network traffic fluctuations: Topics by WorldWideScience.org

Sample records for network traffic fluctuations

A hierarchical clustering scheme approach to assessment of IP-network traffic using detrended fluctuation analysis

Science.gov (United States)

Takuma, Takehisa; Masugi, Masao

2009-03-01

This paper presents an approach to the assessment of IP-network traffic in terms of the time variation of self-similarity. To get a comprehensive view in analyzing the degree of long-range dependence (LRD) of IP-network traffic, we use a hierarchical clustering scheme, which provides a way to classify high-dimensional data with a tree-like structure. Also, in the LRD-based analysis, we employ detrended fluctuation analysis (DFA), which is applicable to the analysis of long-range power-law correlations or LRD in non-stationary time-series signals. Based on sequential measurements of IP-network traffic at two locations, this paper derives corresponding values for the LRD-related parameter α that reflects the degree of LRD of measured data. In performing the hierarchical clustering scheme, we use three parameters: the α value, average throughput, and the proportion of network traffic that exceeds 80% of network bandwidth for each measured data set. We visually confirm that the traffic data can be classified in accordance with the network traffic properties, resulting in that the combined depiction of the LRD and other factors can give us an effective assessment of network conditions at different times.
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.
Understanding characteristics in multivariate traffic flow time series from complex network structure

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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.
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 solu...... 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...... 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......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...
Network traffic anomaly prediction using Artificial Neural Network

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

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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.
Predicting Information Flows in Network Traffic.

Science.gov (United States)

Hinich, Melvin J.; Molyneux, Robert E.

2003-01-01

Discusses information flow in networks and predicting network traffic and describes a study that uses time series analysis on a day's worth of Internet log data. Examines nonlinearity and traffic invariants, and suggests that prediction of network traffic may not be possible with current techniques. (Author/LRW)
The Stability of Multi-modal Traffic Network

International Nuclear Information System (INIS)

Han Linghui; Sun Huijun; Zhu Chengjuan; Jia Bin; Wu Jianjun

2013-01-01

There is an explicit and implicit assumption in multimodal traffic equilibrium models, that is, if the equilibrium exists, then it will also occur. The assumption is very idealized; in fact, it may be shown that the quite contrary could happen, because in multimodal traffic network, especially in mixed traffic conditions the interaction among traffic modes is asymmetric and the asymmetric interaction may result in the instability of traffic system. In this paper, to study the stability of multimodal traffic system, we respectively present the travel cost function in mixed traffic conditions and in traffic network with dedicated bus lanes. Based on a day-to-day dynamical model, we study the evolution of daily route choice of travelers in multimodal traffic network using 10000 random initial values for different cases. From the results of simulation, it can be concluded that the asymmetric interaction between the cars and buses in mixed traffic conditions can lead the traffic system to instability when traffic demand is larger. We also study the effect of travelers' perception error on the stability of multimodal traffic network. Although the larger perception error can alleviate the effect of interaction between cars and buses and improve the stability of traffic system in mixed traffic conditions, the traffic system also become instable when the traffic demand is larger than a number. For all cases simulated in this study, with the same parameters, traffic system with dedicated bus lane has better stability for traffic demand than that in mixed traffic conditions. We also find that the network with dedicated bus lane has higher portion of travelers by bus than it of mixed traffic network. So it can be concluded that building dedicated bus lane can improve the stability of traffic system and attract more travelers to choose bus reducing the traffic congestion. (general)
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.
Spatiotemporal Recurrent Convolutional Networks for Traffic Prediction in Transportation Networks.

Science.gov (United States)

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

2017-06-26

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

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

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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.
Modeling Network Traffic in Wavelet Domain

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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.
Multicast traffic grooming in flexible optical WDM networks

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Patel, Ankitkumar N.; Ji, Philip N.; Jue, Jason P.; Wang, Ting

2012-12-01

In Metropolitan Area Networks (MANs), point-to-multipoint applications, such as IPTV, video-on-demand, distance learning, and content distribution, can be efficiently supported through light-tree-based multicastcommunications instead of lightpath-based unicast-communications. The application of multicasting for such traffic is justified by its inherent benefits of reduced control and management overhead and elimination of redundant resource provisioning. Supporting such multicast traffic in Flexible optical WDM (FWDM) networks that can provision light-trees using optimum amount of spectrum within flexible channel spacing leads to higher wavelength and spectral efficiencies compared to the conventional ITU-T fixed grid networks. However, in spite of such flexibility, the residual channel capacity of stranded channels may not be utilized if the network does not offer channels with arbitrary line rates. Additionally, the spectrum allocated to guard bands used to isolate finer granularity channels remains unutilized. These limitations can be addressed by using traffic grooming in which low-rate multicast connections are aggregated and switched over high capacity light-trees. In this paper, we address the multicast traffic grooming problem in FWDM networks, and propose a novel auxiliary graph-based algorithm for the first time. The performance of multicast traffic grooming is evaluated in terms of spectral, cost, and energy efficiencies compared to lightpath-based transparent FWDM networks, lightpathbased traffic grooming-capable FWDM networks, multicast-enabled transparent FWDM networks, and multicast traffic grooming-capable fixed grid networks. Simulation results demonstrate that multicast traffic grooming in FWDM networks not only improves spectral efficiency, but also cost, and energy efficiencies compared to other multicast traffic provisioning approaches of FWDM and fixed grid networks.
Minimal-delay traffic grooming for WDM star networks

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Choi, Hongsik; Garg, Nikhil; Choi, Hyeong-Ah

2003-10-01

All-optical networks face the challenge of reducing slower opto-electronic conversions by managing assignment of traffic streams to wavelengths in an intelligent manner, while at the same time utilizing bandwidth resources to the maximum. This challenge becomes harder in networks closer to the end users that have insufficient data to saturate single wavelengths as well as traffic streams outnumbering the usable wavelengths, resulting in traffic grooming which requires costly traffic analysis at access nodes. We study the problem of traffic grooming that reduces the need to analyze traffic, for a class of network architecture most used by Metropolitan Area Networks; the star network. The problem being NP-complete, we provide an efficient twice-optimal-bound greedy heuristic for the same, that can be used to intelligently groom traffic at the LANs to reduce latency at the access nodes. Simulation results show that our greedy heuristic achieves a near-optimal solution.
Active Traffic Capture for Network Forensics

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Slaviero, Marco; Granova, Anna; Olivier, Martin

Network traffic capture is an integral part of network forensics, but current traffic capture techniques are typically passive in nature. Under heavy loads, it is possible for a sniffer to miss packets, which affects the quality of forensic evidence.
Self-Similar Traffic In Wireless Networks

OpenAIRE

Jerjomins, R.; Petersons, E.

2005-01-01

Many studies have shown that traffic in Ethernet and other wired networks is self-similar. This paper reveals that wireless network traffic is also self-similar and long-range dependant by analyzing big amount of data captured from the wireless router.
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...
Consistency analysis of network traffic repositories

NARCIS (Netherlands)

Lastdrager, Elmer; Lastdrager, E.E.H.; Pras, Aiko

Traffic repositories with TCP/IP header information are very important for network analysis. Researchers often assume that such repositories reliably represent all traffic that has been flowing over the network; little thoughts are made regarding the consistency of these repositories. Still, for

Noise-Assisted Concurrent Multipath Traffic Distribution in Ad Hoc Networks

Science.gov (United States)

Murata, Masayuki

2013-01-01

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. PMID:24319375
Linking network usage patterns to traffic Gaussianity fit

NARCIS (Netherlands)

de Oliveira Schmidt, R.; Sadre, R.; Melnikov, Nikolay; Schönwälder, Jürgen; Pras, Aiko

Gaussian traffic models are widely used in the domain of network traffic modeling. The central assumption is that traffic aggregates are Gaussian distributed. Due to its importance, the Gaussian character of network traffic has been extensively assessed by researchers in the past years. In 2001,
Classification and Analysis of Computer Network Traffic

OpenAIRE

Bujlow, Tomasz

2014-01-01

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 of traffic for academic purposes. We define the objective of this thesis as finding a way to evaluate the performance of various applications in a high-speed Internet infrastructure. To satisfy the obje...
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.
Consensus-Based Cooperative Control Based on Pollution Sensing and Traffic Information for Urban Traffic Networks

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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.
Fine-granularity inference and estimations to network traffic for SDN.

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Dingde Jiang

Full Text Available An end-to-end network traffic matrix is significantly helpful for network management and for Software Defined Networks (SDN. However, the end-to-end network traffic matrix's inferences and estimations are a challenging problem. Moreover, attaining the traffic matrix in high-speed networks for SDN is a prohibitive challenge. This paper investigates how to estimate and recover the end-to-end network traffic matrix in fine time granularity from the sampled traffic traces, which is a hard inverse problem. Different from previous methods, the fractal interpolation is used to reconstruct the finer-granularity network traffic. Then, the cubic spline interpolation method is used to obtain the smooth reconstruction values. To attain an accurate the end-to-end network traffic in fine time granularity, we perform a weighted-geometric-average process for two interpolation results that are obtained. The simulation results show that our approaches are feasible and effective.
Fine-granularity inference and estimations to network traffic for SDN.

Science.gov (United States)

Jiang, Dingde; Huo, Liuwei; Li, Ya

2018-01-01

An end-to-end network traffic matrix is significantly helpful for network management and for Software Defined Networks (SDN). However, the end-to-end network traffic matrix's inferences and estimations are a challenging problem. Moreover, attaining the traffic matrix in high-speed networks for SDN is a prohibitive challenge. This paper investigates how to estimate and recover the end-to-end network traffic matrix in fine time granularity from the sampled traffic traces, which is a hard inverse problem. Different from previous methods, the fractal interpolation is used to reconstruct the finer-granularity network traffic. Then, the cubic spline interpolation method is used to obtain the smooth reconstruction values. To attain an accurate the end-to-end network traffic in fine time granularity, we perform a weighted-geometric-average process for two interpolation results that are obtained. The simulation results show that our approaches are feasible and effective.
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...
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....
Critical Fluctuations in Spatial Complex Networks

Science.gov (United States)

Bradde, Serena; Caccioli, Fabio; Dall'Asta, Luca; Bianconi, Ginestra

2010-05-01

An anomalous mean-field solution is known to capture the nontrivial phase diagram of the Ising model in annealed complex networks. Nevertheless, the critical fluctuations in random complex networks remain mean field. Here we show that a breakdown of this scenario can be obtained when complex networks are embedded in geometrical spaces. Through the analysis of the Ising model on annealed spatial networks, we reveal, in particular, the spectral properties of networks responsible for critical fluctuations and we generalize the Ginsburg criterion to complex topologies.
Competitive Traffic Assignment in Road Networks

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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.
Intrinsically-generated fluctuating activity in excitatory-inhibitory networks

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Mastrogiuseppe, Francesca; Ostojic, Srdjan

2017-01-01

Recurrent networks of non-linear units display a variety of dynamical regimes depending on the structure of their synaptic connectivity. A particularly remarkable phenomenon is the appearance of strongly fluctuating, chaotic activity in networks of deterministic, but randomly connected rate units. How this type of intrinsically generated fluctuations appears in more realistic networks of spiking neurons has been a long standing question. To ease the comparison between rate and spiking networks, recent works investigated the dynamical regimes of randomly-connected rate networks with segregated excitatory and inhibitory populations, and firing rates constrained to be positive. These works derived general dynamical mean field (DMF) equations describing the fluctuating dynamics, but solved these equations only in the case of purely inhibitory networks. Using a simplified excitatory-inhibitory architecture in which DMF equations are more easily tractable, here we show that the presence of excitation qualitatively modifies the fluctuating activity compared to purely inhibitory networks. In presence of excitation, intrinsically generated fluctuations induce a strong increase in mean firing rates, a phenomenon that is much weaker in purely inhibitory networks. Excitation moreover induces two different fluctuating regimes: for moderate overall coupling, recurrent inhibition is sufficient to stabilize fluctuations; for strong coupling, firing rates are stabilized solely by the upper bound imposed on activity, even if inhibition is stronger than excitation. These results extend to more general network architectures, and to rate networks receiving noisy inputs mimicking spiking activity. Finally, we show that signatures of the second dynamical regime appear in networks of integrate-and-fire neurons. PMID:28437436
Collective fluctuations in networks of noisy components

International Nuclear Information System (INIS)

Masuda, Naoki; Kawamura, Yoji; Kori, Hiroshi

2010-01-01

Collective dynamics result from interactions among noisy dynamical components. Examples include heartbeats, circadian rhythms and various pattern formations. Because of noise in each component, collective dynamics inevitably involve fluctuations, which may crucially affect the functioning of the system. However, the relation between the fluctuations in isolated individual components and those in collective dynamics is not clear. Here, we study a linear dynamical system of networked components subjected to independent Gaussian noise and analytically show that the connectivity of networks determines the intensity of fluctuations in the collective dynamics. Remarkably, in general directed networks including scale-free networks, the fluctuations decrease more slowly with system size than the standard law stated by the central limit theorem. They even remain finite for a large system size when global directionality of the network exists. Moreover, such non-trivial behavior appears even in undirected networks when nonlinear dynamical systems are considered. We demonstrate it with a coupled oscillator system.
Traffic Dynamics on Complex Networks: A Survey

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Shengyong Chen

2012-01-01

Full Text Available Traffic dynamics on complex networks are intriguing in recent years due to their practical implications in real communication networks. In this survey, we give a brief review of studies on traffic routing dynamics on complex networks. Strategies for improving transport efficiency, including designing efficient routing strategies and making appropriate adjustments to the underlying network structure, are introduced in this survey. Finally, a few open problems are discussed in this survey.
Urban Traffic Signal System Control Structural Optimization Based on Network Analysis

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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.
Traffic Policing in Dynamic Military Networks Using Software Defined Networking

OpenAIRE

Skappel, Hans Fredrik

2016-01-01

This thesis looks at how Software Defined Networking (SDN) can be used to provide traffic engineering and to police traffic in an Operational Military Network (OMN). SDN is a concept where the control plane is separated from the forwarding plane, and the control plane is capable of controlling forwarding plane elements located on multiple network nodes using the OpenFlow protocol. Specifically, we have discussed the problems in OMNs, and possible SDN approaches to mitigate the challenges. Bas...
Network Analysis of Urban Traffic with Big Bus Data

OpenAIRE

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 ...
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.
Proactive Traffic Information Control in Emergency Evacuation Network

Directory of Open Access Journals (Sweden)

Zhengfeng Huang

2015-01-01

Full Text Available Traffic demand in emergency evacuation is usually too large to be effectively managed with reactive traffic information control methods. These methods adapt to the road traffic passively by publishing real-time information without consideration of the routing behavior feedback produced by evacuees. Other remedy measures have to be prepared in case of nonrecurring congestion under these methods. To use the network capacity fully to mitigate near-future evacuation traffic congestion, we propose proactive traffic information control (PTIC model. Based on the mechanism between information and routing behavior feedback, this model can change the route choice of evacuees in advance by dissipating strategic traffic information. Generally, the near-future traffic condition is difficult to accurately predict because it is uncertain in evacuation. Assume that the value of traffic information obeys certain distribution within a range, and then real-time traffic information may reflect the most-likely near-future traffic condition. Unlike the real-time information, the proactive traffic information is a selection within the range to achieve a desired level of the road network performance index (total system travel time. In the aspect of the solution algorithm, differential equilibrium decomposed optimization (D-EDO is proposed to compare with other heuristic methods. A field study on a road network around a large stadium is used to validate the PTIC.
Sonification of network traffic flow for monitoring and situational awareness

Science.gov (United States)

2018-01-01

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

Sonification of network traffic flow for monitoring and situational awareness.

Science.gov (United States)

Debashi, Mohamed; Vickers, Paul

2018-01-01

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

Directory of Open Access Journals (Sweden)

Wenju Du

2016-01-01

Full Text Available In order to study the dynamic characteristics of urban public traffic network, this paper establishes the conventional bus traffic network and the urban rail traffic network based on the space R modeling method. Then regarding these two networks as the subnetwork, the paper presents a new bilayer coupled public traffic network through the transfer relationship between subway and bus, and this model well reflects the connection between the passengers and bus operating vehicles. Based on the synchronization theory of coupling network with time-varying delay and taking “Lorenz system” as the network node, the paper studies the synchronization of bilayer coupled public traffic network. Finally, numerical results are given to show the impact of public traffic dispatching, delayed departure, the number of public bus stops between bus lines, and the number of transfer stations between two traffic modes on the bilayer coupled public traffic network balance through Matlab simulation.
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.
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.
Forecasting short-term data center network traffic load with convolutional neural networks

Science.gov (United States)

Ordozgoiti, Bruno; Gómez-Canaval, Sandra

2018-01-01

Efficient resource management in data centers is of central importance to content service providers as 90 percent of the network traffic is expected to go through them in the coming years. In this context we propose the use of convolutional neural networks (CNNs) to forecast short-term changes in the amount of traffic crossing a data center network. This value is an indicator of virtual machine activity and can be utilized to shape the data center infrastructure accordingly. The behaviour of network traffic at the seconds scale is highly chaotic and therefore traditional time-series-analysis approaches such as ARIMA fail to obtain accurate forecasts. We show that our convolutional neural network approach can exploit the non-linear regularities of network traffic, providing significant improvements with respect to the mean absolute and standard deviation of the data, and outperforming ARIMA by an increasingly significant margin as the forecasting granularity is above the 16-second resolution. In order to increase the accuracy of the forecasting model, we exploit the architecture of the CNNs using multiresolution input distributed among separate channels of the first convolutional layer. We validate our approach with an extensive set of experiments using a data set collected at the core network of an Internet Service Provider over a period of 5 months, totalling 70 days of traffic at the one-second resolution. PMID:29408936
Forecasting short-term data center network traffic load with convolutional neural networks.

Science.gov (United States)

Mozo, Alberto; Ordozgoiti, Bruno; Gómez-Canaval, Sandra

2018-01-01

Efficient resource management in data centers is of central importance to content service providers as 90 percent of the network traffic is expected to go through them in the coming years. In this context we propose the use of convolutional neural networks (CNNs) to forecast short-term changes in the amount of traffic crossing a data center network. This value is an indicator of virtual machine activity and can be utilized to shape the data center infrastructure accordingly. The behaviour of network traffic at the seconds scale is highly chaotic and therefore traditional time-series-analysis approaches such as ARIMA fail to obtain accurate forecasts. We show that our convolutional neural network approach can exploit the non-linear regularities of network traffic, providing significant improvements with respect to the mean absolute and standard deviation of the data, and outperforming ARIMA by an increasingly significant margin as the forecasting granularity is above the 16-second resolution. In order to increase the accuracy of the forecasting model, we exploit the architecture of the CNNs using multiresolution input distributed among separate channels of the first convolutional layer. We validate our approach with an extensive set of experiments using a data set collected at the core network of an Internet Service Provider over a period of 5 months, totalling 70 days of traffic at the one-second resolution.
Traffic dynamics on coupled spatial networks

International Nuclear Information System (INIS)

Du, Wen-Bo; Zhou, Xing-Lian; Chen, Zhen; Cai, Kai-Quan; Cao, Xian-Bin

2014-01-01

With the rapid development of modern traffic, various means of transportation systems make it more convenient and diversified for passengers to travel out. In this paper, we establish a two-layered spatial network model where the low-speed lower layer is a regular lattice and the high-speed upper layer is a scale-free network embedded in the lattice. Passengers will travel along the path with the minimal travel time, and they can transfer from one layer to the other, which will induce extra transfer cost. We extensively investigate the traffic process on these coupled spatial networks and focus on the effect of the parameter α, the speed ratio between two networks. It is found that, as α grows, the network capacity of the coupled networks increases in the early stage and then decreases, indicating that cooperation between the coupled networks will induce the highest network capacity at an optimal α. We then provide an explanation for this non-monotonous dependence from a micro-scope point of view. The travel time reliability is also examined. Both in free-flow state and congestion state, the travel time is linearly related to the Euclidean distance. However, the variance of travel time in the congestion state is remarkably larger than that in the free-flow state, namely, people have to set aside more redundant time in an unreliable traffic system
Using OpenSSH to secure mobile LAN network traffic

Science.gov (United States)

Luu, Brian B.; Gopaul, Richard D.

