe and also the location for this research is in Sweden, Europe which has very different traffic condition from Indonesia. Keywords: Roundabout, traffic delay, SUMO, IHCM 1997.

  17. Freeway travel time estimation using existing fixed traffic sensors : phase 1.

    Science.gov (United States)

    2013-08-01

    Freeway travel time is one of the most useful pieces of information for road users and an : important measure of effectiveness (MOE) for traffic engineers and policy makers. In the Greater : St. Louis area, Gateway Guide, the St. Louis Transportation...

  18. Differential patterns, trends and hotspots of road traffic injuries on different road networks in Vellore district, southern India.

    Science.gov (United States)

    Mohan, Venkata Raghava; Sarkar, Rajiv; Abraham, Vinod Joseph; Balraj, Vinohar; Naumova, Elena N

    2015-03-01

    To describe spatial and temporal profiles of Road Traffic Injuries (RTIs) on different road networks in Vellore district of southern India. Using the information in the police maintained First Information Reports (FIRs), daily time series of RTI counts were created and temporal characteristics were analysed with respect to the vehicle, road types and time of the day for the period January 2005 to May 2007. Daily incidence and trend of RTIs were estimated using a Poisson regression analysis. Of the reported 3262 RTIs, 52% had occurred on the National Highway (NH). The overall RTI rate on the NH was 8.8/100 000 vehicles per day with significantly higher pedestrian involvement. The mean numbers of RTIs were significantly higher on weekends. Thirteen percentage of all RTIs were associated with fatalities. Hotspots are major town junctions, and RTI rates differ over different stretches of the NH. In India, FIRs form a valuable source of RTI information. Information on different vehicle profile, RTI patterns, and their spatial and temporal trends can be used by administrators to devise effective strategies for RTI prevention by concentrating on the high-risk areas, thereby optimising the use of available personnel and resources. © 2014 John Wiley & Sons Ltd.

  19. Feasibility of a Networked Air Traffic Infrastructure Validation Environment for Advanced NextGen Concepts

    Science.gov (United States)

    McCormack, Michael J.; Gibson, Alec K.; Dennis, Noah E.; Underwood, Matthew C.; Miller,Lana B.; Ballin, Mark G.

    2013-01-01

    Abstract-Next Generation Air Transportation System (NextGen) applications reliant upon aircraft data links such as Automatic Dependent Surveillance-Broadcast (ADS-B) offer a sweeping modernization of the National Airspace System (NAS), but the aviation stakeholder community has not yet established a positive business case for equipage and message content standards remain in flux. It is necessary to transition promising Air Traffic Management (ATM) Concepts of Operations (ConOps) from simulation environments to full-scale flight tests in order to validate user benefits and solidify message standards. However, flight tests are prohibitively expensive and message standards for Commercial-off-the-Shelf (COTS) systems cannot support many advanced ConOps. It is therefore proposed to simulate future aircraft surveillance and communications equipage and employ an existing commercial data link to exchange data during dedicated flight tests. This capability, referred to as the Networked Air Traffic Infrastructure Validation Environment (NATIVE), would emulate aircraft data links such as ADS-B using in-flight Internet and easily-installed test equipment. By utilizing low-cost equipment that is easy to install and certify for testing, advanced ATM ConOps can be validated, message content standards can be solidified, and new standards can be established through full-scale flight trials without necessary or expensive equipage or extensive flight test preparation. This paper presents results of a feasibility study of the NATIVE concept. To determine requirements, six NATIVE design configurations were developed for two NASA ConOps that rely on ADS-B. The performance characteristics of three existing in-flight Internet services were investigated to determine whether performance is adequate to support the concept. Next, a study of requisite hardware and software was conducted to examine whether and how the NATIVE concept might be realized. Finally, to determine a business case

  20. Parameter estimation using compensatory neural networks

    Indian Academy of Sciences (India)

    Proposed here is a new neuron model, a basis for Compensatory Neural Network Architecture (CNNA), which not only reduces the total number of interconnections among neurons but also reduces the total computing time for training. The suggested model has properties of the basic neuron model as well as the higher ...

  1. Neural networks for estimation of ocean wave parameters

    Digital Repository Service at National Institute of Oceanography (India)

    Mandal, S.; Rao, S.; Raju, D.H.

    Ocean wave parameters play a significant role in the design of all coastal and offshore structures. In the present study, neural networks are used to estimate various ocean wave parameters from theoretical Pierson-Moskowitz spectra as well...

  2. Early estimate of motor vehicle traffic fatalities for the first three quarters (January-September) of 2009 : a brief statistical summary

    Science.gov (United States)

    2010-01-01

    A statistical projection of traffic fatalities for the first three quarters of 2009 shows that an estimated 25,576 people died in motor vehicle traffic crashes. This represents a decline of about 7.9 percent as compared to the 27,771 fa-talities that...

  3. Track wear-and-tear cost by traffic class: Functional form, zero output levels and marginal cost pricing recovery on the French rail network

    OpenAIRE

    Gaudry, Marc; Quinet, Emile

    2009-01-01

    We address the issue of the allocation of railway track maintenance (wear-and-tear) costs to traffic output classes and consider a very general function relating maintenance cost C to a set of technical production characteristics K used to produce traffic output vector T. We neglect other rail cost categories, such as traffic control and track renewal. The data base pertains to over 1500 sections of the French rail infrastructure in 1999, representing about 90% of the total network of 30000 k...

  4. Distributed Estimation, Coding, and Scheduling in Wireless Visual Sensor Networks

    Science.gov (United States)

    Yu, Chao

    2013-01-01

    In this thesis, we consider estimation, coding, and sensor scheduling for energy efficient operation of wireless visual sensor networks (VSN), which consist of battery-powered wireless sensors with sensing (imaging), computation, and communication capabilities. The competing requirements for applications of these wireless sensor networks (WSN)…

  5. Parameter estimation of an aeroelastic aircraft using neural networks

    Indian Academy of Sciences (India)

    e-mail: scr@iitk.ac.in. Abstract. Application of neural networks to the problem of aerodynamic modelling and parameter estimation for aeroelastic aircraft is addressed. A neural model capable of ... of the network in terms of the number of neurons in the hidden layer, the learning rate, the momentum rate etc. is not an exact ...

  6. A Mobility and Traffic Generation Framework for Modeling and Simulating Ad Hoc Communication Networks

    Directory of Open Access Journals (Sweden)

    Chris Barrett

    2004-01-01

    Full Text Available We present a generic mobility and traffic generation framework that can be incorporated into a tool for modeling and simulating large scale ad~hoc networks. Three components of this framework, namely a mobility data generator (MDG, a graph structure generator (GSG and an occlusion modification tool (OMT allow a variety of mobility models to be incorporated into the tool. The MDG module generates positions of transceivers at specified time instants. The GSG module constructs the graph corresponding to the ad hoc network from the mobility data provided by MDG. The OMT module modifies the connectivity of the graph produced by GSG to allow for occlusion effects. With two other modules, namely an activity data generator (ADG which generates packet transmission activities for transceivers and a packet activity simulator (PAS which simulates the movement and interaction of packets among the transceivers, the framework allows the modeling and simulation of ad hoc communication networks. The design of the framework allows a user to incorporate various realistic parameters crucial in the simulation. We illustrate the utility of our framework through a comparative study of three mobility models. Two of these are synthetic models (random waypoint and exponentially correlated mobility proposed in the literature. The third model is based on an urban population mobility modeling tool (TRANSIMS developed at the Los Alamos National Laboratory. This tool is capable of providing comprehensive information about the demographics, mobility and interactions of members of a large urban population. A comparison of these models is carried out by computing a variety of parameters associated with the graph structures generated by the models. There has recently been interest in the structural properties of graphs that arise in real world systems. We examine two aspects of this for the graphs created by the mobility models: change associated with power control (range of

  7. Estimating order statistics of network degrees

    Science.gov (United States)

    Chu, J.; Nadarajah, S.

    2018-01-01

    We model the order statistics of network degrees of big data sets by a range of generalised beta distributions. A three parameter beta distribution due to Libby and Novick (1982) is shown to give the best overall fit for at least four big data sets. The fit of this distribution is significantly better than the fit suggested by Olhede and Wolfe (2012) across the whole range of order statistics for all four data sets.

  8. Flood estimation: a neural network approach

    Energy Technology Data Exchange (ETDEWEB)

    Swain, P.C.; Seshachalam, C.; Umamahesh, N.V. [Regional Engineering Coll., Warangal (India). Water and Environment Div.

    2000-07-01

    The artificial neural network (ANN) approach described in this study aims at predicting the flood flow into a reservoir. This differs from the traditional methods of flow prediction in the sense that it belongs to a class of data driven approaches, where as the traditional methods are model driven. Physical processes influencing the occurrences of streamflow in a river are highly complex, and are very difficult to be modelled by available statistical or deterministic models. ANNs provide model free solutions and hence can be expected to be appropriate in these conditions. Non-linearity, adaptivity, evidential response and fault tolerance are additional properties and capabilities of the neural networks. This paper highlights the applicability of neural networks for predicting daily flood flow taking the Hirakud reservoir on river Mahanadi in Orissa, India as the case study. The correlation between the observed and predicted flows and the relative error are considered to measure the performance of the model. The correlation between the observed and the modelled flows are computed to be 0.9467 in testing phase of the model. (orig.)

  9. Estimation of Anonymous Email Network Characteristics through Statistical Disclosure Attacks

    Directory of Open Access Journals (Sweden)

    Javier Portela

    2016-11-01

    Full Text Available Social network analysis aims to obtain relational data from social systems to identify leaders, roles, and communities in order to model profiles or predict a specific behavior in users’ network. Preserving anonymity in social networks is a subject of major concern. Anonymity can be compromised by disclosing senders’ or receivers’ identity, message content, or sender-receiver relationships. Under strongly incomplete information, a statistical disclosure attack is used to estimate the network and node characteristics such as centrality and clustering measures, degree distribution, and small-world-ness. A database of email networks in 29 university faculties is used to study the method. A research on the small-world-ness and Power law characteristics of these email networks is also developed, helping to understand the behavior of small email networks.

  10. Fiber Orientation Estimation Guided by a Deep Network.

    Science.gov (United States)

    Ye, Chuyang; Prince, Jerry L

    2017-09-01

    Diffusion magnetic resonance imaging (dMRI) is currently the only tool for noninvasively imaging the brain's white matter tracts. The fiber orientation (FO) is a key feature computed from dMRI for tract reconstruction. Because the number of FOs in a voxel is usually small, dictionary-based sparse reconstruction has been used to estimate FOs. However, accurate estimation of complex FO configurations in the presence of noise can still be challenging. In this work we explore the use of a deep network for FO estimation in a dictionary-based framework and propose an algorithm named Fiber Orientation Reconstruction guided by a Deep Network (FORDN). FORDN consists of two steps. First, we use a smaller dictionary encoding coarse basis FOs to represent diffusion signals. To estimate the mixture fractions of the dictionary atoms, a deep network is designed to solve the sparse reconstruction problem. Second, the coarse FOs inform the final FO estimation, where a larger dictionary encoding a dense basis of FOs is used and a weighted ℓ1-norm regularized least squares problem is solved to encourage FOs that are consistent with the network output. FORDN was evaluated and compared with state-of-the-art algorithms that estimate FOs using sparse reconstruction on simulated and typical clinical dMRI data. The results demonstrate the benefit of using a deep network for FO estimation.

  11. Fast, moment-based estimation methods for delay network tomography

    Energy Technology Data Exchange (ETDEWEB)

    Lawrence, Earl Christophre [Los Alamos National Laboratory; Michailidis, George [U OF MICHIGAN; Nair, Vijayan N [U OF MICHIGAN

    2008-01-01

    Consider the delay network tomography problem where the goal is to estimate distributions of delays at the link-level using data on end-to-end delays. These measurements are obtained using probes that are injected at nodes located on the periphery of the network and sent to other nodes also located on the periphery. Much of the previous literature deals with discrete delay distributions by discretizing the data into small bins. This paper considers more general models with a focus on computationally efficient estimation. The moment-based schemes presented here are designed to function well for larger networks and for applications like monitoring that require speedy solutions.

  12. Using Generalized Entropies and OC-SVM with Mahalanobis Kernel for Detection and Classification of Anomalies in Network Traffic

    Directory of Open Access Journals (Sweden)

    Jayro Santiago-Paz

    2015-09-01

    Full Text Available Network anomaly detection and classification is an important open issue in network security. Several approaches and systems based on different mathematical tools have been studied and developed, among them, the Anomaly-Network Intrusion Detection System (A-NIDS, which monitors network traffic and compares it against an established baseline of a “normal” traffic profile. Then, it is necessary to characterize the “normal” Internet traffic. This paper presents an approach for anomaly detection and classification based on Shannon, Rényi and Tsallis entropies of selected features, and the construction of regions from entropy data employing the Mahalanobis distance (MD, and One Class Support Vector Machine (OC-SVM with different kernels (Radial Basis Function (RBF and Mahalanobis Kernel (MK for “normal” and abnormal traffic. Regular and non-regular regions built from “normal” traffic profiles allow anomaly detection, while the classification is performed under the assumption that regions corresponding to the attack classes have been previously characterized. Although this approach allows the use of as many features as required, only four well-known significant features were selected in our case. In order to evaluate our approach, two different data sets were used: one set of real traffic obtained from an Academic Local Area Network (LAN, and the other a subset of the 1998 MIT-DARPA set. For these data sets, a True positive rate up to 99.35%, a True negative rate up to 99.83% and a False negative rate at about 0.16% were yielded. Experimental results show that certain q-values of the generalized entropies and the use of OC-SVM with RBF kernel improve the detection rate in the detection stage, while the novel inclusion of MK kernel in OC-SVM and k-temporal nearest neighbors improve accuracy in classification. In addition, the results show that using the Box-Cox transformation, the Mahalanobis distance yielded high detection rates with

  13. A Network-Constrained Integrated Method for Detecting Spatial Cluster and Risk Location of Traffic Crash: A Case Study from Wuhan, China

    Directory of Open Access Journals (Sweden)

    Ke Nie

    2015-03-01

    Full Text Available Research on spatial cluster detection of traffic crash (TC at the city level plays an essential role in safety improvement and urban development. This study aimed to detect spatial cluster pattern and identify riskier road segments (RRSs of TC constrained by network with a two-step integrated method, called NKDE-GLINCS combining density estimation and spatial autocorrelation. The first step is novel and involves in spreading TC count to a density surface using Network-constrained Kernel Density Estimation (NKDE. The second step is the process of calculating local indicators of spatial association (LISA using Network-constrained Getis-Ord Gi* (GLINCS. GLINCS takes the smoothed TC density as input value to identify locations of road segments with high risk. This method was tested using the TC data in 2007 in Wuhan, China. The results demonstrated that the method was valid to delineate TC cluster and identify risk road segments. Besides, it was more effective compared with traditional GLINCS using TC counting as input. Moreover, the top 20 road segments with high-high TC density at the significance level of 0.1 were listed. These results can promote a better identification of RRS, which is valuable in the pursuit of improving transit safety and sustainability in urban road network. Further research should address spatial-temporal analysis and TC factors exploration.

