WorldWideScience

Sample records for network traffic fluctuations

  1. 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.

  2. Density fluctuations in traffic flow

    CERN Document Server

    Yukawa, S

    1996-01-01

    Density fluctuations in traffic current are studied by computer simulations using the deterministic coupled map lattice model on a closed single-lane circuit. By calculating a power spectral density of temporal density fluctuations at a local section, we find a power-law behavior, \\sim 1/f^{1.8}, on the frequency f, in non-congested flow phase. The distribution of the headway distance h also shows the power law like \\sim 1/h^{3.0} at the same time. The power law fluctuations are destroyed by the occurence of the traffic jam.

  3. 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 ...

  4. 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....

  5. 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...

  6. 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 ...

  7. 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...

  8. 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...

  9. 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.

  10. 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...

  11. 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 ...

  12. 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...

  13. 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...

  14. 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 ...

  15. 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.

  16. 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)

  17. 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...

  18. 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.

  19. 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

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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

  5. 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

  6. 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...

  7. 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....

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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...

  13. 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...

  14. Entropic Fluctuations in Thermally Driven Harmonic Networks

    Science.gov (United States)

    Jakšić, V.; Pillet, C.-A.; Shirikyan, A.

    2017-02-01

    We consider a general network of harmonic oscillators driven out of thermal equilibrium by coupling to several heat reservoirs at different temperatures. The action of the reservoirs is implemented by Langevin forces. Assuming the existence and uniqueness of the steady state of the resulting process, we construct a canonical entropy production functional S^t which satisfies the Gallavotti-Cohen fluctuation theorem. More precisely, we prove that there exists κ _c>1/2 such that the cumulant generating function of S^t has a large-time limit e(α ) which is finite on a closed interval [1/2-κ _c,1/2+κ _c], infinite on its complement and satisfies the Gallavotti-Cohen symmetry e(1-α )=e(α ) for all α in R. Moreover, we show that e(α ) is essentially smooth, i.e., that e'(α )→ ∓ ∞ as α → 1/2 ∓ κ _c. It follows from the Gärtner-Ellis theorem that S^t satisfies a global large deviation principle with a rate function I( s) obeying the Gallavotti-Cohen fluctuation relation I(-s)-I(s)=s for all sin R. We also consider perturbations of S^t by quadratic boundary terms and prove that they satisfy extended fluctuation relations, i.e., a global large deviation principle with a rate function that typically differs from I( s) outside a finite interval. This applies to various physically relevant functionals and, in particular, to the heat dissipation rate of the network. Our approach relies on the properties of the maximal solution of a one-parameter family of algebraic matrix Riccati equations. It turns out that the limiting cumulant generating functions of S^t and its perturbations can be computed in terms of spectral data of a Hamiltonian matrix depending on the harmonic potential of the network and the parameters of the Langevin reservoirs. This approach is well adapted to both analytical and numerical investigations.

  15. 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...

  16. Equilibrium & Nonequilibrium Fluctuation Effects in Biopolymer Networks

    Science.gov (United States)

    Kachan, Devin Michael

    Fluctuation-induced interactions are an important organizing principle in a variety of soft matter systems. In this dissertation, I explore the role of both thermal and active fluctuations within cross-linked polymer networks. The systems I study are in large part inspired by the amazing physics found within the cytoskeleton of eukaryotic cells. I first predict and verify the existence of a thermal Casimir force between cross-linkers bound to a semi-flexible polymer. The calculation is complicated by the appearance of second order derivatives in the bending Hamiltonian for such polymers, which requires a careful evaluation of the the path integral formulation of the partition function in order to arrive at the physically correct continuum limit and properly address ultraviolet divergences. I find that cross linkers interact along a filament with an attractive logarithmic potential proportional to thermal energy. The proportionality constant depends on whether and how the cross linkers constrain the relative angle between the two filaments to which they are bound. The interaction has important implications for the synthesis of biopolymer bundles within cells. I model the cross-linkers as existing in two phases: bound to the bundle and free in solution. When the cross-linkers are bound, they behave as a one-dimensional gas of particles interacting with the Casimir force, while the free phase is a simple ideal gas. Demanding equilibrium between the two phases, I find a discontinuous transition between a sparsely and a densely bound bundle. This discontinuous condensation transition induced by the long-ranged nature of the Casimir interaction allows for a similarly abrupt structural transition in semiflexible filament networks between a low cross linker density isotropic phase and a higher cross link density bundle network. This work is supported by the results of finite element Brownian dynamics simulations of semiflexible filaments and transient cross-linkers. I

  17. 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...

  18. 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.

  19. 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...

  20. 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.

  1. 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...

  2. 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.

  3. 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...

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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

  9. Large Fluctuations and Rare-Events in Complex Networks

    Science.gov (United States)

    Hindes, Jason; Schwartz, Ira

    Networks form the backbone of complex systems ranging from ecological food-webs to computer and social networks, and sustain a variety of important dynamical behaviors necessary for some function or task. However, many networks of interest often operate in noisy environments and fluctuate due to random internal interactions, both of which can cause sudden transitions from one network state to another. These noise induced events can be associated with desirable outcomes, such as the extinction of an epidemic, or undesirable, such as a drastic change in network consensus. In this talk, we discuss a general theory of rare-events occurring in complex networks, including extinction and rare-opinion switches, that captures the transition pathway through a network between states and predicts the characteristic time-scale for switching. Lastly, using the formalism, we demonstrate how to design optimal controls that leverage fluctuations in order to enhance or inhibit rare switches in networks. office of naval research, national research council.

  10. Analysis of heat exchanger network for temperature fluctuation

    Directory of Open Access Journals (Sweden)

    Jin Zunlong

    2015-09-01

    Full Text Available Subject to temperature disturbance, exchangers in heat exchanger network will interact. It is necessary to evaluate the degree of temperature fluctuation in the network. There is inherently linear relationship between output and inlet temperatures of heat exchanger network. Based on this, the concept of temperature-change sensitivity coefficient was put forward. Quantitative influence of temperature fluctuation in the network was carried out in order to examine transmission character of temperature fluctuation in the system. And the information was obtained for improving the design quality of heat exchanger network. Favorable results were obtained by the introduced method compared with the experimental results. These results will assist engineers to distinguish primary and secondary influencing factors, which can be used in observing and controlling influencing factors accurately.

  11. 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

  12. Transportation network with fluctuating input/output designed by the bio-inspired Physarum algorithm.

    Science.gov (United States)

    Watanabe, Shin; Takamatsu, Atsuko

    2014-01-01

    In this paper, we propose designing transportation network topology and traffic distribution under fluctuating conditions using a bio-inspired algorithm. The algorithm is inspired by the adaptive behavior observed in an amoeba-like organism, plasmodial slime mold, more formally known as plasmodium of Physarum plycephalum. This organism forms a transportation network to distribute its protoplasm, the fluidic contents of its cell, throughout its large cell body. In this process, the diameter of the transportation tubes adapts to the flux of the protoplasm. The Physarum algorithm, which mimics this adaptive behavior, has been widely applied to complex problems, such as maze solving and designing the topology of railroad grids, under static conditions. However, in most situations, environmental conditions fluctuate; for example, in power grids, the consumption of electric power shows daily, weekly, and annual periodicity depending on the lifestyles or the business needs of the individual consumers. This paper studies the design of network topology and traffic distribution with oscillatory input and output traffic flows. The network topology proposed by the Physarum algorithm is controlled by a parameter of the adaptation process of the tubes. We observe various rich topologies such as complete mesh, partial mesh, Y-shaped, and V-shaped networks depending on this adaptation parameter and evaluate them on the basis of three performance functions: loss, cost, and vulnerability. Our results indicate that consideration of the oscillatory conditions and the phase-lags in the multiple outputs of the network is important: The building and/or maintenance cost of the network can be reduced by introducing the oscillating condition, and when the phase-lag among the outputs is large, the transportation loss can also be reduced. We use stability analysis to reveal how the system exhibits various topologies depending on the parameter.

  13. Transportation network with fluctuating input/output designed by the bio-inspired Physarum algorithm.

    Directory of Open Access Journals (Sweden)

    Shin Watanabe

    Full Text Available In this paper, we propose designing transportation network topology and traffic distribution under fluctuating conditions using a bio-inspired algorithm. The algorithm is inspired by the adaptive behavior observed in an amoeba-like organism, plasmodial slime mold, more formally known as plasmodium of Physarum plycephalum. This organism forms a transportation network to distribute its protoplasm, the fluidic contents of its cell, throughout its large cell body. In this process, the diameter of the transportation tubes adapts to the flux of the protoplasm. The Physarum algorithm, which mimics this adaptive behavior, has been widely applied to complex problems, such as maze solving and designing the topology of railroad grids, under static conditions. However, in most situations, environmental conditions fluctuate; for example, in power grids, the consumption of electric power shows daily, weekly, and annual periodicity depending on the lifestyles or the business needs of the individual consumers. This paper studies the design of network topology and traffic distribution with oscillatory input and output traffic flows. The network topology proposed by the Physarum algorithm is controlled by a parameter of the adaptation process of the tubes. We observe various rich topologies such as complete mesh, partial mesh, Y-shaped, and V-shaped networks depending on this adaptation parameter and evaluate them on the basis of three performance functions: loss, cost, and vulnerability. Our results indicate that consideration of the oscillatory conditions and the phase-lags in the multiple outputs of the network is important: The building and/or maintenance cost of the network can be reduced by introducing the oscillating condition, and when the phase-lag among the outputs is large, the transportation loss can also be reduced. We use stability analysis to reveal how the system exhibits various topologies depending on the parameter.

  14. 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.

  15. 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.

  16. 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...

  17. 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.

  18. The scaling properties of dynamical fluctuations in temporal networks

    CERN Document Server

    Chi, Liping

    2015-01-01

    The factorial moments analyses are performed to study the scaling properties of the dynamical fluctuations of contacts and nodes in temporal networks based on empirical data sets. The intermittent behaviors are observed in the fluctuations for all orders of the moments. It indicates that the interaction has self-similarity structure in time interval and the fluctuations are not purely random but dynamical and correlated. The scaling exponents for contacts in Prostitution data and nodes in Conference data are very close to that for 2D Ising model undergoing a second-order phase transition.

  19. 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....

  20. 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

  1. Uncoupled Analysis of Stochastic Reaction Networks in Fluctuating Environments

    Science.gov (United States)

    Zechner, Christoph; Koeppl, Heinz

    2014-01-01

    The dynamics of stochastic reaction networks within cells are inevitably modulated by factors considered extrinsic to the network such as, for instance, the fluctuations in ribosome copy numbers for a gene regulatory network. While several recent studies demonstrate the importance of accounting for such extrinsic components, the resulting models are typically hard to analyze. In this work we develop a general mathematical framework that allows to uncouple the network from its dynamic environment by incorporating only the environment's effect onto the network into a new model. More technically, we show how such fluctuating extrinsic components (e.g., chemical species) can be marginalized in order to obtain this decoupled model. We derive its corresponding process- and master equations and show how stochastic simulations can be performed. Using several case studies, we demonstrate the significance of the approach. PMID:25473849

  2. 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.

  3. 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 ...

  4. 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....

  5. Out of control: Fluctuation of cascading dynamics in networks

    Science.gov (United States)

    Wang, Jianwei; Cai, Lin; Xu, Bo; Li, Peng; Sun, Enhui; Zhu, Zhiguo

    2016-11-01

    Applying two preferential selection mechanisms of flow destination, we develop two new methods to quantify the initial load of a node, where the flow is transported along the shortest path between two nodes. We propose a simple cascading model and study cascading dynamics induced by attacking the node with the highest load in some synthetic and actual networks. Surprisingly, we observe the abnormal fluctuation of cascading dynamics, i.e., more damage can be triggered if we spend significantly higher cost to protect a network. In particular, this phenomenon is independent of the initial flow distribution and the preferential selection mechanisms of flow destination. However, it remains unclear which specific structural patterns may affect the fluctuation of cascading dynamics. In this paper, we examine the local evolution of the cascading propagation by constructing some special networks. We show that revivals of some nodes in the double ring structure facilitate the transportation of the flow between two unconnected sub-networks, cause more damage and subsequently lead to the abnormal fluctuation of cascading dynamics. Compared with the traditional definition of the betweenness, we adopt two new proposed methods to further evaluate the resilience of several actual networks. We find that some real world networks reach the strongest resilience level against cascading failures in our preferential selection mechanisms of flow destination. Moreover, we explore how to use the minimum cost to maximize the resilience of the studied networks.

  6. 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...

  7. 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.

  8. 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.

  9. 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%.

  10. Constitutive equation for polymer networks with phonon fluctuations

    DEFF Research Database (Denmark)

    Hansen, Rasmus; Skov, Anne Ladegaard; Hassager, Ole

    2008-01-01

    Recent research by Xing [Phys. Rev. Lett. 98, 075502 (2007)] has provided an expression for the Helmholtz free energy related to phonon fluctuations in polymer networks. We extend this result by constructing the corresponding nonlinear constitutive equation, usable for entirely general, volume...

  11. Listening to the noise: random fluctuations reveal gene network parameters

    Energy Technology Data Exchange (ETDEWEB)

    Munsky, Brian [Los Alamos National Laboratory; Khammash, Mustafa [UCSB

    2009-01-01

    The cellular environment is abuzz with noise. The origin of this noise is attributed to the inherent random motion of reacting molecules that take part in gene expression and post expression interactions. In this noisy environment, clonal populations of cells exhibit cell-to-cell variability that frequently manifests as significant phenotypic differences within the cellular population. The stochastic fluctuations in cellular constituents induced by noise can be measured and their statistics quantified. We show that these random fluctuations carry within them valuable information about the underlying genetic network. Far from being a nuisance, the ever-present cellular noise acts as a rich source of excitation that, when processed through a gene network, carries its distinctive fingerprint that encodes a wealth of information about that network. We demonstrate that in some cases the analysis of these random fluctuations enables the full identification of network parameters, including those that may otherwise be difficult to measure. This establishes a potentially powerful approach for the identification of gene networks and offers a new window into the workings of these networks.

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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...

  19. 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.

  20. 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...

  1. 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.

  2. Propagation of disturbances as voltage fluctuations in transmission networks

    Directory of Open Access Journals (Sweden)

    Albert Hermina

    2016-08-01

    Full Text Available Significant changes occurred in the power system in Romania in recent years by reducing the power used in the system, the number of classic power sources in operation as well as by implementing renewable energy sources, have determined short circuit power reduction (node rigidity in the points where disturbing users are connected, that in the absence of adequate measures, result in disturbances above acceptable levels. The paper analyzes two power systems areas in which are connected users that cause voltage fluctuation. Disturbances as voltage fluctuations resulting in these nodes may exceed the acceptable values and can spread in the transmission network affecting power quality over large system areas. The analysis conducted reveals the influence of short circuit power in nodes where these users are connected and highlights the fact that in some cases (e.g. lines out of operation for maintenance, shutdown of classic units in the area the disturbances in the transmission network sent to the users at lower voltages may have values above those allowed. Technical Code of existing power transmission network makes no reference to voltage fluctuations, as a rule, in the electricity transmission network was considered that this phenomenon should not exist.

  3. 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.

  4. 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.

  5. 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 ...

  6. 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...

  7. 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.

  8. 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

  9. 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...

  10. 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

  11. 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.

  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. 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

  15. 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

  16. 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

  17. 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.

  18. 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.

  19. 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

  20. 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

  1. 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

  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. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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

  8. 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

  9. 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.

  10. 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.

  11. 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.

  12. 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...

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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...

  18. 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.

  19. 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.

  20. 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.

  1. Escape routes, weak links, and desynchronization in fluctuation-driven networks.

    Science.gov (United States)

    Schäfer, Benjamin; Matthiae, Moritz; Zhang, Xiaozhu; Rohden, Martin; Timme, Marc; Witthaut, Dirk

    2017-06-01

    Shifting our electricity generation from fossil fuel to renewable energy sources introduces large fluctuations to the power system. Here, we demonstrate how increased fluctuations, reduced damping, and reduced intertia may undermine the dynamical robustness of power grid networks. Focusing on fundamental noise models, we derive analytic insights into which factors limit the dynamic robustness and how fluctuations may induce a system escape from an operating state. Moreover, we identify weak links in the grid that make it particularly vulnerable to fluctuations. These results thereby not only contribute to a theoretical understanding of how fluctuations act on distributed network dynamics, they may also help designing future renewable energy systems to be more robust.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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...

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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...

  13. 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.

  14. 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.

  15. 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.

  16. 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...

  17. 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.

  18. 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...

  19. 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...

  20. 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...

  1. 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.

  2. 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.

  3. 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.

  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. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. Analysis of the Dynamic Evolutionary Behavior of American Heating Oil Spot and Futures Price Fluctuation Networks

    Directory of Open Access Journals (Sweden)

    Huan Chen

    2017-04-01

    Full Text Available Heating oil is an extremely important heating fuel to consumers in northeastern United States. This paper studies the fluctuations law and dynamic behavior of heating oil spot and futures prices by setting up their complex network models based on the data of America in recent 30 years. Firstly, modes are defined by the method of coarse graining, the spot price fluctuation network of heating oil (HSPFN and its futures price fluctuation network (HFPFN in different periods are established to analyze the transformation characteristics between the modes. Secondly, several indicators are investigated: average path length, node strength and strength distribution, betweeness, etc. In addition, a function is established to measure and analyze the network similarity. The results show the cumulative time of new nodes appearing in either spot or futures price network is not random but exhibits a growth trend of straight line. Meanwhile, the power law distributions of spot and futures price fluctuations in different periods present regularity and complexity. Moreover, these prices are strongly correlated in stable fluctuation period but weak in the phase of sharp fluctuation. Finally, the time distribution characteristics of important modes in the networks and the evolution results of the topological properties mentioned above are obtained.

  11. 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...

  12. 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...

  13. 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....

  14. 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.

  15. 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.

  16. 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.

  17. 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...

  18. 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.

  19. 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.

  20. 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....

  1. 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.

  2. Robustness of scale-free networks to cascading failures induced by fluctuating loads.

    Science.gov (United States)

    Mizutaka, Shogo; Yakubo, Kousuke

    2015-07-01

    Taking into account the fact that overload failures in real-world functional networks are usually caused by extreme values of temporally fluctuating loads that exceed the allowable range, we study the robustness of scale-free networks against cascading overload failures induced by fluctuating loads. In our model, loads are described by random walkers moving on a network and a node fails when the number of walkers on the node is beyond the node capacity. Our results obtained by using the generating function method show that scale-free networks are more robust against cascading overload failures than Erdős-Rényi random graphs with homogeneous degree distributions. This conclusion is contrary to that predicted by previous works, which neglect the effect of fluctuations of loads.

  3. 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.

  4. 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.

  5. 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.

  6. 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...

  7. Transient fluctuation of the prosperity of firms in a network economy

    Science.gov (United States)

    Maeno, Yoshiharu

    2013-08-01

    The transient fluctuation of the prosperity of firms in a network economy is investigated with an abstract stochastic model. The model describes the profit which firms make when they sell materials to a firm which produces a product and the fixed cost expense to the firms to produce those materials and product. The formulas for this model are parallel to those for population dynamics. The swinging changes in the fluctuation in the transient state from the initial growth to the final steady state are the consequence of a topology-dependent time trial competition between the profitable interactions and expense. The firm in a sparse random network economy is more likely to go bankrupt than expected from the value of the limit of the fluctuation in the steady state, and there is a risk of failing to reach by far the less fluctuating steady state.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. Opposing Effects of Intrinsic Conductance and Correlated Synaptic Input on V-Fluctuations during Network Activity

    DEFF Research Database (Denmark)

    Kolind, Jens; Hounsgaard, Jørn Dybkjær; Berg, Rune W

    2012-01-01

    Neurons often receive massive concurrent bombardment of synaptic inhibition and excitation during functional network activity. This increases membrane conductance and causes fluctuations in membrane potential (V(m)) and spike timing. The conductance increase is commonly attributed to synaptic......(m) -fluctuations and conductance observed experimentally during functional network activity leave little room for intrinsic conductance to contribute. Even without intrinsic conductances the variance in V(m) -fluctuations can only be explained by a high degree of correlated firing among presynaptic neurons....... conductance, but also includes the intrinsic conductances recruited during network activity. These two sources of conductance have contrasting dynamic properties at sub-threshold membrane potentials. Synaptic transmitter gated conductance changes abruptly and briefly with each presynaptic action potential...