2002-08-01

Mobile Internet Protocol (IP) Local Area Network (LAN) is a technique, developed by the U.S. Army Research Laboratory, which allows a LAN to be IP mobile when attaching to a foreign IP-based network and using this network as a means to retain connectivity to its home network. In this paper, we describe a technique that uses Open Secure Shell (OpenSSH) software to ensure secure, encrypted transmission of a mobile LAN's network traffic. Whenever a mobile LAN, implemented with Mobile IP LAN, moves to a foreign network, its gateway (router) obtains an IP address from the new network. IP tunnels, using IP encapsulation, are then established from the gateway through the foreign network to a home agent on its home network. These tunnels provide a virtual two-way connection to the home network for the mobile LAN as if the LAN were connected directly to its home network. Hence, when IP mobile, a mobile LAN's tunneled network traffic must traverse one or more foreign networks that may not be trusted. This traffic could be subject to eavesdropping, interception, modification, or redirection by malicious nodes in these foreign networks. To protect network traffic passing through the tunnels, OpenSSH is used as a means of encryption because it prevents surveillance, modification, and redirection of mobile LAN traffic passing across foreign networks. Since the software is found in the public domain, is available for most current operating systems, and is commonly used to provide secure network communications, OpenSSH is the software of choice.
A Bayes Theory-Based Modeling Algorithm to End-to-end Network Traffic

OpenAIRE

Zhao Hong-hao; Meng Fan-bo; Zhao Si-wen; Zhao Si-hang; Lu Yi

2016-01-01

Recently, network traffic has exponentially increasing due to all kind of applications, such as mobile Internet, smart cities, smart transportations, Internet of things, and so on. the end-to-end network traffic becomes more important for traffic engineering. Usually end-to-end traffic estimation is highly difficult. This paper proposes a Bayes theory-based method to model the end-to-end network traffic. Firstly, the end-to-end network traffic is described as a independent identically distrib...
Efficient Algorithms for Network-Wide Road Traffic Control

NARCIS (Netherlands)

van de Weg, G.S.

2017-01-01

Controlling road traffic networks is a complex problem. One of the difficulties is the coordination of actuators, such as traffic lights, variables speed limits, ramp metering and route guidance, with the aim to improve the network performance over a near-future time horizon. This dissertation
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.
A Bayes Theory-Based Modeling Algorithm to End-to-end Network Traffic

Directory of Open Access Journals (Sweden)

Zhao Hong-hao

2016-01-01

Full Text Available Recently, network traffic has exponentially increasing due to all kind of applications, such as mobile Internet, smart cities, smart transportations, Internet of things, and so on. the end-to-end network traffic becomes more important for traffic engineering. Usually end-to-end traffic estimation is highly difficult. This paper proposes a Bayes theory-based method to model the end-to-end network traffic. Firstly, the end-to-end network traffic is described as a independent identically distributed normal process. Then the Bases theory is used to characterize the end-to-end network traffic. By calculating the parameters, the model is determined correctly. Simulation results show that our approach is feasible and effective.
Characterization and Modeling of Network Traffic

DEFF Research Database (Denmark)

Shawky, Ahmed; Bergheim, Hans; Ragnarsson, Olafur

2011-01-01

-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...
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.
Optimum principle for a vehicular traffic network: minimum probability of congestion

International Nuclear Information System (INIS)

Kerner, Boris S

2011-01-01

We introduce an optimum principle for a vehicular traffic network with road bottlenecks. This network breakdown minimization (BM) principle states that the network optimum is reached when link flow rates are assigned in the network in such a way that the probability for spontaneous occurrence of traffic breakdown in at least one of the network bottlenecks during a given observation time reaches the minimum possible value. Based on numerical simulations with a stochastic three-phase traffic flow model, we show that in comparison to the well-known Wardrop's principles, the application of the BM principle permits considerably greater network inflow rates at which no traffic breakdown occurs and, therefore, free flow remains in the whole network. (fast track communication)
Effects of node buffer and capacity on network traffic

International Nuclear Information System (INIS)

Ling Xiang; Ding Jian-Xun; Hu Mao-Bin

2012-01-01

In this paper, we study the optimization of network traffic by considering the effects of node buffer ability and capacity. Two node buffer settings are considered. The node capacity is considered to be proportional to its buffer ability. The node effects on network traffic systems are studied with the shortest path protocol and an extension of the optimal routing [Phys. Rev. E 74 046106 (2006)]. In the diagrams of flux—density relationships, it is shown that a nodes buffer ability and capacity have profound effects on the network traffic
Traffic Management for Next Generation Transport Networks

DEFF Research Database (Denmark)

Yu, Hao

required by the next generation transport network to provide Quality-of-Service (QoS) guaranteed video services. Augmenting network capacity and upgrading network nodes indicate long deployment period, replacement of equipment and thus significant cost to the network service providers. This challenge may...... 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...
Optimum principle for a vehicular traffic network: minimum probability of congestion

Energy Technology Data Exchange (ETDEWEB)

Kerner, Boris S, E-mail: boris.kerner@daimler.com [Daimler AG, GR/PTF, HPC: G021, 71059 Sindelfingen (Germany)

2011-03-04

We introduce an optimum principle for a vehicular traffic network with road bottlenecks. This network breakdown minimization (BM) principle states that the network optimum is reached when link flow rates are assigned in the network in such a way that the probability for spontaneous occurrence of traffic breakdown in at least one of the network bottlenecks during a given observation time reaches the minimum possible value. Based on numerical simulations with a stochastic three-phase traffic flow model, we show that in comparison to the well-known Wardrop's principles, the application of the BM principle permits considerably greater network inflow rates at which no traffic breakdown occurs and, therefore, free flow remains in the whole network. (fast track communication)
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-Fi...... to the network backbone. What is more, we give an overview of existing standardization activities on offloading the mobile traffic through Wi-Fi....
Research of convolutional neural networks for traffic sign recognition

OpenAIRE

Stadalnikas, Kasparas

2017-01-01

In this thesis the convolutional neural networks application for traffic sign recognition is analyzed. Thesis describes the basic operations, techniques that are commonly used to apply in the image classification using convolutional neural networks. Also, this paper describes the data sets used for traffic sign recognition, their problems affecting the final training results. The paper reviews most popular existing technologies – frameworks for developing the solution for traffic sign recogni...

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.
Modelling traffic congestion using queuing networks

Indian Academy of Sciences (India)

Flow-density curves; uninterrupted traffic; Jackson networks. ... ness - also suffer from a big handicap vis-a-vis the Indian scenario: most of these models do .... more well-known queuing network models and onsite data, a more exact Road Cell ...
The Effect of Queueing Strategy on Network Traffic

International Nuclear Information System (INIS)

Zhang Xue-Jun; Guan Xiang-Min; Sun Deng-Feng; Tang Shao-Ting

2013-01-01

In recent years, the transportation system has been faced by increasing challenge in congestion and inefficiency, and research in traffic network has become a significant area of interest. In this paper, we introduce a dynamic-information-based (DIB) queueing strategy into network traffic model under the efficient routing strategy. DIB makes a packet with higher priority to be delivered if there are less packets travelling along its path from the current node to the destination. It is found that, compared with the traditional first-in-first-out (FIFO) queueing strategy, DIB can effectively balance the traffic load of the system via delaying packets to be delivered to congested nodes. Although the network capacity has no obvious changes, some other indexes which reflect transportation efficiency are efficiently improved in the congestion state. Besides, extensive simulation results and discussions are provided to explain the phenomena. The results may provide novel insights for research on traffic systems. (condensed matter: structural, mechanical, and thermal properties)
Traffic engineering and regenerator placement in GMPLS networks with restoration

Science.gov (United States)

Yetginer, Emre; Karasan, Ezhan

2002-07-01

In this paper we study regenerator placement and traffic engineering of restorable paths in Generalized Multipro-tocol Label Switching (GMPLS) networks. Regenerators are necessary in optical networks due to transmission impairments. We study a network architecture where there are regenerators at selected nodes and we propose two heuristic algorithms for the regenerator placement problem. Performances of these algorithms in terms of required number of regenerators and computational complexity are evaluated. In this network architecture with sparse regeneration, offline computation of working and restoration paths is studied with bandwidth reservation and path rerouting as the restoration scheme. We study two approaches for selecting working and restoration paths from a set of candidate paths and formulate each method as an Integer Linear Programming (ILP) prob-lem. Traffic uncertainty model is developed in order to compare these methods based on their robustness with respect to changing traffic patterns. Traffic engineering methods are compared based on number of additional demands due to traffic uncertainty that can be carried. Regenerator placement algorithms are also evaluated from a traffic engineering point of view.
Entropy-based heavy tailed distribution transformation and visual analytics for monitoring massive network traffic

Science.gov (United States)

Han, Keesook J.; Hodge, Matthew; Ross, Virginia W.

2011-06-01

For monitoring network traffic, there is an enormous cost in collecting, storing, and analyzing network traffic datasets. Data mining based network traffic analysis has a growing interest in the cyber security community, but is computationally expensive for finding correlations between attributes in massive network traffic datasets. To lower the cost and reduce computational complexity, it is desirable to perform feasible statistical processing on effective reduced datasets instead of on the original full datasets. Because of the dynamic behavior of network traffic, traffic traces exhibit mixtures of heavy tailed statistical distributions or overdispersion. Heavy tailed network traffic characterization and visualization are important and essential tasks to measure network performance for the Quality of Services. However, heavy tailed distributions are limited in their ability to characterize real-time network traffic due to the difficulty of parameter estimation. The Entropy-Based Heavy Tailed Distribution Transformation (EHTDT) was developed to convert the heavy tailed distribution into a transformed distribution to find the linear approximation. The EHTDT linearization has the advantage of being amenable to characterize and aggregate overdispersion of network traffic in realtime. Results of applying the EHTDT for innovative visual analytics to real network traffic data are presented.
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.
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...
Quantifying fluctuations of resting state networks using arterial spin labeling perfusion MRI.

Science.gov (United States)

Dai, Weiying; Varma, Gopal; Scheidegger, Rachel; Alsop, David C

2016-03-01

Blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) has been widely used to investigate spontaneous low-frequency signal fluctuations across brain resting state networks. However, BOLD only provides relative measures of signal fluctuations. Arterial Spin Labeling (ASL) MRI holds great potential for quantitative measurements of resting state network fluctuations. This study systematically quantified signal fluctuations of the large-scale resting state networks using ASL data from 20 healthy volunteers by separating them from global signal fluctuations and fluctuations caused by residual noise. Global ASL signal fluctuation was 7.59% ± 1.47% relative to the ASL baseline perfusion. Fluctuations of seven detected resting state networks vary from 2.96% ± 0.93% to 6.71% ± 2.35%. Fluctuations of networks and residual noise were 6.05% ± 1.18% and 6.78% ± 1.16% using 4-mm resolution ASL data applied with Gaussian smoothing kernel of 6mm. However, network fluctuations were reduced by 7.77% ± 1.56% while residual noise fluctuation was markedly reduced by 39.75% ± 2.90% when smoothing kernel of 12 mm was applied to the ASL data. Therefore, global and network fluctuations are the dominant structured noise sources in ASL data. Quantitative measurements of resting state networks may enable improved noise reduction and provide insights into the function of healthy and diseased brain. © The Author(s) 2015.
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.
Switching performance of OBS network model under prefetched real traffic

Science.gov (United States)

Huang, Zhenhua; Xu, Du; Lei, Wen

2005-11-01

Optical Burst Switching (OBS) [1] is now widely considered as an efficient switching technique in building the next generation optical Internet .So it's very important to precisely evaluate the performance of the OBS network model. The performance of the OBS network model is variable in different condition, but the most important thing is that how it works under real traffic load. In the traditional simulation models, uniform traffics are usually generated by simulation software to imitate the data source of the edge node in the OBS network model, and through which the performance of the OBS network is evaluated. Unfortunately, without being simulated by real traffic, the traditional simulation models have several problems and their results are doubtable. To deal with this problem, we present a new simulation model for analysis and performance evaluation of the OBS network, which uses prefetched IP traffic to be data source of the OBS network model. The prefetched IP traffic can be considered as real IP source of the OBS edge node and the OBS network model has the same clock rate with a real OBS system. So it's easy to conclude that this model is closer to the real OBS system than the traditional ones. The simulation results also indicate that this model is more accurate to evaluate the performance of the OBS network system and the results of this model are closer to the actual situation.
Outer Synchronization between Two Coupled Complex Networks and Its Application in Public Traffic Supernetwork

Directory of Open Access Journals (Sweden)

Wen-ju Du

2016-01-01

Full Text Available The paper presents a new urban public traffic supernetwork model by using the existing bus network modeling method, consisting of the conventional bus traffic network and the urban rail traffic network. We investigate the synchronization problem of urban public traffic supernetwork model by using the coupled complex network’s outer synchronization theory. Analytical and numerical simulations are given to illustrate the impact of traffic dispatching frequency and traffic lines optimization to the urban public traffic supernetwork balance.
Routing strategies in traffic network and phase transition in network ...

Indian Academy of Sciences (India)

3Department of Electronic Engineering, City University of Hong Kong, Hong Kong ... Routing strategy; network traffic flow; hysteretic loop; phase transition from ... ered from two aspects: modifying the underlying network structure or developing ... capacity corresponds to α = −1 in the case of identical nodes' delivering ability.
An analysis of network traffic classification for botnet detection

DEFF Research Database (Denmark)

Stevanovic, Matija; Pedersen, Jens Myrup

2015-01-01

of detecting botnet network traffic using three methods that target protocols widely considered as the main carriers of botnet Command and Control (C&C) and attack traffic, i.e. TCP, UDP and DNS. We propose three traffic classification methods based on capable Random Forests classifier. The proposed methods...
Failure cascade in interdependent network with traffic loads

International Nuclear Information System (INIS)

Hong, Sheng; Wang, Baoqing; Wang, Jianghui; Zhao, Tingdi; Ma, Xiaomin

2015-01-01

Complex networks have been widely studied recent years, but most researches focus on the single, non-interacting networks. With the development of modern systems, many infrastructure networks are coupled together and therefore should be modeled as interdependent networks. For interdependent networks, failure of nodes in one network may lead to failure of dependent nodes in the other networks. This may happen recursively and lead to a failure cascade. In the real world, different networks carry different traffic loads. Overload and load redistribution may lead to more nodes’ failure. Considering the dependency between the interdependent networks and the traffic load, a small fraction of fault nodes may lead to complete fragmentation of a system. Based on the robust analysis of interdependent networks, we propose a costless defense strategy to suppress the failure cascade. Our findings highlight the need to consider the load and coupling preference when designing robust interdependent networks. And it is necessary to take actions in the early stage of the failure cascade to decrease the losses caused by the large-scale breakdown of infrastructure networks. (paper)
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.
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.
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.
Understanding the context of network traffic alerts

NARCIS (Netherlands)

Cappers, B.C.M.; van Wijk, J.J.; Best, D.M.; Staheli, D.; Prigent, N.; Engle, S.; Harrison, L.

2016-01-01

For the protection of critical infrastructures against complex virus attacks, automated network traffic analysis and deep packet inspection are unavoidable. However, even with the use of network intrusion detection systems, the number of alerts is still too large to analyze manually. In addition,
Traffic sign recognition with deep convolutional neural networks

OpenAIRE

Karamatić, Boris

2016-01-01

The problem of detection and recognition of traffic signs is becoming an important problem when it comes to the development of self driving cars and advanced driver assistance systems. In this thesis we will develop a system for detection and recognition of traffic signs. For the problem of detection we will use aggregate channel features and for the problem of recognition we will use a deep convolutional neural network. We will describe how convolutional neural networks work, how they are co...
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.

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...
Traffic signal synchronization in the saturated high-density grid road network.

Science.gov (United States)

Hu, Xiaojian; Lu, Jian; Wang, Wei; Zhirui, Ye

2015-01-01

Most existing traffic signal synchronization strategies do not perform well in the saturated high-density grid road network (HGRN). Traffic congestion often occurs in the saturated HGRN, and the mobility of the network is difficult to restore. In order to alleviate traffic congestion and to improve traffic efficiency in the network, the study proposes a regional traffic signal synchronization strategy, named the long green and long red (LGLR) traffic signal synchronization strategy. The essence of the strategy is to control the formation and dissipation of queues and to maximize the efficiency of traffic flows at signalized intersections in the saturated HGRN. With this strategy, the same signal control timing plan is used at all signalized intersections in the HGRN, and the straight phase of the control timing plan has a long green time and a long red time. Therefore, continuous traffic flows can be maintained when vehicles travel, and traffic congestion can be alleviated when vehicles stop. Using the strategy, the LGLR traffic signal synchronization model is developed, with the objective of minimizing the number of stops. Finally, the simulation is executed to analyze the performance of the model by comparing it to other models, and the superiority of the LGLR model is evident in terms of delay, number of stops, queue length, and overall performance in the saturated HGRN.
Global forward-predicting dynamic routing for traffic concurrency space stereo multi-layer scale-free network

International Nuclear Information System (INIS)

Xie Wei-Hao; Zhou Bin; Liu En-Xiao; Lu Wei-Dang; Zhou Ting

2015-01-01

Many real communication networks, such as oceanic monitoring network and land environment observation network, can be described as space stereo multi-layer structure, and the traffic in these networks is concurrent. Understanding how traffic dynamics depend on these real communication networks and finding an effective routing strategy that can fit the circumstance of traffic concurrency and enhance the network performance are necessary. In this light, we propose a traffic model for space stereo multi-layer complex network and introduce two kinds of global forward-predicting dynamic routing strategies, global forward-predicting hybrid minimum queue (HMQ) routing strategy and global forward-predicting hybrid minimum degree and queue (HMDQ) routing strategy, for traffic concurrency space stereo multi-layer scale-free networks. By applying forward-predicting strategy, the proposed routing strategies achieve better performances in traffic concurrency space stereo multi-layer scale-free networks. Compared with the efficient routing strategy and global dynamic routing strategy, HMDQ and HMQ routing strategies can optimize the traffic distribution, alleviate the number of congested packets effectively and reach much higher network capacity. (paper)
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.
Power Consumption Evaluation of Distributed Computing Network Considering Traffic Locality

Science.gov (United States)

Ogawa, Yukio; Hasegawa, Go; Murata, Masayuki

When computing resources are consolidated in a few huge data centers, a massive amount of data is transferred to each data center over a wide area network (WAN). This results in increased power consumption in the WAN. A distributed computing network (DCN), such as a content delivery network, can reduce the traffic from/to the data center, thereby decreasing the power consumed in the WAN. In this paper, we focus on the energy-saving aspect of the DCN and evaluate its effectiveness, especially considering traffic locality, i.e., the amount of traffic related to the geographical vicinity. We first formulate the problem of optimizing the DCN power consumption and describe the DCN in detail. Then, numerical evaluations show that, when there is strong traffic locality and the router has ideal energy proportionality, the system's power consumption is reduced to about 50% of the power consumed in the case where a DCN is not used; moreover, this advantage becomes even larger (up to about 30%) when the data center is located farthest from the center of the network topology.
Fragmented network subsystem with traffic filtering for microkernel environment

Directory of Open Access Journals (Sweden)

Anna Urievna Budkina

2016-06-01

Full Text Available The TCP/IP stack in a microkernel operating system executed in a user space, which requires the development of a distributed network infrastructure within a single software environment. Its functions are the organization of interaction between the components of the stack with different processes, as well as the organization of filtering mechanisms and routing of internal network traffic. Use of architectural approaches applicable in monolithic-modular systems is impossible, because the network stack is not a shareable component of the system. As a consequence, the microkernel environment requires development of special network subsystem. In this work we provide overview of major conceptions of network architectures in microkernel environments. Also, we provide own architecture which supports filtering of internal network traffic. We evaluate the architecture by development of high-performance "key-value" store.
Dynamic Traffic Congestion Simulation and Dissipation Control Based on Traffic Flow Theory Model and Neural Network Data Calibration Algorithm

Directory of Open Access Journals (Sweden)

Li Wang

2017-01-01

Full Text Available 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 traffic congestion are simulated by using the improved medium traffic model, and the control strategy of congestion dissipation is studied. From the point of view of quantitative traffic congestion, the paper provides the fact that the simulation platform of urban traffic integration is constructed, and a feasible data analysis, learning, and parameter calibration method based on RBF neural network is proposed, which is used to determine the corresponding decision support system. The simulation results prove that the control strategy proposed in this paper is effective and feasible. According to the temporal and spatial evolution of the paper, we can see that the network has been improved on the whole.
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
A paradox for traffic dynamics in complex networks with ATIS

International Nuclear Information System (INIS)

Zheng Jianfeng; Gao Ziyou

2008-01-01

In this work, we study the statistical properties of traffic (e.g., vehicles) dynamics in complex networks, by introducing advanced transportation information systems (ATIS). The ATIS can provide the information of traffic flow pattern throughout the network and have an obvious effect on path routing strategy for such vehicles equipped with ATIS. The ATIS can be described by the understanding of link cost functions. Different indices such as efficiency and system total cost are discussed in depth. It is found that, for random networks (scale-free networks), the efficiency is effectively improved (decreased) if ATIS is properly equipped; however the system total cost is largely increased (decreased). It indicates that there exists a paradox between the efficiency and system total cost in complex networks. Furthermore, we report the simulation results by considering different kinds of link cost functions, and the paradox is recovered. Finally, we extend our traffic model, and also find the existence of the paradox
Study on network traffic forecast model of SVR optimized by GAFSA

International Nuclear Information System (INIS)

Liu, Yuan; Wang, RuiXue

2016-01-01

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

Science.gov (United States)

Wang, William S.; Vanapalli, Siva A.