  14. Artificial Neural Network Based State Estimators Integrated into Kalmtool

    DEFF Research Database (Denmark)

    Bayramoglu, Enis; Ravn, Ole; Poulsen, Niels Kjølstad

    2012-01-01

    In this paper we present a toolbox enabling easy evaluation and comparison of dierent ltering algorithms. The toolbox is called Kalmtool and is a set of MATLAB tools for state estimation of nonlinear systems. The toolbox now contains functions for Articial Neural Network Based State Estimation...

  15. POLLING AND DUAL-LEVEL TRAFFIC ANALYSIS FOR IMPROVED DOS DETECTION IN IEEE 802.21 NETWORKS

    Directory of Open Access Journals (Sweden)

    Nygil Alex Vadakkan

    2014-06-01

    Full Text Available The IEEE 802.21 standard was developed for communication of devices in a heterogeneous environment which included greater support for handoffs. This paper focuses on the denial of service (DoS vulnerabilities faced by such Media Independent Handover (MIH networks & various effective countermeasures that can be deployed to prevent their impact on such heterogeneous networks. The use of polling mechanism coupled with real time as well as offline traffic analysis can keep a good number of attacks at bay. The use of offline traffic analysis is to use the model and compare it with a lighter model and see if any of the excluded features in the lighter model have had suspicious variations which could be a varied form of DoS attack or an attack that is completely new. The countermeasures that have been developed also allows for the increase in efficiency of data transfer as well as higher rates of success in handoffs.

  16. Spatio-temporal Estimates of CO2 Emissions in the Los Angeles Basin from On-road and Airport Traffic

    Science.gov (United States)

    Rao, P.; Song, Y.; Patarasuk, R.; Gurney, K. R.; Eldering, A.; O'Keeffe, D.; Miller, C. E.; Duren, R. M.

    2014-12-01

    Characterizing the spatio-temporal distribution of fossil fuel CO2 (FFCO2) emissions in urban landscapes is challenging. We use Hestia, an innovative "bottom up" approach for estimating FFCO2 emissions in the Los Angeles (LA) megacity and Southern California Air Basin (SCAB) which account for ~53% of the FFCO2 emissions in California. Hestia-LA, in coordination with "top down" atmospheric CO2 measurements, will provide baseline FFCO2 emissions, help monitor changes in emissions, and develop emissions mitigation policies. Hestia-LA characterizes FFCO2 emissions at the building/street spatial scale (10-100 m) and at hourly time steps in the basin by combining data on residential and commercial building emissions, industrial processes, electricity production, and different transportation sectors. We report here on the construction of the spatial and temporal structure in two key transportation sectors within the SCAB: on-road vehicle (46%) and aircraft (2%) emissions. We quantified on-road traffic emissions by merging traffic data from Southern California Association of Governments, California Freeway Performance Measurement System and modeled motor vehicle emissions from EPA's NMIM model. Preliminary analysis shows that (1) LA and Orange counties dominate the annual FFCO2 emissions from urban freeways and arterials, and (2) LA county has a wider peak traffic period during weekdays (2-6pm) than the other four counties (4-5pm). We characterized airport emissions by integrating information from Federal Aviation Administration, Los Angeles World Airports, and Airnav LLC for the temporal structure of aircraft arrivals and departures, and the National Emissions Inventory for total annual aircraft emissions. We categorized the 47 airports in LA basin based on the volume and type (commercial, general aviation and military) of aircraft traffic, and then assigned appropriate hour-of-day and day-of-week traffic volume-specific CO2 emission patterns to each airport. We found

  17. Time of arrival based location estimation for cooperative relay networks

    KAUST Repository

    Çelebi, Hasari Burak

    2010-09-01

    In this paper, we investigate the performance of a cooperative relay network performing location estimation through time of arrival (TOA). We derive Cramer-Rao lower bound (CRLB) for the location estimates using the relay network. The analysis is extended to obtain average CRLB considering the signal fluctuations in both relay and direct links. The effects of the channel fading of both relay and direct links and amplification factor and location of the relay node on average CRLB are investigated. Simulation results show that the channel fading of both relay and direct links and amplification factor and location of relay node affect the accuracy of TOA based location estimation. ©2010 IEEE.

  18. Optimizing Neural Network Architectures Using Generalization Error Estimators

    DEFF Research Database (Denmark)

    Larsen, Jan

    1994-01-01

    This paper addresses the optimization of neural network architectures. It is suggested to optimize the architecture by selecting the model with minimal estimated averaged generalization error. We consider a least-squares (LS) criterion for estimating neural network models, i.e., the associated...... model weights are estimated by minimizing the LS criterion. The quality of a particular estimated model is measured by the average generalization error. This is defined as the expected squared prediction error on a novel input-output sample averaged over all possible training sets. An essential part...... of the suggested architecture optimization scheme is to calculate an estimate of the average generalization error. We suggest using the GEN-estimator which allows for dealing with nonlinear, incomplete models, i.e., models which are not capable of modeling the underlying nonlinear relationship perfectly. In most...

  19. High-Speed Network Traffic Management Analysis and Optimization Models and Methods

    CERN Document Server

    Zaborovski, V; Podgurski, Y; Shemanin, Y

    1997-01-01

    The main steps of automatic control methodology include the hierarchical representation of management system and the formal definitions of input variables, object and goal of control of each management level. A Petri net model of individual traffic source is presented. It is noted that the current set of traffic parameters recommended by ATM-forum is not enough to synthesize optimal traffic control system. The feature of traffic self-similarity can be used to effectively solve optimal control task. An example of an optimal control scheme for cell discarding algorithm is presented.

  20. The Detection of Emerging Trends Using Wikipedia Traffic Data and Context Networks.

    Science.gov (United States)

    Kämpf, Mirko; Tessenow, Eric; Kenett, Dror Y; Kantelhardt, Jan W

    2015-01-01

    Can online media predict new and emerging trends, since there is a relationship between trends in society and their representation in online systems? While several recent studies have used Google Trends as the leading online information source to answer corresponding research questions, we focus on the online encyclopedia Wikipedia often used for deeper topical reading. Wikipedia grants open access to all traffic data and provides lots of additional (semantic) information in a context network besides single keywords. Specifically, we suggest and study context-normalized and time-dependent measures for a topic's importance based on page-view time series of Wikipedia articles in different languages and articles related to them by internal links. As an example, we present a study of the recently emerging Big Data market with a focus on the Hadoop ecosystem, and compare the capabilities of Wikipedia versus Google in predicting its popularity and life cycles. To support further applications, we have developed an open web platform to share results of Wikipedia analytics, providing context-rich and language-independent relevance measures for emerging trends.

  1. The Detection of Emerging Trends Using Wikipedia Traffic Data and Context Networks.

    Directory of Open Access Journals (Sweden)

    Mirko Kämpf

    Full Text Available Can online media predict new and emerging trends, since there is a relationship between trends in society and their representation in online systems? While several recent studies have used Google Trends as the leading online information source to answer corresponding research questions, we focus on the online encyclopedia Wikipedia often used for deeper topical reading. Wikipedia grants open access to all traffic data and provides lots of additional (semantic information in a context network besides single keywords. Specifically, we suggest and study context-normalized and time-dependent measures for a topic's importance based on page-view time series of Wikipedia articles in different languages and articles related to them by internal links. As an example, we present a study of the recently emerging Big Data market with a focus on the Hadoop ecosystem, and compare the capabilities of Wikipedia versus Google in predicting its popularity and life cycles. To support further applications, we have developed an open web platform to share results of Wikipedia analytics, providing context-rich and language-independent relevance measures for emerging trends.

  2. The Detection of Emerging Trends Using Wikipedia Traffic Data and Context Networks

    Science.gov (United States)

    Kämpf, Mirko; Tessenow, Eric; Kenett, Dror Y.; Kantelhardt, Jan W.

    2015-01-01

    Can online media predict new and emerging trends, since there is a relationship between trends in society and their representation in online systems? While several recent studies have used Google Trends as the leading online information source to answer corresponding research questions, we focus on the online encyclopedia Wikipedia often used for deeper topical reading. Wikipedia grants open access to all traffic data and provides lots of additional (semantic) information in a context network besides single keywords. Specifically, we suggest and study context-normalized and time-dependent measures for a topic’s importance based on page-view time series of Wikipedia articles in different languages and articles related to them by internal links. As an example, we present a study of the recently emerging Big Data market with a focus on the Hadoop ecosystem, and compare the capabilities of Wikipedia versus Google in predicting its popularity and life cycles. To support further applications, we have developed an open web platform to share results of Wikipedia analytics, providing context-rich and language-independent relevance measures for emerging trends. PMID:26720074

  3. p53 as the main traffic controller of the cell signaling network.

    Science.gov (United States)

    Sebastian, Sinto; Azzariti, Amalia; Silvestris, Nicola; Porcelli, Letizia; Russo, Antonio; Paradiso, Angelo

    2010-06-01

    Among different pathological conditions that affect human beings, cancer has received a great deal of attention primarily because it leads to significant morbidity and mortality. This is essentially due to increasing world-wide incidence of this disease and the inability to discover the cause and molecular mechanisms by which normal human cells acquire the characteristics that define cancer cells. Since the discovery of p53 over a quarter of a century ago, it is now recognized that virtually all cell fate pathways of live cells and the decision to die are under the control of p53. Such extensive involvement indicates that p53 protein is acting as a major traffic controller in the cell signaling network. In cancer cells, many cell signaling pathways of normal human cells are rerouted towards immortalization and this is accomplished by the corruption of the main controllers of cell signaling pathways such as p53. This review highlights how p53 signaling activity is altered in cancer cells so that cells acquire the hallmarks of cancer including deregulated infinite self replicative potential.

  4. Spatial variations in estimated chronic exposure to traffic-related air pollution in working populations: A simulation

    Directory of Open Access Journals (Sweden)

    Cloutier-Fisher Denise

    2008-07-01

    Full Text Available Abstract Background Chronic exposure to traffic-related air pollution is associated with a variety of health impacts in adults and recent studies show that exposure varies spatially, with some residents in a community more exposed than others. A spatial exposure simulation model (SESM which incorporates six microenvironments (home indoor, work indoor, other indoor, outdoor, in-vehicle to work and in-vehicle other is described and used to explore spatial variability in estimates of exposure to traffic-related nitrogen dioxide (not including indoor sources for working people. The study models spatial variability in estimated exposure aggregated at the census tracts level for 382 census tracts in the Greater Vancouver Regional District of British Columbia, Canada. Summary statistics relating to the distributions of the estimated exposures are compared visually through mapping. Observed variations are explored through analyses of model inputs. Results Two sources of spatial variability in exposure to traffic-related nitrogen dioxide were identified. Median estimates of total exposure ranged from 8 μg/m3 to 35 μg/m3 of annual average hourly NO2 for workers in different census tracts in the study area. Exposure estimates are highest where ambient pollution levels are highest. This reflects the regional gradient of pollution in the study area and the relatively high percentage of time spent at home locations. However, for workers within the same census tract, variations were observed in the partial exposure estimates associated with time spent outside the residential census tract. Simulation modeling shows that some workers may have exposures 1.3 times higher than other workers residing in the same census tract because of time spent away from the residential census tract, and that time spent in work census tracts contributes most to the differences in exposure. Exposure estimates associated with the activity of commuting by vehicle to work were

  5. Mathematical model of transmission network static state estimation

    Directory of Open Access Journals (Sweden)

    Ivanov Aleksandar

    2012-01-01

    Full Text Available In this paper the characteristics and capabilities of the power transmission network static state estimator are presented. The solving process of the mathematical model containing the measurement errors and their processing is developed. To evaluate difference between the general model of state estimation and the fast decoupled state estimation model, the both models are applied to an example, and so derived results are compared.

  6. A neural network applied to estimate Burr XII distribution parameters

    Energy Technology Data Exchange (ETDEWEB)

    Abbasi, B., E-mail: b.abbasi@gmail.co [Department of Industrial Engineering, Sharif University of Technology, Tehran (Iran, Islamic Republic of); Hosseinifard, S.Z. [Department of Statistics and Operations Research, RMIT University, Melbourne (Australia); Coit, D.W. [Department of Industrial and System Engineering, Rutgers University, Piscataway, NJ (United States)

    2010-06-15

    The Burr XII distribution can closely approximate many other well-known probability density functions such as the normal, gamma, lognormal, exponential distributions as well as Pearson type I, II, V, VII, IX, X, XII families of distributions. Considering a wide range of shape and scale parameters of the Burr XII distribution, it can have an important role in reliability modeling, risk analysis and process capability estimation. However, estimating parameters of the Burr XII distribution can be a complicated task and the use of conventional methods such as maximum likelihood estimation (MLE) and moment method (MM) is not straightforward. Some tables to estimate Burr XII parameters have been provided by Burr (1942) but they are not adequate for many purposes or data sets. Burr tables contain specific values of skewness and kurtosis and their corresponding Burr XII parameters. Using interpolation or extrapolation to estimate other values may provide inappropriate estimations. In this paper, we present a neural network to estimate Burr XII parameters for different values of skewness and kurtosis as inputs. A trained network is presented, and one can use it without previous knowledge about neural networks to estimate Burr XII distribution parameters. Accurate estimation of the Burr parameters is an extension of simulation studies.