  16. 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.

  17. Business fluctuations in a credit-network economy

    Science.gov (United States)

    Delli Gatti, Domenico; Gallegati, Mauro; Greenwald, Bruce; Russo, Alberto; Stiglitz, Joseph E.

    2006-10-01

    We model a network economy with three sectors: downstream firms, upstream firms, and banks. Agents are linked by productive and credit relationships so that the behavior of one agent influences the behavior of the others through network connections. Credit interlinkages among agents are a source of bankruptcy diffusion: in fact, failure of fulfilling debt commitments would lead to bankruptcy chains. All in all, the bankruptcy in one sector can diffuse to other sectors through linkages creating a vicious cycle and bankruptcy avalanches in the network economy. Our analysis show how the choices of credit supply by both banks and firms are interrelated. While the initial impact of monetary policy is on bank behaviour, we show the interactive play between the choices made by banks, the choices made by firms in their role as providers of credit, and the choices made by firms in their role as producers.

  18. 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...

  19. 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...

  20. Impact of visual repetition rate on intrinsic properties of low frequency fluctuations in the visual network.

    Directory of Open Access Journals (Sweden)

    Yi-Chia Li

    Full Text Available BACKGROUND: Visual processing network is one of the functional networks which have been reliably identified to consistently exist in human resting brains. In our work, we focused on this network and investigated the intrinsic properties of low frequency (0.01-0.08 Hz fluctuations (LFFs during changes of visual stimuli. There were two main questions to be discussed in this study: intrinsic properties of LFFs regarding (1 interactions between visual stimuli and resting-state; (2 impact of repetition rate of visual stimuli. METHODOLOGY/PRINCIPAL FINDINGS: We analyzed scanning sessions that contained rest and visual stimuli in various repetition rates with a novel method. The method included three numerical approaches involving ICA (Independent Component Analyses, fALFF (fractional Amplitude of Low Frequency Fluctuation, and Coherence, to respectively investigate the modulations of visual network pattern, low frequency fluctuation power, and interregional functional connectivity during changes of visual stimuli. We discovered when resting-state was replaced by visual stimuli, more areas were involved in visual processing, and both stronger low frequency fluctuations and higher interregional functional connectivity occurred in visual network. With changes of visual repetition rate, the number of areas which were involved in visual processing, low frequency fluctuation power, and interregional functional connectivity in this network were also modulated. CONCLUSIONS/SIGNIFICANCE: To combine the results of prior literatures and our discoveries, intrinsic properties of LFFs in visual network are altered not only by modulations of endogenous factors (eye-open or eye-closed condition; alcohol administration and disordered behaviors (early blind, but also exogenous sensory stimuli (visual stimuli with various repetition rates. It demonstrates that the intrinsic properties of LFFs are valuable to represent physiological states of human brains.

  1. 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.

  2. 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.

  3. 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...

  4. 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.

  5. 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,...

  6. 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...

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. Mind-Body Practice Changes Fractional Amplitude of Low Frequency Fluctuations in Intrinsic Control Networks.

    Science.gov (United States)

    Wei, Gao-Xia; Gong, Zhu-Qing; Yang, Zhi; Zuo, Xi-Nian

    2017-01-01

    Cognitive control impairment is a typical symptom largely reported in populations with neurological disorders. Previous studies have provided evidence about the changes in cognitive control induced by mind-body training. However, the neural correlates underlying the effect of extensive mind-body practice on cognitive control remain largely unknown. Using resting-state functional magnetic resonance imaging, we characterized dynamic fluctuations in large-scale intrinsic connectivity networks associated with mind-body practice, and examined their differences between healthy controls and Tai Chi Chuan (TCC) practitioners. Compared with a control group, the TCC group revealed significantly decreased fractional Amplitude of Low Frequency Fluctuations (fALFF) in the bilateral frontoparietal network, default mode network and dorsal prefrontal-angular gyri network. Furthermore, we detected a significant association between mind-body practice experience and fALFF in the default mode network, as well as an association between cognitive control performance and fALFF of the frontoparietal network. This provides the first evidence of large-scale functional connectivity in brain networks associated with mind-body practice, shedding light on the neural network changes that accompany intensive mind-body training. It also highlights the functionally plastic role of the frontoparietal network in the context of the "immune system" of mental health recently developed in relation to flexible hub theory.

  14. 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

  15. 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.

  16. 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....

  17. 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...

  18. Correlated Fluctuations in Strongly Coupled Binary Networks Beyond Equilibrium

    Directory of Open Access Journals (Sweden)

    David Dahmen

    2016-08-01

    Full Text Available Randomly coupled Ising spins constitute the classical model of collective phenomena in disordered systems, with applications covering glassy magnetism and frustration, combinatorial optimization, protein folding, stock market dynamics, and social dynamics. The phase diagram of these systems is obtained in the thermodynamic limit by averaging over the quenched randomness of the couplings. However, many applications require the statistics of activity for a single realization of the possibly asymmetric couplings in finite-sized networks. Examples include reconstruction of couplings from the observed dynamics, representation of probability distributions for sampling-based inference, and learning in the central nervous system based on the dynamic and correlation-dependent modification of synaptic connections. The systematic cumulant expansion for kinetic binary (Ising threshold units with strong, random, and asymmetric couplings presented here goes beyond mean-field theory and is applicable outside thermodynamic equilibrium; a system of approximate nonlinear equations predicts average activities and pairwise covariances in quantitative agreement with full simulations down to hundreds of units. The linearized theory yields an expansion of the correlation and response functions in collective eigenmodes, leads to an efficient algorithm solving the inverse problem, and shows that correlations are invariant under scaling of the interaction strengths.

  19. Correlated Fluctuations in Strongly Coupled Binary Networks Beyond Equilibrium

    Science.gov (United States)

    Dahmen, David; Bos, Hannah; Helias, Moritz

    2016-07-01

    Randomly coupled Ising spins constitute the classical model of collective phenomena in disordered systems, with applications covering glassy magnetism and frustration, combinatorial optimization, protein folding, stock market dynamics, and social dynamics. The phase diagram of these systems is obtained in the thermodynamic limit by averaging over the quenched randomness of the couplings. However, many applications require the statistics of activity for a single realization of the possibly asymmetric couplings in finite-sized networks. Examples include reconstruction of couplings from the observed dynamics, representation of probability distributions for sampling-based inference, and learning in the central nervous system based on the dynamic and correlation-dependent modification of synaptic connections. The systematic cumulant expansion for kinetic binary (Ising) threshold units with strong, random, and asymmetric couplings presented here goes beyond mean-field theory and is applicable outside thermodynamic equilibrium; a system of approximate nonlinear equations predicts average activities and pairwise covariances in quantitative agreement with full simulations down to hundreds of units. The linearized theory yields an expansion of the correlation and response functions in collective eigenmodes, leads to an efficient algorithm solving the inverse problem, and shows that correlations are invariant under scaling of the interaction strengths.

  20. 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.

  1. 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.

  2. 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.

  3. Attention Network Test in adults with ADHD - the impact of affective fluctuations

    DEFF Research Database (Denmark)

    Lundervold, Astri J; Adolfsdottir, Steinunn; Halleland, Helene

    2011-01-01

    ABSTRACT: BACKGROUND: The Attention Network Test (ANT) generates measures of different aspects of attention/executive function. In the present study we investigated whether adults with ADHD performed different from controls on measures of accuracy, variability and vigilance as well as the control...... network. Secondly, we studied subgroups of adults with ADHD, expecting impairment on measures of the alerting and control networks in a subgroup with additional symptoms of affective fluctuations. METHODS: A group of 114 adults (ADHD n=58; controls n=56) performed the ANT and completed the Adult ADHD...... Rating Scale (ASRS) and the Mood Disorder Questionnaire (MDQ). The latter was used to define affective fluctuations. RESULTS: The sex distribution was similar in the two groups, but the ADHD group was significantly older (p=.005) and their score on a test of intellectual function (WASI) significantly...

  4. 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

  5. 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....

  6. 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

  7. 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...

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. Attention Network Test in adults with ADHD - the impact of affective fluctuations

    Directory of Open Access Journals (Sweden)

    Lundervold Astri J

    2011-07-01

    Full Text Available Abstract Background The Attention Network Test (ANT generates measures of different aspects of attention/executive function. In the present study we investigated whether adults with ADHD performed different from controls on measures of accuracy, variability and vigilance as well as the control network. Secondly, we studied subgroups of adults with ADHD, expecting impairment on measures of the alerting and control networks in a subgroup with additional symptoms of affective fluctuations. Methods A group of 114 adults (ADHD n = 58; controls n = 56 performed the ANT and completed the Adult ADHD Rating Scale (ASRS and the Mood Disorder Questionnaire (MDQ. The latter was used to define affective fluctuations. Results The sex distribution was similar in the two groups, but the ADHD group was significantly older (p = .005 and their score on a test of intellectual function (WASI significantly lower than in the control group (p = .007. The two groups were not significantly different on measures of the three attention networks, but the ADHD group was generally less accurate (p = .001 and showed a higher variability through the task (p = .033. The significance was only retained for the accuracy measure when age and IQ scores were controlled for. Within the ADHD group, individuals reporting affective fluctuations (n = 22 were slower (p = .015 and obtained a lower score on the alerting network (p = .018 and a higher score on the conflict network (p = .023 than those without these symptoms. The significance was retained for the alerting network (p = .011, but not the conflict network (p = .061 when we controlled for the total ASRS and IQ scores. Discussion Adults with ADHD were characterized by impairment on accuracy and variability measures calculated from the ANT. Within the ADHD group, adults reporting affective fluctuations seemed to be more alert (i.e., less impacted by alerting cues, but slower and more distracted by conflicting stimuli than the

  15. 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.

  16. 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.

  17. 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

  18. 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 ...

  19. Task-related modulations of BOLD low-frequency fluctuations within the default mode network

    Science.gov (United States)

    Tommasin, Silvia; Mascali, Daniele; Gili, Tommaso; Eid Assan, Ibrahim; Moraschi, Marta; Fratini, Michela; Wise, Richard G.; Macaluso, Emiliano; Mangia, Silvia; Giove, Federico

    2017-07-01

    Spontaneous low-frequency Blood-Oxygenation Level-Dependent (BOLD) signals acquired during resting state are characterized by spatial patterns of synchronous fluctuations, ultimately leading to the identification of robust brain networks. The resting-state brain networks, including the Default Mode Network (DMN), are demonstrated to persist during sustained task execution, but the exact features of task-related changes of network properties are still not well characterized. In this work we sought to examine in a group of 20 healthy volunteers (age 33±6 years, 8F/12M) the relationship between changes of spectral and spatiotemporal features of one prominent resting-state network, namely the DMN, during the steady-state execution of a sustained working memory n-back task. We found that the steady state execution of such a task impacted on both functional connectivity and amplitude of BOLD fluctuations within large parts of the DMN, but these changes correlated between each other only in a small area of the posterior cingulate. We conclude that combined analysis of multiple parameters related to connectivity, and their changes during the transition from resting state to steady-state task execution, can contribute to a better understanding of how brain networks rearrange themselves in response of a task.

  20. Task-Related Modulations of BOLD Low-Frequency Fluctuations within the Default Mode Network

    Directory of Open Access Journals (Sweden)

    Silvia Tommasin

    2017-07-01

    Full Text Available Spontaneous low-frequency Blood-Oxygenation Level-Dependent (BOLD signals acquired during resting state are characterized by spatial patterns of synchronous fluctuations, ultimately leading to the identification of robust brain networks. The resting-state brain networks, including the Default Mode Network (DMN, are demonstrated to persist during sustained task execution, but the exact features of task-related changes of network properties are still not well characterized. In this work we sought to examine in a group of 20 healthy volunteers (age 33 ± 6 years, 8 F/12 M the relationship between changes of spectral and spatiotemporal features of one prominent resting-state network, namely the DMN, during the continuous execution of a working memory n-back task. We found that task execution impacted on both functional connectivity and amplitude of BOLD fluctuations within large parts of the DMN, but these changes correlated between each other only in a small area of the posterior cingulate. We conclude that combined analysis of multiple parameters related to connectivity, and their changes during the transition from resting state to continuous task execution, can contribute to a better understanding of how brain networks rearrange themselves in response to a task.

  1. 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

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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...

  8. 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.

  9. 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

  10. 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.

  11. 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.

  12. Is there any connection between the network morphology and the fluctuations of the stock market index?

    Science.gov (United States)

    Stefan, F. M.; Atman, A. P. F.

    2015-02-01

    Models which consider behavioral aspects of the investors have attracted increasing interest in the Finance and Econophysics literature in the last years. Different behavioral profiles (imitation, anti-imitation, indifference) were proposed for the investors, which take their decision based on their trust network (neighborhood). Results from agent-based models have shown that most of the features observed in actual stock market indices can be replicated in simulations. Here, we present a deeper investigation of an agent based model considering different network morphologies (regular, random, small-world) for the investors' trust network, in an attempt to answer the question raised in the title. We study the model by considering four scenarios for the investors and different initial conditions to analyze their influence in the stock market fluctuations. We have characterized the stationary limit for each scenario tested, focusing on the changes introduced when complex networks were used, and calculated the Hurst exponent in some cases. Simulations showed interesting results suggesting that the fluctuations of the stock market index are strongly affected by the network morphology, a remarkable result which we believe was never reported or predicted before.

  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. 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.

  7. 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.

  8. 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.

  9. Fluctuation relations between hierarchical kinetically equivalent networks with Arrhenius-type transitions and their roles in systems and structural biology

    Science.gov (United States)

    Deng, De-Ming; Lu, Yi-Ta; Chang, Cheng-Hung

    2017-06-01

    The legality of using simple kinetic schemes to determine the stochastic properties of a complex system depends on whether the fluctuations generated from hierarchical equivalent schemes are consistent with one another. To analyze this consistency, we perform lumping processes on the stochastic differential equations and the generalized fluctuation-dissipation theorem and apply them to networks with the frequently encountered Arrhenius-type transition rates. The explicit Langevin force derived from those networks enables us to calculate the state fluctuations caused by the intrinsic and extrinsic noises on the free energy surface and deduce their relations between kinetically equivalent networks. In addition to its applicability to wide classes of network related systems, such as those in structural and systems biology, the result sheds light on the fluctuation relations for general physical variables in Keizer's canonical theory.

  10. Fractal analysis of spontaneous fluctuations of the BOLD signal in the human brain networks.

    Science.gov (United States)

    Li, Yi-Chia; Huang, Yun-An

    2014-05-01

    To investigate what extent brain regions are continuously interacting during resting-state, independent component analyses (ICA) was applied to analyze resting-state functional MRI (RS-fMRI) data. According to the analyzed results, it was surprisingly found that low frequency fluctuations (LFFs), which belong to the 1/f signal (a signal with power spectrum whose power spectral density is inversely proportional to the frequency), have been classified into groups using ICA; furthermore, the spatial distributions of these groups within the brain were found to resemble the spatial distributions of different networks, which manifests that the signal characteristics of RS LFFs are distinct across networks. In our work, we applied the 1/f model in the fractal analyses to further investigate this distinction. Twenty healthy participants got involved in this study. They were scanned to acquire the RS-fMRI data. The acquired data were first processed with ICA to obtain the networks of the resting brain. Afterward, the blood-oxygenation level dependent (BOLD) signals of these networks were processed with the fractal analyses for obtaining the fractal parameter α. α was found to significantly vary across networks, which reveals that the fractal characteristic of LFFs differs across networks. According to prior literatures, this difference could be brought by the discrepancy of hemodynamic response amplitude (HRA) between networks. Hence, in our work, we also performed the computational simulation to discover the relationship between α and HRA. Based on the simulation results, HRA is highly linear-correlated with the fractal characteristics of LFFs which is revealed by α. Our results support that the origin of RS-fMRI signals contains arterial fluctuations. Hence, in addition to the commonly used method such as synchrony analysis and power spectral analysis, another approach, the fractal analysis, is suggested for acquiring the information of hemodynamic responses by means

  11. Estimation for Up/Down Fluctuation of Stock Prices by Using Neural Network

    Science.gov (United States)

    Watanabe, Toyohide; Iwata, Kenji

    In general, it is not always easy to estimate stock prices exactly and get profits. Until today, many researchers have attacked to this subject, but could not report the successful estimation methods even if various approaches or many heuristics were applied in our knowledge-oriented society. This is because the fluctuation of stock prices is inherently characterized as random walk. In this paper, we address a short-term-specific up/down fluctuation estimation method of stock prices. Our approach is first to select 16 brand companies in Japan Stock Market as the fundamental stock features, and then to define analytically 8 stock attributes as input parameters for our 3-level neural network. We used 32,000 samples of 2,000 days from 16 brands: the first 1,000 days samples were used as learning data for our neural network; and the last 1,000 days samples were as test data. Our experiments showed that the up/down fluctuation estimation method in the short-term from the end value of today to the start value of tomorrow functions effectively.

  12. 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...

  13. Fluctuation-driven mechanotransduction regulates mitochondrial-network structure and function

    Science.gov (United States)

    Bartolák-Suki, Erzsébet; Imsirovic, Jasmin; Parameswaran, Harikrishnan; Wellman, Tyler J.; Martinez, Nuria; Allen, Philip G.; Frey, Urs; Suki, Béla

    2015-10-01

    Cells can be exposed to irregular mechanical fluctuations, such as those arising from changes in blood pressure. Here, we report that ATP production, assessed through changes in mitochondrial membrane potential, is downregulated in vascular smooth muscle cells in culture exposed to monotonous stretch cycles when compared with cells exposed to a variable cyclic stretch that incorporates physiological levels of cycle-by-cycle variability in stretch amplitude. Variable stretch enhances ATP production by increasing the expression of ATP synthase’s catalytic domain, cytochrome c oxidase and its tyrosine phosphorylation, mitofusins and PGC-1α. Such a fluctuation-driven mechanotransduction mechanism is mediated by motor proteins and by the enhancement of microtubule-, actin- and mitochondrial-network complexity. We also show that, in aorta rings isolated from rats, monotonous stretch downregulates--whereas variable stretch maintains--physiological vessel-wall contractility through mitochondrial ATP production. Our results have implications for ATP-dependent and mechanosensitive intracellular processes.

  14. 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.

  15. 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.

  16. 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...

  17. 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%.

  18. 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.

  19. Dynamics of simple gene-network motifs subject to extrinsic fluctuations

    Science.gov (United States)

    Roberts, Elijah; Be'er, Shay; Bohrer, Chris; Sharma, Rati; Assaf, Michael

    2015-12-01

    Cellular processes do not follow deterministic rules; even in identical environments genetically identical cells can make random choices leading to different phenotypes. This randomness originates from fluctuations present in the biomolecular interaction networks. Most previous work has been focused on the intrinsic noise (IN) of these networks. Yet, especially for high-copy-number biomolecules, extrinsic or environmental noise (EN) has been experimentally shown to dominate the variation. Here, we develop an analytical formalism that allows for calculation of the effect of EN on gene-expression motifs. We introduce a method for modeling bounded EN as an auxiliary species in the master equation. The method is fully generic and is not limited to systems with small EN magnitudes. We focus our study on motifs that can be viewed as the building blocks of genetic switches: a nonregulated gene, a self-inhibiting gene, and a self-promoting gene. The role of the EN properties (magnitude, correlation time, and distribution) on the statistics of interest are systematically investigated, and the effect of fluctuations in different reaction rates is compared. Due to its analytical nature, our formalism can be used to quantify the effect of EN on the dynamics of biochemical networks and can also be used to improve the interpretation of data from single-cell gene-expression experiments.