2014-01-01

We report that modular millifluidic networks are simpler, more cost-effective alternatives to traditional microfluidic networks, and they can be rapidly generated and altered to optimize designs. Droplet traffic can also be studied more conveniently and inexpensively at the millimeter scale, as droplets are readily visible to the naked eye. Bifurcated loops, ladder networks, and parking networks were made using only Tygon® tubing and plastic T-junction fittings and visualized using an iPod® camera. As a case study, droplet traffic experiments through a millifluidic bifurcated loop were conducted, and the periodicity of drop spacing at the outlet was mapped over a wide range of inlet drop spacing. We observed periodic, intermittent, and aperiodic behaviors depending on the inlet drop spacing. The experimentally observed periodic behaviors were in good agreement with numerical simulations based on the simple network model. Our experiments further identified three main sources of intermittency between different periodic and/or aperiodic behaviors: (1) simultaneous entering and exiting events, (2) channel defects, and (3) equal or nearly equal hydrodynamic resistances in both sides of the bifurcated loop. In cases of simultaneous events and/or channel defects, the range of input spacings where intermittent behaviors are observed depends on the degree of inherent variation in input spacing. Finally, using a time scale analysis of syringe pump fluctuations and experiment observation times, we find that in most cases, more consistent results can be generated in experiments conducted at the millimeter scale than those conducted at the micrometer scale. Thus, millifluidic networks offer a simple means to probe collective interactions due to drop traffic and optimize network geometry to engineer passive devices for biological and material analysis. PMID:25553188
Behavioral Profiling of Scada Network Traffic Using Machine Learning Algorithms

Science.gov (United States)

2014-03-27

Acquisition ( SCADA ) System Overview SCADA systems control and monitor processes for water distribution, oil and natural gas pipelines , electrical...the desire for remote control and monitoring of industrial processes. The ability to identify SCADA devices on a mixed traffic network with zero...optimal attribute subset, while maintaining the desired TPR of .99 for SCADA network traffic. The attributes and ML algorithms chosen for
From Cellular Attractor Selection to Adaptive Signal Control for Traffic Networks.

Science.gov (United States)

Tian, Daxin; Zhou, Jianshan; Sheng, Zhengguo; Wang, Yunpeng; Ma, Jianming

2016-03-14

The management of varying traffic flows essentially depends on signal controls at intersections. However, design an optimal control that considers the dynamic nature of a traffic network and coordinates all intersections simultaneously in a centralized manner is computationally challenging. Inspired by the stable gene expressions of Escherichia coli in response to environmental changes, we explore the robustness and adaptability performance of signalized intersections by incorporating a biological mechanism in their control policies, specifically, the evolution of each intersection is induced by the dynamics governing an adaptive attractor selection in cells. We employ a mathematical model to capture such biological attractor selection and derive a generic, adaptive and distributed control algorithm which is capable of dynamically adapting signal operations for the entire dynamical traffic network. We show that the proposed scheme based on attractor selection can not only promote the balance of traffic loads on each link of the network but also allows the global network to accommodate dynamical traffic demands. Our work demonstrates the potential of bio-inspired intelligence emerging from cells and provides a deep understanding of adaptive attractor selection-based control formation that is useful to support the designs of adaptive optimization and control in other domains.
End-to-End Traffic Flow Modeling of the Integrated SCaN Network

Science.gov (United States)

Cheung, K.-M.; Abraham, D. S.

2012-05-01

In this article, we describe the analysis and simulation effort of the end-to-end traffic flow for the Integrated Space Communications and Navigation (SCaN) Network. Using the network traffic derived for the 30-day period of July 2018 from the Space Communications Mission Model (SCMM), we generate the wide-area network (WAN) bandwidths of the ground links for different architecture options of the Integrated SCaN Network. We also develop a new analytical scheme to model the traffic flow and buffering mechanism of a store-and-forward network. It is found that the WAN bandwidth of the Integrated SCaN Network is an important differentiator of different architecture options, as the recurring circuit costs of certain architecture options can be prohibitively high.
A new traffic control design method for large networks with signalized intersections

Science.gov (United States)

Leininger, G. G.; Colony, D. C.; Seldner, K.

1979-01-01

The paper presents a traffic control design technique for application to large traffic networks with signalized intersections. It is shown that the design method adopts a macroscopic viewpoint to establish a new traffic modelling procedure in which vehicle platoons are subdivided into main stream queues and turning queues. Optimization of the signal splits minimizes queue lengths in the steady state condition and improves traffic flow conditions, from the viewpoint of the traveling public. Finally, an application of the design method to a traffic network with thirty-three signalized intersections is used to demonstrate the effectiveness of the proposed technique.
Optimized Sensor Network and Multi-Agent Decision Support for Smart Traffic Light Management.

Science.gov (United States)

Cruz-Piris, Luis; Rivera, Diego; Fernandez, Susel; Marsa-Maestre, Ivan

2018-02-02

One of the biggest challenges in modern societies is to solve vehicular traffic problems. Sensor networks in traffic environments have contributed to improving the decision-making process of Intelligent Transportation Systems. However, one of the limiting factors for the effectiveness of these systems is in the deployment of sensors to provide accurate information about the traffic. Our proposal is using the centrality measurement of a graph as a base to locate the best locations for sensor installation in a traffic network. After integrating these sensors in a simulation scenario, we define a Multi-Agent Systems composed of three types of agents: traffic light management agents, traffic jam detection agents, and agents that control the traffic lights at an intersection. The ultimate goal of these Multi-Agent Systems is to improve the trip duration for vehicles in the network. To validate our solution, we have developed the needed elements for modelling the sensors and agents in the simulation environment. We have carried out experiments using the Simulation of Urban MObility (SUMO) traffic simulator and the Travel and Activity PAtterns Simulation (TAPAS) Cologne traffic scenario. The obtained results show that our proposal allows to reduce the sensor network while still obtaining relevant information to have a global view of the environment. Finally, regarding the Multi-Agent Systems, we have carried out experiments that show that our proposal is able to improve other existing solutions such as conventional traffic light management systems (static or dynamic) in terms of reduction of vehicle trip duration and reduction of the message exchange overhead in the sensor network.
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.
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
Congestion transition in air traffic networks.

Directory of Open Access Journals (Sweden)

Bernardo Monechi

Full Text Available Air Transportation represents a very interesting example of a complex techno-social system whose importance has considerably grown in time and whose management requires a careful understanding of the subtle interplay between technological infrastructure and human behavior. Despite the competition with other transportation systems, a growth of air traffic is still foreseen in Europe for the next years. The increase of traffic load could bring the current Air Traffic Network above its capacity limits so that safety standards and performances might not be guaranteed anymore. Lacking the possibility of a direct investigation of this scenario, we resort to computer simulations in order to quantify the disruptive potential of an increase in traffic load. To this end we model the Air Transportation system as a complex dynamical network of flights controlled by humans who have to solve potentially dangerous conflicts by redirecting aircraft trajectories. The model is driven and validated through historical data of flight schedules in a European national airspace. While correctly reproducing actual statistics of the Air Transportation system, e.g., the distribution of delays, the model allows for theoretical predictions. Upon an increase of the traffic load injected in the system, the model predicts a transition from a phase in which all conflicts can be successfully resolved, to a phase in which many conflicts cannot be resolved anymore. We highlight how the current flight density of the Air Transportation system is well below the transition, provided that controllers make use of a special re-routing procedure. While the congestion transition displays a universal scaling behavior, its threshold depends on the conflict solving strategy adopted. Finally, the generality of the modeling scheme introduced makes it a flexible general tool to simulate and control Air Transportation systems in realistic and synthetic scenarios.
Congestion transition in air traffic networks.

Science.gov (United States)

Monechi, Bernardo; Servedio, Vito D P; Loreto, Vittorio

2015-01-01

Air Transportation represents a very interesting example of a complex techno-social system whose importance has considerably grown in time and whose management requires a careful understanding of the subtle interplay between technological infrastructure and human behavior. Despite the competition with other transportation systems, a growth of air traffic is still foreseen in Europe for the next years. The increase of traffic load could bring the current Air Traffic Network above its capacity limits so that safety standards and performances might not be guaranteed anymore. Lacking the possibility of a direct investigation of this scenario, we resort to computer simulations in order to quantify the disruptive potential of an increase in traffic load. To this end we model the Air Transportation system as a complex dynamical network of flights controlled by humans who have to solve potentially dangerous conflicts by redirecting aircraft trajectories. The model is driven and validated through historical data of flight schedules in a European national airspace. While correctly reproducing actual statistics of the Air Transportation system, e.g., the distribution of delays, the model allows for theoretical predictions. Upon an increase of the traffic load injected in the system, the model predicts a transition from a phase in which all conflicts can be successfully resolved, to a phase in which many conflicts cannot be resolved anymore. We highlight how the current flight density of the Air Transportation system is well below the transition, provided that controllers make use of a special re-routing procedure. While the congestion transition displays a universal scaling behavior, its threshold depends on the conflict solving strategy adopted. Finally, the generality of the modeling scheme introduced makes it a flexible general tool to simulate and control Air Transportation systems in realistic and synthetic scenarios.

Analysis and Classification of Traffic in Wireless Sensor Network

National Research Council Canada - National Science Library

Beng, Wang W

2007-01-01

.... Specifically, this thesis studied the traffic generated by wireless sensor networks by setting up two different commonly used network topologies, namely a direct connection to the base and a daisy...
Nonlinearity and chaos in wireless network traffic

International Nuclear Information System (INIS)

Mukherjee, Somenath; Ray, Rajdeep; Samanta, Rajkumar; Khondekar, Mofazzal H.; Sanyal, Goutam

2017-01-01

The natural complexity of wireless mobile network traffic dynamics has been assessed in this article by tracing the presence of nonlinearity and chaos in the profile of daily peak hour call arrival and daily call drop of a sub-urban local mobile switching centre. The tools like Recurrence Plot and Recurrence Quantification Analysis (RQA) has been used to reveal the probable presence of non-stationarity, nonlinearity and chaosity in the network traffic. Information Entropy (IE) and 0–1 test have been employed to provide the quantitative support to the findings. Both the daily peak hour call arrival profile and the daily call drop profile exhibit non-stationarity, determinism and nonlinearity with the former one being more regular while the later one is chaotic.
Global fluctuations of cerebral blood flow indicate a global brain network independent of systemic factors.

Science.gov (United States)

Zhao, Li; Alsop, David C; Detre, John A; Dai, Weiying

2017-01-01

Global synchronization across specialized brain networks is a common feature of network models and in-vivo electrical measurements. Although the imaging of specialized brain networks with blood oxygenation sensitive resting state functional magnetic resonance imaging (rsfMRI) has enabled detailed study of regional networks, the study of globally correlated fluctuations with rsfMRI is confounded by spurious contributions to the global signal from systemic physiologic factors and other noise sources. Here we use an alternative rsfMRI method, arterial spin labeled perfusion MRI, to characterize global correlations and their relationship to correlations and anti-correlations between regional networks. Global fluctuations that cannot be explained by systemic factors dominate the fluctuations in cerebral blood flow. Power spectra of these fluctuations are band limited to below 0.05 Hz, similar to prior measurements of regional network fluctuations in the brain. Removal of these global fluctuations prior to measurement of regional networks reduces all regional network fluctuation amplitudes to below the global fluctuation amplitude and changes the strength and sign of inter network correlations. Our findings support large amplitude, globally synchronized activity across networks that require a reassessment of regional network amplitude and correlation measures.
Optimized Sensor Network and Multi-Agent Decision Support for Smart Traffic Light Management

Directory of Open Access Journals (Sweden)

Luis Cruz-Piris

2018-02-01

Full Text Available One of the biggest challenges in modern societies is to solve vehicular traffic problems. Sensor networks in traffic environments have contributed to improving the decision-making process of Intelligent Transportation Systems. However, one of the limiting factors for the effectiveness of these systems is in the deployment of sensors to provide accurate information about the traffic. Our proposal is using the centrality measurement of a graph as a base to locate the best locations for sensor installation in a traffic network. After integrating these sensors in a simulation scenario, we define a Multi-Agent Systems composed of three types of agents: traffic light management agents, traffic jam detection agents, and agents that control the traffic lights at an intersection. The ultimate goal of these Multi-Agent Systems is to improve the trip duration for vehicles in the network. To validate our solution, we have developed the needed elements for modelling the sensors and agents in the simulation environment. We have carried out experiments using the Simulation of Urban MObility (SUMO traffic simulator and the Travel and Activity PAtterns Simulation (TAPAS Cologne traffic scenario. The obtained results show that our proposal allows to reduce the sensor network while still obtaining relevant information to have a global view of the environment. Finally, regarding the Multi-Agent Systems, we have carried out experiments that show that our proposal is able to improve other existing solutions such as conventional traffic light management systems (static or dynamic in terms of reduction of vehicle trip duration and reduction of the message exchange overhead in the sensor network.
Delay Bound: Fractal Traffic Passes through Network Servers

Directory of Open Access Journals (Sweden)

Ming Li

2013-01-01

Full Text Available Delay analysis plays a role in real-time systems in computer communication networks. This paper gives our results in the aspect of delay analysis of fractal traffic passing through servers. There are three contributions presented in this paper. First, we will explain the reasons why conventional theory of queuing systems ceases in the general sense when arrival traffic is fractal. Then, we will propose a concise method of delay computation for hard real-time systems as shown in this paper. Finally, the delay computation of fractal traffic passing through severs is presented.
Traffic Route Guidance using Feedback of Predicted Travel Times : Improving Travel Times in the Berlin Traffic Network

OpenAIRE

Bergsten, Arvid; Zetterberg, Daniel

2008-01-01

Traffic congestions constitute a problem in many large cities. Congestions can be handled by reducing the network demand, expanding the infrastructure, or by utilizing the road network more efficiently. This master thesis presents a methodology for route guidance, based on automatic feedback control from the current traffic situation. Through variable direction signs or individual in-car devices, all vehicles with a certain origin and destination (which are both normally intermediate) are gui...
Day-to-day evolution of the traffic network with Advanced Traveler Information System

International Nuclear Information System (INIS)

Han Linghui; Sun Huijun; Wu Jianjun; Zhu Chengjuan

2011-01-01

Highlights: → We develop a dynamical system with Advanced Travelers Information System (ATIS). → We use the dynamical system to study stability of the traffic network with ATIS. → It is found that some periodic attractors appear in some cases. → A road pricing is implemented to alleviate the instability of the traffic network with ATIS. - Abstract: Since the notion of user equilibrium (UE) was proposed by Wardrop , it has become a cornerstone for traffic assignment analysis. But, it is not sufficient to only ask whether equilibrium exists or not; it is equally important to ask whether and how the system can achieve equilibrium. Meanwhile, stability is an important performance in the sense that if equilibrium is unsustainable, both the equilibrium and the trajectory are sensitive to disturbances, even a small perturbation will result in the system evolution away from the equilibrium point. These incentive a growing interest in day-to-day dynamics. In this paper, we develop a dynamical system with Advanced Traveler Information System (ATIS) and study the stability of the network with ATIS. A simple network is used to simulate the model, and the results show that there exist periodic attractors in the traffic network in some cases (for example, the market penetration level of ATIS is 0.25 and traffic demand is 2 unit). It is found that the logit parameter of the dynamical model and the traffic demand can also affect the stability of the traffic network. More periodic attractors appear in the system when the traffic demand is large and the low logit parameter can delay the appearance of periodic attractors. By simulation, it can be concluded that if the range of the periodic attractors' domain of the simple network is known, the road pricing based on the range of the attraction domain is effective to alleviate the instability of the system.
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
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.
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.
Modeling Air Traffic Situation Complexity with a Dynamic Weighted Network Approach

Directory of Open Access Journals (Sweden)

Hongyong Wang

2018-01-01

Full Text Available In order to address the flight delays and risks associated with the forecasted increase in air traffic, there is a need to increase the capacity of air traffic management systems. This should be based on objective measurements of traffic situation complexity. In current air traffic complexity research, no simple means is available to integrate airspace and traffic flow characteristics. In this paper, we propose a new approach for the measurement of air traffic situation complexity. This approach considers the effects of both airspace and traffic flow and objectively quantifies air traffic situation complexity. Considering the aircraft, waypoints, and airways as nodes, and the complexity relationships among these nodes as edges, a dynamic weighted network is constructed. Air traffic situation complexity is defined as the sum of the weights of all edges in the network, and the relationships of complexity with some commonly used indices are statistically analyzed. The results indicate that the new complexity index is more accurate than traffic count and reflects the number of trajectory changes as well as the high-risk situations. Additionally, analysis of potential applications reveals that this new index contributes to achieving complexity-based management, which represents an efficient method for increasing airspace system capacity.
Life Times of Simulated Traffic Jams

Science.gov (United States)

Nagel, Kai

We study a model for freeway traffic which includes strong noise taking into account the fluctuations of individual driving behavior. The model shows emergent traffic jams with a self-similar appearance near the throughput maximum of the traffic. The lifetime distribution of these jams shows a short scaling regime, which gets considerably longer if one reduces the fluctuations when driving at maximum speed but leaves the fluctuations for slowing down or accelerating unchanged. The outflow from a traffic jam self-organizes into this state of maximum throughput.
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.
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...
Traffic Dynamics of Computer Networks

Science.gov (United States)

Fekete, Attila

2008-10-01

Two important aspects of the Internet, namely the properties of its topology and the characteristics of its data traffic, have attracted growing attention of the physics community. My thesis has considered problems of both aspects. First I studied the stochastic behavior of TCP, the primary algorithm governing traffic in the current Internet, in an elementary network scenario consisting of a standalone infinite-sized buffer and an access link. The effect of the fast recovery and fast retransmission (FR/FR) algorithms is also considered. I showed that my model can be extended further to involve the effect of link propagation delay, characteristic of WAN. I continued my thesis with the investigation of finite-sized semi-bottleneck buffers, where packets can be dropped not only at the link, but also at the buffer. I demonstrated that the behavior of the system depends only on a certain combination of the parameters. Moreover, an analytic formula was derived that gives the ratio of packet loss rate at the buffer to the total packet loss rate. This formula makes it possible to treat buffer-losses as if they were link-losses. Finally, I studied computer networks from a structural perspective. I demonstrated through fluid simulations that the distribution of resources, specifically the link bandwidth, has a serious impact on the global performance of the network. Then I analyzed the distribution of edge betweenness in a growing scale-free tree under the condition that a local property, the in-degree of the "younger" node of an arbitrary edge, is known in order to find an optimum distribution of link capacity. The derived formula is exact even for finite-sized networks. I also calculated the conditional expectation of edge betweenness, rescaled for infinite networks.
Comparison of classical statistical methods and artificial neural network in traffic noise prediction

International Nuclear Information System (INIS)