  7. A Life-Cycle Cost Estimating Methodology for NASA-Developed Air Traffic Control Decision Support Tools

    Science.gov (United States)

    Wang, Jianzhong Jay; Datta, Koushik; Landis, Michael R. (Technical Monitor)

    2002-01-01

    This paper describes the development of a life-cycle cost (LCC) estimating methodology for air traffic control Decision Support Tools (DSTs) under development by the National Aeronautics and Space Administration (NASA), using a combination of parametric, analogy, and expert opinion methods. There is no one standard methodology and technique that is used by NASA or by the Federal Aviation Administration (FAA) for LCC estimation of prospective Decision Support Tools. Some of the frequently used methodologies include bottom-up, analogy, top-down, parametric, expert judgement, and Parkinson's Law. The developed LCC estimating methodology can be visualized as a three-dimensional matrix where the three axes represent coverage, estimation, and timing. This paper focuses on the three characteristics of this methodology that correspond to the three axes.

  8. An estimate of the unit cost of road traffic collisions in South Africa for 1998

    CSIR Research Space (South Africa)

    Schutte, IC

    2000-03-01

    Full Text Available Road traffic collision result in both human loss and cost to the company. Government and other role players addressing this problem require reliable information on the cost of collisions to the economy. Collisions costs are also used in the economic...

  9. Control and estimation methods over communication networks

    CERN Document Server

    Mahmoud, Magdi S

    2014-01-01

    This book provides a rigorous framework in which to study problems in the analysis, stability and design of networked control systems. Four dominant sources of difficulty are considered: packet dropouts, communication bandwidth constraints, parametric uncertainty, and time delays. Past methods and results are reviewed from a contemporary perspective, present trends are examined, and future possibilities proposed. Emphasis is placed on robust and reliable design methods. New control strategies for improving the efficiency of sensor data processing and reducing associated time delay are presented. The coverage provided features: ·        an overall assessment of recent and current fault-tolerant control algorithms; ·        treatment of several issues arising at the junction of control and communications; ·        key concepts followed by their proofs and efficient computational methods for their implementation; and ·        simulation examples (including TrueTime simulations) to...

  10. Estimating genome-wide gene networks using nonparametric Bayesian network models on massively parallel computers.

    Science.gov (United States)

    Tamada, Yoshinori; Imoto, Seiya; Araki, Hiromitsu; Nagasaki, Masao; Print, Cristin; Charnock-Jones, D Stephen; Miyano, Satoru

    2011-01-01

    We present a novel algorithm to estimate genome-wide gene networks consisting of more than 20,000 genes from gene expression data using nonparametric Bayesian networks. Due to the difficulty of learning Bayesian network structures, existing algorithms cannot be applied to more than a few thousand genes. Our algorithm overcomes this limitation by repeatedly estimating subnetworks in parallel for genes selected by neighbor node sampling. Through numerical simulation, we confirmed that our algorithm outperformed a heuristic algorithm in a shorter time. We applied our algorithm to microarray data from human umbilical vein endothelial cells (HUVECs) treated with siRNAs, to construct a human genome-wide gene network, which we compared to a small gene network estimated for the genes extracted using a traditional bioinformatics method. The results showed that our genome-wide gene network contains many features of the small network, as well as others that could not be captured during the small network estimation. The results also revealed master-regulator genes that are not in the small network but that control many of the genes in the small network. These analyses were impossible to realize without our proposed algorithm.

  11. Vehicle Sideslip Angle Estimation Based on General Regression Neural Network

    Directory of Open Access Journals (Sweden)

    Wang Wei

    2016-01-01

    Full Text Available Aiming at the accuracy of estimation of vehicle’s mass center sideslip angle, an estimation method of slip angle based on general regression neural network (GRNN and driver-vehicle closed-loop system has been proposed: regarding vehicle’s sideslip angle as time series mapping of yaw speed and lateral acceleration; using homogeneous design project to optimize the training samples; building the mapping relationship among sideslip angle, yaw speed, and lateral acceleration; at the same time, using experimental method to measure vehicle’s sideslip angle to verify validity of this method. Estimation results of neural network and real vehicle experiment show the same changing tendency. The mean of error is within 10% of test result’s amplitude. Results show GRNN can estimate vehicle’s sideslip angle correctly. It can offer a reference to the application of vehicle’s stability control system on vehicle’s state estimation.

  12. Utilizing evolutionary information and gene expression data for estimating gene networks with bayesian network models.

    Science.gov (United States)

    Tamada, Yoshinori; Bannai, Hideo; Imoto, Seiya; Katayama, Toshiaki; Kanehisa, Minoru; Miyano, Satoru

    2005-12-01

    Since microarray gene expression data do not contain sufficient information for estimating accurate gene networks, other biological information has been considered to improve the estimated networks. Recent studies have revealed that highly conserved proteins that exhibit similar expression patterns in different organisms, have almost the same function in each organism. Such conserved proteins are also known to play similar roles in terms of the regulation of genes. Therefore, this evolutionary information can be used to refine regulatory relationships among genes, which are estimated from gene expression data. We propose a statistical method for estimating gene networks from gene expression data by utilizing evolutionarily conserved relationships between genes. Our method simultaneously estimates two gene networks of two distinct organisms, with a Bayesian network model utilizing the evolutionary information so that gene expression data of one organism helps to estimate the gene network of the other. We show the effectiveness of the method through the analysis on Saccharomyces cerevisiae and Homo sapiens cell cycle gene expression data. Our method was successful in estimating gene networks that capture many known relationships as well as several unknown relationships which are likely to be novel. Supplementary information is available at http://bonsai.ims.u-tokyo.ac.jp/~tamada/bayesnet/.

  13. A Comparison of Four-Step Model and Path Flow Estimator for Forecasting Network Flow: A Case Study of Cache County in Utah

    OpenAIRE

    Pedaballi, Siddareddy B.

    2006-01-01

    Development of alternative methodologies for travel demand modeling has become important in recent years due to the lack of resources for small and medium communities to adopt conventional four step travel models. Many researchers have proposed alternative tools of travel demand modeling for these communities. But majority of them still require large amount of data and technical sophistication. In this study, the Path Flow Estimator (PFE) is used to estimate the network traffic of Cache Co...

  14. Near real-time traffic routing

    Science.gov (United States)

    Yang, Chaowei (Inventor); Cao, Ying (Inventor); Xie, Jibo (Inventor); Zhou, Bin (Inventor)

    2012-01-01

    A near real-time physical transportation network routing system comprising: a traffic simulation computing grid and a dynamic traffic routing service computing grid. The traffic simulator produces traffic network travel time predictions for a physical transportation network using a traffic simulation model and common input data. The physical transportation network is divided into a multiple sections. Each section has a primary zone and a buffer zone. The traffic simulation computing grid includes multiple of traffic simulation computing nodes. The common input data includes static network characteristics, an origin-destination data table, dynamic traffic information data and historical traffic data. The dynamic traffic routing service computing grid includes multiple dynamic traffic routing computing nodes and generates traffic route(s) using the traffic network travel time predictions.

  15. Estimating the epidemic threshold on networks by deterministic connections

    Energy Technology Data Exchange (ETDEWEB)

    Li, Kezan, E-mail: lkzzr@sohu.com; Zhu, Guanghu [School of Mathematics and Computing Science, Guilin University of Electronic Technology, Guilin 541004 (China); Fu, Xinchu [Department of Mathematics, Shanghai University, Shanghai 200444 (China); Small, Michael [School of Mathematics and Statistics, The University of Western Australia, Crawley, Western Australia 6009 (Australia)

    2014-12-15

    For many epidemic networks some connections between nodes are treated as deterministic, while the remainder are random and have different connection probabilities. By applying spectral analysis to several constructed models, we find that one can estimate the epidemic thresholds of these networks by investigating information from only the deterministic connections. Nonetheless, in these models, generic nonuniform stochastic connections and heterogeneous community structure are also considered. The estimation of epidemic thresholds is achieved via inequalities with upper and lower bounds, which are found to be in very good agreement with numerical simulations. Since these deterministic connections are easier to detect than those stochastic connections, this work provides a feasible and effective method to estimate the epidemic thresholds in real epidemic networks.

  16. Factorized Estimation of Partially Shared Parameters in Diffusion Networks

    Czech Academy of Sciences Publication Activity Database

    Dedecius, Kamil; Sečkárová, Vladimíra

    2017-01-01

    Roč. 65, č. 19 (2017), s. 5153-5163 ISSN 1053-587X R&D Projects: GA ČR(CZ) GP14-06678P; GA ČR(CZ) GA16-09848S Institutional support: RVO:67985556 Keywords : Diffusion network * Diffusion estimation * Heterogeneous parameters * Multitask networks Subject RIV: BD - Theory of Information Impact factor: 4.300, year: 2016 http:// library .utia.cas.cz/separaty/2017/AS/dedecius-0477044.pdf

  17. CLEAR (Calculates Logical Evacuation And Response): A Generic Transportation Network Model for the Calculation of Evacuation Time Estimates

    Energy Technology Data Exchange (ETDEWEB)

    Moeller, M. P.; Urbanik, II, T.; Desrosiers, A. E.

    1982-03-01

    This paper describes the methodology and application of the computer model CLEAR (Calculates Logical Evacuation And Response) which estimates the time required for a specific population density and distribution to evacuate an area using a specific transportation network. The CLEAR model simulates vehicle departure and movement on a transportation network according to the conditions and consequences of traffic flow. These include handling vehicles at intersecting road segments, calculating the velocity of travel on a road segment as a function of its vehicle density, and accounting for the delay of vehicles in traffic queues. The program also models the distribution of times required by individuals to prepare for an evacuation. In order to test its accuracy, the CLEAR model was used to estimate evacuatlon tlmes for the emergency planning zone surrounding the Beaver Valley Nuclear Power Plant. The Beaver Valley site was selected because evacuation time estimates had previously been prepared by the licensee, Duquesne Light, as well as by the Federal Emergency Management Agency and the Pennsylvania Emergency Management Agency. A lack of documentation prevented a detailed comparison of the estimates based on the CLEAR model and those obtained by Duquesne Light. However, the CLEAR model results compared favorably with the estimates prepared by the other two agencies.

  18. Assembly and offset assignment scheme for self-similar traffic in optical burst switched networks

    CSIR Research Space (South Africa)

    Muwonge, KB

    2007-10-01

    Full Text Available are modelled as the burst duration, while the OFF periods are modelled as the offset times. Modelling OBS core traffic in this manner allows for a per channel flow modelling in DWDM wavelengths. Figure 1 shows the overall proposed LER traffic set...-up. Modelling OBS traffic as ON/OFF periods in DWDM conforms to the same distribution theory in Jackson queues. C. The burst queue In this section we develop several rules for the burst queue. Rule 1: After a BHP corresponding to a lower priority burst...

  19. Design and implementation of priority and time-window based traffic scheduling and routing-spectrum allocation mechanism in elastic optical networks

    Science.gov (United States)

    Wang, Honghuan; Xing, Fangyuan; Yin, Hongxi; Zhao, Nan; Lian, Bizhan

    2016-02-01

    With the explosive growth of network services, the reasonable traffic scheduling and efficient configuration of network resources have an important significance to increase the efficiency of the network. In this paper, an adaptive traffic scheduling policy based on the priority and time window is proposed and the performance of this algorithm is evaluated in terms of scheduling ratio. The routing and spectrum allocation are achieved by using the Floyd shortest path algorithm and establishing a node spectrum resource allocation model based on greedy algorithm, which is proposed by us. The fairness index is introduced to improve the capability of spectrum configuration. The results show that the designed traffic scheduling strategy can be applied to networks with multicast and broadcast functionalities, and makes them get real-time and efficient response. The scheme of node spectrum configuration improves the frequency resource utilization and gives play to the efficiency of the network.

  20. Estimation of the proteomic cancer co-expression sub networks by using association estimators.

    Science.gov (United States)

    Erdoğan, Cihat; Kurt, Zeyneb; Diri, Banu

    2017-01-01

    In this study, the association estimators, which have significant influences on the gene network inference methods and used for determining the molecular interactions, were examined within the co-expression network inference concept. By using the proteomic data from five different cancer types, the hub genes/proteins within the disease-associated gene-gene/protein-protein interaction sub networks were identified. Proteomic data from various cancer types is collected from The Cancer Proteome Atlas (TCPA). Correlation and mutual information (MI) based nine association estimators that are commonly used in the literature, were compared in this study. As the gold standard to measure the association estimators' performance, a multi-layer data integration platform on gene-disease associations (DisGeNET) and the Molecular Signatures Database (MSigDB) was used. Fisher's exact test was used to evaluate the performance of the association estimators by comparing the created co-expression networks with the disease-associated pathways. It was observed that the MI based estimators provided more successful results than the Pearson and Spearman correlation approaches, which are used in the estimation of biological networks in the weighted correlation network analysis (WGCNA) package. In correlation-based methods, the best average success rate for five cancer types was 60%, while in MI-based methods the average success ratio was 71% for James-Stein Shrinkage (Shrink) and 64% for Schurmann-Grassberger (SG) association estimator, respectively. Moreover, the hub genes and the inferred sub networks are presented for the consideration of researchers and experimentalists.

  1. Estimation of the proteomic cancer co-expression sub networks by using association estimators.

    Directory of Open Access Journals (Sweden)

    Cihat Erdoğan

    Full Text Available In this study, the association estimators, which have significant influences on the gene network inference methods and used for determining the molecular interactions, were examined within the co-expression network inference concept. By using the proteomic data from five different cancer types, the hub genes/proteins within the disease-associated gene-gene/protein-protein interaction sub networks were identified. Proteomic data from various cancer types is collected from The Cancer Proteome Atlas (TCPA. Correlation and mutual information (MI based nine association estimators that are commonly used in the literature, were compared in this study. As the gold standard to measure the association estimators' performance, a multi-layer data integration platform on gene-disease associations (DisGeNET and the Molecular Signatures Database (MSigDB was used. Fisher's exact test was used to evaluate the performance of the association estimators by comparing the created co-expression networks with the disease-associated pathways. It was observed that the MI based estimators provided more successful results than the Pearson and Spearman correlation approaches, which are used in the estimation of biological networks in the weighted correlation network analysis (WGCNA package. In correlation-based methods, the best average success rate for five cancer types was 60%, while in MI-based methods the average success ratio was 71% for James-Stein Shrinkage (Shrink and 64% for Schurmann-Grassberger (SG association estimator, respectively. Moreover, the hub genes and the inferred sub networks are presented for the consideration of researchers and experimentalists.

  2. Flood quantile estimation at ungauged sites by Bayesian networks

    Science.gov (United States)

    Mediero, L.; Santillán, D.; Garrote, L.