  20. 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.

  1. 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

  2. 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.

  3. 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...

  4. 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.

  5. 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.

  6. 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.

  7. 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...

  8. 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.

  9. 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.

  10. 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,…

  11. 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.

  12. 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...

  13. 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.

  14. 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.

  15. 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.

  16. 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...

  17. 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'...

  18. 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...

  19. 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.

  20. 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.

  1. A knowledge-based system for controlling automobile traffic

    Science.gov (United States)

    Maravas, Alexander; Stengel, Robert F.

    1994-01-01

    Transportation network capacity variations arising from accidents, roadway maintenance activity, and special events as well as fluctuations in commuters' travel demands complicate traffic management. Artificial intelligence concepts and expert systems can be useful in framing policies for incident detection, congestion anticipation, and optimal traffic management. This paper examines the applicability of intelligent route guidance and control as decision aids for traffic management. Basic requirements for managing traffic are reviewed, concepts for studying traffic flow are introduced, and mathematical models for modeling traffic flow are examined. Measures for quantifying transportation network performance levels are chosen, and surveillance and control strategies are evaluated. It can be concluded that automated decision support holds great promise for aiding the efficient flow of automobile traffic over limited-access roadways, bridges, and tunnels.

  2. 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.

  3. 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.

  4. 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].

  5. 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...

  6. 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.

  7. fMRI resting state networks and their association with cognitive fluctuations in dementia with Lewy bodies

    Directory of Open Access Journals (Sweden)

    Luis R. Peraza

    2014-01-01

    Full Text Available Cognitive fluctuations are a core symptom in dementia with Lewy bodies (DLB and may relate to pathological alterations in distributed brain networks. To test this we analysed resting state fMRI changes in a cohort of fluctuating DLB patients (n = 16 compared with age matched controls (n = 17 with the aim of finding functional connectivity (FC differences between these two groups and whether these associate with cognitive fluctuations in DLB. Resting state networks (RSNs were estimated using independent component analysis and FC between the RSN maps and the entirety of the brain was assessed using dual regression. The default mode network (DMN appeared unaffected in DLB compared to controls but significant cluster differences between DLB and controls were found for the left fronto-parietal, temporal, and sensory–motor networks. Desynchronization of a number of cortical and subcortical areas related to the left fronto-parietal network was associated with the severity and frequency of cognitive fluctuations. Our findings provide empirical evidence for the potential role of attention–executive networks in the aetiology of this core symptom in DLB.

  8. 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.

  9. 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.

  10. Evolution of gene regulatory networks by fluctuating selection and intrinsic constraints.

    Directory of Open Access Journals (Sweden)

    Masaki E Tsuda

    Full Text Available Various characteristics of complex gene regulatory networks (GRNs have been discovered during the last decade, e.g., redundancy, exponential indegree distributions, scale-free outdegree distributions, mutational robustness, and evolvability. Although progress has been made in this field, it is not well understood whether these characteristics are the direct products of selection or those of other evolutionary forces such as mutational biases and biophysical constraints. To elucidate the causal factors that promoted the evolution of complex GRNs, we examined the effect of fluctuating environmental selection and some intrinsic constraining factors on GRN evolution by using an individual-based model. We found that the evolution of complex GRNs is remarkably promoted by fixation of beneficial gene duplications under unpredictably fluctuating environmental conditions and that some internal factors inherent in organisms, such as mutational bias, gene expression costs, and constraints on expression dynamics, are also important for the evolution of GRNs. The results indicate that various biological properties observed in GRNs could evolve as a result of not only adaptation to unpredictable environmental changes but also non-adaptive processes owing to the properties of the organisms themselves. Our study emphasizes that evolutionary models considering such intrinsic constraining factors should be used as null models to analyze the effect of selection on GRN evolution.

  11. 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.

  12. 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

  13. 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...

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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%.

  19. 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...

  20. Periodic fluctuations in correlation-based connectivity density time series: Application to wind speed-monitoring network in Switzerland

    Science.gov (United States)

    Laib, Mohamed; Telesca, Luciano; Kanevski, Mikhail

    2018-02-01

    In this paper, we study the periodic fluctuations of connectivity density time series of a wind speed-monitoring network in Switzerland. By using the correlogram-based robust periodogram annual periodic oscillations were found in the correlation-based network. The intensity of such annual periodic oscillations is larger for lower correlation thresholds and smaller for higher. The annual periodicity in the connectivity density seems reasonably consistent with the seasonal meteo-climatic cycle.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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

  15. 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.

  16. 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

  17. Forecasting of groundwater level fluctuations using ensemble hybrid multi-wavelet neural network-based models.

    Science.gov (United States)

    Barzegar, Rahim; Fijani, Elham; Asghari Moghaddam, Asghar; Tziritis, Evangelos

    2017-12-01

    Accurate prediction of groundwater level (GWL) fluctuations can play an important role in water resources management. The aims of the research are to evaluate the performance of different hybrid wavelet-group method of data handling (WA-GMDH) and wavelet-extreme learning machine (WA-ELM) models and to combine different wavelet based models for forecasting the GWL for one, two and three months step-ahead in the Maragheh-Bonab plain, NW Iran, as a case study. The research used totally 367 monthly GWLs (m) datasets (Sep 1985-Mar 2016) which were split into two subsets; the first 312 datasets (85% of total) were used for model development (training) and the remaining 55 ones (15% of total) for model evaluation (testing). The stepwise selection was used to select appropriate lag times as the inputs of the proposed models. The performance criteria such as coefficient of determination (R2), root mean square error (RMSE) and Nash-Sutcliffe efficiency coefficient (NSC) were used for assessing the efficiency of the models. The results indicated that the ELM models outperformed GMDH models. To construct the hybrid wavelet based models, the inputs and outputs were decomposed into sub-time series employing different maximal overlap discrete wavelet transform (MODWT) functions, namely Daubechies, Symlet, Haar and Dmeyer of different orders at level two. Subsequently, these sub-time series were served in the GMDH and ELM models as an input dataset to forecast the multi-step-ahead GWL. The wavelet based models improved the performances of GMDH and ELM models for multi-step-ahead GWL forecasting. To combine the advantages of different wavelets, a least squares boosting (LSBoost) algorithm was applied. The use of the boosting multi-WA-neural network models provided the best performances for GWL forecasts in comparison with single WA-neural network-based models. Copyright © 2017 Elsevier B.V. All rights reserved.

  18. 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.

  19. Azimuthal pion fluctuation in ultra relativistic nuclear collisions and centrality dependence—a study with chaos based complex network analysis

    Science.gov (United States)

    Bhaduri, Anirban; Bhaduri, Susmita; Ghosh, Dipak

    2017-07-01

    Various works on multiplicity fluctuation have investigated the dynamics of particle production process and eventually have tried to reveal a signature of phase transition in ultra-relativistic nuclear collisions. Analysis of fluctuations of spatial patterns has been conducted in terms of conventional approach. However, analysis with fractal dynamics on the scaling behavior of the void has not been explored yet. In this work we have attempted to analyze pion fluctuation in terms of the scaling behavior of the void probability distribution in azimuthal space in ultra-relativistic nuclear collisions in the light of complex networks. A radically different and rigorous method viz. Visibility Graph was applied on the data of 32S-Ag/Br interaction at an incident energy of 200 GeV per nucleon. The analysis reveals strong scaling behavior of void probability distributions in azimuthal space and a strong centrality dependence.

  20. 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.

  1. 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...

  2. 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.

  3. Hidden geometry of traffic jamming

    Science.gov (United States)

    Andjelković, Miroslav; Gupte, Neelima; Tadić, Bosiljka

    2015-05-01

    We introduce an approach based on algebraic topological methods that allow an accurate characterization of jamming in dynamical systems with queues. As a prototype system, we analyze the traffic of information packets with navigation and queuing at nodes on a network substrate in distinct dynamical regimes. A temporal sequence of traffic density fluctuations is mapped onto a mathematical graph in which each vertex denotes one dynamical state of the system. The coupling complexity between these states is revealed by classifying agglomerates of high-dimensional cliques that are intermingled at different topological levels and quantified by a set of geometrical and entropy measures. The free-flow, jamming, and congested traffic regimes result in graphs of different structure, while the largest geometrical complexity and minimum entropy mark the edge of the jamming region.

  4. 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.

  5. Escape routes, weak links, and desynchronization in fluctuation-driven networks

    DEFF Research Database (Denmark)

    Schäfer, Benjamin; Matthiae, Moritz; Zhang, Xiaozhu

    2017-01-01

    on fundamental noise models, we derive analytic insights into which factors limit the dynamic robustness and how fluctuations may induce a system escape from an operating state. Moreover, we identify weak links in the grid that make it particularly vulnerable to fluctuations. These results thereby not only...

  6. Network models predict that reduced excitatory fluctuations can give rise to hippocampal network hyper-excitability in MeCP2-null mice.

    Directory of Open Access Journals (Sweden)

    Ernest C Y Ho

    Full Text Available Rett syndrome is a severe pediatric neurological disorder caused by loss of function mutations within the gene encoding methyl CpG-binding protein 2 (MeCP2. Although MeCP2 is expressed near ubiquitously, the primary pathophysiology of Rett syndrome stems from impairments of nervous system function. One alteration within different regions of the MeCP2-deficient brain is the presence of hyper-excitable network responses. In the hippocampus, such responses exist despite there being an overall decrease in spontaneous excitatory drive within the network. In this study, we generated and used mathematical, neuronal network models to resolve this apparent paradox. We did this by taking advantage of previous mathematical modelling insights that indicated that decreased excitatory fluctuations, but not mean excitatory drive, more critically explain observed changes in hippocampal network oscillations from MeCP2-null mouse slices. Importantly, reduced excitatory fluctuations could also bring about hyper-excitable responses in our network models. Therefore, these results indicate that diminished excitatory fluctuations may be responsible for the hyper-excitable state of MeCP2-deficient hippocampal circuitry.

  7. 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....

  8. 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.

  9. 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....

  10. 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...

  11. Default network is not hypoactive in dementia with fluctuating cognition: an Alzheimer disease/dementia with Lewy bodies comparison.

    Science.gov (United States)

    Franciotti, Raffaella; Falasca, Nicola Walter; Bonanni, Laura; Anzellotti, Francesca; Maruotti, Valerio; Comani, Silvia; Thomas, Astrid; Tartaro, Armando; Taylor, John-Paul; Onofrj, Marco

    2013-04-01

    Default mode network resting state activity in posterior cingulate cortex is abnormally reduced in Alzheimer disease (AD) patients. Fluctuating cognition and electroencephalogram abnormalities are established core and supportive elements respectively for the diagnosis of dementia with Lewy bodies (DLB). Our aim was to assess whether patients with DLB with both of these features have different default mode network patterns during resting state functional magnetic resonance imaging compared with AD. Eighteen patients with DLB, 18 AD patients without fluctuating cognition, and 15 control subjects were selected after appropriate matching and followed for 2-5 years to confirm diagnosis. Independent component analysis with functional connectivity (FC) and Granger causality approaches were applied to isolate and characterize resting state networks. FC was reduced in AD and DLB patients compared with control subjects. Posterior cingulate cortex activity was lower in AD than in control subjects and DLB patients (p < 0.05). Right hemisphere FC was reduced in DLB patients in comparison with control subjects but not in patients with AD, and was correlated with severity of fluctuations (ρ = -0.69; p < 0.01). Causal flow analysis showed differences between patients with DLB and AD and control subjects. Copyright © 2013. Published by Elsevier Inc.

  12. 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...

  13. 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, ...

  14. 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 ...

  15. 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...

  16. 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...

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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

  2. Predicting the Water Level Fluctuation in an Alpine Lake Using Physically Based, Artificial Neural Network, and Time Series Forecasting Models

    Directory of Open Access Journals (Sweden)

    Chih-Chieh Young

    2015-01-01

    Full Text Available Accurate prediction of water level fluctuation is important in lake management due to its significant impacts in various aspects. This study utilizes four model approaches to predict water levels in the Yuan-Yang Lake (YYL in Taiwan: a three-dimensional hydrodynamic model, an artificial neural network (ANN model (back propagation neural network, BPNN, a time series forecasting (autoregressive moving average with exogenous inputs, ARMAX model, and a combined hydrodynamic and ANN model. Particularly, the black-box ANN model and physically based hydrodynamic model are coupled to more accurately predict water level fluctuation. Hourly water level data (a total of 7296 observations was collected for model calibration (training and validation. Three statistical indicators (mean absolute error, root mean square error, and coefficient of correlation were adopted to evaluate model performances. Overall, the results demonstrate that the hydrodynamic model can satisfactorily predict hourly water level changes during the calibration stage but not for the validation stage. The ANN and ARMAX models better predict the water level than the hydrodynamic model does. Meanwhile, the results from an ANN model are superior to those by the ARMAX model in both training and validation phases. The novel proposed concept using a three-dimensional hydrodynamic model in conjunction with an ANN model has clearly shown the improved prediction accuracy for the water level fluctuation.

  3. 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

  4. 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...

  5. Synchronization transitions induced by the fluctuation of adaptive coupling strength in delayed Newman-Watts neuronal networks.

    Science.gov (United States)

    Wang, Qi; Gong, Yubing; Wu, Yanan

    2015-11-01

    Introducing adaptive coupling in delayed neuronal networks and regulating the dissipative parameter (DP) of adaptive coupling by noise, we study the effect of fluctuations of the changing rate of adaptive coupling on the synchronization of the neuronal networks. It is found that time delay can induce synchronization transitions for intermediate DP values, and the synchronization transitions become strongest when DP is optimal. As the intensity of DP noise is varied, the neurons can also exhibit synchronization transitions, and the phenomenon is delay-dependent and is enhanced for certain time delays. Moreover, the synchronization transitions change with the change of DP and become strongest when DP is optimal. These results show that randomly changing adaptive coupling can considerably change the synchronization of the neuronal networks, and hence could play a crucial role in the information processing and transmission in neural systems. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  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. Arterial CO2 Fluctuations Modulate Neuronal Rhythmicity: Implications for MEG and fMRI Studies of Resting-State Networks.

    Science.gov (United States)

    Driver, Ian D; Whittaker, Joseph R; Bright, Molly G; Muthukumaraswamy, Suresh D; Murphy, Kevin

    2016-08-17

    A fast emerging technique for studying human resting state networks (RSNs) is based on spontaneous temporal fluctuations in neuronal oscillatory power, as measured by magnetoencephalography. However, it has been demonstrated recently that this power is sensitive to modulations in arterial CO2 concentration. Arterial CO2 can be modulated by natural fluctuations in breathing pattern, as might typically occur during the acquisition of an RSN experiment. Here, we demonstrate for the first time the fine-scale dependence of neuronal oscillatory power on arterial CO2 concentration, showing that reductions in alpha, beta, and gamma power are observed with even very mild levels of hypercapnia (increased arterial CO2). We use a graded hypercapnia paradigm and participant feedback to rule out a sensory cause, suggesting a predominantly physiological origin. Furthermore, we demonstrate that natural fluctuations in arterial CO2, without administration of inspired CO2, are of a sufficient level to influence neuronal oscillatory power significantly in the delta-, alpha-, beta-, and gamma-frequency bands. A more thorough understanding of the relationship between physiological factors and cortical rhythmicity is required. In light of these findings, existing results, paradigms, and analysis techniques for the study of resting-state brain data should be revisited. In this study, we show for the first time that neuronal oscillatory power is intimately linked to arterial CO2 concentration down to the fine-scale modulations that occur during spontaneous breathing. We extend these results to demonstrate a correlation between neuronal oscillatory power and spontaneous arterial CO2 fluctuations in awake humans at rest. This work identifies a need for studies investigating resting-state networks in the human brain to measure and account for the impact of spontaneous changes in arterial CO2 on the neuronal signals of interest. Changes in breathing pattern that are time locked to task

  8. 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

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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

  14. 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.

  15. Reverse-engineering of biochemical reaction networks from spatio-temporal correlations of fluorescence fluctuations.

    Science.gov (United States)

    Tanaka, Natsuki; Papoian, Garegin A

    2010-05-21

    Recent developments of fluorescence labeling and highly advanced microscopy techniques have enabled observations of activities of biosignaling molecules in living cells. The high spatial and temporal resolutions of these video microscopy experiments allow detection of fluorescence fluctuations at the timescales approaching those of enzymatic reactions. Such fluorescence fluctuation patterns may contain information about the complex reaction-diffusion system driving the dynamics of the labeled molecule. Here, we have developed a method of identifying the reaction-diffusion system of fluorescently labeled signaling molecules in the cell, by combining spatio-temporal correlation function analysis of fluctuating fluorescent patterns, stochastic reaction-diffusion simulations, and an iterative system identification technique using a simulated annealing algorithm. In this report, we discuss the validity and usability of spatio-temporal correlation functions in characterizing the reaction-diffusion dynamics of biomolecules, and demonstrate application of our reaction-diffusion system identification method to a simple conceptual model for small GTPase activation. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

  16. Dynamic fluctuations coincide with periods of high and low modularity in resting-state functional brain networks.

    Science.gov (United States)

    Betzel, Richard F; Fukushima, Makoto; He, Ye; Zuo, Xi-Nian; Sporns, Olaf

    2016-02-15

    We investigate the relationship of resting-state fMRI functional connectivity estimated over long periods of time with time-varying functional connectivity estimated over shorter time intervals. We show that using Pearson's correlation to estimate functional connectivity implies that the range of fluctuations of functional connections over short time-scales is subject to statistical constraints imposed by their connectivity strength over longer scales. We present a method for estimating time-varying functional connectivity that is designed to mitigate this issue and allows us to identify episodes where functional connections are unexpectedly strong or weak. We apply this method to data recorded from N=80 participants, and show that the number of unexpectedly strong/weak connections fluctuates over time, and that these variations coincide with intermittent periods of high and low modularity in time-varying functional connectivity. We also find that during periods of relative quiescence regions associated with default mode network tend to join communities with attentional, control, and primary sensory systems. In contrast, during periods where many connections are unexpectedly strong/weak, default mode regions dissociate and form distinct modules. Finally, we go on to show that, while all functional connections can at times manifest stronger (more positively correlated) or weaker (more negatively correlated) than expected, a small number of connections, mostly within the visual and somatomotor networks, do so a disproportional number of times. Our statistical approach allows the detection of functional connections that fluctuate more or less than expected based on their long-time averages and may be of use in future studies characterizing the spatio-temporal patterns of time-varying functional connectivity. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

  17. 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.

  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. Propagation of fluctuations in interaction networks governed by the law of mass action

    CERN Document Server

    Maslov, Sergei; Ispolatov, Iaroslav

    2007-01-01

    Using an example of physical interactions between proteins, we study how perturbations propagate in interconnected networks whose equilibrium state is governed by the law of mass action. We introduce a comprehensive matrix formalism which predicts the response of this equilibrium to small changes in total concentrations of individual molecules, and explain it using a heuristic analogy to a current flow in a network of resistors. Our main conclusion is that on average changes in free concentrations exponentially decay with the distance from the source of perturbation. We then study how this decay is influenced by such factors as the topology of a network, binding strength, and correlations between concentrations of neighboring nodes. An exact analytic expression for the decay constant is obtained for the case of uniform interactions on the Bethe lattice. Our general findings are illustrated using a real biological network of protein-protein interactions in baker's yeast with experimentally determined protein c...