Nedic, Vladimir; Despotovic, Danijela; Cvetanovic, Slobodan; Despotovic, Milan; Babic, Sasa

2014-01-01

Traffic is the main source of noise in urban environments and significantly affects human mental and physical health and labor productivity. Therefore it is very important to model the noise produced by various vehicles. Techniques for traffic noise prediction are mainly based on regression analysis, which generally is not good enough to describe the trends of noise. In this paper the application of artificial neural networks (ANNs) for the prediction of traffic noise is presented. As input variables of the neural network, the proposed structure of the traffic flow and the average speed of the traffic flow are chosen. The output variable of the network is the equivalent noise level in the given time period L eq . Based on these parameters, the network is modeled, trained and tested through a comparative analysis of the calculated values and measured levels of traffic noise using the originally developed user friendly software package. It is shown that the artificial neural networks can be a useful tool for the prediction of noise with sufficient accuracy. In addition, the measured values were also used to calculate equivalent noise level by means of classical methods, and comparative analysis is given. The results clearly show that ANN approach is superior in traffic noise level prediction to any other statistical method. - Highlights: • We proposed an ANN model for prediction of traffic noise. • We developed originally designed user friendly software package. • The results are compared with classical statistical methods. • The results are much better predictive capabilities of ANN model
Comparison of classical statistical methods and artificial neural network in traffic noise prediction

Energy Technology Data Exchange (ETDEWEB)

Nedic, Vladimir, E-mail: vnedic@kg.ac.rs [Faculty of Philology and Arts, University of Kragujevac, Jovana Cvijića bb, 34000 Kragujevac (Serbia); Despotovic, Danijela, E-mail: ddespotovic@kg.ac.rs [Faculty of Economics, University of Kragujevac, Djure Pucara Starog 3, 34000 Kragujevac (Serbia); Cvetanovic, Slobodan, E-mail: slobodan.cvetanovic@eknfak.ni.ac.rs [Faculty of Economics, University of Niš, Trg kralja Aleksandra Ujedinitelja, 18000 Niš (Serbia); Despotovic, Milan, E-mail: mdespotovic@kg.ac.rs [Faculty of Engineering, University of Kragujevac, Sestre Janjic 6, 34000 Kragujevac (Serbia); Babic, Sasa, E-mail: babicsf@yahoo.com [College of Applied Mechanical Engineering, Trstenik (Serbia)

2014-11-15

Traffic is the main source of noise in urban environments and significantly affects human mental and physical health and labor productivity. Therefore it is very important to model the noise produced by various vehicles. Techniques for traffic noise prediction are mainly based on regression analysis, which generally is not good enough to describe the trends of noise. In this paper the application of artificial neural networks (ANNs) for the prediction of traffic noise is presented. As input variables of the neural network, the proposed structure of the traffic flow and the average speed of the traffic flow are chosen. The output variable of the network is the equivalent noise level in the given time period L{sub eq}. Based on these parameters, the network is modeled, trained and tested through a comparative analysis of the calculated values and measured levels of traffic noise using the originally developed user friendly software package. It is shown that the artificial neural networks can be a useful tool for the prediction of noise with sufficient accuracy. In addition, the measured values were also used to calculate equivalent noise level by means of classical methods, and comparative analysis is given. The results clearly show that ANN approach is superior in traffic noise level prediction to any other statistical method. - Highlights: • We proposed an ANN model for prediction of traffic noise. • We developed originally designed user friendly software package. • The results are compared with classical statistical methods. • The results are much better predictive capabilities of ANN model.
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 performanc...... 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....
Betweenness centrality and its applications from modeling traffic flows to network community detection

Science.gov (United States)

Ren, Yihui

As real-world complex networks are heterogeneous structures, not all their components such as nodes, edges and subgraphs carry the same role or importance in the functions performed by the networks: some elements are more critical than others. Understanding the roles of the components of a network is crucial for understanding the behavior of the network as a whole. One the most basic function of networks is transport; transport of vehicles/people, information, materials, forces, etc., and these quantities are transported along edges between source and destination nodes. For this reason, network path-based importance measures, also called centralities, play a crucial role in the understanding of the transport functions of the network and the network's structural and dynamical behavior in general. In this thesis we study the notion of betweenness centrality, which measures the fraction of lowest-cost (or shortest) paths running through a network component, in particular through a node or an edge. High betweenness centrality nodes/edges are those that will be frequently used by the entities transported through the network and thus they play a key role in the overall transport properties of the network. In the first part of the thesis we present a first-principles based method for traffic prediction using a cost-based generalization of the radiation model (emission/absorbtion model) for human mobility, coupled with a cost-minimizing algorithm for efficient distribution of the mobility fluxes through the network. Using US census and highway traffic data, we show that traffic can efficiently and accurately be computed from a range-limited, network betweenness type calculation. The model based on travel time costs captures the log-normal distribution of the traffic and attains a high Pearson correlation coefficient (0.75) when compared with real traffic. We then focus on studying the extent of changes in traffic flows in the wake of a localized damage or alteration to the
Correlation dimension based nonlinear analysis of network traffics with different application protocols

International Nuclear Information System (INIS)

Wang Jun-Song; Yuan Jing; Li Qiang; Yuan Rui-Xi

2011-01-01

This paper uses a correlation dimension based nonlinear analysis approach to analyse the dynamics of network traffics with three different application protocols—HTTP, FTP and SMTP. First, the phase space is reconstructed and the embedding parameters are obtained by the mutual information method. Secondly, the correlation dimensions of three different traffics are calculated and the results of analysis have demonstrated that the dynamics of the three different application protocol traffics is different from each other in nature, i.e. HTTP and FTP traffics are chaotic, furthermore, the former is more complex than the later; on the other hand, SMTP traffic is stochastic. It is shown that correlation dimension approach is an efficient method to understand and to characterize the nonlinear dynamics of HTTP, FTP and SMTP protocol network traffics. This analysis provided insight into and a more accurate understanding of nonlinear dynamics of internet traffics which have a complex mixture of chaotic and stochastic components. (general)

Algorithm for queueing networks with multi-rate traffic

DEFF Research Database (Denmark)

Iversen, Villy Bæk; Ko, King-Tim

2011-01-01

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......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...... of queueing networks in general, presumes that we have product form between the nodes. Otherwise, we have the state space explosion. Even so, the detailed state space of each node may become very large because there is no product form between chains inside a node. A prerequisite for product form...
A measure theoretic approach to traffic flow optimization on networks

OpenAIRE

Cacace, Simone; Camilli, Fabio; De Maio, Raul; Tosin, Andrea

2018-01-01

We consider a class of optimal control problems for measure-valued nonlinear transport equations describing traffic flow problems on networks. The objective isto minimise/maximise macroscopic quantities, such as traffic volume or average speed,controlling few agents, for example smart traffic lights and automated cars. The measuretheoretic approach allows to study in a same setting local and nonlocal drivers interactionsand to consider the control variables as additional measures interacting ...
Enhancement of large fluctuations to extinction in adaptive networks

Science.gov (United States)

Hindes, Jason; Schwartz, Ira B.; Shaw, Leah B.

2018-01-01

During an epidemic, individual nodes in a network may adapt their connections to reduce the chance of infection. A common form of adaption is avoidance rewiring, where a noninfected node breaks a connection to an infected neighbor and forms a new connection to another noninfected node. Here we explore the effects of such adaptivity on stochastic fluctuations in the susceptible-infected-susceptible model, focusing on the largest fluctuations that result in extinction of infection. Using techniques from large-deviation theory, combined with a measurement of heterogeneity in the susceptible degree distribution at the endemic state, we are able to predict and analyze large fluctuations and extinction in adaptive networks. We find that in the limit of small rewiring there is a sharp exponential reduction in mean extinction times compared to the case of zero adaption. Furthermore, we find an exponential enhancement in the probability of large fluctuations with increased rewiring rate, even when holding the average number of infected nodes constant.
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.
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.
Life-Times of Simulated Traffic Jams

OpenAIRE

Nagel, K.

1993-01-01

We study a model for freeway traffic which includes strong noise taking into account the fluctuations of individual driving behavior. The model shows emergent traffic jams with a self-similar appearance near the throughput maximum of the traffic. The lifetime distribution of these jams shows a short scaling regime, which gets considerably longer if one reduces the fluctuations for driving at maximum speed but leaves the fluctuations for slowing down or accelerating unchanged. The outflow from...
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...
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.
Traffic Management by Using Admission Control Methods in Multiple Node IMS Network

Directory of Open Access Journals (Sweden)

Filip Chamraz

2016-01-01

Full Text Available The paper deals with Admission Control methods (AC as a possible solution for traffic management in IMS networks (IP Multimedia Subsystem - from the point of view of an efficient redistribution of the available network resources and keeping the parameters of Quality of Service (QoS. The paper specifically aims at the selection of the most appropriate method for the specific type of traffic and traffic management concept using AC methods on multiple nodes. The potential benefit and disadvantage of the used solution is evaluated.
SNAPS : semantic network traffic analysis through projection and selection

NARCIS (Netherlands)

Cappers, B.C.M.; van Wijk, J.J.; Harrison, L.; Prigent, N.; Engle, S.; Best, D.; Goodall, J.

2015-01-01

Most network traffic analysis applications are designed to discover malicious activity by only relying on high-level flow-based message properties. However, to detect security breaches that are specifically designed to target one network (e.g., Advanced Persistent Threats), deep packet inspection
Forecasting of passenger traffic in Moscow metro applying artificial neural networks

International Nuclear Information System (INIS)

Ivanov, V.V.; Natsional'nyj Issledovatel'skij Yadernyj Univ. MIFI, Moscow; FKU Rostransmodernizatsiya, Moscow

2016-01-01

Methods for the forecasting of passenger traffic in Moscow metro have been developed using artificial neural networks. To this end, the factors primarily determining passenger traffic in the subway have been analyzed and selected [ru
A Wavelet Neural Network Optimal Control Model for Traffic-Flow Prediction in Intelligent Transport Systems

Science.gov (United States)

Huang, Darong; Bai, Xing-Rong

Based on wavelet transform and neural network theory, a traffic-flow prediction model, which was used in optimal control of Intelligent Traffic system, is constructed. First of all, we have extracted the scale coefficient and wavelet coefficient from the online measured raw data of traffic flow via wavelet transform; Secondly, an Artificial Neural Network model of Traffic-flow Prediction was constructed and trained using the coefficient sequences as inputs and raw data as outputs; Simultaneous, we have designed the running principium of the optimal control system of traffic-flow Forecasting model, the network topological structure and the data transmitted model; Finally, a simulated example has shown that the technique is effectively and exactly. The theoretical results indicated that the wavelet neural network prediction model and algorithms have a broad prospect for practical application.
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...
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.
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.
Variable speed limit strategies analysis with mesoscopic traffic flow model based on complex networks

Science.gov (United States)

Li, Shu-Bin; Cao, Dan-Ni; Dang, Wen-Xiu; Zhang, Lin

As a new cross-discipline, the complexity science has penetrated into every field of economy and society. With the arrival of big data, the research of the complexity science has reached its summit again. In recent years, it offers a new perspective for traffic control by using complex networks theory. The interaction course of various kinds of information in traffic system forms a huge complex system. A new mesoscopic traffic flow model is improved with variable speed limit (VSL), and the simulation process is designed, which is based on the complex networks theory combined with the proposed model. This paper studies effect of VSL on the dynamic traffic flow, and then analyzes the optimal control strategy of VSL in different network topologies. The conclusion of this research is meaningful to put forward some reasonable transportation plan and develop effective traffic management and control measures to help the department of traffic management.
Resilience of traffic networks: From perturbation to recovery via a dynamic restricted equilibrium model

International Nuclear Information System (INIS)

Nogal, Maria; O'Connor, Alan; Caulfield, Brian; Martinez-Pastor, Beatriz

2016-01-01

When a disruptive event takes place in a traffic network some important questions arise, such as how stressed the traffic network is, whether the system is able to respond to this stressful situation, or how long the system needs to recover a new equilibrium position after suffering this perturbation. Quantifying these aspects allows the comparison of different systems, to scale the degree of damage, to identify traffic network weaknesses, and to analyse the effect of user knowledge about the traffic network state. The indicator that accounts for performance and recovery pattern under disruptive events is known as resilience. This paper presents a methodology to assess the resilience of a traffic network when a given perturbation occurs, from the beginning of the perturbation to the total system recovery. To consider the dynamic nature of the problem, a new dynamic equilibrium-restricted assignment model is presented to simulate the network performance evolution, which takes into consideration important aspects, such as the cost increment due to the perturbation, the system impedance to alter its previous state and the user stress level. Finally, this methodology is used to evaluate the resilience indices of a real network. - Highlights: • Method to assess the resilience of a traffic network suffering progressive impacts. • It simulates the dynamic response during the perturbation and system recovery. • The resilience index is based on the travel costs and the stress level of users. • It considers the capacity of adaptation of the system to the new situations. • The model evaluates redundancy, adaptability, ability to recover, etc.
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.
Algorithm for queueing networks with multi-rate traffic

DEFF Research Database (Denmark)

Iversen, Villy Bæk; King-Tim, Ko

2011-01-01

the nodes behave as independent nodes. For closed queueing networks with multiple servers in every node and multi-rate services we may apply multidimensional convolutions to aggregate the nodes so that we end up with two nodes, the aggregated node and a single node, for which we can calculate the detailed......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...... of queueing networks in general presumes that we have product form between the nodes. Other ways we have the state space explosion. Even so the detailed state space of each node may easily become very large because there is no product form between chains inside a node. A prerequisite for product form...
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...

Characterization of traffic-related PM concentration distribution and fluctuation patterns in near-highway urban residential street canyons.

Science.gov (United States)

Hahn, Intaek; Brixey, Laurie A; Wiener, Russell W; Henkle, Stacy W; Baldauf, Richard

2009-12-01

Analyses of outdoor traffic-related particulate matter (PM) concentration distribution and fluctuation patterns in urban street canyons within a microscale distance of less than 500 m from a highway source are presented as part of the results from the Brooklyn Traffic Real-Time Ambient Pollutant Penetration and Environmental Dispersion (B-TRAPPED) study. Various patterns of spatial and temporal changes in the street canyon PM concentrations were investigated using time-series data of real-time PM concentrations measured during multiple monitoring periods. Concurrent time-series data of local street canyon wind conditions and wind data from the John F. Kennedy (JFK) International Airport National Weather Service (NWS) were used to characterize the effects of various wind conditions on the behavior of street canyon PM concentrations.Our results suggest that wind direction may strongly influence time-averaged mean PM concentration distribution patterns in near-highway urban street canyons. The rooftop-level wind speeds were found to be strongly correlated with the PM concentration fluctuation intensities in the middle sections of the street blocks. The ambient turbulence generated by shifting local wind directions (angles) showed a good correlation with the PM concentration fluctuation intensities along the entire distance of the first and second street blocks only when the wind angle standard deviations were larger than 30 degrees. Within-canyon turbulent shearing, caused by fluctuating local street canyon wind speeds, showed no correlation with PM concentration fluctuation intensities. The time-averaged mean PM concentration distribution along the longitudinal distances of the street blocks when wind direction was mostly constantly parallel to the street was found to be similar to the distribution pattern for the entire monitoring period when wind direction fluctuated wildly. Finally, we showed that two different PM concentration metrics-time-averaged mean
Listening to the Noise: Random Fluctuations Reveal Gene Network Parameters

Science.gov (United States)

Munsky, Brian; Trinh, Brooke; Khammash, Mustafa

2010-03-01

The cellular environment is abuzz with noise originating from the inherent random motion of reacting molecules in the living cell. In this noisy environment, clonal cell populations exhibit cell-to-cell variability that can manifest significant prototypical differences. Noise induced stochastic fluctuations in cellular constituents can be measured and their statistics quantified using flow cytometry, single molecule fluorescence in situ hybridization, time lapse fluorescence microscopy and other single cell and single molecule measurement techniques. 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. We use theoretical investigations to establish experimental guidelines for the identification of gene regulatory networks, and we apply these guideline to experimentally identify predictive models for different regulatory mechanisms in bacteria and yeast.
Classification and Analysis of Computer Network Traffic

DEFF Research Database (Denmark)

Bujlow, Tomasz

2014-01-01

various classification modes (decision trees, rulesets, boosting, softening thresholds) regarding the classification accuracy and the time required to create the classifier. We showed how to use our VBS tool to obtain per-flow, per-application, and per-content statistics of traffic in computer networks...
Main concept of local area network protection on the basis of the SAAM 'TRAFFIC'

International Nuclear Information System (INIS)

Vasil'ev, P.M.; Kryukov, Yu.A.; Kuptsov, S.I.; Ivanov, V.V.; Koren'kov, V.V.

2002-01-01

In our previous paper we developed a system for acquisition, analysis and management of the network traffic (SAAM 'Traffic') for a segment of the JINR local area computer network (JINR LAN). In our present work we consider well-known scenarios of attacks on local area networks and propose protection methods based on the SAAM 'Traffic'. Although the system for LAN protection is installed on a router computer, it is not analogous to the firewall scheme and, thus, it does not hinder the performance of distributed network applications. This provides a possibility to apply such an approach to GRID-technologies, where network protection on the firewall basis can not be basically used. (author)
A NEURAL NETWORK BASED TRAFFIC-AWARE FORWARDING STRATEGY IN NAMED DATA NETWORKING

OpenAIRE

Parisa Bazmi; Manijeh Keshtgary

2016-01-01

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 ...
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...
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.
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.
Research on the Application of Wireless Network in Collecting Road Traffic Information

Institute of Scientific and Technical Information of China (English)

DU Hui-jiang

2015-01-01

Due to the characteristics of variability and dispersion in traffic information, to get the reliable real-time traffic information has been a bottleneck in the development of intelligent transportation systems. However, with the development of wireless network technology and mobile Internet, the mobile phones are rapidly developed and more popular, so it is possible to get road traffic information by locating the mobile phones in vehicles. The system structure for the road traffic information collection is designed based on wireless network and mobile phones in vehicles, and the vehicle recognition and its information computation methods are given and discussed. Also the simulation is done for vehicle recognition and computation based on fuzzy cluster analysis method and the results are obtained and analyzed.
Congestion Control and Traffic Scheduling for Collaborative Crowdsourcing in SDN Enabled Mobile Wireless Networks

Directory of Open Access Journals (Sweden)

Dawei Shen

2018-01-01

Full Text Available Currently, a number of crowdsourcing-based mobile applications have been implemented in mobile networks and Internet of Things (IoT, targeted at real-time services and recommendation. The frequent information exchanges and data transmissions in collaborative crowdsourcing are heavily injected into the current communication networks, which poses great challenges for Mobile Wireless Networks (MWN. This paper focuses on the traffic scheduling and load balancing problem in software-defined MWN and designs a hybrid routing forwarding scheme as well as a congestion control algorithm to achieve the feasible solution. The traffic scheduling algorithm first sorts the tasks in an ascending order depending on the amount of tasks and then solves it using a greedy scheme. In the proposed congestion control scheme, the traffic assignment is first transformed into a multiknapsack problem, and then the Artificial Fish Swarm Algorithm (AFSA is utilized to solve this problem. Numerical results on practical network topology reveal that, compared with the traditional schemes, the proposed congestion control and traffic scheduling schemes can achieve load balancing, reduce the probability of network congestion, and improve the network throughput.
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...
Energy Saving Scheme Based On Traffic Forwarding For Optical Fiber Access Networks

DEFF Research Database (Denmark)

Lopez, G. Arturo Rodes; Estaran Tolosa, Jose Manuel; Vegas Olmos, Juan José

2013-01-01

We report on an energy saving block that regroups and powers off OLTs during low traffic periods, resulting in energy savings up to 87,5% in the central office of optical access networks.......We report on an energy saving block that regroups and powers off OLTs during low traffic periods, resulting in energy savings up to 87,5% in the central office of optical access networks....
Improved routing strategies for data traffic in scale-free networks

International Nuclear Information System (INIS)

Wu, Zhi-Xi; Peng, Gang; Wong, Wing-Ming; Yeung, Kai-Hau

2008-01-01

We study the information packet routing process in scale-free networks by mimicking Internet traffic delivery. We incorporate both the global shortest paths information and local degree information of the network in the dynamic process, via two tunable parameters, α and β, to guide the packet routing. We measure the performance of the routing method by both the average transit times of packets and the critical packet generation rate (above which packet aggregation occurs in the network). We found that the routing strategies which integrate ingredients of both global and local topological information of the underlying networks perform much better than the traditional shortest path routing protocol taking into account the global topological information only. Moreover, by doing comparative studies with some related works, we found that the performance of our proposed method shows universal efficiency characteristic against the amount of traffic
Modeling of fluctuating reaction networks

International Nuclear Information System (INIS)

Lipshtat, A.; Biham, O.