    2012-04-01

    Estimating flood quantiles at a site for which no observed measurements are available is essential for water resources planning and management. Ungauged sites have no observations about the magnitude of floods, but some site and basin characteristics are known. The most common technique used is the multiple regression analysis, which relates physical and climatic basin characteristic to flood quantiles. Regression equations are fitted from flood frequency data and basin characteristics at gauged sites. Regression equations are a rigid technique that assumes linear relationships between variables and cannot take the measurement errors into account. In addition, the prediction intervals are estimated in a very simplistic way from the variance of the residuals in the estimated model. Bayesian networks are a probabilistic computational structure taken from the field of Artificial Intelligence, which have been widely and successfully applied to many scientific fields like medicine and informatics, but application to the field of hydrology is recent. Bayesian networks infer the joint probability distribution of several related variables from observations through nodes, which represent random variables, and links, which represent causal dependencies between them. A Bayesian network is more flexible than regression equations, as they capture non-linear relationships between variables. In addition, the probabilistic nature of Bayesian networks allows taking the different sources of estimation uncertainty into account, as they give a probability distribution as result. A homogeneous region in the Tagus Basin was selected as case study. A regression equation was fitted taking the basin area, the annual maximum 24-hour rainfall for a given recurrence interval and the mean height as explanatory variables. Flood quantiles at ungauged sites were estimated by Bayesian networks. Bayesian networks need to be learnt from a huge enough data set. As observational data are reduced, a

  3. Exposure to Traffic-related Air Pollution During Pregnancy and Term Low Birth Weight: Estimation of Causal Associations in a Semiparametric Model

    Science.gov (United States)

    Padula, Amy M.; Mortimer, Kathleen; Hubbard, Alan; Lurmann, Frederick; Jerrett, Michael; Tager, Ira B.

    2012-01-01

    Traffic-related air pollution is recognized as an important contributor to health problems. Epidemiologic analyses suggest that prenatal exposure to traffic-related air pollutants may be associated with adverse birth outcomes; however, there is insufficient evidence to conclude that the relation is causal. The Study of Air Pollution, Genetics and Early Life Events comprises all births to women living in 4 counties in California's San Joaquin Valley during the years 2000–2006. The probability of low birth weight among full-term infants in the population was estimated using machine learning and targeted maximum likelihood estimation for each quartile of traffic exposure during pregnancy. If everyone lived near high-volume freeways (approximated as the fourth quartile of traffic density), the estimated probability of term low birth weight would be 2.27% (95% confidence interval: 2.16, 2.38) as compared with 2.02% (95% confidence interval: 1.90, 2.12) if everyone lived near smaller local roads (first quartile of traffic density). Assessment of potentially causal associations, in the absence of arbitrary model assumptions applied to the data, should result in relatively unbiased estimates. The current results support findings from previous studies that prenatal exposure to traffic-related air pollution may adversely affect birth weight among full-term infants. PMID:23045474

  4. Estimating functional brain networks by incorporating a modularity prior.

    Science.gov (United States)

    Qiao, Lishan; Zhang, Han; Kim, Minjeong; Teng, Shenghua; Zhang, Limei; Shen, Dinggang

    2016-11-01

    Functional brain network analysis has become one principled way of revealing informative organization architectures in healthy brains, and providing sensitive biomarkers for diagnosis of neurological disorders. Prior to any post hoc analysis, however, a natural issue is how to construct "ideal" brain networks given, for example, a set of functional magnetic resonance imaging (fMRI) time series associated with different brain regions. Although many methods have been developed, it is currently still an open field to estimate biologically meaningful and statistically robust brain networks due to our limited understanding of the human brain as well as complex noises in the observed data. Motivated by the fact that the brain is organized with modular structures, in this paper, we propose a novel functional brain network modeling scheme by encoding a modularity prior under a matrix-regularized network learning framework, and further formulate it as a sparse low-rank graph learning problem, which can be solved by an efficient optimization algorithm. Then, we apply the learned brain networks to identify patients with mild cognitive impairment (MCI) from normal controls. We achieved 89.01% classification accuracy even with a simple feature selection and classification pipeline, which significantly outperforms the conventional brain network construction methods. Moreover, we further explore brain network features that contributed to MCI identification, and discovered potential biomarkers for personalized diagnosis. Copyright © 2016 Elsevier Inc. All rights reserved.

  5. A Best Effort Traffic Management Solution for Server and Agent-Based Active Network Management (SAAM)

    Science.gov (United States)

    2002-03-01

    14 c. Link State Protocols ............................................................... 14 2. Interdomain Routing...Shortest Widest Least Congested Path (SWLCP) ................. 38 4. Traffic Splitting...c. Reversion Interval .................................................................. 43 d. Congestion Bypass Time

  6. Analysis of traffic state variation patterns for urban road network based on spectral clustering

    National Research Council Canada - National Science Library

    Yang, Senyan; Wu, Jianping; Qi, Geqi; Tian, Kun

    2017-01-01

    ... on section-based traffic speed dataset. The proposed method transforms traditional clustering problems into graph partition problems, which is suitable for the clustering problems with multiple attributes by dimension reduction...

  7. Agent-based traffic management and reinforcement learning in congested intersection network.

    Science.gov (United States)

    2012-08-01

    This study evaluates the performance of traffic control systems based on reinforcement learning (RL), also called approximate dynamic programming (ADP). Two algorithms have been selected for testing: 1) Q-learning and 2) approximate dynamic programmi...

  8. Estimating topological properties of weighted networks from limited information.

    Science.gov (United States)

    Cimini, Giulio; Squartini, Tiziano; Gabrielli, Andrea; Garlaschelli, Diego

    2015-10-01

    A problem typically encountered when studying complex systems is the limitedness of the information available on their topology, which hinders our understanding of their structure and of the dynamical processes taking place on them. A paramount example is provided by financial networks, whose data are privacy protected: Banks publicly disclose only their aggregate exposure towards other banks, keeping individual exposures towards each single bank secret. Yet, the estimation of systemic risk strongly depends on the detailed structure of the interbank network. The resulting challenge is that of using aggregate information to statistically reconstruct a network and correctly predict its higher-order properties. Standard approaches either generate unrealistically dense networks, or fail to reproduce the observed topology by assigning homogeneous link weights. Here, we develop a reconstruction method, based on statistical mechanics concepts, that makes use of the empirical link density in a highly nontrivial way. Technically, our approach consists in the preliminary estimation of node degrees from empirical node strengths and link density, followed by a maximum-entropy inference based on a combination of empirical strengths and estimated degrees. Our method is successfully tested on the international trade network and the interbank money market, and represents a valuable tool for gaining insights on privacy-protected or partially accessible systems.

  9. Estimating topological properties of weighted networks from limited information

    Science.gov (United States)

    Gabrielli, Andrea; Cimini, Giulio; Garlaschelli, Diego; Squartini, Angelo

    A typical problem met when studying complex systems is the limited information available on their topology, which hinders our understanding of their structural and dynamical properties. A paramount example is provided by financial networks, whose data are privacy protected. Yet, the estimation of systemic risk strongly depends on the detailed structure of the interbank network. The resulting challenge is that of using aggregate information to statistically reconstruct a network and correctly predict its higher-order properties. Standard approaches either generate unrealistically dense networks, or fail to reproduce the observed topology by assigning homogeneous link weights. Here we develop a reconstruction method, based on statistical mechanics concepts, that exploits the empirical link density in a highly non-trivial way. Technically, our approach consists in the preliminary estimation of node degrees from empirical node strengths and link density, followed by a maximum-entropy inference based on a combination of empirical strengths and estimated degrees. Our method is successfully tested on the international trade network and the interbank money market, and represents a valuable tool for gaining insights on privacy-protected or partially accessible systems. Acknoweledgement to ``Growthcom'' ICT - EC project (Grant No: 611272) and ``Crisislab'' Italian Project.

  10. Particle filter-based real-time estimation and prediction of traffic conditions. In: Christos H. Skiadas (Ed.), Recent Advances in Stochastic Modelling and Data Analysis

    OpenAIRE

    Sau, J.; EL-FAOUZI, NE; BEN-AISSA, A; DE MOUZON, O

    2007-01-01

    Real-time estimation and short-term prediction of traffic conditions is one of major concern of traffic managers and ITS-oriented systems. Model-based methods appear now as very promising ways in order to reach this purpose. Such methods are already used in process control (Kalman filtering, Luenberger observers). In the application presented in this paper, due to the high non linearity of the traffic models, particle filter (PF) approach is applied in combination with the well-known first or...

  11. Estimation of blood flow rates in large microvascular networks.

    Science.gov (United States)

    Fry, Brendan C; Lee, Jack; Smith, Nicolas P; Secomb, Timothy W

    2012-08-01

    Recent methods for imaging microvascular structures provide geometrical data on networks containing thousands of segments. Prediction of functional properties, such as solute transport, requires information on blood flow rates also, but experimental measurement of many individual flows is difficult. Here, a method is presented for estimating flow rates in a microvascular network based on incomplete information on the flows in the boundary segments that feed and drain the network. With incomplete boundary data, the equations governing blood flow form an underdetermined linear system. An algorithm was developed that uses independent information about the distribution of wall shear stresses and pressures in microvessels to resolve this indeterminacy, by minimizing the deviation of pressures and wall shear stresses from target values. The algorithm was tested using previously obtained experimental flow data from four microvascular networks in the rat mesentery. With two or three prescribed boundary conditions, predicted flows showed relatively small errors in most segments and fewer than 10% incorrect flow directions on average. The proposed method can be used to estimate flow rates in microvascular networks, based on incomplete boundary data, and provides a basis for deducing functional properties of microvessel networks. © 2012 John Wiley & Sons Ltd.

  12. Parameter estimation of an aeroelastic aircraft using neural networks

    Indian Academy of Sciences (India)

    Application of neural networks to the problem of aerodynamic modelling and parameter estimation for aeroelastic aircraft is addressed. A neural model capable of predicting generalized force and moment coefficients using measured motion and control variables only, without any need for conventional normal elastic ...

  13. Voltage Estimation in Active Distribution Grids Using Neural Networks

    DEFF Research Database (Denmark)

    Pertl, Michael; Heussen, Kai; Gehrke, Oliver

    2016-01-01

    the observability of distribution systems has to be improved. To increase the situational awareness of the power system operator data driven methods can be employed. These methods benefit from newly available data sources such as smart meters. This paper presents a voltage estimation method based on neural networks...

  14. Iterative Available Bandwidth Estimation for Mobile Transport Networks

    DEFF Research Database (Denmark)

    Ubeda Castellanos, Carlos; López Villa, Dimas; Teyeb, Oumer Mohammed

    2007-01-01

    Available bandwidth estimation has lately been proposed to be used for end-to-end resource management in existing and emerging mobile communication systems, whose transport networks could end up being the bottleneck rather than the air interface. Algorithms for admission control, handover...

  15. Energy parameter estimation in solar powered wireless sensor networks

    KAUST Repository

    Mousa, Mustafa

    2014-02-24

    The operation of solar powered wireless sensor networks is associated with numerous challenges. One of the main challenges is the high variability of solar power input and battery capacity, due to factors such as weather, humidity, dust and temperature. In this article, we propose a set of tools that can be implemented onboard high power wireless sensor networks to estimate the battery condition and capacity as well as solar power availability. These parameters are very important to optimize sensing and communications operations and maximize the reliability of the complete system. Experimental results show that the performance of typical Lithium Ion batteries severely degrades outdoors in a matter of weeks or months, and that the availability of solar energy in an urban solar powered wireless sensor network is highly variable, which underlines the need for such power and energy estimation algorithms.

  16. Satellite-based estimates of reduced CO and CO2 emissions due to traffic restrictions during the 2008 Beijing Olympics

    Science.gov (United States)

    Worden, Helen M.; Cheng, Yafang; Pfister, Gabriele; Carmichael, Gregory R.; Zhang, Qiang; Streets, David G.; Deeter, Merritt; Edwards, David P.; Gille, John C.; Worden, John R.

    2012-07-01

    During the 2008 Olympics, the Chinese government made a significant effort to improve air quality in Beijing, including restrictions on traffic. Here we estimate the reductions in carbon monoxide (CO) and carbon dioxide (CO2) emissions resulting from the control measures on Beijing transportation. Using MOPITT (Measurements Of Pollution In The Troposphere) multispectral satellite observations of near-surface CO along with WRF-Chem (Weather Research and Forecasting model with Chemistry) simulations for Beijing during August, 2007 and 2008, we estimate changes in CO due to meteorology and transportation sector emissions. Applying a reported CO/CO2 emission ratio for fossil fuels, we find the corresponding reduction in CO2, 60 ± 36 Gg[CO2]/day. As compared to emission scenarios being considered for the IPCC AR5 (Intergovernmental Panel on Climate Change, 5th Assessment Report), this result suggests that urban traffic controls on the Beijing Olympics scale could play a significant role in meeting target reductions for global CO2 emissions.

  17. Age estimation of facial image based on convolution neural network

    Science.gov (United States)

    Meng, Xiaodong; Wang, Yifeng; Zheng, Haihong

    2017-07-01

    Age is an inherent biological characteristic of human and is reflected in facial images to a certain extent. A method for estimating age from a facial image by combining CNN (Convolution Neural Network) with SVR (Support Vector Regression) is proposed. First, a deep CNN is trained to automatically extract age features from facial images and classify them into variant age groups. Then different SVRs are trained for each age group to estimate the age of a facial image. The experimental results show that a lower MAE (Mean Absolute Error) of age estimation on MORPH database is obtained.

  18. Distributed estimation based on observations prediction in wireless sensor networks

    KAUST Repository

    Bouchoucha, Taha

    2015-03-19

    We consider wireless sensor networks (WSNs) used for distributed estimation of unknown parameters. Due to the limited bandwidth, sensor nodes quantize their noisy observations before transmission to a fusion center (FC) for the estimation process. In this letter, the correlation between observations is exploited to reduce the mean-square error (MSE) of the distributed estimation. Specifically, sensor nodes generate local predictions of their observations and then transmit the quantized prediction errors (innovations) to the FC rather than the quantized observations. The analytic and numerical results show that transmitting the innovations rather than the observations mitigates the effect of quantization noise and hence reduces the MSE. © 2015 IEEE.