  1. 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

  2. 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...

  3. 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...

  4. Dwelling Quietly in the Rich Club: Brain Network Determinants of Slow Cortical Fluctuations

    CERN Document Server

    Gollo, Leonardo L; Hutchison, R Matthew; Heuvel, Martijn van den; Breakspear, Michael

    2016-01-01

    For more than a century, cerebral cartography has been driven by investigations of structural and morphological properties of the brain across spatial scales and the temporal/functional phenomena that emerge from these underlying features. The next era of brain mapping will be driven by studies that consider both of these components of brain organization simultaneously -- elucidating their interactions and dependencies. Using this guiding principle, we explored the origin of slowly fluctuating patterns of synchronization within the topological core of brain regions known as the rich club, implicated in the regulation of mood and introspection. We find that a constellation of densely interconnected regions that constitute the rich club (including the anterior insula, amygdala, and precuneus) play a central role in promoting a stable, dynamical core of spontaneous activity in the primate cortex. The slow time scales are well matched to the regulation of internal visceral states, corresponding to the somatic cor...

  5. Lognormal firing rate distribution reveals prominent fluctuation-driven regime in spinal motor networks

    DEFF Research Database (Denmark)

    Petersen, Peter C.; Berg, Rune W.

    2016-01-01

    When spinal circuits generate rhythmic movements it is important that the neuronal activity remains within stable bounds to avoid saturation and to preserve responsiveness. Here, we simultaneously record from hundreds of neurons in lumbar spinal circuits of turtles and establish the neuronal...... fraction that operates within either a ‘mean-driven’ or a ‘fluctuation–driven’ regime. Fluctuation-driven neurons have a ‘supralinear’ input-output curve, which enhances sensitivity, whereas the mean-driven regime reduces sensitivity. We find a rich diversity of firing rates across the neuronal population...... as reflected in a lognormal distribution and demonstrate that half of the neurons spend at least 50 %% of the time in the ‘fluctuation–driven’ regime regardless of behavior. Because of the disparity in input–output properties for these two regimes, this fraction may reflect a fine trade–off between stability...

  6. Interictal functional connectivity of human epileptic networks assessed by intracerebral EEG and BOLD signal fluctuations.

    Directory of Open Access Journals (Sweden)

    Gaelle Bettus

    Full Text Available In this study, we aimed to demonstrate whether spontaneous fluctuations in the blood oxygen level dependent (BOLD signal derived from resting state functional magnetic resonance imaging (fMRI reflect spontaneous neuronal activity in pathological brain regions as well as in regions spared by epileptiform discharges. This is a crucial issue as coherent fluctuations of fMRI signals between remote brain areas are now widely used to define functional connectivity in physiology and in pathophysiology. We quantified functional connectivity using non-linear measures of cross-correlation between signals obtained from intracerebral EEG (iEEG and resting-state functional MRI (fMRI in 5 patients suffering from intractable temporal lobe epilepsy (TLE. Functional connectivity was quantified with both modalities in areas exhibiting different electrophysiological states (epileptic and non affected regions during the interictal period. Functional connectivity as measured from the iEEG signal was higher in regions affected by electrical epileptiform abnormalities relative to non-affected areas, whereas an opposite pattern was found for functional connectivity measured from the BOLD signal. Significant negative correlations were found between the functional connectivities of iEEG and BOLD signal when considering all pairs of signals (theta, alpha, beta and broadband and when considering pairs of signals in regions spared by epileptiform discharges (in broadband signal. This suggests differential effects of epileptic phenomena on electrophysiological and hemodynamic signals and/or an alteration of the neurovascular coupling secondary to pathological plasticity in TLE even in regions spared by epileptiform discharges. In addition, indices of directionality calculated from both modalities were consistent showing that the epileptogenic regions exert a significant influence onto the non epileptic areas during the interictal period. This study shows that functional

  7. 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.

  8. 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.

  9. 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.

  10. 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....

  11. Evolution of Chinese airport network

    CERN Document Server

    Zhang, Jun; Du, Wen-Bo; Cai, Kai-Quan

    2011-01-01

    With the rapid development of economy and the accelerated globalization process, the aviation industry plays more and more critical role in today's world, in both developed and developing countries. As the infrastructure of aviation industry, the airport network is one of the most important indicators of economic growth. In this paper, we investigate the evolution of Chinese airport network (CAN) via complex network theory. It is found that although the topology of CAN remains steady during the past several years, there are many dynamic switchings inside the network, which changes the relative relevance of airports and airlines. Moreover, we investigate the evolution of traffic flow (passengers and cargoes) on CAN. It is found that the traffic keeps growing in an exponential form and it has evident seasonal fluctuations. We also found that cargo traffic and passenger traffic are positively related but the correlations are quite different for different kinds of cities.

  12. 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.

  13. 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.

  14. 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

  15. 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

  16. 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...

  17. 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...

  18. 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 ...

  19. Deformation and concentration fluctuations under stretching in a polymer network with free chains. The ``butterfly`` effect; Fluctuations de deformation et de concentration sous etirement dans un reseau polymere contenant des chaines libres. L`effet ``papillon``

    Energy Technology Data Exchange (ETDEWEB)

    Ramzi, A.

    1994-06-01

    Small Angle Neutron Scattering gives access to concentration fluctuations of mobile labeled polymer chains embedded in a polymer network. At rest they appear progressively larger than for random mixing, with increasing ratio. Under uniaxial stretching, they decrease towards ideal mixing along the direction perpendicular to stretching, and can grow strongly along the parallel one, including the zero scattering vector q limit. This gives rise to intensity contours with double-winged patterns, in the shape of the figure `8`, or of `butterfly`. Random crosslinking and end-linking of monodisperse chains have both been studied. The strength of the `butterfly` effect increases with the molecular weight of the free chains, the crosslinking ratio, the network heterogeneity, and the elongation ratio. Eventually, the signal collapses on an `asymptotic` function I(q), of increasing correlation length with the elongation ratio. Deformation appears heterogeneous, maximal for soft areas, where the mobile chains localize preferentially. This could be due to spontaneous fluctuations, or linked to frozen fluctuations of the crosslink density. However, disagreement with the corresponding theoretical expressions makes it necessary to account for the spatial correlations of crosslink density, and their progressive unscreening as displayed by the asymptotic behavior. Networks containing pending labeled chains and free labeled stars lead to more precise understanding of the diffusion of free species and the heterogeneity of the deformation. It seems that the latter occurs even without diffusion for heterogeneous enough networks. In extreme cases (of the crosslinking parameters), the spatial correlations display on apparent fractal behavior, of dimensions 2 to 2.5, which is discussed here in terms of random clusters. 200 refs., 95 figs., 21 tabs., 10 appends.

  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. 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...

  2. 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,...

  3. 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...

  4. 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....

  5. 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...

  6. Analysis of the impact of crude oil price fluctuations on China's stock market in different periods-Based on time series network model

    Science.gov (United States)

    An, Yang; Sun, Mei; Gao, Cuixia; Han, Dun; Li, Xiuming

    2018-02-01

    This paper studies the influence of Brent oil price fluctuations on the stock prices of China's two distinct blocks, namely, the petrochemical block and the electric equipment and new energy block, applying the Shannon entropy of information theory. The co-movement trend of crude oil price and stock prices is divided into different fluctuation patterns with the coarse-graining method. Then, the bivariate time series network model is established for the two blocks stock in five different periods. By joint analysis of the network-oriented metrics, the key modes and underlying evolutionary mechanisms were identified. The results show that the both networks have different fluctuation characteristics in different periods. Their co-movement patterns are clustered in some key modes and conversion intermediaries. The study not only reveals the lag effect of crude oil price fluctuations on the stock in Chinese industry blocks but also verifies the necessity of research on special periods, and suggests that the government should use different energy policies to stabilize market volatility in different periods. A new way is provided to study the unidirectional influence between multiple variables or complex time series.

  7. 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...

  8. Signal Fluctuation Sensitivity: An Improved Metric for Optimizing Detection of Resting-State fMRI Networks

    Science.gov (United States)

    DeDora, Daniel J.; Nedic, Sanja; Katti, Pratha; Arnab, Shafique; Wald, Lawrence L.; Takahashi, Atsushi; Van Dijk, Koene R. A.; Strey, Helmut H.; Mujica-Parodi, Lilianne R.

    2016-01-01

    Task-free connectivity analyses have emerged as a powerful tool in functional neuroimaging. Because the cross-correlations that underlie connectivity measures are sensitive to distortion of time-series, here we used a novel dynamic phantom to provide a ground truth for dynamic fidelity between blood oxygen level dependent (BOLD)-like inputs and fMRI outputs. We found that the de facto quality-metric for task-free fMRI, temporal signal to noise ratio (tSNR), correlated inversely with dynamic fidelity; thus, studies optimized for tSNR actually produced time-series that showed the greatest distortion of signal dynamics. Instead, the phantom showed that dynamic fidelity is reasonably approximated by a measure that, unlike tSNR, dissociates signal dynamics from scanner artifact. We then tested this measure, signal fluctuation sensitivity (SFS), against human resting-state data. As predicted by the phantom, SFS—and not tSNR—is associated with enhanced sensitivity to both local and long-range connectivity within the brain's default mode network. PMID:27199643

  9. 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.

  10. Noise-induced organized slow fluctuations in networks of neural areas with interarea feed-forward excitation and inhibition.

    Science.gov (United States)

    Lee, Dongmyeong; Kim, Seunghwan; Ko, Tae-Wook

    2014-06-01

    Slow coherent spontaneous fluctuations (feed-forward inhibition in addition to excitation between brain areas, which we assume to be in up (active) or down (quiescent) states, we propose a model for the generation and organization of the slow fluctuations. Connectivity with feed-forward excitation and inhibition between the areas makes the system have multiple stable states and organized slow fluctuations manifest as noise-induced slow transitions between the states. With various connectivities, we observe slow fluctuations and various organizations, including anticorrelated clusters, through numerical simulations.

  11. 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.

  12. Constant properties of plant-frugivore networks despite fluctuations in fruit and bird communities in space and time.

    Science.gov (United States)

    Plein, Michaela; Längsfeld, Laura; Neuschulz, Eike Lena; Schultheiss, Christina; Ingmann, Lili; Töpfer, Till; Böhning-Gaese, Katrin; Schleuning, Matthias

    2013-06-01

    along gradients of structural diversity at the landscape scale. Although seasonal fluctuations influenced the functional diversity of avian frugivore communities, we found constant interaction diversity of plant-frugivore networks in space and time, probably due to the functional redundancy of frugivorous birds. These findings indicate a high robustness of avian frugivory to moderate levels of human-induced landscape modification in temperate ecosystems and call for studies testing the generality of these findings for ultimate avian seed dispersal functions.

  13. Investigating the Geoelectric Fluctuations Measured in Izmir-Urla-Demircili Village (Western Turkey) with Artificial Neural Networks

    Science.gov (United States)

    Sindirgi, Petek; Kaftan, Ilknur

    2013-04-01

    Turkey is one of the countries frequently facing significant earthquakes because of its geological and tectonic position on the earth. Especially, graben systems of Western Turkey occur as a result of seismically quite active tensional tectonics. Prediction of earthquakes has been one of the important subjects taking interest of human being for a long time. Recently Artificial Neural Networks (ANN) is being used for earthquake prediction besides its successful application to broad spectrum of data-intensive applications from stock market prediction to process control. ANN was used to predict time of occurrence and the locations of the earthquakes, experienced for a specified time interval. Also ANN were analyzed the predictability of time series. İzmir city and its surroundings are located in the strike-slip dominated zone of weakness known as the İzmir-Balıkesir Transfer Zone. The latest activity of the zone was evidenced by the Urla and Sıǧacık earthquakes. 10 April 2003 Urla (M=5.7) and 17-21 October 2005 (M=5.7, M=5.9 and M=5.9) Sıǧacık earthquakes were the important seismic activities in the region. Recently, geoelectrical fluctuations measured in seismic areas have been attributed to stress and strain changes, associated with earthquakes. This study has been realized for the evaluation of self potential (SP) and ground temperature monitoring data, which has been collected from İzmir-Urla-Demircili Village, to investigate the relationship of the SP and the seasonal climatic changing and earthquakes. Collected data during the eight months has been evaluated by artificial neural networks. Ground temperature and SP data has been recorded as a function of time. In addition to these two variables with each other relations, the relationship with daily average of SP data to daily rainfall and earthquakes were also investigated. We analyzed the correlation between the sequence of extreme events in geoelectrical signals, measured by the monitoring station

  14. 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.

  15. A new approach of chaos and complex network method to study fluctuation and phase transition in nuclear collision at high energy

    Energy Technology Data Exchange (ETDEWEB)

    Bhaduri, Susmita; Bhaduri, Anirban; Ghosh, Dipak [Deepa Ghosh Research Foundation, Kolkata (India)

    2017-06-15

    In the endeavour to study fluctuation and a signature of phase transition in ultrarelativistic nuclear collision during the process of particle production, an approach based on chaos and complex network is proposed. In this work we have attempted an exhaustive study of pion fluctuation in η space, φ space, their cross-correlation and finally two-dimensional fluctuation in terms of scaling of void probability distribution. The analysis is done on the η values and their corresponding φ values extracted from the {sup 32}S-Ag/Br interaction at an incident energy of 200 GeV per nucleon. The methods used are Multifractal Detrended Cross-Correlation Analysis (MF-DXA) and a chaos-based rigorous complex network method -Visibility Graph. The analysis reveals that the highest degree of cross-correlation between pseudorapidity and azimuthal angles exists in the most central region of the interaction. The analysis further shows that two-dimensional void distribution corresponding to the η-φ space reveals a strong scaling behaviour. Both cross-correlation coefficients of MF-DXA and PSVG (Power of the Scale-freeness in Visibility Graph, which is implicitly connected with the Hurst exponent) can be effectively used for the quantitative assessment of pion fluctuation in a very precise manner and have the capability to assess the tendency of approaching criticality for phase transitions. (orig.)

  16. A Virtual Channel Network-on-Chip for GT and BE traffic

    NARCIS (Netherlands)

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

    2005-01-01

    This paper presents an on-chip network for a run-time reconfigurable System-on-Chip. The network uses packet-switching with virtual channels. It can provide guaranteed services as well as best effort services. The guaranteed services are based on virtual channel allocation, in contrast to other

  17. Energy savings in dynamic and resilient optical networks based on traffic-aware strategies

    DEFF Research Database (Denmark)

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

    2014-01-01

    -mode and rate adaptive capabilities) is implementedwithin atraffic-aware networking approach.The impact of dedicated 1:1protection in a dynamic network scenarioisconsideredandacomparison is madewith the unprotected case. A GMPLS controlplane is implemented and used to re-configure the power-adaptive devices...

  18. Dynamic aggregation of traffic flows in SDN Applied to backhaul networks

    DEFF Research Database (Denmark)

    Kentis, Angelos Mimidis; Caba, Cosmin Marius; Soler, José

    2016-01-01

    A challenge in the adoption of the OpenFlow (OF)-based SDN paradigm is related to the limited number of OF rules supported by the network devices. The technology used to implement the OF rules is TCAM, which is expensive and power demanding. Due to this, the network devices are either very costly...

  19. A New Prediction Model for Transformer Winding Hotspot Temperature Fluctuation Based on Fuzzy Information Granulation and an Optimized Wavelet Neural Network

    Directory of Open Access Journals (Sweden)

    Li Zhang

    2017-12-01

    Full Text Available Winding hotspot temperature is the key factor affecting the load capacity and service life of transformers. For the early detection of transformer winding hotspot temperature anomalies, a new prediction model for the hotspot temperature fluctuation range based on fuzzy information granulation (FIG and the chaotic particle swarm optimized wavelet neural network (CPSO-WNN is proposed in this paper. The raw data are firstly processed by FIG to extract useful information from each time window. The extracted information is then used to construct a wavelet neural network (WNN prediction model. Furthermore, the structural parameters of WNN are optimized by chaotic particle swarm optimization (CPSO before it is used to predict the fluctuation range of the hotspot temperature. By analyzing the experimental data with four different prediction models, we find that the proposed method is more effective and is of guiding significance for the operation and maintenance of transformers.

  20. Visualization of Traffic Accidents

    Science.gov (United States)

    Wang, Jie; Shen, Yuzhong; Khattak, Asad

    2010-01-01

    Traffic accidents have tremendous impact on society. Annually approximately 6.4 million vehicle accidents are reported by police in the US and nearly half of them result in catastrophic injuries. Visualizations of traffic accidents using geographic information systems (GIS) greatly facilitate handling and analysis of traffic accidents in many aspects. Environmental Systems Research Institute (ESRI), Inc. is the world leader in GIS research and development. ArcGIS, a software package developed by ESRI, has the capabilities to display events associated with a road network, such as accident locations, and pavement quality. But when event locations related to a road network are processed, the existing algorithm used by ArcGIS does not utilize all the information related to the routes of the road network and produces erroneous visualization results of event locations. This software bug causes serious problems for applications in which accurate location information is critical for emergency responses, such as traffic accidents. This paper aims to address this problem and proposes an improved method that utilizes all relevant information of traffic accidents, namely, route number, direction, and mile post, and extracts correct event locations for accurate traffic accident visualization and analysis. The proposed method generates a new shape file for traffic accidents and displays them on top of the existing road network in ArcGIS. Visualization of traffic accidents along Hampton Roads Bridge Tunnel is included to demonstrate the effectiveness of the proposed method.

  1. Energy-Efficient Multicasting of Session Traffic in Bandwidth- and Transceiver-Limited Wireless Networks

    National Research Council Canada - National Science Library

    Wieselthier, Jeffrey E; Nguyen, Gam D; Ephremides, Anthony

    2002-01-01

    In this paper, we address the impact of resource limitations on the operation and performance of the broadcasting and multicasting schemes developed for infrastructureless wireless networks in our earlier studies...

  2. Report: Improvements Needed in EPA’s Network Traffic Management Practices

    Science.gov (United States)

    Report #11-P-0159, March 14, 2011. OEI does not have consistent, repeatable intrusion detection system monitoring practices in place, which inhibits EPA’s ability to monitor unusual network activity and thus protect Agency systems and associated data.

  3. IPTV traffic management using topology-based hierarchical scheduling in Carrier Ethernet transport networks

    DEFF Research Database (Denmark)

    Yu, Hao; Yan, Ying; Berger, Michael Stubert

    2009-01-01

    Carrier Ethernet is becoming a favorable access technology for Next Generation Network (NGN). The features of cost-efficiency, operation flexibility and high bandwidth have a great attraction to service providers. However, to achieve these characteristics, Carrier Ethernet needs to have Quality o....... This work has been carried out as a part of the research project HIPT (High quality IP network for IPTV and VoIP) founded by Danish Advanced Technology Foundation....

  4. Stochastic Model of Traffic Jam and Traffic Signal Control

    Science.gov (United States)

    Shin, Ji-Sun; Cui, Cheng-You; Lee, Tae-Hong; Lee, Hee-Hyol

    Traffic signal control is an effective method to solve the traffic jam. and forecasting traffic density has been known as an important part of the Intelligent Transportation System (ITS). The several methods of the traffic signal control are known such as random walk method, Neuron Network method, Bayesian Network method, and so on. In this paper, we propose a new method of a traffic signal control using a predicted distribution of traffic jam based on a Dynamic Bayesian Network model. First, a forecasting model to predict a probabilistic distribution of the traffic jam during each period of traffic lights is built. As the forecasting model, the Dynamic Bayesian Network is used to predict the probabilistic distribution of a density of the traffic jam. According to measurement of two crossing points for each cycle, the inflow and outflow of each direction and the number of standing vehicles at former cycle are obtained. The number of standing vehicle at k-th cycle will be calculated synchronously. Next, the probabilistic distribution of the density of standing vehicle in each cycle will be predicted using the Dynamic Bayesian Network constructed for the traffic jam. And then a control rule to adjust the split and the cycle to increase the probability between a lower limit and ceiling of the standing vehicles is deduced. As the results of the simulation using the actual traffic data of Kitakyushu city, the effectiveness of the method is shown.