2004-01-01

Full Text:Various dynamical systems are organized as reaction networks, where the population size of one component affects the populations of all its neighbors. Such networks can be found in interstellar surface chemistry, cell biology, thin film growth and other systems. I cases where the populations of reactive species are large, the network can be modeled by rate equations which provide all reaction rates within mean field approximation. However, in small systems that are partitioned into sub-micron size, these populations strongly fluctuate. Under these conditions rate equations fail and the master equation is needed for modeling these reactions. However, the number of equations in the master equation grows exponentially with the number of reactive species, severely limiting its feasibility for complex networks. Here we present a method which dramatically reduces the number of equations, thus enabling the incorporation of the master equation in complex reaction networks. The method is examplified in the context of reaction network on dust grains. Its applicability for genetic networks will be discussed. 1. Efficient simulations of gas-grain chemistry in interstellar clouds. Azi Lipshtat and Ofer Biham, Phys. Rev. Lett. 93 (2004), 170601. 2. Modeling of negative autoregulated genetic networks in single cells. Azi Lipshtat, Hagai B. Perets, Nathalie Q. Balaban and Ofer Biham, Gene: evolutionary genomics (2004), In press
Communication Networks - Analysis of jitter due to call-level fluctuations

NARCIS (Netherlands)

Mandjes, M.R.H.

2007-01-01

Abstract In communication networks used by constant bit rate applications, call-level dynamics (i.e. entering and leaving calls) lead to fluctuations in the load, and therefore also fluctuations in the delay (jitter). By intentionally delaying the packets at the destination, one can transform the
Escape routes, weak links, and desynchronization in fluctuation-driven networks

DEFF Research Database (Denmark)

Schäfer, Benjamin; Matthiae, Moritz; Zhang, Xiaozhu

2017-01-01

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...
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...... research and consists of six papers. The first four considers data transmission in grid context. The last two solves the data transmission problem, where the number of paths per data connection is bounded from above. The thesis shows that it is possible to solve the integrated job scheduling and network...
Traffic routing for multicomputer networks with virtual cut-through capability

Science.gov (United States)

Kandlur, Dilip D.; Shin, Kang G.

1992-01-01

Consideration is given to the problem of selecting routes for interprocess communication in a network with virtual cut-through capability, while balancing the network load and minimizing the number of times that a message gets buffered. An approach is proposed that formulates the route selection problem as a minimization problem with a link cost function that depends upon the traffic through the link. The form of this cost function is derived using the probability of establishing a virtual cut-through route. The route selection problem is shown to be NP-hard, and an algorithm is developed to incrementally reduce the cost by rerouting the traffic. The performance of this algorithm is exemplified by two network topologies: the hypercube and the C-wrapped hexagonal mesh.
A Survey on Urban Traffic Management System Using Wireless Sensor Networks

Science.gov (United States)

Nellore, Kapileswar; Hancke, Gerhard P.

2016-01-01

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. PMID:26828489
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.

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.
Stochastic fluctuations and the detectability limit of network communities.

Science.gov (United States)

Floretta, Lucio; Liechti, Jonas; Flammini, Alessandro; De Los Rios, Paolo

2013-12-01

We have analyzed the detectability limits of network communities in the framework of the popular Girvan and Newman benchmark. By carefully taking into account the inevitable stochastic fluctuations that affect the construction of each and every instance of the benchmark, we come to the conclusion that the native, putative partition of the network is completely lost even before the in-degree/out-degree ratio becomes equal to that of a structureless Erdös-Rényi network. We develop a simple iterative scheme, analytically well described by an infinite branching process, to provide an estimate of the true detectability limit. Using various algorithms based on modularity optimization, we show that all of them behave (semiquantitatively) in the same way, with the same functional form of the detectability threshold as a function of the network parameters. Because the same behavior has also been found by further modularity-optimization methods and for methods based on different heuristics implementations, we conclude that indeed a correct definition of the detectability limit must take into account the stochastic fluctuations of the network construction.
Capacity planning of link restorable optical networks under dynamic change of traffic

Science.gov (United States)

Ho, Kwok Shing; Cheung, Kwok Wai

2005-11-01

Future backbone networks shall require full-survivability and support dynamic changes of traffic demands. The Generalized Survivable Networks (GSN) was proposed to meet these challenges. GSN is fully-survivable under dynamic traffic demand changes, so it offers a practical and guaranteed characterization framework for ASTN / ASON survivable network planning and bandwidth-on-demand resource allocation 4. The basic idea of GSN is to incorporate the non-blocking network concept into the survivable network models. In GSN, each network node must specify its I/O capacity bound which is taken as constraints for any allowable traffic demand matrix. In this paper, we consider the following generic GSN network design problem: Given the I/O bounds of each network node, find a routing scheme (and the corresponding rerouting scheme under failure) and the link capacity assignment (both working and spare) which minimize the cost, such that any traffic matrix consistent with the given I/O bounds can be feasibly routed and it is single-fault tolerant under the link restoration scheme. We first show how the initial, infeasible formal mixed integer programming formulation can be transformed into a more feasible problem using the duality transformation of the linear program. Then we show how the problem can be simplified using the Lagrangian Relaxation approach. Previous work has outlined a two-phase approach for solving this problem where the first phase optimizes the working capacity assignment and the second phase optimizes the spare capacity assignment. In this paper, we present a jointly optimized framework for dimensioning the survivable optical network with the GSN model. Experiment results show that the jointly optimized GSN can bring about on average of 3.8% cost savings when compared with the separate, two-phase approach. Finally, we perform a cost comparison and show that GSN can be deployed with a reasonable cost.
Inside the Mechanics of Network Development: How Competition and Strategy Reorganize European Air Traffic

Science.gov (United States)

Huber, Hans

2006-01-01

Air transport forms complex networks that can be measured in order to understand its structural characteristics and functional properties. Recent models for network growth (i.e., preferential attachment, etc.) remain stochastic and do not seek to understand other network-specific mechanisms that may account for their development in a more microscopic way. Air traffic is made up of many constituent airlines that are either privately or publicly owned and that operate their own networks. They follow more or less similar business policies each. The way these airline networks organize among themselves into distinct traffic distributions reveals complex interaction among them, which in turn can be aggregated into larger (macro-) traffic distributions. Our approach allows for a more deterministic methodology that will assess the impact of airline strategies on the distinct distributions for air traffic, particularly inside Europe. One key question this paper is seeking to answer is whether there are distinct patterns of preferential attachment for given classes of airline networks to distinct types of European airports. Conclusions about the advancing degree of concentration in this industry and the airline operators that accelerate this process can be drawn.
Methodology for neural networks prototyping. Application to traffic control

Energy Technology Data Exchange (ETDEWEB)

Belegan, I.C.

1998-07-01

The work described in this report was carried out in the context of the European project ASTORIA (Advanced Simulation Toolbox for Real-World Industrial Application in Passenger Management and Adaptive Control), and concerns the development of an advanced toolbox for complex transportation systems. Our work was focused on the methodology for prototyping a set of neural networks corresponding to specific strategies for traffic control and congestion management. The tool used for prototyping is SNNS (Stuggart Neural Network Simulator), developed at the University of Stuggart, Institute for Parallel and Distributed High Performance Systems, and the real data from the field were provided by ZELT. This report is structured into six parts. The introduction gives some insights about traffic control and its approaches. The second chapter discusses the various control strategies existing. The third chapter is an introduction to the field of neural networks. The data analysis and pre-processing is described in the fourth chapter. In the fifth chapter, the methodology for prototyping the neural networks is presented. Finally, conclusions and further work are presented. (author) 14 refs.
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
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

andconnections. Results show that symbol-rateadaptation provides high savings for unprotected scenarios (37% energy savings w.r.t. unprotected Baseline), while for theprotected scenarios better results are obtained for modulationformat adaptation which includes sleep-mode (57.1% energysavings w.r.t. protected...... Baseline). Moreover, compared to theBaseline scenarios the Mixed adaptation, combining bothsymbol-rate and modulation format, is the most power-efficientstrategy providing 39% energy savings for unprotected scenarioand 70% energy savings for dedicated protection scenario.......An analysis of the energy savingsis presentedwhen taking into account a complete traffic model for a one-yeartime period. Daily and weekly traffic fluctuations as well asyearly traffic growth are considered whenanalyzing the powerconsumption.Low power mode in optoelectronic devices (sleep...
Dynamic traffic grooming with Spectrum Engineering (TG-SE) in flexible grid optical networks

Science.gov (United States)

Yu, Xiaosong; Zhao, Yongli; Zhang, Jiawei; Wang, Jianping; Zhang, Guoying; Chen, Xue; Zhang, Jie

2015-12-01

Flexible grid has emerged as an evolutionary technology to satisfy the ever increasing demand for higher spectrum efficiency and operational flexibility. To optimize the spectrum resource utilization, this paper introduces the concept of Spectrum Engineering in flex-grid optical networks. The sliceable optical transponder has been proposed to offload IP traffic to the optical layer and reduce the number of IP router ports and transponders. We discuss the impact of sliceable transponder in traffic grooming and propose several traffic-grooming schemes with Spectrum Engineering (TG-SE). Our results show that there is a tradeoff among different traffic grooming policies, which should be adopted based on the network operator's objectives. The proposed traffic grooming with Spectrum Engineering schemes can reduce OPEX as well as increase spectrum efficiency by efficiently utilizing the bandwidth variability and capability of sliceable optical transponders.
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.
Early Model of Traffic Sign Reminder Based on Neural Network

Directory of Open Access Journals (Sweden)

Budi Rahmani

2012-12-01

Full Text Available Recognizing the traffic signs installed on the streets is one of the requirements of driving on the road. Laxity in driving may result in traffic accident. This paper describes a real-time reminder model, by utilizing a camera that can be installed in a car to capture image of traffic signs, and is processed and later to inform the driver. The extracting feature harnessing the morphological elements (strel is used in this paper. Artificial Neural Networks is used to train the system and to produce a final decision. The result shows that the accuracy in detecting and recognizing the ten types of traffic signs in real-time is 80%.
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.
Wavelength-converted long-reach reconfigurable optical access network

NARCIS (Netherlands)

Tran, N.C.; Tangdiongga, E.; Koonen, A.M.J.

2012-01-01

Next generation optical access networks should not only increase the capacity but also be able to redistribute the capacity on the fly in order to manage more fluctuated traffic patterns. Wavelength reconfigurability is the instrument to enable such capability of network-wide bandwidth
Controlling P2P File-Sharing Networks Traffic

OpenAIRE

García Pineda, Miguel; HAMMOUMI, MOHAMMED; Canovas Solbes, Alejandro; Lloret, Jaime

2011-01-01

Since the appearance of Peer-To-Peer (P2P) file-sharing networks some time ago, many Internet users have chosen this technology to share and search programs, videos, music, documents, etc. The total number of P2P file-sharing users has been increasing and decreasing in the last decade depending on the creation or end of some well known P2P file-sharing systems. P2P file-sharing networks traffic is currently overloading some data networks and it is a major headache for netw...
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.
The study of RMB exchange rate complex networks based on fluctuation mode

Science.gov (United States)

Yao, Can-Zhong; Lin, Ji-Nan; Zheng, Xu-Zhou; Liu, Xiao-Feng

2015-10-01

In the paper, we research on the characteristics of RMB exchange rate time series fluctuation with methods of symbolization and coarse gaining. First, based on fluctuation features of RMB exchange rate, we define the first type of fluctuation mode as one specific foreign currency against RMB in four days' fluctuating situations, and the second type as four different foreign currencies against RMB in one day's fluctuating situation. With the transforming method, we construct the unique-currency and multi-currency complex networks. Further, through analyzing the topological features including out-degree, betweenness centrality and clustering coefficient of fluctuation-mode complex networks, we find that the out-degree distribution of both types of fluctuation mode basically follows power-law distributions with exponents between 1 and 2. The further analysis reveals that the out-degree and the clustering coefficient generally obey the approximated negative correlation. With this result, we confirm previous observations showing that the RMB exchange rate exhibits a characteristic of long-range memory. Finally, we analyze the most probable transmission route of fluctuation modes, and provide probability prediction matrix. The transmission route for RMB exchange rate fluctuation modes exhibits the characteristics of partially closed loop, repeat and reversibility, which lays a solid foundation for predicting RMB exchange rate fluctuation patterns with large volume of data.
Monitoring individual traffic flows within the ATLAS TDAQ network

CERN Document Server

Sjoen, R; Ciobotaru, M; Batraneanu, S M; Leahu, L; Martin, B; Al-Shabibi, A

2010-01-01

The ATLAS data acquisition system consists of four different networks interconnecting up to 2000 processors using up to 200 edge switches and five multi-blade chassis devices. The architecture of the system has been described in [1] and its operational model in [2]. Classical, SNMP-based, network monitoring provides statistics on aggregate traffic, but for performance monitoring and troubleshooting purposes there was an imperative need to identify and quantify single traffic flows. sFlow [3] is an industry standard based on statistical sampling which attempts to provide a solution to this. Due to the size of the ATLAS network, the collection and analysis of the sFlow data from all devices generates a data handling problem of its own. This paper describes how this problem is addressed by making it possible to collect and store data either centrally or distributed according to need. The methods used to present the results in a relevant fashion for system analysts are discussed and we explore the possibilities a...
Traffic sharing algorithms for hybrid mobile networks

Science.gov (United States)

Arcand, S.; Murthy, K. M. S.; Hafez, R.

1995-01-01

In a hybrid (terrestrial + satellite) mobile personal communications networks environment, a large size satellite footprint (supercell) overlays on a large number of smaller size, contiguous terrestrial cells. We assume that the users have either a terrestrial only single mode terminal (SMT) or a terrestrial/satellite dual mode terminal (DMT) and the ratio of DMT to the total terminals is defined gamma. It is assumed that the call assignments to and handovers between terrestrial cells and satellite supercells take place in a dynamic fashion when necessary. The objectives of this paper are twofold, (1) to propose and define a class of traffic sharing algorithms to manage terrestrial and satellite network resources efficiently by handling call handovers dynamically, and (2) to analyze and evaluate the algorithms by maximizing the traffic load handling capability (defined in erl/cell) over a wide range of terminal ratios (gamma) given an acceptable range of blocking probabilities. Two of the algorithms (G & S) in the proposed class perform extremely well for a wide range of gamma.
Wireless Magnetic Sensor Network for Road Traffic Monitoring and Vehicle Classification

Directory of Open Access Journals (Sweden)

Velisavljevic Vladan

2016-12-01

Full Text Available Efficiency of transportation of people and goods is playing a vital role in economic growth. A key component for enabling effective planning of transportation networks is the deployment and operation of autonomous monitoring and traffic analysis tools. For that reason, such systems have been developed to register and classify road traffic usage. In this paper, we propose a novel system for road traffic monitoring and classification based on highly energy efficient wireless magnetic sensor networks. We develop novel algorithms for vehicle speed and length estimation and vehicle classification that use multiple magnetic sensors. We also demonstrate that, using such a low-cost system with simplified installation and maintenance compared to current solutions, it is possible to achieve highly accurate estimation and a high rate of positive vehicle classification.
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....
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

Urban traffic network model is illustrated by state-charts and object-diagram. However, they have limitations to show the behavioral perspective of the Traffic Information flow. Consequently, a state space model is used to calculate the half-value waiting time of vehicles. In this study......, 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...

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

KAUST Repository

Canepa, Edward S.; Claudel, Christian G.

2017-01-01

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.
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.
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.
A cyberciege traffic analysis extension for teaching network security

OpenAIRE

Chang, Xuquan Stanley.; Chua, Kim Yong.

2011-01-01

CyberCIEGE is an interactive game simulating realistic scenarios that teaches the players Information Assurance (IA) concepts. The existing game scenarios only provide a high-level abstraction of the networked environment, e.g., nodes do not have Internet protocol (IP) addresses or belong to proper subnets, and there is no packet-level network simulation. This research explored endowing the game with network level traffic analysis, and implementing a game scenario to take advantage of this ne...
Traffic analysis and signal processing in optical packet switched networks

DEFF Research Database (Denmark)

Fjelde, Tina

2002-01-01

/s optical packet switched network exploiting the best of optics and electronics, is used as a thread throughout the thesis. An overview of the DAVID network architecture is given, focussing on the MAN and WAN architecture as well as the MPLS-based network hierarchy. Subsequently, the traffic performance...... of the DAVID core optical packet router, which exploits wavelength conversion and fibre delay-line buffers for contention resolution, is analysed using a numerical model developed for that purpose. The robustness of the shared recirculating loop buffer with respect to´bursty traffic is demonstrated...... the injection of an additional clock signal into the IWC is presented. Results show very good transmission capabilities combined with a high-speed response. It is argued that signal regeneration is an inherent attribute of the IWC employed as a wavelength converter due to the sinusoidal transfer function...
Traffic sign classification with dataset augmentation and convolutional neural network

Science.gov (United States)

Tang, Qing; Kurnianggoro, Laksono; Jo, Kang-Hyun

2018-04-01

This paper presents a method for traffic sign classification using a convolutional neural network (CNN). In this method, firstly we transfer a color image into grayscale, and then normalize it in the range (-1,1) as the preprocessing step. To increase robustness of classification model, we apply a dataset augmentation algorithm and create new images to train the model. To avoid overfitting, we utilize a dropout module before the last fully connection layer. To assess the performance of the proposed method, the German traffic sign recognition benchmark (GTSRB) dataset is utilized. Experimental results show that the method is effective in classifying traffic signs.
Network Traffic Forensics on Firefox Mobile OS: Facebook, Twitter and Telegram as Case Studies

OpenAIRE

Yusoff, Mohd Najwadi; Dehghantanha, Ali; Mahmod, Ramlan

2017-01-01

Development of mobile web-centric OS such as Firefox OS has created new challenges, and opportunities for digital investigators. Network traffic forensic plays an important role in cybercrime investigation to detect subject(s) and object(s) of the crime. In this chapter, we detect and analyze residual network traffic artefacts of Firefox OS in relation to two popular social networking applications (Facebook and Twitter) and one instant messaging application (Telegram). We utilized a Firefox O...
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....... With the humongous popularity of Internet the overall traffic on Internet has the same story. Focusing on transmission of IP traffic in an optical network with signals remaining in their optical nature generated at particular wavelength, proposed is the switching of optically generated IP packets through optical...... cross connects based on translation of wavelength when an IP packet is crossing the optical cross connect. Adding the concepts of layer 3 routing protocols along with the wavelength translation scheme, will help in spanning the overall optical network for a larger area....
Deep Bidirectional and Unidirectional LSTM Recurrent Neural Network for Network-wide Traffic Speed Prediction

OpenAIRE

Cui, Zhiyong; Ke, Ruimin; Wang, Yinhai

2018-01-01

Short-term traffic forecasting based on deep learning methods, especially long short-term memory (LSTM) neural networks, has received much attention in recent years. However, the potential of deep learning methods in traffic forecasting has not yet fully been exploited in terms of the depth of the model architecture, the spatial scale of the prediction area, and the predictive power of spatial-temporal data. In this paper, a deep stacked bidirectional and unidirectional LSTM (SBU- LSTM) neura...
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.
Communication efficiency and congestion of signal traffic in large-scale brain networks.