  19. Golden Ratio Genetic Algorithm Based Approach for Modelling and Analysis of the Capacity Expansion of Urban Road Traffic Network

    Directory of Open Access Journals (Sweden)

    Lun Zhang

    2015-01-01

    Full Text Available This paper presents the modelling and analysis of the capacity expansion of urban road traffic network (ICURTN. Thebilevel programming model is first employed to model the ICURTN, in which the utility of the entire network is maximized with the optimal utility of travelers’ route choice. Then, an improved hybrid genetic algorithm integrated with golden ratio (HGAGR is developed to enhance the local search of simple genetic algorithms, and the proposed capacity expansion model is solved by the combination of the HGAGR and the Frank-Wolfe algorithm. Taking the traditional one-way network and bidirectional network as the study case, three numerical calculations are conducted to validate the presented model and algorithm, and the primary influencing factors on extended capacity model are analyzed. The calculation results indicate that capacity expansion of road network is an effective measure to enlarge the capacity of urban road network, especially on the condition of limited construction budget; the average computation time of the HGAGR is 122 seconds, which meets the real-time demand in the evaluation of the road network capacity.

  20. Path capacity estimation in heterogeneous, best-effort, small-scale IP networks

    NARCIS (Netherlands)

    Delphinanto, A.; Koonen, T.; Zhang, S.; Den Hartog, F.

    2010-01-01

    Current QoS solutions for IP networks are usually based on traffic classification and need to be supported by every device in the end-to-end path to be effective. This is relatively expensive for home networks. Alternative techniques have been proposed that require end-user services to pragmatically

  1. Estimating Ads’ Click through Rate with Recurrent Neural Network

    Directory of Open Access Journals (Sweden)

    Chen Qiao-Hong

    2016-01-01

    Full Text Available With the development of the Internet, online advertising spreads across every corner of the world, the ads' click through rate (CTR estimation is an important method to improve the online advertising revenue. Compared with the linear model, the nonlinear models can study much more complex relationships between a large number of nonlinear characteristics, so as to improve the accuracy of the estimation of the ads’ CTR. The recurrent neural network (RNN based on Long-Short Term Memory (LSTM is an improved model of the feedback neural network with ring structure. The model overcomes the problem of the gradient of the general RNN. Experiments show that the RNN based on LSTM exceeds the linear models, and it can effectively improve the estimation effect of the ads’ click through rate.

  2. An RSS based location estimation technique for cognitive relay networks

    KAUST Repository

    Qaraqe, Khalid A.

    2010-11-01

    In this paper, a received signal strength (RSS) based location estimation method is proposed for a cooperative wireless relay network where the relay is a cognitive radio. We propose a method for the considered cognitive relay network to determine the location of the source using the direct and the relayed signal at the destination. We derive the Cramer-Rao lower bound (CRLB) expressions separately for x and y coordinates of the location estimate. We analyze the effects of cognitive behaviour of the relay on the performance of the proposed method. We also discuss and quantify the reliability of the location estimate using the proposed technique if the source is not stationary. The overall performance of the proposed method is presented through simulations. ©2010 IEEE.

  3. Using arborescences to estimate hierarchicalness in directed complex networks

    Science.gov (United States)

    2018-01-01

    Complex networks are a useful tool for the understanding of complex systems. One of the emerging properties of such systems is their tendency to form hierarchies: networks can be organized in levels, with nodes in each level exerting control on the ones beneath them. In this paper, we focus on the problem of estimating how hierarchical a directed network is. We propose a structural argument: a network has a strong top-down organization if we need to delete only few edges to reduce it to a perfect hierarchy—an arborescence. In an arborescence, all edges point away from the root and there are no horizontal connections, both characteristics we desire in our idealization of what a perfect hierarchy requires. We test our arborescence score in synthetic and real-world directed networks against the current state of the art in hierarchy detection: agony, flow hierarchy and global reaching centrality. These tests highlight that our arborescence score is intuitive and we can visualize it; it is able to better distinguish between networks with and without a hierarchical structure; it agrees the most with the literature about the hierarchy of well-studied complex systems; and it is not just a score, but it provides an overall scheme of the underlying hierarchy of any directed complex network. PMID:29381761

  4. Convolutional neural networks for estimating spatially distributed evapotranspiration

    Science.gov (United States)

    García-Pedrero, Angel M.; Gonzalo-Martín, Consuelo; Lillo-Saavedra, Mario F.; Rodriguéz-Esparragón, Dionisio; Menasalvas, Ernestina

    2017-10-01

    Efficient water management in agriculture requires an accurate estimation of evapotranspiration (ET). There are available several balance energy surface models that provide a daily ET estimation (ETd) spatially and temporarily distributed for different crops over wide areas. These models need infrared thermal spectral band (gathered from remotely sensors) to estimate sensible heat flux from the surface temperature. However, this spectral band is not available for most current operational remote sensors. Even though the good results provided by machine learning (ML) methods in many different areas, few works have applied these approaches for forecasting distributed ETd on space and time when aforementioned information is missing. However, these methods do not exploit the land surface characteristics and the relationships among land covers producing estimation errors. In this work, we have developed and evaluated a methodology that provides spatial distributed estimates of ETd without thermal information by means of Convolutional Neural Networks.

  5. Estimating the Capacity of Urban Transportation Networks with an Improved Sensitivity Based Method

    Directory of Open Access Journals (Sweden)

    Muqing Du

    2015-01-01

    Full Text Available The throughput of a given transportation network is always of interest to the traffic administrative department, so as to evaluate the benefit of the transportation construction or expansion project before its implementation. The model of the transportation network capacity formulated as a mathematic programming with equilibrium constraint (MPEC well defines this problem. For practical applications, a modified sensitivity analysis based (SAB method is developed to estimate the solution of this bilevel model. The high-efficient origin-based (OB algorithm is extended for the precise solution of the combined model which is integrated in the network capacity model. The sensitivity analysis approach is also modified to simplify the inversion of the Jacobian matrix in large-scale problems. The solution produced in every iteration of SAB is restrained to be feasible to guarantee the success of the heuristic search. From the numerical experiments, the accuracy of the derivatives for the linear approximation could significantly affect the converging of the SAB method. The results also show that the proposed method could obtain good suboptimal solutions from different starting points in the test examples.

  6. Estimating the stochastic bifurcation structure of cellular networks.

    Directory of Open Access Journals (Sweden)

    Carl Song

    2010-03-01

    Full Text Available High throughput measurement of gene expression at single-cell resolution, combined with systematic perturbation of environmental or cellular variables, provides information that can be used to generate novel insight into the properties of gene regulatory networks by linking cellular responses to external parameters. In dynamical systems theory, this information is the subject of bifurcation analysis, which establishes how system-level behaviour changes as a function of parameter values within a given deterministic mathematical model. Since cellular networks are inherently noisy, we generalize the traditional bifurcation diagram of deterministic systems theory to stochastic dynamical systems. We demonstrate how statistical methods for density estimation, in particular, mixture density and conditional mixture density estimators, can be employed to establish empirical bifurcation diagrams describing the bistable genetic switch network controlling galactose utilization in yeast Saccharomyces cerevisiae. These approaches allow us to make novel qualitative and quantitative observations about the switching behavior of the galactose network, and provide a framework that might be useful to extract information needed for the development of quantitative network models.

  7. Energy-efficient multicast traffic grooming strategy based on light-tree splitting for elastic optical networks

    Science.gov (United States)

    Liu, Huanlin; Yin, Yarui; Chen, Yong

    2017-07-01

    In order to address the problem of optimizing the spectrum resources and power consumption in elastic optical networks (EONs), we investigate the potential gains by jointly employing the light-tree splitting and traffic grooming for multicast requests. An energy-efficient multicast traffic grooming strategy based on light-tree splitting (EED-MTGS-LS) is proposed in this paper. Firstly, we design a traffic pre-processing mechanism to decide the multicast requests' routing order, which considers the request's bandwidth requirement and physical hops synthetically. Then, by dividing a light-tree to some sub-light-trees and grooming the request to these sub-light-trees, the light-tree sharing ratios of multicast requests can be improved. What's more, a priority scheduling vector is constructed, which aims to improve the success rate of spectrum assignment for grooming requests. Finally, a grooming strategy is designed to optimize the total power consumption by reducing the use of transponders and IP routers during routing. Simulation results show that the proposed strategy can significantly improve the spectrum utilization and save the power consumption.

  8. Influence of traffic on build-up of polycyclic aromatic hydrocarbons on urban road surfaces: A Bayesian network modelling approach.

    Science.gov (United States)

    Li, Yingxia; Jia, Ziliang; Wijesiri, Buddhi; Song, Ningning; Goonetilleke, Ashantha

    2017-12-04

    Due to their carcinogenic effects, Polycyclic Aromatic Hydrocarbons (PAHs) deposited on urban surfaces are a major concern in the context of stormwater pollution. However, the design of effective pollution mitigation strategies is challenging due to the lack of reliability in stormwater quality modelling outcomes. Current modelling approaches do not adequately replicate the interdependencies between pollutant processes and their influential factors. Using Bayesian Network modelling, this research study characterised the influence of vehicular traffic on the build-up of the sixteen US EPA classified priority PAHs. The predictive analysis was conditional on the structure of the proposed BN, which can be further improved by including more variables. This novel modelling approach facilitated the characterisation of the influence of traffic as a source of origin and also as a key factor that influences the re-distribution of PAHs, with positive or negative relationship between traffic volume and PAH build-up. It was evident that the re-distribution of particle-bound PAHs is determined by the particle size rather than the chemical characteristics such as volatility. Moreover, compared to commercial and residential land uses, mostly industrial land use contributes to the PAHs load released to the environment. Carcinogenic PAHs in industrial areas are likely to be associated with finer particles, while PAHs, which are not classified as human carcinogens, are likely to be found in the coarser particle fraction. Copyright © 2017 Elsevier Ltd. All rights reserved.

  9. An Improved Convolutional Neural Network on Crowd Density Estimation

    Directory of Open Access Journals (Sweden)

    Pan Shao-Yun

    2016-01-01

    Full Text Available In this paper, a new method is proposed for crowd density estimation. An improved convolutional neural network is combined with traditional texture feature. The data calculated by the convolutional layer can be treated as a new kind of features.So more useful information of images can be extracted by different features.In the meantime, the size of image has little effect on the result of convolutional neural network. Experimental results indicate that our scheme has adequate performance to allow for its use in real world applications.

  10. Rare event estimation for a large-scale stochastic hybrid system with air traffic application

    NARCIS (Netherlands)

    Blom, Henk A.P.; Bakker, G.J. (Bert); Krystul, J.; Rubino, G.; Tuffin, B.

    Embedding of rare event estimation theory within a stochastic analysis framework has recently led to signi��?cant novel results in rare event estimation for a diffusion process using sequential MC simulation. This chapter presents this rare event estimation theory for diffusions to a Stochastic

  11. Precipitation Estimation from Remotely Sensed Data Using Deep Neural Network

    Science.gov (United States)

    Tao, Y.; Gao, X.; Hsu, K. L.; Sorooshian, S.; Ihler, A.

    2015-12-01

    This research develops a precipitation estimation system from remote sensed data using state-of-the-art machine learning algorithms. Compared to ground-based precipitation measurements, satellite-based precipitation estimation products have advantages of temporal resolution and spatial coverage. Also, the massive amount of satellite data contains various measures related to precipitation formation and development. On the other hand, deep learning algorithms were newly developed in the area of machine learning, which was a breakthrough to deal with large and complex dataset, especially to image data. Here, we attempt to engage deep learning techniques to provide hourly precipitation estimation from satellite information, such as long wave infrared data. The brightness temperature data from infrared data is considered to contain cloud information. Radar stage IV dataset is used as ground measurement for parameter calibration. Stacked denoising auto-encoders (SDAE) is applied here to build a 4-layer neural network with 1000 hidden nodes for each hidden layer. SDAE involves two major steps: (1) greedily pre-training each layer as a denoising auto-encoder using the outputs of previous trained hidden layer output starting from visible layer to initialize parameters; (2) fine-tuning the whole deep neural network with supervised criteria. The results are compared with satellite precipitation product PERSIANN-CCS (Precipitation Estimation from Remotely Sensed Imagery using an Artificial Neural Network Cloud Classification System). Based on the results, we have several valuable conclusions: By properly training the neural network, it is able to extract useful information for precipitation estimation. For example, it can reduce the mean squared error of the precipitation by 58% for the summer season in the central United States of the validation period. The SDAE method captures the shape of the precipitation from the cloud shape better compared to the CCS product. Design of

  12. An optimal general type-2 fuzzy controller for Urban Traffic Network

    DEFF Research Database (Denmark)

    Khooban, Mohammad Hassan; Vafamand, Navid; Liaghat, Alireza

    2017-01-01

    , a combination of the general type-2 fuzzy logic sets and the Modified Backtracking Search Algorithm (MBSA) techniques are used in order to control the traffic signal scheduling and phase succession so as to guarantee a smooth flow of traffic with the least wait times and average queue length. The parameters...... of input and output membership functions are optimized simultaneously by the novel heuristic algorithm MBSA. A comparison is made between the achieved results with those of optimal and conventional type-1 fuzzy logic controllers....

  13. Assessment of potential improvements on regional air quality modelling related with implementation of a detailed methodology for traffic emission estimation.

    Science.gov (United States)

    Coelho, Margarida C; Fontes, Tânia; Bandeira, Jorge M; Pereira, Sérgio R; Tchepel, Oxana; Dias, Daniela; Sá, Elisa; Amorim, Jorge H; Borrego, Carlos

    2014-02-01

    The accuracy and precision of air quality models are usually associated with the emission inventories. Thus, in order to assess if there are any improvements on air quality regional simulations using detailed methodology of road traffic emission estimation, a regional air quality modelling system was applied. For this purpose, a combination of top-down and bottom-up approaches was used to build an emission inventory. To estimate the road traffic emissions, the bottom-up approach was applied using an instantaneous emission model (Vehicle Specific Power - VSP methodology), and an average emission model (CORINAIR methodology), while for the remaining activity sectors the top-down approach was used. Weather Research and Forecasting (WRF) and Comprehensive Air quality (CAMx) models were selected to assess two emission scenarios: (i) scenario 1, which includes the emissions from the top-down approach; and (ii) scenario 2, which includes the emissions resulting from integration of top-down and bottom-up approaches. The results show higher emission values for PM10, NOx and HC, for scenario 1, and an inverse behaviour to CO. The highest differences between these scenarios were observed for PM10 and HC, about 55% and 75% higher (respectively for each pollutant) than emissions provided by scenario 2. This scenario gives better results for PM10, CO and O3. For NO2 concentrations better results were obtained with scenario 1. Thus, the results obtained suggest that with the combination of the top-down and bottom-up approaches to emission estimation several improvements in the air quality results can be achieved, mainly for PM10, CO and O3. © 2013 Elsevier B.V. All rights reserved.