  5. ReFlow: Reports on Internet Traffic

    NARCIS (Netherlands)

    Hoogesteger, Martijn; de Oliveira Schmidt, R.; Sperotto, Anna; Pras, Aiko

    Internet traffic statistics can provide valuable information to network analysts and researchers about the traffic, technologies and main characteristics of today’s networks. For many years Internet2 maintained a public website with statistics about the traffic in the Abilene network. This site was

  6. Traffic Load on Interconnection Lines of Generalized Double Ring Network Structures

    DEFF Research Database (Denmark)

    Pedersen, Jens Myrup; Riaz, Muhammad Tahir; Madsen, Ole Brun

    2005-01-01

    Generalized Double Ring (N2R) network structures possess a number of good properties, but being not planar they are hard to physically embed in communication networks. However, if some of the lines, the interconnection lines, are implemented by wireless technologies, the remaining structure...... consists of two planar rings, which are easily embedded by fiber or other wired solutions. It is shown that for large N2R structures, the interconnection lines carry notably lower loads than the other lines if shortest-path routing is used, and the effects of two other routing schemes are explored, leading...

  7. Traffic Load on Interconnection Lines of Generalized Double Ring Network Structures

    DEFF Research Database (Denmark)

    Pedersen, Jens Myrup; Riaz, Muhammad Tahir; Madsen, Ole Brun

    2004-01-01

    Generalized Double Ring (N2R) network structures possess a number of good properties, but being not planar they are hard to physically embed in communication networks. However, if some of the lines, the interconnection lines, are implemented by wireless technologies, the remaining structure...... consists of two planar rings, which are easily embedded by fiber or other wired solutions. It is shown that for large N2R structures, the interconnection lines carry notably lower loads than the other lines if shortest-path routing is used, and the effects of two other routing schemes are explored, leading...

  8. CoreFlow: Enriching Bro security events using network traffic monitoring data

    NARCIS (Netherlands)

    Koning, R.; Buraglio, N.; de Laat, C.; Grosso, P.

    Attacks against network infrastructures can be detected by Intrusion Detection Systems (IDS). Still reaction to these events are often limited by the lack of larger contextual information in which they occurred. In this paper we present CoreFlow, a framework for the correlation and enrichment of IDS

  9. Monitoring of traffic noise in an urban area using a wireless sensor network

    NARCIS (Netherlands)

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

    2014-01-01

    Developments in systems for monitoring environmental noise have made it possible to monitor the acoustic situation within large urban areas. The developments in hardware size and costs, combined with the developments in wireless communication allow to deploy networks with many acoustic sensors

  10. Power Efficient Service Differentiation Based on Traffic-Aware Survivable Elastic Optical Networks

    DEFF Research Database (Denmark)

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

    2014-01-01

    This study assesses the feasible energy savings whendefining different service classes based on protection schemesincore optical networks.Wepropose a dedicated energy savingstrategy for each of the service classes in order to minimize theoverall power consumption of the network.Four Classes of Se...... while for the proposed approach the difference in power consumption is almost negligible.Moreover, incase of the proposed approach,silver serviceclass can benefit for superior quality of service compared to the gold service class, due to the grooming mechanism.......This study assesses the feasible energy savings whendefining different service classes based on protection schemesincore optical networks.Wepropose a dedicated energy savingstrategy for each of the service classes in order to minimize theoverall power consumption of the network.Four Classes...... of Serviceareconsidered: platinum, gold, silver and best effort.Platinumconnections benefit from a 1+1 protection scheme, gold connections and silver connections are assigned to a 1:1 protection with the difference that in case of gold connections the same pair of transponders is shared by the working and protection...

  11. VBR video traffic models

    CERN Document Server

    Tanwir, Savera

    2014-01-01

    There has been a phenomenal growth in video applications over the past few years. An accurate traffic model of Variable Bit Rate (VBR) video is necessary for performance evaluation of a network design and for generating synthetic traffic that can be used for benchmarking a network. A large number of models for VBR video traffic have been proposed in the literature for different types of video in the past 20 years. Here, the authors have classified and surveyed these models and have also evaluated the models for H.264 AVC and MVC encoded video and discussed their findings.

  12. Adapting risk management and computational intelligence network optimization techniques to improve traffic throughput and tail risk analysis.

    Science.gov (United States)

    2014-04-01

    Risk management techniques are used to analyze fluctuations in uncontrollable variables and keep those fluctuations from impeding : the core function of a system or business. Examples of this are making sure that volatility in copper and aluminum pri...

  13. Performance Testing of GPU-Based Approximate Matching Algorithm on Network Traffic

    Science.gov (United States)

    2015-03-01

    26  E .  COMPARING REFERENCE SET AND TARGET SET USING THE CPU IMPLEMENTATION OF SDHASH...network either by sending it as an attachment in electronic mail (email), Instant Messenger (IM), posting it on social media sites such as Facebook ... Instagram , Twitter, LinkedIn, etc., or transferring it to cloud storage services such as Google Drive, Microsoft OneDrive, DropBox, Apple iCloud. In

  14. TCP Traffic Control Evaluation and Reduction over Wireless Networks Using Parallel Sequential Decoding Mechanism

    Directory of Open Access Journals (Sweden)

    Ramazan Aygün

    2007-11-01

    Full Text Available The assumption of TCP-based protocols that packet error (lost or damaged is due to network congestion is not true for wireless networks. For wireless networks, it is important to reduce the number of retransmissions to improve the effectiveness of TCP-based protocols. In this paper, we consider improvement at the data link layer for systems that use stop-and-wait ARQ as in IEEE 802.11 standard. We show that increasing the buffer size will not solve the actual problem and moreover it is likely to degrade the quality of delivery (QoD. We firstly study a wireless router system model with a sequential convolutional decoder for error detection and correction in order to investigate QoD of flow and error control. To overcome the problems along with high packet error rate, we propose a wireless router system with parallel sequential decoders. We simulate our systems and provide performance in terms of average buffer occupancy, blocking probability, probability of decoding failure, system throughput, and channel throughput. We have studied these performance metrics for different channel conditions, packet arrival rates, decoding time-out limits, system capacities, and the number of sequential decoders. Our results show that parallel sequential decoders have great impact on the system performance and increase QoD significantly.

  15. TCP Traffic Control Evaluation and Reduction over Wireless Networks Using Parallel Sequential Decoding Mechanism

    Directory of Open Access Journals (Sweden)

    Aygün Ramazan

    2007-01-01

    Full Text Available The assumption of TCP-based protocols that packet error (lost or damaged is due to network congestion is not true for wireless networks. For wireless networks, it is important to reduce the number of retransmissions to improve the effectiveness of TCP-based protocols. In this paper, we consider improvement at the data link layer for systems that use stop-and-wait ARQ as in IEEE 802.11 standard. We show that increasing the buffer size will not solve the actual problem and moreover it is likely to degrade the quality of delivery (QoD. We firstly study a wireless router system model with a sequential convolutional decoder for error detection and correction in order to investigate QoD of flow and error control. To overcome the problems along with high packet error rate, we propose a wireless router system with parallel sequential decoders. We simulate our systems and provide performance in terms of average buffer occupancy, blocking probability, probability of decoding failure, system throughput, and channel throughput. We have studied these performance metrics for different channel conditions, packet arrival rates, decoding time-out limits, system capacities, and the number of sequential decoders. Our results show that parallel sequential decoders have great impact on the system performance and increase QoD significantly.

  16. Rehabilitation of a secondary network of forest traffic infrastructure (skid roads - skid trails

    Directory of Open Access Journals (Sweden)

    Bajrić Muhamed

    2015-01-01

    Full Text Available Forest transport infrastructure is the key segment of rational forest resource management. One of its constituent and inseparable segments are skid roads and skid trails whose network density significantly exceeds the primary network, i.e. truck roads. Skid road -skid trail network density in high economic forests of FB&H is most often between 40 and 100 m/ha. Simplified way of construction, non-existence of road construction, objects for surface water drainage as well as significant longitudinal inclination (up to 50% in which they are constructed, makes them subject to erosion processes. The lack of rehabilitation measures on skid roads - skid trails causes significant damages in post-exploitation period, and very often to the extent that the ones in the following exploitation round are unusable for skidding. Utilization of skid roads - skid trails damaged by erosion processes for forest operations often represents a significant expense. This paper considers rehabilitation measures efficient from the point of remedying erosion processes, and at the same time, acceptable from the point of financial expenditure for forest operations.

  17. Bi-Criteria System Optimum Traffic Assignment in Networks With Continuous Value of Time

    Directory of Open Access Journals (Sweden)

    Xin Wang

    2013-04-01

    Full Text Available For an elastic demand transportation network with continuously distributed value of time, the system disutility can be measured either in time units or in cost units. The user equilibrium model and the system optimization model are each formulated in two different criteria. The conditions required for making the system optimum link flow pattern equivalent to the user equilibrium link flow pattern are derived. Furthermore, a bi-objective model has been developed which minimizes simultaneously the system travel time and the system travel cost. The existence of a pricing scheme with anonymous link tolls which can decentralize a Pareto system optimum into the user equilibrium has been investigated.

  18. Online traffic grooming using timing information in WDM–TDM networks

    Directory of Open Access Journals (Sweden)

    Tabarak allah Ali Mohamed

    2013-03-01

    Full Text Available In this paper, the effect of holding time awareness on the process of time slot assignment in WDM–TDM is considered. Use has been made of Markov model in order to predict the wavelength congestion. A routing algorithm is developed based on the Markov modeling. The results are compared with existing algorithms—ASP, WSP and OTGA. Validation results have shown that the performance of the system is significantly improved in terms of bandwidth blocking ratio, network utilization and fairness.

  19. 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.

  20. Online social network use by health care providers in a high traffic patient care environment.

    Science.gov (United States)

    Black, Erik; Light, Jennifer; Paradise Black, Nicole; Thompson, Lindsay

    2013-05-17

    The majority of workers, regardless of age or occupational status, report engaging in personal Internet use in the workplace. There is little understanding of the impact that personal Internet use may have on patient care in acute clinical settings. The objective of this study was to investigate the volume of one form of personal Internet use-online social networking (Facebook)-generated by workstations in the emergency department (ED) in contrast to measures of clinical volume and severity. The research team analyzed anonymous network utilization records for 68 workstations located in the emergency medicine department within one academic medical center for 15 consecutive days (12/29/2009 to 1/12/2010). This data was compared to ED work index (EDWIN) data derived by the hospital information systems. Health care workers spent an accumulated 4349 minutes (72.5 hours) browsing Facebook, staff cumulatively visited Facebook 9369 times and spent, on average, 12.0 minutes per hour browsing Facebook. There was a statistically significant difference in the time spent on Facebook according to time of day (19.8 minutes per hour versus 4.3 minutes per hour, P<.001). There was a significant, positive correlation between EDWIN scores and time spent on Facebook (r=.266, P<.001). Facebook use constituted a substantive percentage of staff time during the 15-day observation period. Facebook use increased with increased patient volume and severity within the ED.

  1. Function and activity classification in network traffic data: existing methods, their weaknesses, and a path forward

    Science.gov (United States)

    Levchuk, Georgiy

    2016-05-01

    The cyber spaces are increasingly becoming the battlefields between friendly and adversary forces, with normal users caught in the middle. Accordingly, planners of enterprise defensive policies and offensive cyber missions alike have an essential goal to minimize the impact of their own actions and adversaries' attacks on normal operations of the commercial and government networks. To do this, the cyber analysis need accurate "cyber battle maps", where the functions, roles, and activities of individual and groups of devices and users are accurately identified. Most of the research in cyber exploitation has focused on the identification of attacks, attackers, and their devices. Many tools exist for device profiling, malware identification, user attribution, and attack analysis. However, most of the tools are intrusive, sensitive to data obfuscation, or provide anomaly flagging and not able to correctly classify the semantics and causes of network activities. In this paper, we review existing solutions that can identify functional and social roles of entities in cyberspace, discuss their weaknesses, and propose an approach for developing functional and social layers of cyber battle maps.

  2. ON THE RELEVANCE OF ON-LINE TRAFFIC ENGINEERING

    NARCIS (Netherlands)

    Fu, B.; Uhlig, S.P.W.G.

    The evaluation of dynamic Traffic Engineering (TE) algorithms is usually carried out using some specific network(s), traffic pattern(s) and traffic engineering objective(s). As the behavior of a TE algorithm is a consequence of the interactions between the network, the traffic demand and the

  3. Green supply chain: Simulating road traffic congestion

    Science.gov (United States)

    Jalal, Muhammad Zulqarnain Hakim Abd; Nawawi, Mohd Kamal Mohd; Laailatul Hanim Mat Desa, Wan; Khalid, Ruzelan; Khalid Abduljabbar, Waleed; Ramli, Razamin

    2017-09-01

    With the increasing awareness of the consumers about environmental issues, businesses, households and governments increasingly want use green products and services which lead to green supply chain. This paper discusses a simulation study of a selected road traffic system that will contribute to the air pollution if in the congestion state. Road traffic congestion (RTC) can be caused by a temporary obstruction, a permanent capacity bottleneck in the network itself, and stochastic fluctuation in demand within a particular sector of the network, leading to spillback and queue propagation. A discrete-event simulation model is developed to represent the real traffic light control (TLC) system condition during peak hours. Certain performance measures such as average waiting time and queue length were measured using the simulation model. Existing system uses pre-set cycle time to control the light changes which is fixed time cycle. In this research, we test several other combination of pre-set cycle time with the objective to find the best system. In addition, we plan to use a combination of the pre-set cycle time and a proximity sensor which have the authority to manipulate the cycle time of the lights. The sensors work in such situation when the street seems to have less occupied vehicles, obviously it may not need a normal cycle for green light, and automatically change the cycle to street where vehicle is present.

  4. Bandwidth characteristics of multimedia data traffic on a local area network

    Science.gov (United States)

    Chuang, Shery L.; Doubek, Sharon; Haines, Richard F.

    1993-01-01

    Limited spacecraft communication links call for users to investigate the potential use of video compression and multimedia technologies to optimize bandwidth allocations. The objective was to determine the transmission characteristics of multimedia data - motion video, text or bitmap graphics, and files transmitted independently and simultaneously over an ethernet local area network. Commercial desktop video teleconferencing hardware and software and Intel's proprietary Digital Video Interactive (DVI) video compression algorithm were used, and typical task scenarios were selected. The transmission time, packet size, number of packets, and network utilization of the data were recorded. Each data type - compressed motion video, text and/or bitmapped graphics, and a compressed image file - was first transmitted independently and its characteristics recorded. The results showed that an average bandwidth of 7.4 kilobits per second (kbps) was used to transmit graphics; an average bandwidth of 86.8 kbps was used to transmit an 18.9-kilobyte (kB) image file; a bandwidth of 728.9 kbps was used to transmit compressed motion video at 15 frames per second (fps); and a bandwidth of 75.9 kbps was used to transmit compressed motion video at 1.5 fps. Average packet sizes were 933 bytes for graphics, 498.5 bytes for the image file, 345.8 bytes for motion video at 15 fps, and 341.9 bytes for motion video at 1.5 fps. Simultaneous transmission of multimedia data types was also characterized. The multimedia packets used transmission bandwidths of 341.4 kbps and 105.8kbps. Bandwidth utilization varied according to the frame rate (frames per second) setting for the transmission of motion video. Packet size did not vary significantly between the data types. When these characteristics are applied to Space Station Freedom (SSF), the packet sizes fall within the maximum specified by the Consultative Committee for Space Data Systems (CCSDS). The uplink of imagery to SSF may be performed at

  5. Reports on internet traffic statistics

    NARCIS (Netherlands)

    Hoogesteger, Martijn; de Oliveira Schmidt, R.; Sperotto, Anna; Pras, Aiko

    2013-01-01

    Internet traffic statistics can provide valuable information to network analysts and researchers about the way nowadays networks are used. In the past, such information was provided by Internet2 in a public website called Internet2 NetFlow: Weekly Reports. The website reported traffic statistics

  6. Queues and Lévy fluctuation theory

    CERN Document Server

    Dębicki, Krzysztof

    2015-01-01

    The book provides an extensive introduction to queueing models driven by Lévy-processes as well as a systematic account of the literature on Lévy-driven queues. The objective is to make the reader familiar with the wide set of probabilistic techniques that have been developed over the past decades, including transform-based techniques, martingales, rate-conservation arguments, change-of-measure, importance sampling, and large deviations. On the application side, it demonstrates how Lévy traffic models arise when modelling current queueing-type systems (as communication networks) and includes applications to finance. Queues and Lévy Fluctuation Theory will appeal to graduate/postgraduate students and researchers in mathematics, computer science, and electrical engineering. Basic prerequisites are probability theory and stochastic processes.

  7. Network Traffic Analysis With Query Driven VisualizationSC 2005HPC Analytics Results

    Energy Technology Data Exchange (ETDEWEB)

    Stockinger, Kurt; Wu, Kesheng; Campbell, Scott; Lau, Stephen; Fisk, Mike; Gavrilov, Eugene; Kent, Alex; Davis, Christopher E.; Olinger,Rick; Young, Rob; Prewett, Jim; Weber, Paul; Caudell, Thomas P.; Bethel,E. Wes; Smith, Steve

    2005-09-01

    Our analytics challenge is to identify, characterize, and visualize anomalous subsets of large collections of network connection data. We use a combination of HPC resources, advanced algorithms, and visualization techniques. To effectively and efficiently identify the salient portions of the data, we rely on a multi-stage workflow that includes data acquisition, summarization (feature extraction), novelty detection, and classification. Once these subsets of interest have been identified and automatically characterized, we use a state-of-the-art-high-dimensional query system to extract data subsets for interactive visualization. Our approach is equally useful for other large-data analysis problems where it is more practical to identify interesting subsets of the data for visualization than to render all data elements. By reducing the size of the rendering workload, we enable highly interactive and useful visualizations. As a result of this work we were able to analyze six months worth of data interactively with response times two orders of magnitude shorter than with conventional methods.

  8. Data Gathering Using Mobile Agents for Reducing Traffic in Dense Mobile Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Keisuke Goto

    2013-01-01

    Full Text Available Recently, there has been increasing interest in Mobile Wireless Sensor Networks (MWSNs that are constructed by mobile sensor nodes held by ordinary people, and it has led to a new concept called urban sensing. In such MWSNs, mobile sensor nodes densely exist, and thus, there are basically many sensor nodes that can sense a geographical point in the entire sensing area. To reduce the communication cost for gathering sensor data, it is desirable to gather the sensor data from the minimum number of mobile sensor nodes which are necessary to guarantee the sensing coverage or the quality of services. In this paper, to achieve this, we propose a data gathering method using mobile agents in dense MWSNs. The proposed method guarantees the sensing coverage of the entire area using mobile agents that autonomously perform sensing operations, transmit sensor data, and move between sensor nodes. By gathering only sensor data generated by sensor nodes where mobile agents are running, our proposed method can achieve efficient gathering of sensor data.