Science.gov (United States)

Mišić, Bratislav; Sporns, Olaf; McIntosh, Anthony R

2014-01-01

The complex connectivity of the cerebral cortex suggests that inter-regional communication is a primary function. Using computational modeling, we show that anatomical connectivity may be a major determinant for global information flow in brain networks. A macaque brain network was implemented as a communication network in which signal units flowed between grey matter nodes along white matter paths. Compared to degree-matched surrogate networks, information flow on the macaque brain network was characterized by higher loss rates, faster transit times and lower throughput, suggesting that neural connectivity may be optimized for speed rather than fidelity. Much of global communication was mediated by a "rich club" of hub regions: a sub-graph comprised of high-degree nodes that are more densely interconnected with each other than predicted by chance. First, macaque communication patterns most closely resembled those observed for a synthetic rich club network, but were less similar to those seen in a synthetic small world network, suggesting that the former is a more fundamental feature of brain network topology. Second, rich club regions attracted the most signal traffic and likewise, connections between rich club regions carried more traffic than connections between non-rich club regions. Third, a number of rich club regions were significantly under-congested, suggesting that macaque connectivity actively shapes information flow, funneling traffic towards some nodes and away from others. Together, our results indicate a critical role of the rich club of hub nodes in dynamic aspects of global brain communication.
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.
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.
Learning in neural networks based on a generalized fluctuation theorem

Science.gov (United States)

Hayakawa, Takashi; Aoyagi, Toshio

2015-11-01

Information maximization has been investigated as a possible mechanism of learning governing the self-organization that occurs within the neural systems of animals. Within the general context of models of neural systems bidirectionally interacting with environments, however, the role of information maximization remains to be elucidated. For bidirectionally interacting physical systems, universal laws describing the fluctuation they exhibit and the information they possess have recently been discovered. These laws are termed fluctuation theorems. In the present study, we formulate a theory of learning in neural networks bidirectionally interacting with environments based on the principle of information maximization. Our formulation begins with the introduction of a generalized fluctuation theorem, employing an interpretation appropriate for the present application, which differs from the original thermodynamic interpretation. We analytically and numerically demonstrate that the learning mechanism presented in our theory allows neural networks to efficiently explore their environments and optimally encode information about them.
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...
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.
Urban traffic simulated from the dual representation: Flow, crisis and congestion

International Nuclear Information System (INIS)

Hu Maobin; Jiang Rui; Wang Ruili; Wu Qingsong

2009-01-01

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.
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
Fuzzy Multiobjective Traffic Light Signal Optimization

Directory of Open Access Journals (Sweden)

N. Shahsavari Pour

2013-01-01

Full Text Available Traffic congestion is a major concern for many cities throughout the world. In a general traffic light controller, the traffic lights change at a constant cycle time. Hence it does not provide an optimal solution. Many traffic light controllers in current use are based on the “time-of-the-day” scheme, which use a limited number of predetermined traffic light patterns and implement these patterns depending upon the time of the day. These automated systems do not provide an optimal control for fluctuating traffic volumes. In this paper, the fuzzy traffic light controller is used to optimize the control of fluctuating traffic volumes such as oversaturated or unusual load conditions. The problem is solved by genetic algorithm, and a new defuzzification method is introduced. The performance of the new defuzzification method (NDM is compared with the centroid point defuzzification method (CPDM by using ANOVA. Finally, an illustrative example is presented to show the competency of proposed algorithm.
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

2018-03-01

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.

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.
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
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.
An Architecture to Manage Incoming Traffic of Inter-Domain Routing Using OpenFlow Networks

Directory of Open Access Journals (Sweden)

Walber José Adriano Silva

2018-04-01

Full Text Available The Border Gateway Protocol (BGP is the current state-of-the-art inter-domain routing between Autonomous Systems (ASes. Although BGP has different mechanisms to manage outbound traffic in an AS domain, it lacks an efficient tool for inbound traffic control from transit ASes such as Internet Service Providers (ISPs. For inter-domain routing, the BGP’s destination-based forwarding paradigm limits the granularity of distributing the network traffic among the multiple paths of the current Internet topology. Thus, this work offered a new architecture to manage incoming traffic in the inter-domain using OpenFlow networks. The architecture explored direct inter-domain communication to exchange control information and the functionalities of the OpenFlow protocol. Based on the achieved results of the size of exchanging messages, the proposed architecture is not only scalable, but also capable of performing load balancing for inbound traffic using different strategies.
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.
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.
A Bio-Inspired Approach to Traffic Network Equilibrium Assignment Problem.

Science.gov (United States)

Zhang, Xiaoge; Mahadevan, Sankaran

2018-04-01

Finding an equilibrium state of the traffic assignment plays a significant role in the design of transportation networks. We adapt the path finding mathematical model of slime mold Physarum polycephalum to solve the traffic equilibrium assignment problem. We make three contributions in this paper. First, we propose a generalized Physarum model to solve the shortest path problem in directed and asymmetric graphs. Second, we extend it further to resolve the network design problem with multiple source nodes and sink nodes. At last, we demonstrate that the Physarum solver converges to the user-optimized (Wardrop) equilibrium by dynamically updating the costs of links in the network. In addition, convergence of the developed algorithm is proved. Numerical examples are used to demonstrate the efficiency of the proposed algorithm. The superiority of the proposed algorithm is demonstrated in comparison with several other algorithms, including the Frank-Wolfe algorithm, conjugate Frank-Wolfe algorithm, biconjugate Frank-Wolfe algorithm, and gradient projection algorithm.
Performability indicators for the traffic analysis of wide area networks

International Nuclear Information System (INIS)

Tsopelas, Panagiotis; Platis, Agapios

2003-01-01

In connecting computing networks, reliability term is strongly related to the availability of connections of Wide Area networks (WANs) or Local Area networks (LANs). In this paper we will examine the network connections activity of a Greek University in order to provide two sources of information: The Quantity of Information Not Delivered (QIND) and the Information Flow Interruption (IFI). These indicators will provide us with the inference of information from observable characteristics of data flow(s), even when the data is encrypted or otherwise not directly available (traffic), which is lost due to failures or upgrades inside this network. The reliability analysis is obtained by collecting the network failures data (duration and frequency) and traffic (total and average) for a specified period of 1 year. It is assumed that the numerical analysis is based on the fact that the lifetime follows and exponential distribution (here as we are working on discrete time the distribution must be the geometric distribution). Hence a Markov chain model seems suitable for modelling the functioning of this system. An algorithm concentrates the results in a transition probability matrix and calculates the reward functions for the QIND/IFI indicators with the use of the power method. Finally, the application part provides an example of how final results can be used to evaluate the observed network
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....... Optical network reconfigurations are performed by GMPLS node controllers according to monitored traffic information. The investigated energy reduction strategies are simulated on two large scale transport networks (DT17 and COST37). The results show that the energy savings obtained by these strategies......-Europea n COST37 network, for both symbol-rate and modulation format adaptations significant savings are obtained . Mixed adaptation (jointly performing symbol-rate and modulation format adaptations) used together with optical grooming allows up to 4 4 % and 4 7 % power savings in DT17 and COST37 networks...
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.
Traffic Generator (TrafficGen) Version 1.4.2: Users Guide

Science.gov (United States)

2016-06-01

the network with Transmission Control Protocol and User Datagram Protocol Internet Protocol traffic. Each node generating network traffic in an...TrafficGen Graphical User Interface (GUI) 3 3.1 Anatomy of the User Interface 3 3.2 Scenario Configuration and MGEN Files 4 4. Working with...for public release; distribution is unlimited. vi List of Figures Fig. 1 TrafficGen user interface
Geometry of river networks. I. Scaling, fluctuations, and deviations

International Nuclear Information System (INIS)

Dodds, Peter Sheridan; Rothman, Daniel H.

2001-01-01

This paper is the first in a series of three papers investigating the detailed geometry of river networks. Branching networks are a universal structure employed in the distribution and collection of material. Large-scale river networks mark an important class of two-dimensional branching networks, being not only of intrinsic interest but also a pervasive natural phenomenon. In the description of river network structure, scaling laws are uniformly observed. Reported values of scaling exponents vary, suggesting that no unique set of scaling exponents exists. To improve this current understanding of scaling in river networks and to provide a fuller description of branching network structure, here we report a theoretical and empirical study of fluctuations about and deviations from scaling. We examine data for continent-scale river networks such as the Mississippi and the Amazon and draw inspiration from a simple model of directed, random networks. We center our investigations on the scaling of the length of a subbasin's dominant stream with its area, a characterization of basin shape known as Hack's law. We generalize this relationship to a joint probability density, and provide observations and explanations of deviations from scaling. We show that fluctuations about scaling are substantial, and grow with system size. We find strong deviations from scaling at small scales which can be explained by the existence of a linear network structure. At intermediate scales, we find slow drifts in exponent values, indicating that scaling is only approximately obeyed and that universality remains indeterminate. At large scales, we observe a breakdown in scaling due to decreasing sample space and correlations with overall basin shape. The extent of approximate scaling is significantly restricted by these deviations, and will not be improved by increases in network resolution
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.
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.
Network Traffic Monitoring Using Poisson Dynamic Linear Models

Energy Technology Data Exchange (ETDEWEB)

Merl, D. M. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

2011-05-09

In this article, we discuss an approach for network forensics using a class of nonstationary Poisson processes with embedded dynamic linear models. As a modeling strategy, the Poisson DLM (PoDLM) provides a very flexible framework for specifying structured effects that may influence the evolution of the underlying Poisson rate parameter, including diurnal and weekly usage patterns. We develop a novel particle learning algorithm for online smoothing and prediction for the PoDLM, and demonstrate the suitability of the approach to real-time deployment settings via a new application to computer network traffic monitoring.
G-ROME : semantic-driven capacity sharing among P2P networks

NARCIS (Netherlands)

Exarchakos, G.; Antonopoulos, N.; Salter, J.

2007-01-01

Purpose – The purpose of this paper is to propose a model for sharing network capacity on demand among different underloaded and overloaded P2P ROME-enabled networks. The paper aims to target networks of nodes with highly dynamic workload fluctuations that may experience a burst of traffic and/or
Decentralized State-Observer-Based Traffic Density Estimation of Large-Scale Urban Freeway Network by Dynamic Model

Directory of Open Access Journals (Sweden)

Yuqi Guo

2017-08-01

Full Text Available In order to estimate traffic densities in a large-scale urban freeway network in an accurate and timely fashion when traffic sensors do not cover the freeway network completely and thus only local measurement data can be utilized, this paper proposes a decentralized state observer approach based on a macroscopic traffic flow model. Firstly, by using the well-known cell transmission model (CTM, the urban freeway network is modeled in the way of distributed systems. Secondly, based on the model, a decentralized observer is designed. With the help of the Lyapunov function and S-procedure theory, the observer gains are computed by using linear matrix inequality (LMI technique. So, the traffic densities of the whole road network can be estimated by the designed observer. Finally, this method is applied to the outer ring of the Beijing’s second ring road and experimental results demonstrate the effectiveness and applicability of the proposed approach.
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.
Monitoring individual traffic flows within the ATLAS TDAQ network

International Nuclear Information System (INIS)

Sjoen, R; Batraneanu, S M; Leahu, L; Martin, B; Al-Shabibi, A; Stancu, S; Ciobotaru, M

2010-01-01

The ATLAS data acquisition system consists of four different networks interconnecting up to 2000 processors using up to 200 edge switches and five multi-blade chassis devices. The architecture of the system has been described in [1] and its operational model in [2]. Classical, SNMP-based, network monitoring provides statistics on aggregate traffic, but for performance monitoring and troubleshooting purposes there was an imperative need to identify and quantify single traffic flows. sFlow [3] is an industry standard based on statistical sampling which attempts to provide a solution to this. Due to the size of the ATLAS network, the collection and analysis of the sFlow data from all devices generates a data handling problem of its own. This paper describes how this problem is addressed by making it possible to collect and store data either centrally or distributed according to need. The methods used to present the results in a relevant fashion for system analysts are discussed and we explore the possibilities and limitations of this diagnostic tool, giving an example of its use in solving system problems that arise during the ATLAS data taking.
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

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

DEFF Research Database (Denmark)

Popovska Avramova, Andrijana; Iversen, Villy Bæk

2015-01-01

nature of radio access networks are considered as important factors for performance improvement by multi-stream aggregation. Therefore, in our model, the networks are represented by different queueing systems in order to indicate networks with opposite quality of service provisioning, capacity and delay...... 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....
Comparing detection and disclosure of traffic incidents in social networks: an intelligent approach based on Twitter vs. Waze

Directory of Open Access Journals (Sweden)

Sebastián Vallejos

2018-03-01

Full Text Available Nowadays, social networks have become in a communication medium widely used to disseminate any type of information. In particular, the shared information in social networks usually includes a considerable number of traffic incidents reports of specific cities. In light of this, specialized social networks have emerged for detecting and disseminating traffic incidents, differentiating from generic social networks in which a wide variety of topics are communicated. In this context, Twitter is a case in point of a generic social network in which its users often share information about traffic incidents, while Waze is a social network specialized in traffic. In this paper we present a comparative study between Waze and an intelligent approach that detects traffic incidents by analyzing publications shared in Twitter. The comparative study was carried out considering Ciudad Autónoma de Buenos Aires (CABA, Argentina, as the region of interest. The results of this work suggest that both social networks should be considered as complementary sources of information. This conclusion is based on the fact that the proportion of mutual detections, i.e. traffic incidents detected by both approaches, was considerably low since it did not exceed 6% of the cases. Moreover, the results do not show that any of the approaches tend to anticipate in time to the other one in the detection of traffic incidents.
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.
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.
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.
HOW TRAVEL DEMAND AFFECTS DETECTION OF NON-RECURRENT TRAFFIC CONGESTION ON URBAN ROAD NETWORKS

Directory of Open Access Journals (Sweden)

B. Anbaroglu

2016-06-01

Full Text Available Occurrence of non-recurrent traffic congestion hinders the economic activity of a city, as travellers could miss appointments or be late for work or important meetings. Similarly, for shippers, unexpected delays may disrupt just-in-time delivery and manufacturing processes, which could lose them payment. Consequently, research on non-recurrent congestion detection on urban road networks has recently gained attention. By analysing large amounts of traffic data collected on a daily basis, traffic operation centres can improve their methods to detect non-recurrent congestion rapidly and then revise their existing plans to mitigate its effects. Space-time clusters of high link journey time estimates correspond to non-recurrent congestion events. Existing research, however, has not considered the effect of travel demand on the effectiveness of non-recurrent congestion detection methods. Therefore, this paper investigates how travel demand affects detection of non-recurrent traffic congestion detection on urban road networks. Travel demand has been classified into three categories as low, normal and high. The experiments are carried out on London’s urban road network, and the results demonstrate the necessity to adjust the relative importance of the component evaluation criteria depending on the travel demand level.
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.
Fermi-Dirac statistics and traffic in complex networks.

Science.gov (United States)

de Moura, Alessandro P S

2005-06-01

We propose an idealized model for traffic in a network, in which many particles move randomly from node to node, following the network's links, and it is assumed that at most one particle can occupy any given node. This is intended to mimic the finite forwarding capacity of nodes in communication networks, thereby allowing the possibility of congestion and jamming phenomena. We show that the particles behave like free fermions, with appropriately defined energy-level structure and temperature. The statistical properties of this system are thus given by the corresponding Fermi-Dirac distribution. We use this to obtain analytical expressions for dynamical quantities of interest, such as the mean occupation of each node and the transport efficiency, for different network topologies and particle densities. We show that the subnetwork of free nodes always fragments into small isolated clusters for a sufficiently large number of particles, implying a communication breakdown at some density for all network topologies. These results are compared to direct simulations.
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.
Ongoing activity in temporally coherent networks predicts intra-subject fluctuation of response time to sporadic executive control demands.

Science.gov (United States)

Nozawa, Takayuki; Sugiura, Motoaki; Yokoyama, Ryoichi; Ihara, Mizuki; Kotozaki, Yuka; Miyauchi, Carlos Makoto; Kanno, Akitake; Kawashima, Ryuta

2014-01-01

Can ongoing fMRI BOLD signals predict fluctuations in swiftness of a person's response to sporadic cognitive demands? This is an important issue because it clarifies whether intrinsic brain dynamics, for which spatio-temporal patterns are expressed as temporally coherent networks (TCNs), have effects not only on sensory or motor processes, but also on cognitive processes. Predictivity has been affirmed, although to a limited extent. Expecting a predictive effect on executive performance for a wider range of TCNs constituting the cingulo-opercular, fronto-parietal, and default mode networks, we conducted an fMRI study using a version of the color-word Stroop task that was specifically designed to put a higher load on executive control, with the aim of making its fluctuations more detectable. We explored the relationships between the fluctuations in ongoing pre-trial activity in TCNs and the task response time (RT). The results revealed the existence of TCNs in which fluctuations in activity several seconds before the onset of the trial predicted RT fluctuations for the subsequent trial. These TCNs were distributed in the cingulo-opercular and fronto-parietal networks, as well as in perceptual and motor networks. Our results suggest that intrinsic brain dynamics in these networks constitute "cognitive readiness," which plays an active role especially in situations where information for anticipatory attention control is unavailable. Fluctuations in these networks lead to fluctuations in executive control performance.
Global and system-specific resting-state fMRI fluctuations are uncorrelated: principal component analysis reveals anti-correlated networks.

Science.gov (United States)

Carbonell, Felix; Bellec, Pierre; Shmuel, Amir

2011-01-01

The influence of the global average signal (GAS) on functional-magnetic resonance imaging (fMRI)-based resting-state functional connectivity is a matter of ongoing debate. The global average fluctuations increase the correlation between functional systems beyond the correlation that reflects their specific functional connectivity. Hence, removal of the GAS is a common practice for facilitating the observation of network-specific functional connectivity. This strategy relies on the implicit assumption of a linear-additive model according to which global fluctuations, irrespective of their origin, and network-specific fluctuations are super-positioned. However, removal of the GAS introduces spurious negative correlations between functional systems, bringing into question the validity of previous findings of negative correlations between fluctuations in the default-mode and the task-positive networks. Here we present an alternative method for estimating global fluctuations, immune to the complications associated with the GAS. Principal components analysis was applied to resting-state fMRI time-series. A global-signal effect estimator was defined as the principal component (PC) that correlated best with the GAS. The mean correlation coefficient between our proposed PC-based global effect estimator and the GAS was 0.97±0.05, demonstrating that our estimator successfully approximated the GAS. In 66 out of 68 runs, the PC that showed the highest correlation with the GAS was the first PC. Since PCs are orthogonal, our method provides an estimator of the global fluctuations, which is uncorrelated to the remaining, network-specific fluctuations. Moreover, unlike the regression of the GAS, the regression of the PC-based global effect estimator does not introduce spurious anti-correlations beyond the decrease in seed-based correlation values allowed by the assumed additive model. After regressing this PC-based estimator out of the original time-series, we observed robust anti
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.
Uncovering the footprints of malicious traffic in cellular data networks

OpenAIRE

Raghuramu, A; Zang, H; Chuah, CN

2015-01-01

© Springer International Publishing Switzerland 2015. In this paper, we present a comprehensive characterization of malicious traffic generated by mobile devices using Deep Packet Inspection (DPI) records and security event logs from a large US based cellular provider network. Our analysis reveals that 0.17% of mobile devices in the cellular network are affected by security threats. This proportion, while small, is orders of magnitude higher than the last reported (in 2013) infection rate of ...
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.
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.
Advanced Models and Algorithms for Self-Similar IP Network Traffic Simulation and Performance Analysis

Science.gov (United States)

Radev, Dimitar; Lokshina, Izabella

2010-11-01

The paper examines self-similar (or fractal) properties of real communication network traffic data over a wide range of time scales. These self-similar properties are very different from the properties of traditional models based on Poisson and Markov-modulated Poisson processes. Advanced fractal models of sequentional generators and fixed-length sequence generators, and efficient algorithms that are used to simulate self-similar behavior of IP network traffic data are developed and applied. Numerical examples are provided; and simulation results are obtained and analyzed.
Phase dynamics of complex-valued neural networks and its application to traffic signal control.

Science.gov (United States)

Nishikawa, Ikuko; Iritani, Takeshi; Sakakibara, Kazutoshi; Kuroe, Yasuaki

2005-01-01

Complex-valued Hopfield networks which possess the energy function are analyzed. The dynamics of the network with certain forms of an activation function is de-composable into the dynamics of the amplitude and phase of each neuron. Then the phase dynamics is described as a coupled system of phase oscillators with a pair-wise sinusoidal interaction. Therefore its phase synchronization mechanism is useful for the area-wide offset control of the traffic signals. The computer simulations show the effectiveness under the various traffic conditions.