  14. Use of high-scale traffic modeling to estimate road vehicle emissions of CO2 and impact on the atmospheric concentration in São Paulo, Brazil.

    Science.gov (United States)

    Miranda, R. M.; Perez-Martinez, P.; Andrade, M. D. F.

    2015-12-01

    Adequate estimations of motor vehicle CO2 emission inventories at high spatial and temporal urban scales are needed to establish transport policy measures aim to reduce climate change impacts from global cities. The Metropolitan Region of São Paulo (MRSP) is impacted by the emission of 7 million vehicles (97% light-duty gasoline vehicles LDVs and 3% heavy-duty diesel vehicles HDVs) and several environmental programs were implemented to reduce the emissions. Inventories match site measurements and remote sensing and help to assess the real impact of road vehicle emissions on city's air quality. In this paper we presented a high-resolution vehicle-based inventory of motor CO2 emissions mapped at a scale of 100 m and 1 hour. We used origin and destination (O/D) transport area zone trips from the mobility survey of the São Paulo Transport Metropolitan Company (Metro), a road network of the region and traffic datasets from the São Paulo Transport Engineering Company (CET). The inventory was done individually for LDVs and HDVs for the years 2008 and 2013 and was complemented with air quality datasets from the State Environmental Company (CETESB), together with census data from the Brazilian Institute of Geography and Statistics (IBGE). Our inventory showed partial disagreement with the São Paulo State's GHG inventory, caused by the different approach used - bottom vs. top down - and characteristic spatial and temporal biases of the population inputs used (different emission factors). Higher concentrations became apparent near the road-network at the spatial scale used. The total emissions were estimated in 20,781 million tons per year of CO2eq (83.7% by LDVs and 16.3% HDVs). Temporal profiles - diurnal, weekly and monthly - in vehicle emission distributions were calculated using CET's traffic counts and surrogates of congestion. These profiles were compared with average road-site measurements of CO2 for the year 2013. Measurements showed two peaks associated to the

  15. A Simplified Approach to Estimate the Urban Expressway Capacity after Traffic Accidents Using a Micro-Simulation Model

    Directory of Open Access Journals (Sweden)

    Hong Chen

    2013-01-01

    Full Text Available Based on the decomposition of the evolution processes of the urban expressway capacity after traffic accidents and the influence factors analysis, an approach for estimating the capacity has been proposed. Firstly, the approach introduces the Decision Tree ID algorithm, solves the accident delay time of different accident types by the Information Gain Value, and determines congestion dissipation time by the Traffic Flow Wave Theory. Secondly, taking the accident delay time as the observation cycle, the maximum number of the vehicles through the accident road per unit time was considered as its capacity. Finally, the attenuation simulation of the capacity for different accident types was calculated by the VISSIM software. The simulation results suggest that capacity attenuation of vehicle anchor is minimal and the rate is 30.074%; the next is vehicles fire, rear-end, and roll-over, and the rate is 38.389%, 40.204%, and 43.130%, respectively; the capacity attenuation of vehicle collision is the largest, and the rate is 50.037%. Moreover, the further research shows that the accident delay time is proportional to congestion dissipation time, time difference, and the ratio between them, but it is an inverse relationship with the residual capacity of urban expressway.

  16. pathChirp: Efficient Available Bandwidth Estimation for Network Paths

    Energy Technology Data Exchange (ETDEWEB)

    Cottrell, Les

    2003-04-30

    This paper presents pathChirp, a new active probing tool for estimating the available bandwidth on a communication network path. Based on the concept of ''self-induced congestion,'' pathChirp features an exponential flight pattern of probes we call a chirp. Packet chips offer several significant advantages over current probing schemes based on packet pairs or packet trains. By rapidly increasing the probing rate within each chirp, pathChirp obtains a rich set of information from which to dynamically estimate the available bandwidth. Since it uses only packet interarrival times for estimation, pathChirp does not require synchronous nor highly stable clocks at the sender and receiver. We test pathChirp with simulations and Internet experiments and find that it provides good estimates of the available bandwidth while using only a fraction of the number of probe bytes that current state-of-the-art techniques use.

  17. Distributed estimation for adaptive sensor selection in wireless sensor networks

    Science.gov (United States)

    Mahmoud, Magdi S.; Hassan Hamid, Matasm M.

    2014-05-01

    Wireless sensor networks (WSNs) are usually deployed for monitoring systems with the distributed detection and estimation of sensors. Sensor selection in WSNs is considered for target tracking. A distributed estimation scenario is considered based on the extended information filter. A cost function using the geometrical dilution of precision measure is derived for active sensor selection. A consensus-based estimation method is proposed in this paper for heterogeneous WSNs with two types of sensors. The convergence properties of the proposed estimators are analyzed under time-varying inputs. Accordingly, a new adaptive sensor selection (ASS) algorithm is presented in which the number of active sensors is adaptively determined based on the absolute local innovations vector. Simulation results show that the tracking accuracy of the ASS is comparable to that of the other algorithms.

  18. An artificial neural network for estimating haplotype frequencies.

    Science.gov (United States)

    Cartier, Kevin C; Baechle, Daniel

    2005-12-30

    The problem of estimating haplotype frequencies from population data has been considered by numerous investigators, resulting in a wide variety of possible algorithmic and statistical solutions. We propose a relatively unique approach that employs an artificial neural network (ANN) to predict the most likely haplotype frequencies from a sample of population genotype data. Through an innovative ANN design for mapping genotype patterns to diplotypes, we have produced a prototype that demonstrates the feasibility of this approach, with provisional results that correlate well with estimates produced by the expectation maximization algorithm for haplotype frequency estimation. Given the computational demands of estimating haplotype frequencies for 20 or more single-nucleotide polymorphisms, the ANN approach is promising because its design fits well with parallel computing architectures.

  19. Estimation of missing water-level data for the Everglades Depth Estimation Network (EDEN), 2013 update

    Science.gov (United States)

    Petkewich, Matthew D.; Conrads, Paul

    2013-01-01

    The Everglades Depth Estimation Network is an integrated network of real-time water-level gaging stations, a ground-elevation model, and a water-surface elevation model designed to provide scientists, engineers, and water-resource managers with water-level and water-depth information (1991-2013) for the entire freshwater portion of the Greater Everglades. The U.S. Geological Survey Greater Everglades Priority Ecosystems Science provides support for the Everglades Depth Estimation Network in order for the Network to provide quality-assured monitoring data for the U.S. Army Corps of Engineers Comprehensive Everglades Restoration Plan. In a previous study, water-level estimation equations were developed to fill in missing data to increase the accuracy of the daily water-surface elevation model. During this study, those equations were updated because of the addition and removal of water-level gaging stations, the consistent use of water-level data relative to the North American Vertical Datum of 1988, and availability of recent data (March 1, 2006, to September 30, 2011). Up to three linear regression equations were developed for each station by using three different input stations to minimize the occurrences of missing data for an input station. Of the 667 water-level estimation equations developed to fill missing data at 223 stations, more than 72 percent of the equations have coefficients of determination greater than 0.90, and 97 percent have coefficients of determination greater than 0.70.

  20. Robust state estimation for stochastic genetic regulatory networks

    Science.gov (United States)

    Liang, Jinling; Lam, James

    2010-01-01

    In this article, the state estimation problem is investigated for genetic regulatory networks (GRNs) with parameter uncertainties and stochastic disturbances. To account for the unavoidable modelling errors and parameter fluctuations, the network parameters are assumed to be time-varying but norm-bounded. Furthermore, scalar multiplicative white noises are introduced into both the translation process and the feedback regulation process in order to reflect the inherent intracellular and extracellular noise perturbations. The purpose of the addressed problem is to design a linear state estimator that can estimate the true concentration of the mRNA and the protein of the uncertain GRNs. By resorting to the Lyapunov-Krasovskii functional method combined with the linear matrix inequality (LMI) technique, sufficient conditions are first established for ensuring the stochastic stability of the dynamics of the estimation error, and the estimator gains are then designed in terms of the solutions to some LMIs that can be easily solved by using the standard numerical software. A three-node GRN is presented to show the effectiveness of the proposed design procedures.

  1. Channel estimation for physical layer network coding systems

    CERN Document Server

    Gao, Feifei; Wang, Gongpu

    2014-01-01

    This SpringerBrief presents channel estimation strategies for the physical later network coding (PLNC) systems. Along with a review of PLNC architectures, this brief examines new challenges brought by the special structure of bi-directional two-hop transmissions that are different from the traditional point-to-point systems and unidirectional relay systems. The authors discuss the channel estimation strategies over typical fading scenarios, including frequency flat fading, frequency selective fading and time selective fading, as well as future research directions. Chapters explore the performa

  2. Evaluating the effects of traffic noise on reaction time and rate of error in drivers′ movement time estimation

    Directory of Open Access Journals (Sweden)

    Iraj Alimohammadi

    2015-01-01

    Conclusion: The results suggest that traffic noise may be associated with poorer mental processing, which can result in longer RT during driving. Therefore, traffic noise would expose drivers to consequent accidents and incidents.

  3. Artificial neural networks for stiffness estimation in magnetic resonance elastography.

    Science.gov (United States)

    Murphy, Matthew C; Manduca, Armando; Trzasko, Joshua D; Glaser, Kevin J; Huston, John; Ehman, Richard L

    2017-11-28

    To investigate the feasibility of using artificial neural networks to estimate stiffness from MR elastography (MRE) data. Artificial neural networks were fit using model-based training patterns to estimate stiffness from images of displacement using a patch size of ∼1 cm in each dimension. These neural network inversions (NNIs) were then evaluated in a set of simulation experiments designed to investigate the effects of wave interference and noise on NNI accuracy. NNI was also tested in vivo, comparing NNI results against currently used methods. In 4 simulation experiments, NNI performed as well or better than direct inversion (DI) for predicting the known stiffness of the data. Summary NNI results were also shown to be significantly correlated with DI results in the liver (R 2  = 0.974) and in the brain (R 2  = 0.915), and also correlated with established biological effects including fibrosis stage in the liver and age in the brain. Finally, repeatability error was lower in the brain using NNI compared to DI, and voxel-wise modeling using NNI stiffness maps detected larger effects than using DI maps with similar levels of smoothing. Artificial neural networks represent a new approach to inversion of MRE data. Summary results from NNI and DI are highly correlated and both are capable of detecting biologically relevant signals. Preliminary evidence suggests that NNI stiffness estimates may be more resistant to noise than an algebraic DI approach. Taken together, these results merit future investigation into NNIs to improve the estimation of stiffness in small regions. Magn Reson Med, 2017. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

  4. An artificial neural network for estimating haplotype frequencies

    OpenAIRE

    Baechle Daniel; Cartier Kevin C

    2005-01-01

    Abstract The problem of estimating haplotype frequencies from population data has been considered by numerous investigators, resulting in a wide variety of possible algorithmic and statistical solutions. We propose a relatively unique approach that employs an artificial neural network (ANN) to predict the most likely haplotype frequencies from a sample of population genotype data. Through an innovative ANN design for mapping genotype patterns to diplotypes, we have produced a prototype that d...

  5. A Piecewise Deterministic Markov Toy Model for Traffic/Maintenance and Associated Hamilton–Jacobi Integrodifferential Systems on Networks

    Energy Technology Data Exchange (ETDEWEB)

    Goreac, Dan, E-mail: Dan.Goreac@u-pem.fr; Kobylanski, Magdalena, E-mail: Magdalena.Kobylanski@u-pem.fr; Martinez, Miguel, E-mail: Miguel.Martinez@u-pem.fr [Université Paris-Est, LAMA (UMR 8050), UPEMLV, UPEC, CNRS (France)

    2016-10-15

    We study optimal control problems in infinite horizon whxen the dynamics belong to a specific class of piecewise deterministic Markov processes constrained to star-shaped networks (corresponding to a toy traffic model). We adapt the results in Soner (SIAM J Control Optim 24(6):1110–1122, 1986) to prove the regularity of the value function and the dynamic programming principle. Extending the networks and Krylov’s “shaking the coefficients” method, we prove that the value function can be seen as the solution to a linearized optimization problem set on a convenient set of probability measures. The approach relies entirely on viscosity arguments. As a by-product, the dual formulation guarantees that the value function is the pointwise supremum over regular subsolutions of the associated Hamilton–Jacobi integrodifferential system. This ensures that the value function satisfies Perron’s preconization for the (unique) candidate to viscosity solution.

  6. System and Method for Network Bandwidth, Buffers and Timing Management Using Hybrid Scheduling of Traffic with Different Priorities and Guarantees

    Science.gov (United States)

    Varadarajan, Srivatsan (Inventor); Hall, Brendan (Inventor); Smithgall, William Todd (Inventor); Bonk, Ted (Inventor); DeLay, Benjamin F. (Inventor)

    2017-01-01

    Systems and methods for network bandwidth, buffers and timing management using hybrid scheduling of traffic with different priorities and guarantees are provided. In certain embodiments, a method of managing network scheduling and configuration comprises, for each transmitting end station, reserving one exclusive buffer for each virtual link to be transmitted from the transmitting end station; for each receiving end station, reserving exclusive buffers for each virtual link to be received at the receiving end station; and for each switch, reserving a exclusive buffer for each virtual link to be received at an input port of the switch. The method further comprises determining if each respective transmitting end station, receiving end station, and switch has sufficient capability to support the reserved buffers; and reporting buffer infeasibility if each respective transmitting end station, receiving end station, and switch does not have sufficient capability to support the reserved buffers.

  7. A scalable acoustic sensor network for model based monitoring of urban traffic noise

    NARCIS (Netherlands)

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

    2012-01-01

    A good understanding of the acoustic environment due to traffic in urban areas is very important. Long term monitoring within large areas provides a clear insight in the actual noise situation. This is needed to take appropriate and cost efficient measures; to asses the effect of measures by

  8. A real-time traffic scheduling algorithm in CDMA packet networks

    NARCIS (Netherlands)

    Zan, Lei; Heijenk, Geert; El Zarki, Magda; Gong, K.; Niu, Z.