  9. Algorithms and tools for anonymization of the internet traffic

    OpenAIRE

    Farah, Tanjila

    2013-01-01

    Collecting network traffic traces from deployed networks is one of the basic steps in under-standing communication networks and ensuring adequate quality of service. Traffic traces may be used for network management, traffic engineering, packet classification, and for analyzing user behavior. They may also be used for identifying and tracking network anomalies and for maintaining network security. For privacy and security reasons, monitored traffic traces should be anonymization before they m...

  10. 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...

  11. McMAC: towards a MAC protocol with multi-constrained QoS provisioning for diverse traffic in Wireless Body Area Networks.

    Science.gov (United States)

    Monowar, Muhammad Mostafa; Hassan, Mohammad Mehedi; Bajaber, Fuad; Al-Hussein, Musaed; Alamri, Atif

    2012-11-12

    The emergence of heterogeneous applications with diverse requirements for resource-constrained Wireless Body Area Networks (WBANs) poses significant challenges for provisioning Quality of Service (QoS) with multi-constraints (delay and reliability) while preserving energy efficiency. To address such challenges, this paper proposes McMAC,a MAC protocol with multi-constrained QoS provisioning for diverse traffic classes in WBANs. McMAC classifies traffic based on their multi-constrained QoS demands and introduces a novel superframe structure based on the "transmit-whenever-appropriate"principle, which allows diverse periods for diverse traffic classes according to their respective QoS requirements. Furthermore, a novel emergency packet handling mechanism is proposedto ensure packet delivery with the least possible delay and the highest reliability. McMAC is also modeled analytically, and extensive simulations were performed to evaluate its performance. The results reveal that McMAC achieves the desired delay and reliability guarantee according to the requirements of a particular traffic class while achieving energy efficiency.

  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. MQ-MAC: a multi-constrained QoS-aware duty cycle MAC for heterogeneous traffic in wireless sensor networks.

    Science.gov (United States)

    Monowar, Muhammad Mostafa; Rahman, Md Obaidur; Hong, Choong Seon; Lee, Sungwon

    2010-01-01

    Energy conservation is one of the striking research issues now-a-days for power constrained wireless sensor networks (WSNs) and hence, several duty-cycle based MAC protocols have been devised for WSNs in the last few years. However, assimilation of diverse applications with different QoS requirements (i.e., delay and reliability) within the same network also necessitates in devising a generic duty-cycle based MAC protocol that can achieve both the delay and reliability guarantee, termed as multi-constrained QoS, while preserving the energy efficiency. To address this, in this paper, we propose a Multi-constrained QoS-aware duty-cycle MAC for heterogeneous traffic in WSNs (MQ-MAC). MQ-MAC classifies the traffic based on their multi-constrained QoS demands. Through extensive simulation using ns-2 we evaluate the performance of MQ-MAC. MQ-MAC provides the desired delay and reliability guarantee according to the nature of the traffic classes as well as achieves energy efficiency.

  14. MQ-MAC: A Multi-Constrained QoS-Aware Duty Cycle MAC for Heterogeneous Traffic in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Sungwon Lee

    2010-11-01

    Full Text Available Energy conservation is one of the striking research issues now-a-days for power constrained wireless sensor networks (WSNs and hence, several duty-cycle based MAC protocols have been devised for WSNs in the last few years. However, assimilation of diverse applications with different QoS requirements (i.e., delay and reliability within the same network also necessitates in devising a generic duty-cycle based MAC protocol that can achieve both the delay and reliability guarantee, termed as multi-constrained QoS, while preserving the energy efficiency. To address this, in this paper, we propose a Multi-constrained QoS-aware duty-cycle MAC for heterogeneous traffic in WSNs (MQ-MAC. MQ-MAC classifies the traffic based on their multi-constrained QoS demands. Through extensive simulation using ns-2 we evaluate the performance of MQ-MAC. MQ-MAC provides the desired delay and reliability guarantee according to the nature of the traffic classes as well as achieves energy efficiency.

  15. Comsat's TDMA traffic terminal

    Science.gov (United States)

    Benjamin, M. C.; Bogaert, W. M.

    1985-06-01

    Comsat has installed two traffic terminals in the Etam earth-station and is currently installing a third in the new Roaring Creek earth-station to access the Intelsat TDMA network. This paper describes the Comsat TDMA traffic terminal equipment from the supergroup interface to the antenna. Comsat's 1: N redundancy approach for terrestrial interface equipment and DSI unit back-up is described as well as electrical path length, amplitude and group delay equalization techniques, special on-line RF monitoring and failure reporting facilities and the operation and maintenance center which can operate and perform diagnostic testing on up to four traffic terminals from a central location.

  16. Structuration of the overall volume of transport operations at handling of the inbound waggon traffic of metallurgical enterprise with one railway siding connecting to the external network

    Directory of Open Access Journals (Sweden)

    Ганна Вікторовна Маслак

    2016-07-01

    Full Text Available The article deals with the operation analysis of a metallurgical enterprise transport system with one railway siding connected to the external network. Three functional modules were determined: transport complex for incoming wagon traffic processing, transport-and-handling complex for raw materials unloading, transport-and-handling complex for finished products shipment. For each of the complexes basic functions were determined: the first module distributes empty and loaded waggons between the freight railway stations within the enterprise; the second module provides timely supply of production shops with required volumes of raw materials; the third module enables timely supply of production shops with railway rolling stock for finished products shipment. Structuration of overall volume of transport operations has been conducted for each of the complexes within the transport system of the metallurgical enterprise, basic technological operations have been determined, and causes for time waste have been found out. Overall volume of transport operations per day has been determined, it comprising planned transport operations and extra transport operations as well. As a result of the research it has been determined, that maximum volume of extra transport operations occur at the transport complex for incoming wagon traffic processing. Its operation is based on time norms which not always fit the dynamics of external network operation, as well as production shops operation. Furthermore, this module is a connecting link making the dynamics of external waggon traffic, the internal dynamics of the enterprise, and the dynamics of production shops compatible. As a consequence, considerable extra time waste occurs when waggon traffic goes through this module

  17. Surface Air Temperature Fluctuations and Lapse Rates on Olivares Gamma Glacier, Rio Olivares Basin, Central Chile, from a Novel Meteorological Sensor Network

    Directory of Open Access Journals (Sweden)

    Edward Hanna

    2017-01-01

    Full Text Available Empirically based studies of glacier meteorology, especially for the Southern Hemisphere, are relatively sparse in the literature. Here, we use an innovative network of highly portable, low-cost thermometers to report on high-frequency (1-min time resolution surface air temperature fluctuations and lapse rates (LR in a ~800-m elevational range (from 3,675 to 4,492 m a.s.l. across the glacier Olivares Gamma in the central Andes, Chile. Temperatures were measured during an intense field campaign in late Southern summer, 19–27 March 2015, under varying weather conditions. We found a complex dependence of high-frequency LR on time of day, topography, and wider meteorological conditions, with hourly temperature variations during this week that were probably mainly associated with short- and long-wave radiation changes and not with wind speed/direction changes. Using various pairs of sites within our station network, we also analyze spatial variations in LR. Uniquely in this study, we compare temperatures measured at heights of 1-m and 2-m above the glacier surface for the network of five sites and found that temperatures at these two heights occasionally differed by more than ±4°C during the early afternoons, although the mean temperature difference is much smaller (~0.3°C. An implication of our results is that daily, hourly, or even monthly averaged LR may be insufficient for feeding into accurate melt models of glacier change, with the adoption of subhourly (ideally 1–10-min resolution LR likely to prove fruitful in developing new innovative high-time-resolution melt modelling. Our results are potentially useful as input LR for local glacier melt models and for improving the understanding of lapse rate fluctuations and glacier response to climate change.

  18. Synergistic Allosteric Mechanism of Fructose-1,6-bisphosphate and Serine for Pyruvate Kinase M2 via Dynamics Fluctuation Network Analysis.

    Science.gov (United States)

    Yang, Jingxu; Liu, Hao; Liu, Xiaorui; Gu, Chengbo; Luo, Ray; Chen, Hai-Feng

    2016-06-27

    Pyruvate kinase M2 (PKM2) plays a key role in tumor metabolism and regulates the rate-limiting final step of glycolysis. In tumor cells, there are two allosteric effectors for PKM2: fructose-1,6-bisphosphate (FBP) and serine. However, the relationship between FBP and serine for allosteric regulation of PKM2 is unknown. Here we constructed residue/residue fluctuation correlation network based on all-atom molecular dynamics simulations to reveal the regulation mechanism. The results suggest that the correlation network in bound PKM2 is distinctly different from that in the free state, FBP/PKM2, or Ser/PKM2. The community network analysis indicates that the information can freely transfer from the allosteric sites of FBP and serine to the substrate site in bound PKM2, while there exists a bottleneck for information transfer in the network of the free state. Furthermore, the binding free energy between the substrate and PKM2 for bound PKM2 is significantly lower than either of FBP/PKM2 or Ser/PKM2. Thus, a hypothesis of "synergistic allosteric mechanism" is proposed for the allosteric regulation of FBP and serine. This hypothesis was further confirmed by the perturbational and mutational analyses of community networks and binding free energies. Finally, two possible synergistic allosteric pathways of FBP-K433-T459-R461-A109-V71-R73-MG2-OXL and Ser-I47-C49-R73-MG2-OXL were identified based on the shortest path algorithm and were confirmed by the network perturbation analysis. Interestingly, no similar pathways could be found in the free state. The process targeting on the allosteric pathways can better regulate the glycolysis of PKM2 and significantly inhibit the progression of tumor.

  19. Urban traffic simulated from the dual representation: Flow, crisis and congestion

    Science.gov (United States)

    Hu, Mao-Bin; Jiang, Rui; Wang, Ruili; Wu, Qing-Song

    2009-05-01

    We propose a traffic simulation model for urban system based on the dual graph representation of a urban road network and with a random entering vehicle rate. To avoid the shortcoming of “Space Syntax” of ignoring the road's metric distance, we consider both the motion of the vehicles along roads and the navigation of the vehicles in the network. Simulations have shown some basic properties of urban traffic system, such as flux fluctuation, crisis and dissipation, phase transition from a free flow to jams, overall capacity, the distribution of traveling time, and the fundamental diagram. The system's behavior greatly depends on the topology of the transportation network. A well-planned lattice grid can keep more vehicles travelling. The critical entering vehicle rate is much greater in lattice grid than in a self-organized network. The vehicles have to travel longer time in a self-organized urban system due to the navigation cost.

  20. Modelling of H.264 MPEG2 TS Traffic Source

    Directory of Open Access Journals (Sweden)

    Stanislav Klucik

    2013-01-01

    Full Text Available 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.

  1. Interdomain traffic engineering with BGP

    OpenAIRE

    Quoitin, Bruno; Uhlig, Steve; Pelsser, Cristel; Swinnen, Louis; Bonaventure, Olivier

    2003-01-01

    Traffic engineering is performed by means of a set of techniques that can be used to better control the flow of packets inside an IP network We discuss the utilization of these techniques across interdomain boundaries in the global Internet. We first analyze the characteristics of interdomain traffic on the basis of measurements from three different Internet service providers and show that a small number of sources are responsible for a large fraction of the traffic. Across interdomain bounda...

  2. Synchronization, non-linear dynamics and low-frequency fluctuations: Analogy between spontaneous brain activity and networked single-transistor chaotic oscillators

    Science.gov (United States)

    Minati, Ludovico; Chiesa, Pietro; Tabarelli, Davide; D'Incerti, Ludovico; Jovicich, Jorge

    2015-03-01

    In this paper, the topographical relationship between functional connectivity (intended as inter-regional synchronization), spectral and non-linear dynamical properties across cortical areas of the healthy human brain is considered. Based upon functional MRI acquisitions of spontaneous activity during wakeful idleness, node degree maps are determined by thresholding the temporal correlation coefficient among all voxel pairs. In addition, for individual voxel time-series, the relative amplitude of low-frequency fluctuations and the correlation dimension (D2), determined with respect to Fourier amplitude and value distribution matched surrogate data, are measured. Across cortical areas, high node degree is associated with a shift towards lower frequency activity and, compared to surrogate data, clearer saturation to a lower correlation dimension, suggesting presence of non-linear structure. An attempt to recapitulate this relationship in a network of single-transistor oscillators is made, based on a diffusive ring (n = 90) with added long-distance links defining four extended hub regions. Similarly to the brain data, it is found that oscillators in the hub regions generate signals with larger low-frequency cycle amplitude fluctuations and clearer saturation to a lower correlation dimension compared to surrogates. The effect emerges more markedly close to criticality. The homology observed between the two systems despite profound differences in scale, coupling mechanism and dynamics appears noteworthy. These experimental results motivate further investigation into the heterogeneity of cortical non-linear dynamics in relation to connectivity and underline the ability for small networks of single-transistor oscillators to recreate collective phenomena arising in much more complex biological systems, potentially representing a future platform for modelling disease-related changes.

  3. Synchronization, non-linear dynamics and low-frequency fluctuations: Analogy between spontaneous brain activity and networked single-transistor chaotic oscillators

    Energy Technology Data Exchange (ETDEWEB)

    Minati, Ludovico, E-mail: lminati@ieee.org, E-mail: ludovico.minati@unitn.it, E-mail: lminati@istituto-besta.it [Scientific Department, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan (Italy); Center for Mind/Brain Sciences, University of Trento, Trento (Italy); Chiesa, Pietro; Tabarelli, Davide; Jovicich, Jorge [Center for Mind/Brain Sciences, University of Trento, Trento (Italy); D' Incerti, Ludovico [Neuroradiology Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan (Italy)

    2015-03-15

    In this paper, the topographical relationship between functional connectivity (intended as inter-regional synchronization), spectral and non-linear dynamical properties across cortical areas of the healthy human brain is considered. Based upon functional MRI acquisitions of spontaneous activity during wakeful idleness, node degree maps are determined by thresholding the temporal correlation coefficient among all voxel pairs. In addition, for individual voxel time-series, the relative amplitude of low-frequency fluctuations and the correlation dimension (D{sub 2}), determined with respect to Fourier amplitude and value distribution matched surrogate data, are measured. Across cortical areas, high node degree is associated with a shift towards lower frequency activity and, compared to surrogate data, clearer saturation to a lower correlation dimension, suggesting presence of non-linear structure. An attempt to recapitulate this relationship in a network of single-transistor oscillators is made, based on a diffusive ring (n = 90) with added long-distance links defining four extended hub regions. Similarly to the brain data, it is found that oscillators in the hub regions generate signals with larger low-frequency cycle amplitude fluctuations and clearer saturation to a lower correlation dimension compared to surrogates. The effect emerges more markedly close to criticality. The homology observed between the two systems despite profound differences in scale, coupling mechanism and dynamics appears noteworthy. These experimental results motivate further investigation into the heterogeneity of cortical non-linear dynamics in relation to connectivity and underline the ability for small networks of single-transistor oscillators to recreate collective phenomena arising in much more complex biological systems, potentially representing a future platform for modelling disease-related changes.

  4. Design considerations for energy efficient, resilient, multi-layer networks

    DEFF Research Database (Denmark)

    Fagertun, Anna Manolova; Hansen, Line Pyndt; Ruepp, Sarah Renée

    2016-01-01

    This work investigates different network design considerations with respect to energy-efficiency, under green-field resilient multi-layer network deployment. The problem of energy efficient, reliable multi-layer network design is known to result in different trade-offs between key performance...... in multi-layer networks and performance measures such as network resource utilization, availability, agility to traffic fluctuations and energy consumption. A green-field network deployment scenario is considered, where different resiliency methods, design methodologies and grooming strategies are applied...

  5. Using traffic speed deflectometer to measure deflections and evaluate bearing capacity of asphalt road pavements at network level

    Science.gov (United States)

    Březina, Ilja; Stryk, Josef; Grošek, Jiří

    2017-09-01

    The paper deals with diagnostics of bearing capacity of asphalt pavements by a Traffic Speed Deflectometer (TSD device), which allows to measure pavement deflections continually at the traffic speed on the basis of dynamic loading induced by moving wheel of a reference axle at the speed of up to 80 km/h. The paper aims to inform of a new method to measure road pavement deflections, describes the principles of measuring pavement deflections by TSD device, and presents results of comparative measurements between FWD (Falling Weight Deflectometer) and TSD devices organized by CDV in Italy and Slovakia. Particular attention was paid to the difference between deflections measured by FWD and TSD devices.

  6. Game theory and traffic assignment.

    Science.gov (United States)

    2013-09-01

    Traffic assignment is used to determine the number of users on roadway links in a network. While this problem has : been widely studied in transportation literature, its use of the concept of equilibrium has attracted considerable interest : in the f...

  7. The Pseudo-Self-Similar Traffic Model: Application and Validation

    NARCIS (Netherlands)

    El Abdouni Khayari, Rachid; Haverkort, Boudewijn R.H.M.; Sadre, R.; Ost, Alexander

    2004-01-01

    Since the early 1990s, a variety of studies have shown that network traffic, both for local- and wide-area networks, has self-similar properties. This led to new approaches in network traffic modelling because most traditional traffic approaches result in the underestimation of performance measures

  8. Traffic and Granular Flow ’07

    CERN Document Server

    Chevoir, François; Gondret, Philippe; Lassarre, Sylvain; Lebacque, Jean-Patrick; Schreckenberg, Michael

    2009-01-01

    This book covers several research fields, all of which deal with transport. Three main topics are treated: road traffic, granular matter, and biological transport. Different points of view, i.e. modelling, simulations, experiments, and phenomenological observations, are considered. Sub-topics include: highway or urban vehicular traffic (dynamics of traffic, macro/micro modelling, measurements, data analysis, security issues, psychological issues), pedestrian traffic, animal traffic (e.g. social insects), collective motion in biological systems (molecular motors...), granular flow (dense flows, intermittent flows, solid/liquid transition, jamming, force networks, fluid and solid friction), networks (biological networks, urban traffic, the internet, vulnerability of networks, optimal transport networks) and cellular automata applied to the various aforementioned fields.

  9. Long-term observation of a pollination network: fluctuation in species and interactions, relative invariance of network structure and implications for estimates of specialization.

    Science.gov (United States)

    Petanidou, Theodora; Kallimanis, Athanasios S; Tzanopoulos, Joseph; Sgardelis, Stefanos P; Pantis, John D

    2008-06-01

    We analysed the dynamics of a plant-pollinator interaction network of a scrub community surveyed over four consecutive years. Species composition within the annual networks showed high temporal variation. Temporal dynamics were also evident in the topology of the network, as interactions among plants and pollinators did not remain constant through time. This change involved both the number and the identity of interacting partners. Strikingly, few species and interactions were consistently present in all four annual plant-pollinator networks (53% of the plant species, 21% of the pollinator species and 4.9% of the interactions). The high turnover in species-to-species interactions was mainly the effect of species turnover (c. 70% in pairwise comparisons among years), and less the effect of species flexibility to interact with new partners (c. 30%). We conclude that specialization in plant-pollinator interactions might be highly overestimated when measured over short periods of time. This is because many plant or pollinator species appear as specialists in 1 year, but tend to be generalists or to interact with different partner species when observed in other years. The high temporal plasticity in species composition and interaction identity coupled with the low variation in network structure properties (e.g. degree centralization, connectance, nestedness, average distance and network diameter) imply (i) that tight and specialized coevolution might not be as important as previously suggested and (ii) that plant-pollinator interaction networks might be less prone to detrimental effects of disturbance than previously thought. We suggest that this may be due to the opportunistic nature of plant and animal species regarding the available partner resources they depend upon at any particular time.

  10. 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.

  11. Fluctuating Arctic Sea ice thickness changes estimated by an in situ learned and empirically forced neural network model

    Science.gov (United States)

    Belchansky, G.I.; Douglas, D.C.; Platonov, N.G.