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.
From Goods to Traffic:First Steps Toward an Auction-based Traffic Signal Controller

OpenAIRE

Raphael, Jeffery; Maskell, Simon; Sklar, Elizabeth Ida

2015-01-01

Traffic congestion is a major issue that plagues many urban road networks large and small. Traffic engineers are now leaning towards Intelligent Traffic Systems as many physical changes to road networks are costly or infeasible. Multi-Agent Systems (MAS) have become a popular paradigm for intelligent solutions to traffic management problems. There are many MAS approaches to traffic management that utilise market mechanisms. In market-based approaches, drivers “pay” to use the roadways. Howeve...
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.
Long-range correlation analysis of urban traffic data

International Nuclear Information System (INIS)

Peng, Sheng; Jun-Feng, Wang; Shu-Long, Zhao; Tie-Qiao, Tang

2010-01-01

This paper investigates urban traffic data by analysing the long-range correlation with detrended fluctuation analysis. Through a large number of real data collected by the travel time detection system in Beijing, the variation of flow in different time periods and intersections is studied. According to the long-range correlation in different time scales, it mainly discusses the effect of intersection location in road net, people activity customs and special traffic controls on urban traffic flow. As demonstrated by the obtained results, the urban traffic flow represents three-phase characters similar to highway traffic. Moreover, compared by the two groups of data obtained before and after the special traffic restrictions (vehicles with special numbered plates only run in a special workday) enforcement, it indicates that the rules not only reduce the flow but also avoid irregular fluctuation. (general)
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
Cross-layer model design in wireless ad hoc networks for the Internet of Things.

Science.gov (United States)

Yang, Xin; Wang, Ling; Xie, Jian; Zhang, Zhaolin

2018-01-01

Wireless ad hoc networks can experience extreme fluctuations in transmission traffic in the Internet of Things, which is widely used today. Currently, the most crucial issues requiring attention for wireless ad hoc networks are making the best use of low traffic periods, reducing congestion during high traffic periods, and improving transmission performance. To solve these problems, the present paper proposes a novel cross-layer transmission model based on decentralized coded caching in the physical layer and a content division multiplexing scheme in the media access control layer. Simulation results demonstrate that the proposed model effectively addresses these issues by substantially increasing the throughput and successful transmission rate compared to existing protocols without a negative influence on delay, particularly for large scale networks under conditions of highly contrasting high and low traffic periods.
Cross-layer model design in wireless ad hoc networks for the Internet of Things.

Directory of Open Access Journals (Sweden)

Xin Yang

Full Text Available Wireless ad hoc networks can experience extreme fluctuations in transmission traffic in the Internet of Things, which is widely used today. Currently, the most crucial issues requiring attention for wireless ad hoc networks are making the best use of low traffic periods, reducing congestion during high traffic periods, and improving transmission performance. To solve these problems, the present paper proposes a novel cross-layer transmission model based on decentralized coded caching in the physical layer and a content division multiplexing scheme in the media access control layer. Simulation results demonstrate that the proposed model effectively addresses these issues by substantially increasing the throughput and successful transmission rate compared to existing protocols without a negative influence on delay, particularly for large scale networks under conditions of highly contrasting high and low traffic periods.
Protein Signaling Networks from Single Cell Fluctuations and Information Theory Profiling

Science.gov (United States)

Shin, Young Shik; Remacle, F.; Fan, Rong; Hwang, Kiwook; Wei, Wei; Ahmad, Habib; Levine, R.D.; Heath, James R.

2011-01-01

Protein signaling networks among cells play critical roles in a host of pathophysiological processes, from inflammation to tumorigenesis. We report on an approach that integrates microfluidic cell handling, in situ protein secretion profiling, and information theory to determine an extracellular protein-signaling network and the role of perturbations. We assayed 12 proteins secreted from human macrophages that were subjected to lipopolysaccharide challenge, which emulates the macrophage-based innate immune responses against Gram-negative bacteria. We characterize the fluctuations in protein secretion of single cells, and of small cell colonies (n = 2, 3,···), as a function of colony size. Measuring the fluctuations permits a validation of the conditions required for the application of a quantitative version of the Le Chatelier's principle, as derived using information theory. This principle provides a quantitative prediction of the role of perturbations and allows a characterization of a protein-protein interaction network. PMID:21575571
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.
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.
From trees to forest: relational complexity network and workload of air traffic controllers.

Science.gov (United States)

Zhang, Jingyu; Yang, Jiazhong; Wu, Changxu

2015-01-01

In this paper, we propose a relational complexity (RC) network framework based on RC metric and network theory to model controllers' workload in conflict detection and resolution. We suggest that, at the sector level, air traffic showing a centralised network pattern can provide cognitive benefits in visual search and resolution decision which will in turn result in lower workload. We found that the network centralisation index can account for more variance in predicting perceived workload and task completion time in both a static conflict detection task (Study 1) and a dynamic one (Study 2) in addition to other aircraft-level and pair-level factors. This finding suggests that linear combination of aircraft-level or dyad-level information may not be adequate and the global-pattern-based index is necessary. Theoretical and practical implications of using this framework to improve future workload modelling and management are discussed. We propose a RC network framework to model the workload of air traffic controllers. The effect of network centralisation was examined in both a static conflict detection task and a dynamic one. Network centralisation was predictive of perceived workload and task completion time over and above other control variables.
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.
Effects of packet retransmission with finite packet lifetime on traffic capacity in scale-free networks

Science.gov (United States)

Jiang, Zhong-Yuan; Ma, Jian-Feng

Existing routing strategies such as the global dynamic routing [X. Ling, M. B. Hu, R. Jiang and Q. S. Wu, Phys. Rev. E 81, 016113 (2010)] can achieve very high traffic capacity at the cost of extremely long packet traveling delay. In many real complex networks, especially for real-time applications such as the instant communication software, extremely long packet traveling time is unacceptable. In this work, we propose to assign a finite Time-to-Live (TTL) parameter for each packet. To guarantee every packet to arrive at its destination within its TTL, we assume that a packet is retransmitted by its source once its TTL expires. We employ source routing mechanisms in the traffic model to avoid the routing-flaps induced by the global dynamic routing. We compose extensive simulations to verify our proposed mechanisms. With small TTL, the effects of packet retransmission on network traffic capacity are obvious, and the phase transition from flow free state to congested state occurs. For the purpose of reducing the computation frequency of the routing table, we employ a computing cycle Tc within which the routing table is recomputed once. The simulation results show that the traffic capacity decreases with increasing Tc. Our work provides a good insight into the understanding of effects of packet retransmission with finite packet lifetime on traffic capacity in scale-free networks.
Stochastic lumping analysis for linear kinetics and its application to the fluctuation relations between hierarchical kinetic networks

Energy Technology Data Exchange (ETDEWEB)

Deng, De-Ming; Chang, Cheng-Hung [Institute of Physics, National Chiao Tung University, Hsinchu 300, Taiwan (China)

2015-05-14

Conventional studies of biomolecular behaviors rely largely on the construction of kinetic schemes. Since the selection of these networks is not unique, a concern is raised whether and under which conditions hierarchical schemes can reveal the same experimentally measured fluctuating behaviors and unique fluctuation related physical properties. To clarify these questions, we introduce stochasticity into the traditional lumping analysis, generalize it from rate equations to chemical master equations and stochastic differential equations, and extract the fluctuation relations between kinetically and thermodynamically equivalent networks under intrinsic and extrinsic noises. The results provide a theoretical basis for the legitimate use of low-dimensional models in the studies of macromolecular fluctuations and, more generally, for exploring stochastic features in different levels of contracted networks in chemical and biological kinetic systems.
Stochastic lumping analysis for linear kinetics and its application to the fluctuation relations between hierarchical kinetic networks.

Science.gov (United States)

Deng, De-Ming; Chang, Cheng-Hung

2015-05-14

Conventional studies of biomolecular behaviors rely largely on the construction of kinetic schemes. Since the selection of these networks is not unique, a concern is raised whether and under which conditions hierarchical schemes can reveal the same experimentally measured fluctuating behaviors and unique fluctuation related physical properties. To clarify these questions, we introduce stochasticity into the traditional lumping analysis, generalize it from rate equations to chemical master equations and stochastic differential equations, and extract the fluctuation relations between kinetically and thermodynamically equivalent networks under intrinsic and extrinsic noises. The results provide a theoretical basis for the legitimate use of low-dimensional models in the studies of macromolecular fluctuations and, more generally, for exploring stochastic features in different levels of contracted networks in chemical and biological kinetic systems.
Resistance and resistance fluctuations in random resistor networks under biased percolation.

Science.gov (United States)

Pennetta, Cecilia; Reggiani, L; Trefán, Gy; Alfinito, E

2002-06-01

We consider a two-dimensional random resistor network (RRN) in the presence of two competing biased processes consisting of the breaking and recovering of elementary resistors. These two processes are driven by the joint effects of an electrical bias and of the heat exchange with a thermal bath. The electrical bias is set up by applying a constant voltage or, alternatively, a constant current. Monte Carlo simulations are performed to analyze the network evolution in the full range of bias values. Depending on the bias strength, electrical failure or steady state are achieved. Here we investigate the steady state of the RRN focusing on the properties of the non-Ohmic regime. In constant-voltage conditions, a scaling relation is found between /(0) and V/V(0), where is the average network resistance, (0) the linear regime resistance, and V0 the threshold value for the onset of nonlinearity. A similar relation is found in constant-current conditions. The relative variance of resistance fluctuations also exhibits a strong nonlinearity whose properties are investigated. The power spectral density of resistance fluctuations presents a Lorentzian spectrum and the amplitude of fluctuations shows a significant non-Gaussian behavior in the prebreakdown region. These results compare well with electrical breakdown measurements in thin films of composites and of other conducting materials.
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...
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...
Traffic-Adaptive and Energy-Efficient Small Cell Networks-Energy, Delay and Throughput

OpenAIRE

Nazrul Alam, Mirza

2016-01-01

The low power small cell network has emerged as a promising and feasible solution to address the massive wireless traffic resulting from the aggressive growth of wireless applications. It is also estimated that Internet of things (IoT) will consist of around 50 billion physical objects by 2020. As a result, besides capacity enhancement, other challenges, e.g., energy efficiency, dynamic addressing of UL/DL traffic asymmetry, low latency, multi-hop communications, reliability and coverage have...
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.

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

current network traffic. To overcome the drawbacks of existing methods for traffic classification, usage of C5.0 Machine Learning Algorithm (MLA) was proposed. On the basis of statistical traffic information received from volunteers and C5.0 algorithm we constructed a boosted classifier, which was shown...... 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...
Using mobile probes to inform and measure the effectiveness of traffic control strategies on urban networks.

Science.gov (United States)

2015-07-01

Urban traffic congestion is a problem that plagues many cities in the United States. Testing strategies to alleviate this : congestion is especially challenging due to the difficulty of modeling complex urban traffic networks. However, recent work ha...
Modeling the heterogeneous traffic correlations in urban road systems using traffic-enhanced community detection approach

Science.gov (United States)

Lu, Feng; Liu, Kang; Duan, Yingying; Cheng, Shifen; Du, Fei

2018-07-01

A better characterization of the traffic influence among urban roads is crucial for traffic control and traffic forecasting. The existence of spatial heterogeneity imposes great influence on modeling the extent and degree of road traffic correlation, which is usually neglected by the traditional distance based method. In this paper, we propose a traffic-enhanced community detection approach to spatially reveal the traffic correlation in city road networks. First, the road network is modeled as a traffic-enhanced dual graph with the closeness between two road segments determined not only by their topological connection, but also by the traffic correlation between them. Then a flow-based community detection algorithm called Infomap is utilized to identify the road segment clusters. Evaluated by Moran's I, Calinski-Harabaz Index and the traffic interpolation application, we find that compared to the distance based method and the community based method, our proposed traffic-enhanced community based method behaves better in capturing the extent of traffic relevance as both the topological structure of the road network and the traffic correlations among urban roads are considered. It can be used in more traffic-related applications, such as traffic forecasting, traffic control and guidance.
Fiber fault location utilizing traffic signal in optical network.

Science.gov (United States)

Zhao, Tong; Wang, Anbang; Wang, Yuncai; Zhang, Mingjiang; Chang, Xiaoming; Xiong, Lijuan; Hao, Yi

2013-10-07

We propose and experimentally demonstrate a method for fault location in optical communication network. This method utilizes the traffic signal transmitted across the network as probe signal, and then locates the fault by correlation technique. Compared with conventional techniques, our method has a simple structure and low operation expenditure, because no additional device is used, such as light source, modulator and signal generator. The correlation detection in this method overcomes the tradeoff between spatial resolution and measurement range in pulse ranging technique. Moreover, signal extraction process can improve the location result considerably. Experimental results show that we achieve a spatial resolution of 8 cm and detection range of over 23 km with -8-dBm mean launched power in optical network based on synchronous digital hierarchy protocols.
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.
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
A Spike Neural Controller for Traffic Load Parameter with Priority-Based Rate in Wireless Multimedia Sensor Networks

Directory of Open Access Journals (Sweden)

Nadia Adnan Shiltagh

2015-11-01

Full Text Available Wireless Multimedia Sensor Networks (WMSNs are a type of sensor network that contains sensor nodes equipped with cameras, microphones; therefore the WMSNS are able to produce multimedia data such as video and audio streams, still images, and scalar data from the surrounding environment. Most multimedia applications typically produce huge volumes of data, this leads to congestion. To address this challenge, This paper proposes Modify Spike Neural Network control for Traffic Load Parameter with Exponential Weight of Priority Based Rate Control algorithm (MSNTLP with EWBPRC. The Modify Spike Neural Network controller (MSNC can calculate the appropriate traffic load parameter μ for each parent node and then use in the EWPBRC algorithm to estimate the transmission rate of parent nodes and then assign a suitable transmission rate for each child node. A comparative study between (MSNTLP with EWBPRC and fuzzy logic controller for traffic load parameter with Exponential Weight of Priority Based Rate Control algorithm (FTLP with EWBPRC algorithm shows that the (MSNTLP with EWBPRC is more efficient than (FTLP with EWBPRC algorithm in terms of packet loss, queue delay and throughput. Another comparative study between (MSNTLP with EWBPRC and EWBPRC with fixed traffic load parameter (µ shows that the MSNTLP with EWBPRC is more efficient than EWBPRC with fixed traffic load parameter (µ in terms of packet loss ratio and queue delay. A simulation process is developed and tested using the network simulator _2 (NS2 in a computer having the following properties: windows 7 (64-bit, core i7, RAM 8GB, hard 1TB.
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.
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.
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
Mathematical programs with complementarity constraints in traffic and telecommunications networks.

Science.gov (United States)

Ralph, Daniel

2008-06-13

Given a suitably parametrized family of equilibrium models and a higher level criterion by which to measure an equilibrium state, mathematical programs with equilibrium constraints (MPECs) provide a framework for improving or optimizing the equilibrium state. An example is toll design in traffic networks, which attempts to reduce total travel time by choosing which arcs to toll and what toll levels to impose. Here, a Wardrop equilibrium describes the traffic response to each toll design. Communication networks also have a deep literature on equilibrium flows that suggest some MPECs. We focus on mathematical programs with complementarity constraints (MPCCs), a subclass of MPECs for which the lower level equilibrium system can be formulated as a complementarity problem and therefore, importantly, as a nonlinear program (NLP). Although MPECs and MPCCs are typically non-convex, which is a consequence of the upper level objective clashing with the users' objectives in the lower level equilibrium program, the last decade of research has paved the way for finding local solutions of MPCCs via standard NLP techniques.
Dynamic segment shared protection for multicast traffic in meshed wavelength-division-multiplexing optical networks

Science.gov (United States)

Liao, Luhua; Li, Lemin; Wang, Sheng

2006-12-01

We investigate the protection approach for dynamic multicast traffic under shared risk link group (SRLG) constraints in meshed wavelength-division-multiplexing optical networks. We present a shared protection algorithm called dynamic segment shared protection for multicast traffic (DSSPM), which can dynamically adjust the link cost according to the current network state and can establish a primary light-tree as well as corresponding SRLG-disjoint backup segments for a dependable multicast connection. A backup segment can efficiently share the wavelength capacity of its working tree and the common resources of other backup segments based on SRLG-disjoint constraints. The simulation results show that DSSPM not only can protect the multicast sessions against a single-SRLG breakdown, but can make better use of the wavelength resources and also lower the network blocking probability.
Task-Related Modulations of BOLD Low-Frequency Fluctuations within the Default Mode Network

Science.gov (United States)

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

2017-01-01

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, 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. PMID:28845420
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.
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 at the Label Edge Router (LER) to buffer traffic in the electronic domain. Burst assembly and offset assignment schemes are implemented in a complementary manner to improve QoS of an OBS network. The authors show that OBS network performance is directly related...
Using mobile probes to inform and measure the effectiveness of macroscopic traffic control strategies on urban networks.

Science.gov (United States)

2015-06-01

Urban traffic congestion is a problem that plagues many cities in the United States. Testing strategies to alleviate this : congestion is especially challenging due to the difficulty of modeling complex urban traffic networks. However, recent work ha...
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.
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.
Admission Control for Multiservices Traffic in Hierarchical Mobile IPv6 Networks by Using Fuzzy Inference System

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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.
An auxiliary graph based dynamic traffic grooming algorithm in spatial division multiplexing enabled elastic optical networks with multi-core fibers

Science.gov (United States)

Zhao, Yongli; Tian, Rui; Yu, Xiaosong; Zhang, Jiawei; Zhang, Jie

2017-03-01

A proper traffic grooming strategy in dynamic optical networks can improve the utilization of bandwidth resources. An auxiliary graph (AG) is designed to solve the traffic grooming problem under a dynamic traffic scenario in spatial division multiplexing enabled elastic optical networks (SDM-EON) with multi-core fibers. Five traffic grooming policies achieved by adjusting the edge weights of an AG are proposed and evaluated through simulation: maximal electrical grooming (MEG), maximal optical grooming (MOG), maximal SDM grooming (MSG), minimize virtual hops (MVH), and minimize physical hops (MPH). Numeric results show that each traffic grooming policy has its own features. Among different traffic grooming policies, an MPH policy can achieve the lowest bandwidth blocking ratio, MEG can save the most transponders, and MSG can obtain the fewest cores for each request.

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

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

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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
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.
Traffic of indistinguishable particles in complex networks

International Nuclear Information System (INIS)

Qing-Kuan, Meng; Jian-Yang, Zhu

2009-01-01

In this paper, we apply a simple walk mechanism to the study of the traffic of many indistinguishable particles in complex networks. The network with particles stands for a particle system, and every vertex in the network stands for a quantum state with the corresponding energy determined by the vertex degree. Although the particles are indistinguishable, the quantum states can be distinguished. When the many indistinguishable particles walk randomly in the system for a long enough time and the system reaches dynamic equilibrium, we find that under different restrictive conditions the particle distributions satisfy different forms, including the Bose–Einstein distribution, the Fermi–Dirac distribution and the non-Fermi distribution (as we temporarily call it). As for the Bose–Einstein distribution, we find that only if the particle density is larger than zero, with increasing particle density, do more and more particles condense in the lowest energy level. While the particle density is very low, the particle distribution transforms from the quantum statistical form to the classically statistical form, i.e., transforms from the Bose distribution or the Fermi distribution to the Boltzmann distribution. The numerical results fit well with the analytical predictions
Packet traffic features of IPv6 and IPv4 protocol traffic

OpenAIRE

ÇİFLİKLİ, Cebrail; GEZER, Ali; ÖZŞAHİN, Abdullah Tuncay

2012-01-01

Nowadays, the IPv6 protocol is in a transition phase in operational networks. The ratio of its traffic volume is increasing day by day. The many provided facilities for IPv6 connection increasethe total IPv6 traffic load. IPv6-over-IPv4 tunnels, pilot programsto provide IPv6 connections, IPv6/IPv4 dual stack operating systems,and free IPv6 tunnel brokers cause the IPv6 protocol to expand quickly. For efficient resource utilization, the characteristics of network traffic should be determ...
A wireless sensor network for urban traffic characterization and trend monitoring.