    2003-01-01

    The demands for multimedia and packet data services over wireless devices have increased over the past few years. The direct impact on performance makes scheduling for real-time traffic important. This paper presents a novel scheduling algorithm called fair channel-dependent scheduling which

  9. Efficient IP Traffic over Optical Network Based on Wavelength Translation Switching

    DEFF Research Database (Denmark)

    Jha, Vikas; Kalia, Kartik; Chowdhary, Bhawani Shankar

    2016-01-01

    With the advent of TCP/IP protocol suite the overall era of communication technologies had been redefined. Now, we can’t ignore the presence of huge amount of IP traffic; data, voice or video increasing day by day creating more pressure on existing communicating media and supporting back bone...

  10. A method for classification of network traffic based on C5.0 Machine Learning Algorithm

    DEFF Research Database (Denmark)

    Bujlow, Tomasz; Riaz, M. Tahir; Pedersen, Jens Myrup

    2012-01-01

    and classification, an algorithm for recognizing flow direction and the C5.0 itself. Classified applications include Skype, FTP, torrent, web browser traffic, web radio, interactive gaming and SSH. We performed subsequent tries using different sets of parameters and both training and classification options...

  11. Using Of Learning Vector Quantization Network for Pan Evaporation Estimation

    Directory of Open Access Journals (Sweden)

    Kamil7 A. Abdulmohsen

    2013-05-01

    Full Text Available A modern technique is presented to study the evaporation process which is considered as an important component of the hydrological cycle. The Pan Evaporation depth is estimated depending upon four metrological factors viz. (temperature, relative humidity, sunshine, and wind speed. Unsupervised Artificial Neural Network has been proposed to accomplish the study goal, specifically, a type called Linear Vector Quantitization, (LVQ.  A step by step method is used to cope with difficulties that usually associated with computation procedures inherent in these kind of networks. Such systematic approach may close the gap between the hesitation of the user to make use of the capabilities of these type of neural networks and the relative complexity involving the computations procedures. The results reveal the possibility of using LVQ for of Pan Evaporation depth estimation where a good agreement has been noticed between the outputs of the proposed network and the observed values of the Pan Evaporation depth with a correlation coefficient of 0.986. 

  12. A Timing Estimation Method Based-on Skewness Analysis in Vehicular Wireless Networks.

    Science.gov (United States)

    Cui, Xuerong; Li, Juan; Wu, Chunlei; Liu, Jian-Hang

    2015-11-13

    Vehicle positioning technology has drawn more and more attention in vehicular wireless networks to reduce transportation time and traffic accidents. Nowadays, global navigation satellite systems (GNSS) are widely used in land vehicle positioning, but most of them are lack precision and reliability in situations where their signals are blocked. Positioning systems base-on short range wireless communication are another effective way that can be used in vehicle positioning or vehicle ranging. IEEE 802.11p is a new real-time short range wireless communication standard for vehicles, so a new method is proposed to estimate the time delay or ranges between vehicles based on the IEEE 802.11p standard which includes three main steps: cross-correlation between the received signal and the short preamble, summing up the correlated results in groups, and finding the maximum peak using a dynamic threshold based on the skewness analysis. With the range between each vehicle or road-side infrastructure, the position of neighboring vehicles can be estimated correctly. Simulation results were presented in the International Telecommunications Union (ITU) vehicular multipath channel, which show that the proposed method provides better precision than some well-known timing estimation techniques, especially in low signal to noise ratio (SNR) environments.

  13. Application of transport demand modeling in pollution estimation of a street network

    Directory of Open Access Journals (Sweden)

    Jović Jadranka J.

    2009-01-01

    Full Text Available The importance of transportation modeling, especially personal car flow modeling, is well recognized in transportation planning. Modern software tools give the possibility of generating many development scenarios of transport system, which can be tested quickly. Transportation models represent a good (and necessary basis in the procedure of environmental traffic impacts and energy emission estimation. Research in this paper deals with the possibility of using transportation modeling as a tool for estimation of some air pollution and global warming indicators on street network, produced by personal cars with internal combustion engines. These indicators could be the basis for defining planning and management solutions for transport system with respect to their environmental impacts. All the analyses are based on several years of research experience in Belgrade. According to the emissions of gases from the model, the values of other green house gases can be estimated using the known relations between the pollutants. There is a possibility that all these data can be used to calculate the transportation systems impact on temperature increase in urban areas.

  14. A Timing Estimation Method Based-on Skewness Analysis in Vehicular Wireless Networks

    Directory of Open Access Journals (Sweden)

    Xuerong Cui

    2015-11-01

    Full Text Available Vehicle positioning technology has drawn more and more attention in vehicular wireless networks to reduce transportation time and traffic accidents. Nowadays, global navigation satellite systems (GNSS are widely used in land vehicle positioning, but most of them are lack precision and reliability in situations where their signals are blocked. Positioning systems base-on short range wireless communication are another effective way that can be used in vehicle positioning or vehicle ranging. IEEE 802.11p is a new real-time short range wireless communication standard for vehicles, so a new method is proposed to estimate the time delay or ranges between vehicles based on the IEEE 802.11p standard which includes three main steps: cross-correlation between the received signal and the short preamble, summing up the correlated results in groups, and finding the maximum peak using a dynamic threshold based on the skewness analysis. With the range between each vehicle or road-side infrastructure, the position of neighboring vehicles can be estimated correctly. Simulation results were presented in the International Telecommunications Union (ITU vehicular multipath channel, which show that the proposed method provides better precision than some well-known timing estimation techniques, especially in low signal to noise ratio (SNR environments.

  15. Estimation of parameter sensitivities for stochastic reaction networks

    KAUST Repository

    Gupta, Ankit

    2016-01-07

    Quantification of the effects of parameter uncertainty is an important and challenging problem in Systems Biology. We consider this problem in the context of stochastic models of biochemical reaction networks where the dynamics is described as a continuous-time Markov chain whose states represent the molecular counts of various species. For such models, effects of parameter uncertainty are often quantified by estimating the infinitesimal sensitivities of some observables with respect to model parameters. The aim of this talk is to present a holistic approach towards this problem of estimating parameter sensitivities for stochastic reaction networks. Our approach is based on a generic formula which allows us to construct efficient estimators for parameter sensitivity using simulations of the underlying model. We will discuss how novel simulation techniques, such as tau-leaping approximations, multi-level methods etc. can be easily integrated with our approach and how one can deal with stiff reaction networks where reactions span multiple time-scales. We will demonstrate the efficiency and applicability of our approach using many examples from the biological literature.

  16. Degeneracy estimation in interference models on wireless networks

    Science.gov (United States)

    McBride, Neal; Bulava, John; Galiotto, Carlo; Marchetti, Nicola; Macaluso, Irene; Doyle, Linda

    2017-03-01

    We present a Monte Carlo study of interference in real-world wireless networks using the Potts model. Our approach maps the Potts energy to discrete interference levels. These levels depend on the configurations of radio frequency allocation in the network. For the first time, we estimate the degeneracy of these interference levels using the Wang-Landau algorithm. The cumulative distribution function of the resulting density of states is found to increase rapidly at a critical interference value. We compare these critical values for several different real-world interference networks and Potts models. Our results show that models with a greater number of available frequency channels and less dense interference networks result in the majority of configurations having lower interference levels. Consequently, their critical interference levels occur at lower values. Furthermore, the area under the density of states increases and shifts to lower interference values. Therefore, the probability of randomly sampling low interference configurations is higher under these conditions. This result can be used to consider dynamic and distributed spectrum allocation in future wireless networks.

  17. Steady traffic scheduler for internet video traffic across large delay ...

    African Journals Online (AJOL)

    Steady traffic scheduler for internet video traffic across large delay networks. O.E. Ojo, A.O. Oluwatope, I.T. Arowobusoye. Abstract. No Abstract. Keywords: Computer Networks, Multimedia Networking, TCP and Large-Delay Networks. Full Text: EMAIL FULL TEXT EMAIL FULL TEXT · DOWNLOAD FULL TEXT DOWNLOAD ...

  18. Sparse and shrunken estimates of MRI networks in the brain and their influence on network properties

    Science.gov (United States)

    Romero-Garcia, Rafael; Clemmensen, Line H.

    2014-03-01

    Estimation of morphometric relationships between cortical regions is a widely used approach to identify and characterize structural connectivity. The elevated number of regions that can be considered in a whole-brain correlation analysis might lead to overfitted models. However, the overfitting can be avoided by using regularization methods. We found that, as expected, non-regularized correlations had low variability when a scarce number of variables were considered. However, a slight increase of variables led to an increase of variance of several magnitude orders. On the other hand, the regularized approaches showed more stable results with a relative low variance at the expense of a little bias. Interestingly, topological properties as local and global efficiency estimated in networks constructed from traditional non-regularized correlations also showed higher variability when compared to those from regularized networks. Our findings suggest that a population-based connectivity study can achieve a more robust description of cortical topology through regularization of the correlation estimates. Four regularization methods were examined: Two with shrinkage (Ridge and Schäfer's shrinkage), one with sparsity (Lasso) and one with both shrinkage and sparsity (Elastic net). Furthermore, the different regularizations resulted in different correlation estimates as well as network properties. The shrunken estimates resulted in lower variance of the estimates than the sparse estimates.

  19. Estimation of decrease in cancer risk by biodegradation of PAHs content from an urban traffic soil.

    Science.gov (United States)

    Tarafdar, Abhrajyoti; Sinha, Alok

    2017-04-01

    The role of preferential biodegradation in the reduction of cancer risk caused by polycyclic aromatic hydrocarbons (PAHs) has been studied. A consortium of microorganisms isolated from aged oil refinery exposed soil was used to degrade 13 PAHs content extracted from an urban traffic site soil. The biodegradation arranged in a batch process with a mineral salt broth, where PAHs were the sole carbon source. 70.46% biodegradation of the total PAHs occurred in an incubation period of 25 days. Sequential or preferential biodegradation took place as the lower molecular weight (LMW) PAHs were more prone to biodegradation than that of the higher molecular weight (HMW) PAHs. Microorganisms from the isolated consortia preferred the simpler carbon sources first. The relatively higher carcinogenicity of the HMW PAHs than that of the LMW PAHs leads to only 40.26% decrement in cancer risk. Initial cancer risk for children was 1.60E-05, which was decreased to 9.47E-06, whereas, for the adults, the risk decreased to 1.01E-05 from an initial value of 1.71E-05. The relative skin adherence factor for soil (AF) turned out to be the most influential parameter with 54.2% contributions to variance in total cancer risk followed by the exposure duration (ED) for children. For the adults, most contributions to the variance in total cancer risk were 58.5% by ED and followed by AF.

  20. Traffic accident reconstruction and an approach for prediction of fault rates using artificial neural networks: A case study in Turkey.

    Science.gov (United States)

    Can Yilmaz, Ali; Aci, Cigdem; Aydin, Kadir

    2016-08-17

    Currently, in Turkey, fault rates in traffic accidents are determined according to the initiative of accident experts (no speed analyses of vehicles just considering accident type) and there are no specific quantitative instructions on fault rates related to procession of accidents which just represents the type of collision (side impact, head to head, rear end, etc.) in No. 2918 Turkish Highway Traffic Act (THTA 1983). The aim of this study is to introduce a scientific and systematic approach for determination of fault rates in most frequent property damage-only (PDO) traffic accidents in Turkey. In this study, data (police reports, skid marks, deformation, crush depth, etc.) collected from the most frequent and controversial accident types (4 sample vehicle-vehicle scenarios) that consist of PDO were inserted into a reconstruction software called vCrash. Sample real-world scenarios were simulated on the software to generate different vehicle deformations that also correspond to energy-equivalent speed data just before the crash. These values were used to train a multilayer feedforward artificial neural network (MFANN), function fitting neural network (FITNET, a specialized version of MFANN), and generalized regression neural network (GRNN) models within 10-fold cross-validation to predict fault rates without using software. The performance of the artificial neural network (ANN) prediction models was evaluated using mean square error (MSE) and multiple correlation coefficient (R). It was shown that the MFANN model performed better for predicting fault rates (i.e., lower MSE and higher R) than FITNET and GRNN models for accident scenarios 1, 2, and 3, whereas FITNET performed the best for scenario 4. The FITNET model showed the second best results for prediction for the first 3 scenarios. Because there is no training phase in GRNN, the GRNN model produced results much faster than MFANN and FITNET models. However, the GRNN model had the worst prediction results. The

  1. Estimation of Handling Flexible Cystoscope Using Neural Network

    Science.gov (United States)

    Nakamura, Munehiro; Kanaya, Jiro; Kimura, Haruhiko

    This paper presents a system for estimating handling of a flexible cystoscope in bladder checkup. In the checkup, all the seven parts of the bladder wall can be observed with a flexible cystoscope. However, since the shape and color of the parts are depended on participants and five of the parts have same shape and color, it is difficult to grasp the location that the cystoscope is projecting. For the reason, it is often happened that urologists can not confirm that all the parts were observed. Since urologists conduct the checkup by handling the cystoscope and watching movement of the location that the cystoscope is projecting, reproducing the checkup by a computer would recognize oversights. And then, the proposed method extracts movement of the location and estimates the handling by the neural network. The experimental results of the estimations for 9 videos recorded in the checkup have shown a possibility of reproducing the checkup.

  2. Will Automated Vehicles Negatively Impact Traffic Flow?

    Directory of Open Access Journals (Sweden)

    S. C. Calvert

    2017-01-01

    Full Text Available With low-level vehicle automation already available, there is a necessity to estimate its effects on traffic flow, especially if these could be negative. A long gradual transition will occur from manual driving to automated driving, in which many yet unknown traffic flow dynamics will be present. These effects have the potential to increasingly aid or cripple current road networks. In this contribution, we investigate these effects using an empirically calibrated and validated simulation experiment, backed up with findings from literature. We found that low-level automated vehicles in mixed traffic will initially have a small negative effect on traffic flow and road capacities. The experiment further showed that any improvement in traffic flow will only be seen at penetration rates above 70%. Also, the capacity drop appeared to be slightly higher with the presence of low-level automated vehicles. The experiment further investigated the effect of bottleneck severity and truck shares on traffic flow. Improvements to current traffic models are recommended and should include a greater detail and understanding of driver-vehicle interaction, both in conventional and in mixed traffic flow. Further research into behavioural shifts in driving is also recommended due to limited data and knowledge of these dynamics.