    2008-01-01

    Sea ice thickness (SIT) is a key parameter of scientific interest because understanding the natural spatiotemporal variability of ice thickness is critical for improving global climate models. In this paper, changes in Arctic SIT during 1982-2003 are examined using a neural network (NN) algorithm trained with in situ submarine ice draft and surface drilling data. For each month of the study period, the NN individually estimated SIT of each ice-covered pixel (25-km resolution) based on seven geophysical parameters (four shortwave and longwave radiative fluxes, surface air temperature, ice drift velocity, and ice divergence/convergence) that were cumulatively summed at each monthly position along the pixel's previous 3-yr drift track (or less if the ice was <3 yr old). Average January SIT increased during 1982-88 in most regions of the Arctic (+7.6 ?? 0.9 cm yr-1), decreased through 1996 Arctic-wide (-6.1 ?? 1.2 cm yr-1), then modestly increased through 2003 mostly in the central Arctic (+2.1 ?? 0.6 cm yr-1). Net ice volume change in the Arctic Ocean from 1982 to 2003 was negligible, indicating that cumulative ice growth had largely replaced the estimated 45 000 km3 of ice lost by cumulative export. Above 65??N, total annual ice volume and interannual volume changes were correlated with the Arctic Oscillation (AO) at decadal and annual time scales, respectively. Late-summer ice thickness and total volume varied proportionally until the mid-1990s, but volume did not increase commensurate with the thickening during 1996-2002. The authors speculate that decoupling of the ice thickness-volume relationship resulted from two opposing mechanisms with different latitudinal expressions: a recent quasi-decadal shift in atmospheric circulation patterns associated with the AO's neutral state facilitated ice thickening at high latitudes while anomalously warm thermal forcing thinned and melted the ice cap at its periphery. ?? 2008 American Meteorological Society.

  12. The Technical Issues Of Traffic Analysis

    Directory of Open Access Journals (Sweden)

    Pavel Vladimirovich Yegorov

    2016-03-01

    Full Text Available The main problem in the analysis of Internet traffic associated with a large number of network applications, complex patterns of communication and a significant amounts of information. The definition of the category of traffic using the analysis of the number of port is irrelevant for P2P applications, streaming data and many other types of network applications. The article describes some of technical issues related to the analysis of Internet traffic.

  13. Aplikasi Traffic Monitoring Server Menggunakan SMS

    OpenAIRE

    Ilona, Clarissa

    2010-01-01

    This study aims to build traffic monitoring application that can help network administrator to monitor server anytime and anywhere, by using SMS. Things to be monitored are data traffic and server network connection. Literature study, and field study were done before designing the application.The result is application that can send and receive SMS to / from network administrator, check the connection to the server, and respond to network administrator in a relatively fast time when the connec...

  14. Travelers ability to observe changes in traffic intensities and traffic light settings

    NARCIS (Netherlands)

    Vreeswijk, Jacob Dirk; Do, Michael; Middag, Wilco; Martens, Marieke Hendrikje; van Berkum, Eric C.; van Arem, Bart; ITSC,

    2011-01-01

    Travel choice behavior is an important determinant in traffic and subject to human imperfection and bounded rationality. In decision-making processes travelers seldom act perfectly rational. Traffic models and traffic network management measure could become more realistic and effective, if

  15. Forecasting Multivariate Road Traffic Flows Using Bayesian Dynamic Graphical Models, Splines and Other Traffic Variables

    NARCIS (Netherlands)

    Anacleto, Osvaldo; Queen, Catriona; Albers, Casper J.

    Traffic flow data are routinely collected for many networks worldwide. These invariably large data sets can be used as part of a traffic management system, for which good traffic flow forecasting models are crucial. The linear multiregression dynamic model (LMDM) has been shown to be promising for

  16. Real-Time Corrected Traffic Correlation Model for Traffic Flow Forecasting

    Directory of Open Access Journals (Sweden)

    Hua-pu Lu

    2015-01-01

    Full Text Available This paper focuses on the problems of short-term traffic flow forecasting. The main goal is to put forward traffic correlation model and real-time correction algorithm for traffic flow forecasting. Traffic correlation model is established based on the temporal-spatial-historical correlation characteristic of traffic big data. In order to simplify the traffic correlation model, this paper presents correction coefficients optimization algorithm. Considering multistate characteristic of traffic big data, a dynamic part is added to traffic correlation model. Real-time correction algorithm based on Fuzzy Neural Network is presented to overcome the nonlinear mapping problems. A case study based on a real-world road network in Beijing, China, is implemented to test the efficiency and applicability of the proposed modeling methods.

  17. An Evaluation of Best Effort Traffic Management of Server and Agent-Based Active Network Management (SAAM) Architecture

    National Research Council Canada - National Science Library

    Ayvat, Birol

    2003-01-01

    The Server and Agent-based Active Network Management (SAAM) architecture was initially designed to work with the next generation Internet where increasingly sophisticated applications will require QoS guarantees...

  18. Load characterization and anomaly detection for voice over IP traffic

    NARCIS (Netherlands)

    M.R.H. Mandjes (Michel); I. Saniee; A. Stolyar

    2005-01-01

    textabstractWe consider the problem of traffic anomaly detection in IP networks. Traffic anomalies typically arise when there is focused overload or when a network element fails and it is desired to infer these purely from the measured traffic. We derive new general formulae for the variance of the

  19. Busy hour traffic congestion analysis in mobile macrocells | Ozovehe ...

    African Journals Online (AJOL)

    In this work, real live traffic data from integrated GSM/GPRS network was used for traffic congestion analysis. The analysis was carried out on 10 congesting cells using network management system (NMS) statistics data span for three years period. Correlation test showed that traffic channel (TCH) congestion depend only ...

  20. busy hour traffic congestion analysis in mobile macrocells

    African Journals Online (AJOL)

    HOD

    In this work, real live traffic data from integrated GSM/GPRS network was used for traffic congestion analysis. The analysis was carried out on 10 congesting cells using network management system (NMS) statistics data span for three years period. Correlation test showed that traffic channel (TCH) congestion depend only.

  1. Traffic forecaster for MPLS multimedia data streams

    Science.gov (United States)

    Ambrose, Barry; Lin, Freddie

    2006-05-01

    Contemporary high performance data networks carry a wide range of multimedia services (voice, video, audio, text, sensor data, etc.) that require an outstanding Quality of Service (QoS) to provide performance guarantees in priority delivery, latency, bandwidth utilization, load balancing, etc. With the advent of recent Multi-Protocol Label Switching (MPLS) network standards, the QoS has made significant progress in performance to provide these performance guarantees. Right now, attention has turned to the task of managing these QoS networks more efficiently through the handling of network traffic. We have investigated a novel Network Traffic Forecasting Assisted QoS Planner technology that will provide constantly updated forecasts of data traffic and server loads to any application that needs this information. Using source models of voice, video and data traffic based on empirical studies of TCP/IP data traffic carried out by Paxson and Floyd in the 1990's, our studies have shown that the system may provide up to 43% bandwidth savings for MPLS data streams, by predicting future traffic flows and reserving network resources to accommodate the predicted traffic. The system additionally provides a means to submit bandwidth reservation requests for those applications that need assured service guarantees for data delivery. The technology essentially increases the efficiency and effectiveness of multimedia information and communication network infrastructure that supports multiple or adaptive QoS levels for multimedia data networking and information system applications.

  2. Fixed Point Learning Based Intelligent Traffic Control System

    Science.gov (United States)

    Zongyao, Wang; Cong, Sui; Cheng, Shao

    2017-10-01

    Fixed point learning has become an important tool to analyse large scale distributed system such as urban traffic network. This paper presents a fixed point learning based intelligence traffic network control system. The system applies convergence property of fixed point theorem to optimize the traffic flow density. The intelligence traffic control system achieves maximum road resources usage by averaging traffic flow density among the traffic network. The intelligence traffic network control system is built based on decentralized structure and intelligence cooperation. No central control is needed to manage the system. The proposed system is simple, effective and feasible for practical use. The performance of the system is tested via theoretical proof and simulations. The results demonstrate that the system can effectively solve the traffic congestion problem and increase the vehicles average speed. It also proves that the system is flexible, reliable and feasible for practical use.

  3. Application of AirCell Cellular AMPS Network and Iridium Satellite System Dual Mode Service to Air Traffic Management

    Science.gov (United States)

    Shamma, Mohammed A.

    2004-01-01

    The AirCell/Iridium dual mode service is evaluated for potential applications to Air Traffic Management (ATM) communication needs. The AirCell system which is largely based on the Advanced Mobile Phone System (AMPS) technology, and the Iridium FDMA/TDMA system largely based on the Global System for Mobile Communications(GSM) technology, can both provide communication relief for existing or future aeronautical communication links. Both have a potential to serve as experimental platforms for future technologies via a cost effective approach. The two systems are well established in the entire CONUS and globally hence making it feasible to utilize in all regions, for all altitudes, and all classes of aircraft. Both systems have been certified for air usage. The paper summarizes the specifications of the AirCell/Iridium system, as well as the ATM current and future links, and application specifications. the paper highlights the scenarios, applications, and conditions under which the AirCell/Iridium technology can be suited for ATM Communication.

  4. An Evaluation of Best Effort Traffic Management of Server and Agent-Based Active Network Management (SAAM) Architecture

    Science.gov (United States)

    2003-03-01

    Interdomain Routing ........................................................................10 C. NEW APPROACHES FOR ROUTING...Internet routing protocols, such as OSPF or RIP. It also aims to provide better performance in avoiding congestion and in achieving fairness than other...Effort networks treat packets equally during congestion , so packets are dropped arbitrarily. This might bottleneck an application that is sensitive

  5. Hydro-Climatic Data Network (HCDN) -- A USGS Streamflow Data Set for the U.S. for the Study of Climate Fluctuations

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — A streamflow data set, which is specifically suitable for the study of surface-water conditions throughout the United States under fluctuations in the prevailing...

  6. Using Visualization Techniques in Multilayer Traffic Modeling

    Science.gov (United States)

    Bragg, Arnold

    We describe visualization techniques for multilayer traffic modeling - i.e., traffic models that span several protocol layers, and traffic models of protocols that cross layers. Multilayer traffic modeling is challenging, as one must deal with disparate traffic sources; control loops; the effects of network elements such as IP routers; cross-layer protocols; asymmetries in bandwidth, session lengths, and application behaviors; and an enormous number of complex interactions among the various factors. We illustrate by using visualization techniques to identify relationships, transformations, and scaling; to smooth simulation and measurement data; to examine boundary cases, subtle effects and interactions, and outliers; to fit models; and to compare models with others that have fewer parameters. Our experience suggests that visualization techniques can provide practitioners with extraordinary insight about complex multilayer traffic effects and interactions that are common in emerging next-generation networks.

  7. International Workshop on Traffic and Granular Flow

    CERN Document Server

    Herrmann, Hans; Schreckenberg, Michael; Wolf, Dietrich; Social, Traffic and Granular Dynamics

    2000-01-01

    "Are there common phenomena and laws in the dynamic behavior of granular materials, traffic, and socio-economic systems?" The answers given at the international workshop "Traffic and Granular Flow '99" are presented in this volume. From a physical standpoint, all these systems can be treated as (self)-driven many-particle systems with strong fluctuations, showing multistability, phase transitions, non-linear waves, etc. The great interest in these systems is due to several unexpected new discoveries and their practical relevance for solving some fundamental problems of today's societies. This includes intelligent measures for traffic flow optimization and methods from "econophysics" for stabilizing (stock) markets.

  8. Dynamic Power-Saving Method for Wi-Fi Direct Based IoT Networks Considering Variable-Bit-Rate Video Traffic.

    Science.gov (United States)

    Jin, Meihua; Jung, Ji-Young; Lee, Jung-Ryun

    2016-10-12

    With the arrival of the era of Internet of Things (IoT), Wi-Fi Direct is becoming an emerging wireless technology that allows one to communicate through a direct connection between the mobile devices anytime, anywhere. In Wi-Fi Direct-based IoT networks, all devices are categorized by group of owner (GO) and client. Since portability is emphasized in Wi-Fi Direct devices, it is essential to control the energy consumption of a device very efficiently. In order to avoid unnecessary power consumed by GO, Wi-Fi Direct standard defines two power-saving methods: Opportunistic and Notice of Absence (NoA) power-saving methods. In this paper, we suggest an algorithm to enhance the energy efficiency of Wi-Fi Direct power-saving, considering the characteristics of multimedia video traffic. Proposed algorithm utilizes the statistical distribution for the size of video frames and adjusts the lengths of awake intervals in a beacon interval dynamically. In addition, considering the inter-dependency among video frames, the proposed algorithm ensures that a video frame having high priority is transmitted with higher probability than other frames having low priority. Simulation results show that the proposed method outperforms the traditional NoA method in terms of average delay and energy efficiency.

  9. Traffic calming schemes : opportunities and implementation strategies.

    NARCIS (Netherlands)

    Schagen, I.N.L.G. van (ed.)

    2003-01-01

    Commissioned by the Swedish National Road Authority, this report aims to provide a concise overview of knowledge of and experiences with traffic calming schemes in urban areas, both on a technical level and on a policy level. Traffic calming refers to a combination of network planning and

  10. Traffic Monitor

    Science.gov (United States)

    1995-01-01

    Intelligent Vision Systems, Inc. (InVision) needed image acquisition technology that was reliable in bad weather for its TDS-200 Traffic Detection System. InVision researchers used information from NASA Tech Briefs and assistance from Johnson Space Center to finish the system. The NASA technology used was developed for Earth-observing imaging satellites: charge coupled devices, in which silicon chips convert light directly into electronic or digital images. The TDS-200 consists of sensors mounted above traffic on poles or span wires, enabling two sensors to view an intersection; a "swing and sway" feature to compensate for movement of the sensors; a combination of electronic shutter and gain control; and sensor output to an image digital signal processor, still frame video and optionally live video.

  11. Cross-Layer Resource Scheduling for Video Traffic in the Downlink of OFDMA-Based Wireless 4G Networks

    Directory of Open Access Journals (Sweden)

    2009-03-01

    Full Text Available Designing scheduling algorithms at the medium access control (MAC layer relies on a variety of parameters including quality of service (QoS requirements, resource allocation mechanisms, and link qualities from the corresponding layers. In this paper, we present an efficient cross-layer scheduling scheme, namely, Adaptive Token Bank Fair Queuing (ATBFQ algorithm, which is designed for packet scheduling and resource allocation in the downlink of OFDMA-based wireless 4G networks. This algorithm focuses on the mechanisms of efficiency and fairness in multiuser frequency-selective fading environments. We propose an adaptive method for ATBFQ parameter selection which integrates packet scheduling with resource mapping. The performance of the proposed scheme is compared to that of the round-robin (RR and the score-based (SB schedulers. It is observed from simulation results that the proposed scheme with adaptive parameter selection provides enhanced performance in terms of queuing delay, packet dropping rate, and cell-edge user performance, while the total sector throughput remains comparable. We further analyze and compare achieved fairness of the schemes in terms of different fairness indices available in literature.

  12. Research on the Method of Traffic Organization and Optimization Based on Dynamic Traffic Flow Model

    Directory of Open Access Journals (Sweden)

    Shu-bin Li

    2017-01-01

    Full Text Available The modern transportation system is becoming sluggish by traffic jams, so much so that it can harm the economic and society in our country. One of the reasons is the surging vehicles day by day. Another reason is the shortage of the traffic supply seriously. But the most important reason is that the traffic organization and optimization hardly met the conditions of modern transport development. In this paper, the practical method of the traffic organization and optimization used in regional area is explored by the dynamic traffic network analysis method. Firstly, the operational states of the regional traffic network are obtained by simulation method based on the self-developed traffic simulation software DynaCHINA, in which the improved traffic flow simulation model was proposed in order to be more suitable for actual domestic urban transport situation. Then the appropriated optimization model and algorithm were proposed according to different optimized content and organization goals, and the traffic simulation processes more suitable to regional optimization were designed exactly. Finally, a regional network in Tai’an city was selected as an example. The simulation results show that the proposed method is effective and feasible. It can provide strong scientific and technological support for the traffic management department.

  13. assessment of traffic flow on enugu highways using speed density

    African Journals Online (AJOL)

    HOD

    effectively if traffic behaviours under all conditions are modeled accurately [2]. Traffic flow in engineering is the study of interaction between vehicles, commuters and infrastructure. (including the highways, signage and traffic control devices) with the aim of understanding and developing an optimal road network with efficient ...

  14. modified traffic s modified traffic signal phasing at traffic warden ...

    African Journals Online (AJOL)

    eobe

    centred' notion in traffic engineering is now being replaced by the new 'human centred' notion which takes all road users into consideration in its planning, design and operations and attaches more importance to vulnerable traffic participants such as the pedestrians [4]. Thus the pedestrian traffic safety management at TWC ...

  15. Quantum Fluctuation Relations

    OpenAIRE

    Facchi, Paolo; Garnero, Giancarlo; Ligabò, Marilena

    2017-01-01

    We present here a set of lecture notes on exact fluctuation relations. We prove the Jarzynski equality and the Crooks fluctuation theorem, two paradigmatic examples of classical fluctuation relations. Finally we consider their quantum versions, and analyze analogies and differences with the classical case.

  16. TrafficTurk evaluation.

    Science.gov (United States)

    2014-04-01

    This report summarizes a project undertaken by the University of Illinois on behalf of the Illinois Department of : Transportation to evaluate a smartphone application called TrafficTurk for traffic safety and traffic monitoring : applications. Traff...

  17. Crowding effects in vehicular traffic.

    Directory of Open Access Journals (Sweden)

    Jay Samuel L Combinido

    Full Text Available While the impact of crowding on the diffusive transport of molecules within a cell is widely studied in biology, it has thus far been neglected in traffic systems where bulk behavior is the main concern. Here, we study the effects of crowding due to car density and driving fluctuations on the transport of vehicles. Using a microscopic model for traffic, we found that crowding can push car movement from a superballistic down to a subdiffusive state. The transition is also associated with a change in the shape of the probability distribution of positions from a negatively-skewed normal to an exponential distribution. Moreover, crowding broadens the distribution of cars' trap times and cluster sizes. At steady state, the subdiffusive state persists only when there is a large variability in car speeds. We further relate our work to prior findings from random walk models of transport in cellular systems.

  18. Traffic and Granular Flow '11

    CERN Document Server

    Buslaev, Alexander; Bugaev, Alexander; Yashina, Marina; Schadschneider, Andreas; Schreckenberg, Michael; TGF11

    2013-01-01

    This book continues the biannual series of conference proceedings, which has become a classical reference resource in traffic and granular research alike. It addresses new developments at the interface between physics, engineering and computational science. Complex systems, where many simple agents, be they vehicles or particles, give rise to surprising and fascinating phenomena.   The contributions collected in these proceedings cover several research fields, all of which deal with transport. Topics include highway, pedestrian and internet traffic, granular matter, biological transport, transport networks, data acquisition, data analysis and technological applications. Different perspectives, i.e. modeling, simulations, experiments and phenomenological observations, are considered.

  19. A computerized traffic control algorithm to determine optimal traffic signal settings. Ph.D. Thesis - Toledo Univ.

    Science.gov (United States)

    Seldner, K.

    1977-01-01

    An algorithm was developed to optimally control the traffic signals at each intersection using a discrete time traffic model applicable to heavy or peak traffic. Off line optimization procedures were applied to compute the cycle splits required to minimize the lengths of the vehicle queues and delay at each intersection. The method was applied to an extensive traffic network in Toledo, Ohio. Results obtained with the derived optimal settings are compared with the control settings presently in use.