  3. Sensor data security level estimation scheme for wireless sensor networks.

    Science.gov (United States)

    Ramos, Alex; Filho, Raimir Holanda

    2015-01-19

    Due to their increasing dissemination, wireless sensor networks (WSNs) have become the target of more and more sophisticated attacks, even capable of circumventing both attack detection and prevention mechanisms. This may cause WSN users, who totally trust these security mechanisms, to think that a sensor reading is secure, even when an adversary has corrupted it. For that reason, a scheme capable of estimating the security level (SL) that these mechanisms provide to sensor data is needed, so that users can be aware of the actual security state of this data and can make better decisions on its use. However, existing security estimation schemes proposed for WSNs fully ignore detection mechanisms and analyze solely the security provided by prevention mechanisms. In this context, this work presents the sensor data security estimator (SDSE), a new comprehensive security estimation scheme for WSNs. SDSE is designed for estimating the sensor data security level based on security metrics that analyze both attack prevention and detection mechanisms. In order to validate our proposed scheme, we have carried out extensive simulations that show the high accuracy of SDSE estimates.

  4. Measurement of traffic network vulnerability for Mississippi coastal region : final research report.

    Science.gov (United States)

    2017-08-15

    Natural disasters such as a hurricane can cause great damages to the transportation networks and significantly affect the evacuation trip operations. An accurate understanding and measurement of the network vulnerability can enhance the evacuees p...

  5. Traffic Signal Synchronization in the Saturated High-Density Grid Road Network

    National Research Council Canada - National Science Library

    Hu, Xiaojian; Lu, Jian; Wang, Wei; Zhirui, Ye

    2015-01-01

    ... has inspired several urban road network development trends, including increased use of the high-density grid road network (HGRN). The structure of the HGRN is the orthogonal checkerboard pattern,...

  6. Large graph visualization of millions of connections in the CERN control system network traffic: analysis and design of routing and firewall rules with a new approach

    CERN Document Server

    Gallerani, Luigi

    2015-01-01

    Abstract The CERN Technical Network (TN) TN was intended to be a network for accelerator and infrastructure operations. However, today, more than 60 million IP packets are routed every hour between the General Purpose Network (GPN) and the TN, involving more than 6000 different hosts. In order to improve the security of the accelerator control system, it is fundamental to understand the network traffic between the two networks and to define new appropriate routing and firewall rules without impacting operations. The complexity and huge size of the infrastructure and the number of protocols and services involved, have discouraged for years any attempt to understand and control the network traffic between the GPN and the TN. In this paper, we show a new way to solve the problem graphically. Combining the network traffic analysis with the use of large graph visualization algorithms we produced usable 2D large color topology maps of the network identifying the inter-relations of the control system machines and s...

  7. Multiple Depots Vehicle Routing Problem in the Context of Total Urban Traffic Equilibrium

    Directory of Open Access Journals (Sweden)

    Dongxu Chen

    2017-01-01

    Full Text Available A multidepot VRP is solved in the context of total urban traffic equilibrium. Under the total traffic equilibrium, the multidepot VRP is changed to GDAP (the problem of Grouping Customers + Estimating OD Traffic + Assigning traffic and bilevel programming is used to model the problem, where the upper model determines the customers that each truck visits and adds the trucks’ trips to the initial OD (Origin/Destination trips, and the lower model assigns the OD trips to road network. Feedback between upper model and lower model is iterated through OD trips; thus total traffic equilibrium can be simulated.

  8. A Two-Stage Method to Estimate the Contribution of Road Traffic to PM2.5 Concentrations in Beijing, China

    Science.gov (United States)

    Fang, Xin; Li, Runkui; Xu, Qun; Bottai, Matteo; Fang, Fang; Cao, Yang

    2016-01-01

    Background: Fine particulate matters with aerodynamic diameters smaller than 2.5 micrometers (PM2.5) have been a critical environmental problem in China due to the rapid road vehicle growth in recent years. To date, most methods available to estimate traffic contributions to ambient PM2.5 concentration are often hampered by the need for collecting data on traffic volume, vehicle type and emission profile. Objective: To develop a simplified and indirect method to estimate the contribution of traffic to PM2.5 concentration in Beijing, China. Methods: Hourly PM2.5 concentration data, daily meteorological data and geographic information were collected at 35 air quality monitoring (AQM) stations in Beijing between 2013 and 2014. Based on the PM2.5 concentrations of different AQM station types, a two-stage method comprising a dispersion model and generalized additive mixed model (GAMM) was developed to estimate separately the traffic and non-traffic contributions to daily PM2.5 concentration. The geographical trend of PM2.5 concentrations was investigated using generalized linear mixed model. The temporal trend of PM2.5 and non-linear relationship between PM2.5 and meteorological conditions were assessed using GAMM. Results: The medians of daily PM2.5 concentrations during 2013–2014 at 35 AQM stations in Beijing ranged from 40 to 92 μg/m3. There was a significant increasing trend of PM2.5 concentration from north to south. The contributions of road traffic to daily PM2.5 concentrations ranged from 17.2% to 37.3% with an average 30%. The greatest contribution was found at AQM stations near busy roads. On average, the contribution of road traffic at urban stations was 14% higher than that at rural stations. Conclusions: Traffic emissions account for a substantial share of daily total PM2.5 concentrations in Beijing. Our two-stage method is a useful and convenient tool in ecological and epidemiological studies to estimate the traffic contribution to PM2.5 concentrations

  9. Volunteer-Based System for classification of traffic in computer networks

    DEFF Research Database (Denmark)

    Bujlow, Tomasz; Balachandran, Kartheepan; Riaz, M. Tahir

    2011-01-01

    To overcome the drawbacks of existing methods for traffic classification (by ports, Deep Packet Inspection, statistical classification) a new system was developed, in which the data are collected from client machines. This paper presents design of the system, implementation, initial runs...... and obtained results. Furthermore, it proves that the system is feasible in terms of uptime and resource usage, assesses its performance and proposes future enhancements....

  10. Prediction of Ship Traffic Flow Based on BP Neural Network and Markov Model

    OpenAIRE

    Lv Pengfei; Zhuang Yuan; Yang Kun

    2016-01-01

    This paper discusses the distribution regularity of ship arrival and departure and the method of prediction of ship traffic flow. Depict the frequency histograms of ships arriving to port every day and fit the curve of the frequency histograms with a variety of distribution density function by using the mathematical statistic methods based on the samples of ship-to-port statistics of Fangcheng port nearly a year. By the chi-square testing: the fitting with Negative Binomial distribution and t...

  11. Fastlane : Traffic flow modeling and multi-class dynamic traffic management

    NARCIS (Netherlands)

    Schreiter, T.; Van Wageningen-Kessels, F.L.M.; Yuan, Y.; Van Lint, J.W.C.; Hoogendoorn, S.P.

    2012-01-01

    Dynamic Traffic Management (DTM) aims to improve traffic conditions. DTM usually consists of two steps: first the current traffic is estimated, then appropriate control actions are determined based on that estimate. In order to estimate and control the traffic, a suitable traffic flow model that

  12. An Approach to Modeling the Impact of Traffic Incident on Urban Expressway

    Directory of Open Access Journals (Sweden)

    Yaping Li

    2015-01-01

    Full Text Available To identify network bottlenecks of urban expressway effectively is a foundational work for improving network traffic condition and preventing traffic congestion. This study proposes a methodology to estimate the impact of traffic incident on urban expressway on the basis of modified cell transmission model. The metastable state was taken into account in the proposed method to reflect the actual operating state of traffic flow on urban expressway as much as possible. Regarding the location of traffic incident, the method of cell restructuring settings was discussed. We then proceed to introduce a new concept of the effected length in a given time period as the evaluation indicator to directly depict the influence of traffic incident. The proposed method was tested on a 6516-meter urban expressway section of west second ring road in Beijing. The simulation results indicated that the proposed methodology performs well to predict the impact of traffic incident on urban expressway.

  13. Multirate IP traffic transmission in flexible access networks based on optical FFH-CDMA

    DEFF Research Database (Denmark)

    Raddo, Thiago R.; Sanches, Anderson L.; Tafur Monroy, Idelfonso

    2016-01-01

    In this paper, we propose a new IP transmission architecture over optical fast frequency hopping code-division multiple-access (OFFH-CDMA) network capable of supporting multirate transmissions for applications in flexible optical access networks. The proposed network architecture is independent...

  14. Estimating Type Ia Supernova Metallicities Using Neural Networks

    Science.gov (United States)

    Villar, V. Ashley

    2017-01-01

    Normal Type Ia supernovae (SNe) can be used as standardizable candles because their progenitors, white dwarfs, are a fairly homogenous class of objects. However, intrinsic variability in these events arise from a number of factors, including metallicity. Recent studies have investigated the effects of metallicity on Type Ia SNe observables from both a theoretical approach, by tuning model metallicity to analyze spectral features, and an observational approach, by studying the effect of host metallicity on light curves. In this work, we take a new, data-driven approach to the problem. Inspired by the success of neural networks in the field of image processing, we aim to estimate the metallicities of Type Ia SNe progenitors from their near-maximum spectra using feed-forward neural networks. We first collect a sample of near-maximum Type Ia SNe spectra from the literature to be smoothed and down-sampled. We then estimate the metallicities of the SNe hosts using the B-band magnitudes. We build a multilayer perceptron to generate a model that takes as input the down-sampled spectra and returns a scalar metallicity. Finally, we discuss basic considerations to be taken when working with spectral (as opposed to image) data using neural networks.

  15. Deep convolutional neural network approach for forehead tissue thickness estimation

    Directory of Open Access Journals (Sweden)

    Manit Jirapong

    2017-09-01

    Full Text Available In this paper, we presented a deep convolutional neural network (CNN approach for forehead tissue thickness estimation. We use down sampled NIR laser backscattering images acquired from a novel marker-less near-infrared laser-based head tracking system, combined with the beam’s incident angle parameter. These two-channel augmented images were constructed for the CNN input, while a single node output layer represents the estimated value of the forehead tissue thickness. The models were – separately for each subject – trained and tested on datasets acquired from 30 subjects (high resolution MRI data is used as ground truth. To speed up training, we used a pre-trained network from the first subject to bootstrap training for each of the other subjects. We could show a clear improvement for the tissue thickness estimation (mean RMSE of 0.096 mm. This proposed CNN model outperformed previous support vector regression (mean RMSE of 0.155 mm or Gaussian processes learning approaches (mean RMSE of 0.114 mm and eliminated their restrictions for future research.

  16. A Note on Bayesian Estimation of the Traffic Intensity in M/M/1 Queue and Queue Characteristics under Quadratic Loss Function

    Directory of Open Access Journals (Sweden)

    Sanku Dey

    2009-01-01

    Full Text Available Bayes' estimators of the traffic intensity r and various queue characteristics in an M/M/1 queue have been derived under the assumptions of different priors for r and the quadratic error loss function (QELF. Finally, a numerical example is given to illustrate the results

  17. Modelling of H.264 MPEG2 TS traffic source

    OpenAIRE

    Kľúčik, Stanislav; Lackovič, Martin

    2013-01-01

    This paper deals with IPTV traffic source modelling. Traffic sources are used for simulation, emulation and real network testing. This model is made as a derivation of known recorded traffic sources that are analysed and statistically processed. As the results show the proposed model causes in comparison to the known traffic source very similar network traffic parameters when used in a simulated network.

  18. Satellite based estimates of reduced CO and CO2 emissions due to traffic restrictions during the 2008 Beijing Olympics

    Science.gov (United States)

    Worden, H. M.; Cheng, Y.; Pfister, G.; Carmichael, G. R.; Zhang, Q.; Streets, D. G.; Deeter, M. N.; Edwards, D. P.; Gille, J. C.; Worden, J.

    2012-12-01

    We present estimates of the reductions in CO and CO2 emissions resulting from the control measures on the Beijing transportation sector taken during the 2008 Beijing Olympics. This study used MOPITT (Measurements Of Pollution In The Troposphere) multispectral satellite measurements of near surface CO along with WRF Chem (Weather Research and Forecasting model with Chemistry) simulations for Beijing during August, 2007 and 2008 to estimate changes in CO due to meteorology and emissions. Using fractional changes in the emissions inventory transportation sector along with a reported CO/CO2 emission ratio for Beijing vehicles, we find the corresponding reduction in CO2 emissions. We then compare this reduction to target CO2 emissions in the RCP (representative concentration pathway) scenarios being considered for the IPCC AR5 (Intergovernmental Panel on Climate Change, 5th Assessment Report). Our result suggests that urban traffic reductions could play a significant role in meeting target cuts for global CO2 emissions, even for the most aggressive control scenario (RCP2.6).

  19. Electronic document delivery: directing interlibrary loan traffic through multiple electronic networks.

    Science.gov (United States)

    Weaver, C G

    1984-04-01

    The University of Nebraska Medical Center (UNMC) uses five different electronic networks for interlibrary loan (ILL) request transmission. The advantages and problems of using electronic networks for ILL request transmission are discussed. Advantages include speed of request transmission, improved capabilities for locating documents, lower labor costs, improved turnaround time, and production of user reports and statistics. Disadvantages include increased work load, additional staff training, coordination of non-standard networks, determining access protocols, and establishing priorities for handling requests.

  20. An estimation of vehicle kilometer traveled and on-road emissions using the traffic volume and travel speed on road links in Incheon City.

    Science.gov (United States)

    Jung, Sungwoon; Kim, Jounghwa; Kim, Jeongsoo; Hong, Dahee; Park, Dongjoo

    2017-04-01

    The objective of this study is to estimate the vehicle kilometer traveled (VKT) and on-road emissions using the traffic volume in urban. We estimated two VKT; one is based on registered vehicles and the other is based on traffic volumes. VKT for registered vehicles was 2.11 times greater than that of the applied traffic volumes because each VKT estimation method is different. Therefore, we had to define the inner VKT is moved VKT inner in urban to compare two values. Also, we focused on freight modes because these are discharged much air pollutant emissions. From analysis results, we found middle and large trucks registered in other regions traveled to target city in order to carry freight, target city has included many industrial and logistics areas. Freight is transferred through the harbors, large logistics centers, or via locations before being moved to the final destination. During this process, most freight is moved by middle and large trucks, and trailers rather than small trucks for freight import and export. Therefore, these trucks from other areas are inflow more than registered vehicles. Most emissions from diesel trucks had been overestimated in comparison to VKT from applied traffic volumes in target city. From these findings, VKT is essential based on traffic volume and travel speed on road links in order to estimate accurately the emissions of diesel trucks in target city. Our findings support the estimation of the effect of on-road emissions on urban air quality in Korea. Copyright © 2016. Published by Elsevier B.V.