  20. Analysis of discrete-time queue for broadband ISDN with priorities among traffic classes

    Science.gov (United States)

    Takine, Tetsuya; Sengupta, Bhaskar; Hasegawa, Toshiharu

    1994-02-01

    In Broadband ISDN (Integrated Service Digital Network), different classes of traffic expect to receive different quality of service. One way of providing service is to implement a priority structure among traffic classes. We analyze a single server queue in which video and voice traffic receive priority over data traffic.

  1. Optimal traffic control via smartphone app users: A model for actuator and departure optimisation

    NARCIS (Netherlands)

    D. van Leeuwen (Daphne); R.D. van der Mei (Rob); F. Ottenhof

    2015-01-01

    htmlabstractFor many years traffic control has been the task of traffic centres. Road congestion is reduced via traffic control based on the sensor information of the current traffic state. Actuators are used to create a better spread and throughput over the network. A powerful means to further

  2. Robust, Optimal, Predictive, and Integrated Road Traffic Control : Research proposal

    NARCIS (Netherlands)

    Van de Weg, G.S.; Hegyi, A.; Hoogendoorn, S.P.

    2014-01-01

    The development of control strategies for traffic lights, ramp metering installations, and variable speed limits to improve the throughput of road traffic networks can contribute to a more efficient use of road networks. In this project, a hierarchical controller will be developed for the

  3. Reducing habitat fragmentation on minor rural roads through traffic calming

    NARCIS (Netherlands)

    Jaarsma, C.F.; Willems, G.P.A.

    2002-01-01

    The rural road network suffers continually from ambiguity. On the one hand, the presence of this network and its traffic flows offer accessibility and make a contribution to economic development. While on the other, its presence and its traffic flows cause fragmentation. The actual ecological impact

  4. Modelling and control of broadband traffic using multiplicative ...

    Indian Academy of Sciences (India)

    R. Narasimhan (Krishtel eMaging) 1461 1996 Oct 15 13:05:22

    Modelling of broadband network traffic has emerged as an active area in the last decade. This has been primarily ... that broadband network traffic exhibits statistical self-similarity triggered off an immense volume of ...... with CAC control techniques and adaptive prediction of delay for bandwidth management in broadband ...

  5. Latin American Clinical Epidemiology Network Series - Paper 5: Years of life lost due to premature death in traffic accidents in Bogota, Colombia.

    Science.gov (United States)

    Quitian-Reyes, Hoover; Gómez-Restrepo, Carlos; Gómez, Maria Juliana; Naranjo, Salome; Heredia, Patricia; Villegas, John

    2017-06-01

    This study aimed to quantify the number of years of life lost in traffic accidents in Bogota, Colombia. The years of life lost were calculated using the 'age-standardized expected years of life lost' method, the table of Japanese adjusted life expectancy and the database of the Institute of Legal Medicine and Forensic Science between September 2012 and August 2013. During a period of 1 year, 430 people died and 10,056.3 years of life were lost in Bogota due to traffic accidents. The mortality burden of traffic accidents in Bogota is high. Further studies are required in order to characterize the accidents and develop effective policy decisions. Copyright © 2016 Elsevier Inc. All rights reserved.

  6. Structuring of Road Traffic Flows

    Directory of Open Access Journals (Sweden)

    Planko Rožić

    2005-09-01

    Full Text Available Systemic traffic count on the Croatian road network hasbeen carried out for more than three decades in different ways.During this period a large number of automatic traffic countershave been installed, and they operate on different principles.The traffic count has been analyzed from the aspect of vehicleclassification. The count results can be only partly comparedsince they yield different structures of traffic flows. Special analysisrefers to the classification of vehicles by automatic trafficcounters.During the research, a database has been formed with physicalelements of vehicles of over five thousand vehicle types. Theresearch results prove that the vehicle length only is not sufficientfor the classification of vehicles, the way it is used in thepresent automatic traffic counts, but rather the number of axles,the wheelbase as well as the front and rear overhangs needto be considered as well. Therefore, the detector system shouldapply also the detector of axles.The results have been presented that were obtained as partof the program TEST- Technological, research, developmentproject supported by the Minist1y of Science, Education andSport.

  7. Traffic modeling of transit oriented development : evaluation of transit friendly strategies and innovative intersection designs in West Valley City, UT.

    Science.gov (United States)

    2014-07-01

    Street networks designed to support Transit Oriented Development (TOD) increase accessibility for non-motorized traffic. However, the implications of TOD supportive networks for still dominant vehicular : traffic are rarely addressed. Due to this lac...

  8. Queueing and traffic

    NARCIS (Netherlands)

    Baër, Niek

    2015-01-01

    Traffic jams are everywhere, some are caused by constructions or accidents but a large portion occurs naturally. These "natural" traffic jams are a result of variable driving speeds combined with a high number of vehicles. To prevent these traffic jams, we must understand traffic in general, and to

  9. Jamitons: Phantom Traffic Jams

    Science.gov (United States)

    Kowszun, Jorj

    2013-01-01

    Traffic on motorways can slow down for no apparent reason. Sudden changes in speed by one or two drivers can create a chain reaction that causes a traffic jam for the vehicles that are following. This kind of phantom traffic jam is called a "jamiton" and the article discusses some of the ways in which traffic engineers produce…

  10. SOME EMPIRICAL RELATIONS BETWEEN TRAVEL SPEED, TRAFFIC VOLUME AND TRAFFIC COMPOSITION IN URBAN ARTERIALS

    Directory of Open Access Journals (Sweden)

    Eleni I. VLAHOGIANNI, Ph.D.

    2007-01-01

    Full Text Available The effects of traffic mix (the percentage of cars, trucks, buses and so on are of particular interest in the speed-volume relationship in urban signalized arterials under various geometric and control characteristics. The paper presents some empirical observations on the relation between travel speed, traffic volume and traffic composition in urban signalized arterials. A methodology based on emerging self-organizing structures of neural networks to identify regions in the speed-volume relationship with respect to traffic composition and Bayesian networks to evaluate the effect of different types of motorized vehicles on prevailing traffic conditions is proposed. Results based on data from a large urban network indicate that the variability in traffic conditions can be described by eight regions in speed-volume relationship with respect to traffic composition. Further evaluation of the effect of motorized vehicles in each region separately indicates that the effect of traffic composition decreases with the onset of congestion. Moreover, taxis and motorcycles are the primary affecting parameter of the form of the speed-volume relationship in urban arterials.

  11. Traffic Speed Data Imputation Method Based on Tensor Completion

    Directory of Open Access Journals (Sweden)

    Bin Ran

    2015-01-01

    Full Text Available Traffic speed data plays a key role in Intelligent Transportation Systems (ITS; however, missing traffic data would affect the performance of ITS as well as Advanced Traveler Information Systems (ATIS. In this paper, we handle this issue by a novel tensor-based imputation approach. Specifically, tensor pattern is adopted for modeling traffic speed data and then High accurate Low Rank Tensor Completion (HaLRTC, an efficient tensor completion method, is employed to estimate the missing traffic speed data. This proposed method is able to recover missing entries from given entries, which may be noisy, considering severe fluctuation of traffic speed data compared with traffic volume. The proposed method is evaluated on Performance Measurement System (PeMS database, and the experimental results show the superiority of the proposed approach over state-of-the-art baseline approaches.

  12. Load characterization, overload prediction, and anomaly detection for voice over IP traffic

    NARCIS (Netherlands)

    Mandjes, Michel; Saniee, Iraj; Stolyar, Alexander; Heidelberger, P.

    2001-01-01

    We consider the problem of traffic anomaly detection in IP networks. Traffic anomalies arise when there is overload due to failures in a network. We present general formulae for the variance of the cumulative traffic over a fixed time interval and show how the derived analytical expression

  13. An efficient method to detect periodic behavior in botnet traffic by analyzing control plane traffic.

    Science.gov (United States)

    AsSadhan, Basil; Moura, José M F

    2014-07-01

    Botnets are large networks of bots (compromised machines) that are under the control of a small number of bot masters. They pose a significant threat to Internet's communications and applications. A botnet relies on command and control (C2) communications channels traffic between its members for its attack execution. C2 traffic occurs prior to any attack; hence, the detection of botnet's C2 traffic enables the detection of members of the botnet before any real harm happens. We analyze C2 traffic and find that it exhibits a periodic behavior. This is due to the pre-programmed behavior of bots that check for updates to download them every T seconds. We exploit this periodic behavior to detect C2 traffic. The detection involves evaluating the periodogram of the monitored traffic. Then applying Walker's large sample test to the periodogram's maximum ordinate in order to determine if it is due to a periodic component or not. If the periodogram of the monitored traffic contains a periodic component, then it is highly likely that it is due to a bot's C2 traffic. The test looks only at aggregate control plane traffic behavior, which makes it more scalable than techniques that involve deep packet inspection (DPI) or tracking the communication flows of different hosts. We apply the test to two types of botnet, tinyP2P and IRC that are generated by SLINGbot. We verify the periodic behavior of their C2 traffic and compare it to the results we get on real traffic that is obtained from a secured enterprise network. We further study the characteristics of the test in the presence of injected HTTP background traffic and the effect of the duty cycle on the periodic behavior.

  14. An efficient method to detect periodic behavior in botnet traffic by analyzing control plane traffic

    Directory of Open Access Journals (Sweden)

    Basil AsSadhan

    2014-07-01

    Full Text Available Botnets are large networks of bots (compromised machines that are under the control of a small number of bot masters. They pose a significant threat to Internet’s communications and applications. A botnet relies on command and control (C2 communications channels traffic between its members for its attack execution. C2 traffic occurs prior to any attack; hence, the detection of botnet’s C2 traffic enables the detection of members of the botnet before any real harm happens. We analyze C2 traffic and find that it exhibits a periodic behavior. This is due to the pre-programmed behavior of bots that check for updates to download them every T seconds. We exploit this periodic behavior to detect C2 traffic. The detection involves evaluating the periodogram of the monitored traffic. Then applying Walker’s large sample test to the periodogram’s maximum ordinate in order to determine if it is due to a periodic component or not. If the periodogram of the monitored traffic contains a periodic component, then it is highly likely that it is due to a bot’s C2 traffic. The test looks only at aggregate control plane traffic behavior, which makes it more scalable than techniques that involve deep packet inspection (DPI or tracking the communication flows of different hosts. We apply the test to two types of botnet, tinyP2P and IRC that are generated by SLINGbot. We verify the periodic behavior of their C2 traffic and compare it to the results we get on real traffic that is obtained from a secured enterprise network. We further study the characteristics of the test in the presence of injected HTTP background traffic and the effect of the duty cycle on the periodic behavior.

  15. Particle density fluctuations

    Energy Technology Data Exchange (ETDEWEB)

    Aggarwal, M.M.; Ahammed, Z.; Angelis, A.L.S.; Antonenko, V.; Arefiev, V.; Astakhov, V.; Avdeitchikov, V.; Awes, T.C.; Baba, P.V.K.S.; Badyal, S.K.; Bathe, S.; Batiounia, B.; Bernier, T.; Bhalla, K.B.; Bhatia, V.S.; Blume, C.; Bucher, D.; Buesching, H.; Carlen, L.; Chattopadhyay, S.; Das, A.C.; Decowski, M.P.; Donni, P.; Dubey, A.K.; Dutta Majumdar, M.R.; Enosawa, K.; Fokin, S.; Frolov, V.; Ganti, M.S.; Garpman, S.; Gavrishcuk, O.; Geurts, F.J.M.; Glasow, R.; Guskov, B.; Gustafsson, H.A.; Gutbrod, H.H.; Hrivnacova, I.; Ippolitov, M.; Kalechofsky, H.; Kamermans, R.; Karadjev, K.; Karpio, K.; Kolb, B.W.; Kosarev, I.; Koutcheryaev, I.; Kugler, A.; Kulinich, P.; Kurata, M.; Lebedev, A.; Loehner, H.; Mahapatra, D.P.; Manko, V.; Martin, M.; Miake, Y.; Mishra, G.C.; Mohanty, B.; Morrison, D.; Mukhopadhayay, D.S.; Naef, H.; Nandi, B.K.; Nayak, S.K.; Nayak, T.K.; Nianine, A.; Nikitine, V.; Nikolaev, S.; Nishimura, S.; Nomokov, P.; Petracek, V.; Plasil, F.; Purschke, M.L.; Rak, J.; Raniwala, R.; Raniwala, S.; Rao, N.K.; Retiere, F.; Reygers, K.; Roland, G.; Rosselet, L.; Roufanov, I.; Rubio, J.M.; Sambyal, S.S.; Santo, R.; Sato, S.; Schlagheck, H.; Schmidt, H.-R.; Schutz, Y.; Shabratova, G.; Sibiriak, I.; Siemiarczuk, T.; Sinha, B.C.; Slavine, N.; Soederstroem, K.; Sood, G.; Soerensen, S.P.; Stankus, P.; Steinberg, P.; Stenlund, E.; Sumbera, M.; Svensson, T.; Trivedi, M.D.; Tsvetkov, A.; Tykarski, L.; Urbahn, J.; Eijinhoven, N. van; Niewenhuizen, G.J. van; Vinogradov, A.; Viyogi, Y.P.; Vodopianov, A.; Voeroes, S.; Wyslouch, B.; Young, G.R

    2003-03-10

    Event-by-event fluctuations in the multiplicities of charged particles and photons at SPS energies are discussed. Fluctuations are studied by controlling the centrality of the reaction and rapidity acceptance of the detectors. Results are also presented on the event-by-event study of correlations between the multiplicity of charged particles and photons to search for DCC-like signals.

  16. Particle density fluctuations

    CERN Document Server

    Mohanty, Bedangadas; Ahammed, Z.; Angelis, A.L.S.; Antonenko, V.; Arefev, V.; Astakhov, V.; Avdeitchikov, V.; Awes, T.C.; Baba, P.V.K.S.; Badyal, S.K.; Bathe, S.; Batiounia, B.; Bernier, T.; Bhalla, K.B.; Bhatia, V.S.; Blume, C.; Bucher, D.; Busching, H.; Carlen, L.; Chattopadhyay, S.; Das, A.C.; Decowski, M.P.; Donni, P.; Dubey, A.K.; Dutta Majumdar, M.R.; Enosawa, K.; Fokin, S.; Frolov, V.; Ganti, M.S.; Garpman, S.; Gavrishchuk, O.; Geurts, F.J.M.; Glasow, R.; Guskov, B.; Gustafsson, H.A.; Gutbrod, H.H.; Hrivnacova, I.; Ippolitov, M.; Kalechofsky, H.; Kamermans, R.; Karadjev, K.; Karpio, K.; Kolb, B.W.; Kosarev, I.; Koutcheryaev, I.; Kugler, A.; Kulinich, P.; Kurata, M.; Lebedev, A.; Lohne, H.; Mahapatra, D.P.; Manko, V.; Martin, M.; Miake, Y.; Mishra, G.C.; Morrison, D.; Mukhopadhyay, D.S.; Naef, H.; Nandi, B.K.; Nayak, S.K.; Nayak, T.K.; Nianine, A.; Nikitine, V.; Nikolaev, S.; Nishimura, S.; Nomokov, P.; Nystrand, J.; Oskarsson, A.; Otterlund, I.; Phatak, S.C.; Pavliouk, S.; Peitzmann, T.; Petracek, V.; Plasil, F.; Purschke, M.L.; Rak, J.; Raniwala, R.; Raniwala, S.; Rao, N.K.; Retiere, F.; Reygers, K.; Roland, G.; Rosselet, L.; Roufanov, I.; Rubio, J.M.; Sambyal, S.S.; Santo, R.; Sato, S.; Schlagheck, H.; Schmidt, H.R.; Schutz, Y.; Shabratova, G.; Sibiriak, I.; Siemiarczuk, T.; Sinha, B.C.; Slavine, N.; Soderstrom, K.; Sood, G.; Sorensen, S.P.; Stankus, P.; Stefanek, G.; Steinberg, P.; Stenlund, E.; Sumbera, M.; Svensson, T.; Trivedi, M.D.; Tsvetkov, A.; Tykarski, L.; Urbahn, J.; van Eijndhoven, N.; van Nieuwenhuizen, G.J.; Vinogradov, A.; Viyogi, Y.P.; Vodopianov, A.S.; Voros, S.; Wyslouch, B.; Young, G.R.; Mohanty, Bedangadas

    2003-01-01

    Event-by-event fluctuations in the multiplicities of charged particles and photons at SPS energies are discussed. Fluctuations are studied by controlling the centrality of the reaction and rapidity acceptance of the detectors. Results are also presented on the event-by-event study of correlations between the multiplicity of charged particles and photons to search for DCC-like signals.

  17. 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.

  18. Self-organizing feature map (neural networks) as a tool to select the best indicator of road traffic pollution (soil, leaves or bark of Robinia pseudoacacia L.).

    Science.gov (United States)

    Samecka-Cymerman, A; Stankiewicz, A; Kolon, K; Kempers, A J

    2009-07-01

    Concentrations of the elements Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb and Zn were measured in the leaves and bark of Robinia pseudoacacia and the soil in which it grew, in the town of Oleśnica (SW Poland) and at a control site. We selected this town because emission from motor vehicles is practically the only source of air pollution, and it seemed interesting to evaluate its influence on soil and plants. The self-organizing feature map (SOFM) yielded distinct groups of soils and R. pseudoacacia leaves and bark, depending on traffic intensity. Only the map classifying bark samples identified an additional group of highly polluted sites along the main highway from Wrocław to Warszawa. The bark of R. pseudoacacia seems to be a better bioindicator of long-term cumulative traffic pollution in the investigated area, while leaves are good indicators of short-term seasonal accumulation trends.

  19. Continuous information flow fluctuations

    Science.gov (United States)

    Rosinberg, Martin Luc; Horowitz, Jordan M.

    2016-10-01

    Information plays a pivotal role in the thermodynamics of nonequilibrium processes with feedback. However, much remains to be learned about the nature of information fluctuations in small-scale devices and their relation with fluctuations in other thermodynamics quantities, like heat and work. Here we derive a series of fluctuation theorems for information flow and partial entropy production in a Brownian particle model of feedback cooling and extend them to arbitrary driven diffusion processes. We then analyze the long-time behavior of the feedback-cooling model in detail. Our results provide insights into the structure and origin of large deviations of information and thermodynamic quantities in autonomous Maxwell's demons.

  20. Fluctuation scaling, Taylor's law, and crime.

    Science.gov (United States)

    Hanley, Quentin S; Khatun, Suniya; Yosef, Amal; Dyer, Rachel-May

    2014-01-01

    Fluctuation scaling relationships have been observed in a wide range of processes ranging from internet router traffic to measles cases. Taylor's law is one such scaling relationship and has been widely applied in ecology to understand communities including trees, birds, human populations, and insects. We show that monthly crime reports in the UK show complex fluctuation scaling which can be approximated by Taylor's law relationships corresponding to local policing neighborhoods and larger regional and countrywide scales. Regression models applied to local scale data from Derbyshire and Nottinghamshire found that different categories of crime exhibited different scaling exponents with no significant difference between the two regions. On this scale, violence reports were close to a Poisson distribution (α = 1.057 ± 0.026) while burglary exhibited a greater exponent (α = 1.292 ± 0.029) indicative of temporal clustering. These two regions exhibited significantly different pre-exponential factors for the categories of anti-social behavior and burglary indicating that local variations in crime reports can be assessed using fluctuation scaling methods. At regional and countrywide scales, all categories exhibited scaling behavior indicative of temporal clustering evidenced by Taylor's law exponents from 1.43 ± 0.12 (Drugs) to 2.094 ± 0081 (Other Crimes). Investigating crime behavior via fluctuation scaling gives insight beyond that of raw numbers and is unique in reporting on all processes contributing to the observed variance and is either robust to or exhibits signs of many types of data manipulation.