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

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Gao-Xia Wei

2017-07-01

Full Text Available 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.
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.
Optimized Virtual Machine Placement with Traffic-Aware Balancing in Data Center Networks

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

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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.
A Fair Contention Access Scheme for Low-Priority Traffic in Wireless Body Area Networks

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Shagufta Henna

2017-08-01

Full Text Available Recently, wireless body area networks (WBANs have attracted significant consideration in ubiquitous healthcare. A number of medium access control (MAC protocols, primarily derived from the superframe structure of the IEEE 802.15.4, have been proposed in literature. These MAC protocols aim to provide quality of service (QoS by prioritizing different traffic types in WBANs. A contention access period (CAPwith high contention in priority-based MAC protocols can result in higher number of collisions and retransmissions. During CAP, traffic classes with higher priority are dominant over low-priority traffic; this has led to starvation of low-priority traffic, thus adversely affecting WBAN throughput, delay, and energy consumption. Hence, this paper proposes a traffic-adaptive priority-based superframe structure that is able to reduce contention in the CAP period, and provides a fair chance for low-priority traffic. Simulation results in ns-3 demonstrate that the proposed MAC protocol, called traffic- adaptive priority-based MAC (TAP-MAC, achieves low energy consumption, high throughput, and low latency compared to the IEEE 802.15.4 standard, and the most recent priority-based MAC protocol, called priority-based MAC protocol (PA-MAC.
Competition between Local Collisions and Collective Hydrodynamic Feedback Controls Traffic Flows in Microfluidic Networks

Science.gov (United States)

Belloul, M.; Engl, W.; Colin, A.; Panizza, P.; Ajdari, A.

2009-05-01

By studying the repartition of monodisperse droplets at a simple T junction, we show that the traffic of discrete fluid systems in microfluidic networks results from two competing mechanisms, whose significance is driven by confinement. Traffic is dominated by collisions occurring at the junction for small droplets and by collective hydrodynamic feedback for large ones. For each mechanism, we present simple models in terms of the pertinent dimensionless parameters of the problem.
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
Performance Evaluation of Hadoop-based Large-scale Network Traffic Analysis Cluster

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Tao Ran

2016-01-01

Full Text Available As Hadoop has gained popularity in big data era, it is widely used in various fields. The self-design and self-developed large-scale network traffic analysis cluster works well based on Hadoop, with off-line applications running on it to analyze the massive network traffic data. On purpose of scientifically and reasonably evaluating the performance of analysis cluster, we propose a performance evaluation system. Firstly, we set the execution times of three benchmark applications as the benchmark of the performance, and pick 40 metrics of customized statistical resource data. Then we identify the relationship between the resource data and the execution times by a statistic modeling analysis approach, which is composed of principal component analysis and multiple linear regression. After training models by historical data, we can predict the execution times by current resource data. Finally, we evaluate the performance of analysis cluster by the validated predicting of execution times. Experimental results show that the predicted execution times by trained models are within acceptable error range, and the evaluation results of performance are accurate and reliable.
Research on the Method of Traffic Organization and Optimization Based on Dynamic Traffic Flow Model

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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.
Effective distance adaptation traffic dispatching in software defined IP over optical network

Science.gov (United States)

Duan, Zhiwei; Li, Hui; Liu, Yuze; Ji, Yuefeng; Li, Hongfa; Lin, Yi

2017-10-01

The rapid growth of IP traffic has contributed to the wide deployment of optical devices (ROADM/OXC, etc.). Meanwhile, with the emergence and application of high-performance network services such as ultra-high video transmission, people are increasingly becoming more and more particular about the quality of service (QoS) of network. However, the pass-band shape of WSSs which is utilized in the ROADM/OXC is not ideal, causing narrowing of spectrum. Spectral narrowing can lead to signal impairment. Therefore, guard-bands need to be inserted between adjacent paths. In order to minimize the bandwidth waste due to guard bands, we propose an effective distance-adaptation traffic dispatching algorithm in IP over optical network based on SDON architecture. We use virtualization technology to set up virtual resources direct links by extracting part of the resources on paths which meet certain specific constraints. We also assign different bandwidth to each IP request based on path length. There is no need for guard-bands between the adjacent paths on the virtual link, which can effectively reduce the number of guard-bands and save the spectrum.
Distributed Traffic Control for Reduced Fuel Consumption and Travel Time in Transportation Networks

Science.gov (United States)

2018-04-01

Current technology in traffic control is limited to a centralized approach that has not paid appropriate attention to efficiency of fuel consumption and is subject to the scale of transportation networks. This project proposes a transformative approa...
File Detection On Network Traffic Using Approximate Matching

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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.
Mechanics of Fluctuating Elastic Plates and Fiber Networks

Science.gov (United States)

Liang, Xiaojun

Lipid membranes and fiber networks in biological systems perform important mechanical functions at the cellular and tissue levels. In this thesis I delve into two detailed problems--thermal fluctuation of membranes and non-linear compression response of fiber networks. Typically, membrane fluctuations are analysed by decomposing into normal modes or by molecular simulations. In the first part of my thesis, I propose a new semi-analytic method to calculate the partition function of a membrane. The membrane is viewed as a fluctuating von Karman plate and discretized into triangular elements. Its energy is expressed as a function of nodal displacements, and then the partition function and co-variance matrix are computed using Gaussian integrals. I recover well-known results for the dependence of the projected area of a lipid bilayer membrane on the applied tension, and recent simulation results on the ependence of membrane free energy on geometry, spontaneous curvature and tension. As new applications I use this technique to study a membrane with heterogeneity and different boundary conditions. I also use this technique to study solid membranes by taking account of the non-linear coupling of in-plane strains with out-of-plane deflections using a penalty energy, and apply it to graphene, an ultra-thin two-dimensional solid. The scaling of graphene fluctuations with membrane size is recovered. I am able to capture the dependence of the thermal expansion coefficient of graphene on temperature. Next, I study curvature mediated interactions between inclusions in membranes. I assume the inclusions to be rigid, and show that the elastic and entropic forces between them can compete to yield a local maximum in the free energy if the membrane bending modulus is small. If the spacing between the inclusions is less than this local maximum then the attractive entropic forces dominate and the separation between the inclusions will be determined by short range interactions; if the

Using Generalized Entropies and OC-SVM with Mahalanobis Kernel for Detection and Classification of Anomalies in Network Traffic

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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
New Solutions Based On Wireless Networks For Dynamic Traffic Lights Management: A Comparison Between IEEE 802.15.4 And Bluetooth

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Collotta Mario

2015-09-01

Full Text Available The Wireless Sensor Networks are widely used to detect and exchange information and in recent years they have been increasingly involved in Intelligent Transportation System applications, especially in dynamic management of signalized intersections. In fact, the real-time knowledge of information concerning traffic light junctions represents a valid solution to congestion problems. In this paper, a wireless network architecture, based on IEEE 802.15.4 or Bluetooth, in order to monitor vehicular traffic flows near to traffic lights, is introduced. Moreover, an innovative algorithm is proposed in order to determine dynamically green times and phase sequence of traffic lights, based on measured values of traffic flows. Several simulations compare IEEE 802.15.4 and Bluetooth protocols in order to identify the more suitable communication protocol for ITS applications. Furthermore, in order to confirm the validity of the proposed algorithm for the dynamic management of traffic lights, some case studies have been considered and several simulations have been performed.
Cybersecurity and Network Forensics: Analysis of Malicious Traffic towards a Honeynet with Deep Packet Inspection

OpenAIRE

Gabriel Arquelau Pimenta Rodrigues; Robson de Oliveira Albuquerque; Flávio Elias Gomes de Deus; Rafael Timóteo de Sousa Jr.; Gildásio Antônio de Oliveira Júnior; Luis Javier García Villalba; Tai-Hoon Kim

2017-01-01

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 laye...
Examining perimeter gating control of urban traffic networkswith locally adaptive traffic signals

NARCIS (Netherlands)

Keyvan Ekbatani, M.; Gao, X.; Gayah, V.V.; Knoop, V.L.

2015-01-01

Traditionally, urban traffic is controlled by traffic lights. Recent findings of the Macroscopic or Network Fundamental Diagram (MFD or NFD) have led to the development of novel traffic control strategies that can be applied at a networkwide level. One pertinent example is perimeter flow control
Traffic Command Gesture Recognition for Virtual Urban Scenes Based on a Spatiotemporal Convolution Neural Network

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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.
Modelling of H.264 MPEG2 TS Traffic Source

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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.
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.
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
Green provisioning of the traffic partition grooming in robust, reconfigurable and heterogeneous optical networks

Science.gov (United States)

Hou, Weigang; Yu, Yao; Song, Qingyang; Gong, Xiaoxue

2013-01-01

In recent years, various high-speed network architectures have been widespread deployed. Dense Wavelength Division Multiplexing (DWDM) has gained favor as a terabit solution. The optical circuit switching has also been provided for "sub-rate" aggregation. Such that, the granular types of demands tend to be diverse and must be evaluated. However, current dedicated optical networks do not offer sufficient flexibility to satisfy the requirements of demands with such wide range of granularities. The traffic grooming becomes a power-efficient one only when it does not utilize the aggregation of Coarse-Granularity (CG) demands. The waveband switching merely provides port-cost-effective connections for CG demands regardless of fine-granularity ones. Consequently, in this paper, we devise a heterogeneous grooming method called traffic partition grooming. It combines the power efficiency advantage of the traffic grooming under fine-granularity environment and the port savings advantage of the waveband switching under coarse-granularity environment to provide green provisioning. In addition, the optical virtual topology self-reconfigures along with various optimization objectives variation and has the robustness to determine the pre-unknown information. This paper is also the first work on investigating the issue of Robust, Reconfigurable and Heterogeneous Optical Networking (R2HON). The effective green provisioning and OPEX savings of our R2HON have been demonstrated by numerical simulations.
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.
Fluctuations of Attentional Networks and Default Mode Network during the Resting State Reflect Variations in Cognitive States: Evidence from a Novel Resting-state Experience Sampling Method.

Science.gov (United States)

Van Calster, Laurens; D'Argembeau, Arnaud; Salmon, Eric; Peters, Frédéric; Majerus, Steve

2017-01-01

Neuroimaging studies have revealed the recruitment of a range of neural networks during the resting state, which might reflect a variety of cognitive experiences and processes occurring in an individual's mind. In this study, we focused on the default mode network (DMN) and attentional networks and investigated their association with distinct mental states when participants are not performing an explicit task. To investigate the range of possible cognitive experiences more directly, this study proposes a novel method of resting-state fMRI experience sampling, informed by a phenomenological investigation of the fluctuation of mental states during the resting state. We hypothesized that DMN activity would increase as a function of internal mentation and that the activity of dorsal and ventral networks would indicate states of top-down versus bottom-up attention at rest. Results showed that dorsal attention network activity fluctuated as a function of subjective reports of attentional control, providing evidence that activity of this network reflects the perceived recruitment of controlled attentional processes during spontaneous cognition. Activity of the DMN increased when participants reported to be in a subjective state of internal mentation, but not when they reported to be in a state of perception. This study provides direct evidence for a link between fluctuations of resting-state neural activity and fluctuations in specific cognitive processes.
The Impact of Traffic Prioritization on Deep Space Network Mission Traffic

Science.gov (United States)

Jennings, Esther; Segui, John; Gao, Jay; Clare, Loren; Abraham, Douglas

2011-01-01

A select number of missions supported by NASA's Deep Space Network (DSN) are demanding very high data rates. For example, the Kepler Mission was launched March 7, 2009 and at that time required the highest data rate of any NASA mission, with maximum rates of 4.33 Mb/s being provided via Ka band downlinks. The James Webb Space Telescope will require a maximum 28 Mb/s science downlink data rate also using Ka band links; as of this writing the launch is scheduled for a June 2014 launch. The Lunar Reconnaissance Orbiter, launched June 18, 2009, has demonstrated data rates at 100 Mb/s at lunar-Earth distances using NASA's Near Earth Network (NEN) and K-band. As further advances are made in high data rate space telecommunications, particularly with emerging optical systems, it is expected that large surges in demand on the supporting ground systems will ensue. A performance analysis of the impact of high variance in demand has been conducted using our Multi-mission Advanced Communications Hybrid Environment for Test and Evaluation (MACHETE) simulation tool. A comparison is made regarding the incorporation of Quality of Service (QoS) mechanisms and the resulting ground-to-ground Wide Area Network (WAN) bandwidth necessary to meet latency requirements across different user missions. It is shown that substantial reduction in WAN bandwidth may be realized through QoS techniques when low data rate users with low-latency needs are mixed with high data rate users having delay-tolerant traffic.
A QoS Framework with Traffic Request in Wireless Mesh Network

Science.gov (United States)

Fu, Bo; Huang, Hejiao

In this paper, we consider major issues in ensuring greater Quality-of-Service (QoS) in Wireless Mesh Networks (WMNs), specifically with regard to reliability and delay. To this end, we use traffic request to record QoS requirements of data flows. In order to achieve required QoS for all data flows efficiently and with high portability, we develop Network State Update Algorithm. All assumptions, definitions, and algorithms are made exclusively with WMNs in mind, guaranteeing the portability of our framework to various environments in WMNs. The simulation results in proof that our framework is correct.
Implementation of a FPGA-Based Feature Detection and Networking System for Real-time Traffic Monitoring

OpenAIRE

Chen, Jieshi; Schafer, Benjamin Carrion; Ho, Ivan Wang-Hei

2016-01-01

With the growing demand of real-time traffic monitoring nowadays, software-based image processing can hardly meet the real-time data processing requirement due to the serial data processing nature. In this paper, the implementation of a hardware-based feature detection and networking system prototype for real-time traffic monitoring as well as data transmission is presented. The hardware architecture of the proposed system is mainly composed of three parts: data collection, feature detection,...
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
Multivariate correlation analysis technique based on euclidean distance map for network traffic characterization

NARCIS (Netherlands)

Tan, Zhiyuan; Jamdagni, Aruna; He, Xiangjian; Nanda, Priyadarsi; Liu, Ren Ping; Qing, Sihan; Susilo, Willy; Wang, Guilin; Liu, Dongmei

2011-01-01

The quality of feature has significant impact on the performance of detection techniques used for Denial-of-Service (DoS) attack. The features that fail to provide accurate characterization for network traffic records make the techniques suffer from low accuracy in detection. Although researches
Ontology-Based Architecture for Intelligent Transportation Systems Using a Traffic Sensor Network

Directory of Open Access Journals (Sweden)

Susel Fernandez

2016-08-01

Full Text Available Intelligent transportation systems are a set of technological solutions used to improve the performance and safety of road transportation. A crucial element for the success of these systems is the exchange of information, not only between vehicles, but also among other components in the road infrastructure through different applications. One of the most important information sources in this kind of systems is sensors. Sensors can be within vehicles or as part of the infrastructure, such as bridges, roads or traffic signs. Sensors can provide information related to weather conditions and traffic situation, which is useful to improve the driving process. To facilitate the exchange of information between the different applications that use sensor data, a common framework of knowledge is needed to allow interoperability. In this paper an ontology-driven architecture to improve the driving environment through a traffic sensor network is proposed. The system performs different tasks automatically to increase driver safety and comfort using the information provided by the sensors.
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

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....... Feed-forward back-propagation neural networks indicate that sociodemographic characteristics of drivers and victims, accident location, and period of the day are extremely relevant factors. Accident patterns suggest that countermeasures are necessary for identified problems concerning mainly vulnerable...
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.
Monitor Network Traffic with Packet Capture (pcap) on an Android Device

Science.gov (United States)

2015-09-01

administrative privileges . Under the current design Android development requirement, an Android Graphical User Interface (GUI) application cannot directly...build an Android application to monitor network traffic using open source packet capture (pcap) libraries. 15. SUBJECT TERMS ELIDe, Android , pcap 16...Building Application with Native Codes 5 8.1 Calling Native Codes Using JNI 5 8.2 Calling Native Codes from an Android Application 8 9. Retrieve Live

Testing Application (End-to-End Performance of Networks With EFT Traffic

Directory of Open Access Journals (Sweden)

Vlatko Lipovac

2009-01-01

Full Text Available This paper studies how end-to-end application peiformance(of Electronic Financial Transaction traffic, in particulardepends on the actual protocol stacks, operating systemsand network transmission rates. With this respect, the respectivesimulation tests of peiformance of TCP and UDP protocolsrunning on various operating systems, ranging from Windows,Sun Solmis, to Linux have been implemented, and thedifferences in peiformance addressed focusing on throughputand response time.
A Two-Stage Fuzzy Logic Control Method of Traffic Signal Based on Traffic Urgency Degree

OpenAIRE

Yan Ge

2014-01-01

City intersection traffic signal control is an important method to improve the efficiency of road network and alleviate traffic congestion. This paper researches traffic signal fuzzy control method on a single intersection. A two-stage traffic signal control method based on traffic urgency degree is proposed according to two-stage fuzzy inference on single intersection. At the first stage, calculate traffic urgency degree for all red phases using traffic urgency evaluation module and select t...
77 FR 3544 - Meeting and Webinar on the Active Traffic and Demand Management and Intelligent Network Flow...

Science.gov (United States)

2012-01-24

... Intelligent Network Flow Optimization Operational Concepts; Notice of Public Meeting AGENCY: Research and... Demand Management (ADTM) and Intelligent Network Flow Optimization (INFLO) operational concepts. The ADTM... infrastructure. The vision for ATDM research is to allow transportation agencies to increase traffic flow...
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.
Analysis of Roadway Traffic Accidents Based on Rough Sets and Bayesian Networks

Directory of Open Access Journals (Sweden)

Xiaoxia Xiong

2018-02-01

Full Text Available The paper integrates Rough Sets (RS and Bayesian Networks (BN for roadway traffic accident analysis. RS reduction of attributes is first employed to generate the key set of attributes affecting accident outcomes, which are then fed into a BN structure as nodes for BN construction and accident outcome classification. Such RS-based BN framework combines the advantages of RS in knowledge reduction capability and BN in describing interrelationships among different attributes. The framework is demonstrated using the 100-car naturalistic driving data from Virginia Tech Transportation Institute to predict accident type. Comparative evaluation with the baseline BNs shows the RS-based BNs generally have a higher prediction accuracy and lower network complexity while with comparable prediction coverage and receiver operating characteristic curve area, proving that the proposed RS-based BN overall outperforms the BNs with/without traditional feature selection approaches. The proposed RS-based BN indicates the most significant attributes that affect accident types include pre-crash manoeuvre, driver’s attention from forward roadway to centre mirror, number of secondary tasks undertaken, traffic density, and relation to junction, most of which feature pre-crash driver states and driver behaviours that have not been extensively researched in literature, and could give further insight into the nature of traffic accidents.
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.
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.
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.
Reports on internet traffic statistics

OpenAIRE

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 from the Abilene network on a weekly basis. At that time, the network connected 230 research institutes with a 10Gb/s link. Although these reports were limited to the behavior of the Albeline's users,...
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.
Traffic intensity monitoring using multiple object detection with traffic surveillance cameras

Science.gov (United States)

Hamdan, H. G. Muhammad; Khalifah, O. O.

2017-11-01

Object detection and tracking is a field of research that has many applications in the current generation with increasing number of cameras on the streets and lower cost for Internet of Things(IoT). In this paper, a traffic intensity monitoring system is implemented based on the Macroscopic Urban Traffic model is proposed using computer vision as its source. The input of this program is extracted from a traffic surveillance camera which has another program running a neural network classification which can identify and differentiate the vehicle type is implanted. The neural network toolbox is trained with positive and negative input to increase accuracy. The accuracy of the program is compared to other related works done and the trends of the traffic intensity from a road is also calculated. relevant articles in literature searches, great care should be taken in constructing both. Lastly the limitation and the future work is concluded.
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...
Energy-minimized design in all-optical networks using unicast/multicast traffic grooming

Science.gov (United States)

Puche, William S.; Amaya, Ferney O.; Sierra, Javier E.

2013-09-01

The increased bandwidth required by applications, tends to raise the amount of optical equipment, for this reason, it is essential to maintain a balance between the wavelength allocation, available capacity and number of optical devices to achieve the lowest power consumption. You could say that we propose a model that minimizes energy consumption, using unicast / multicast traffic grooming in optical networks.
A Traffic Restriction Scheme for Enhancing Carpooling

Directory of Open Access Journals (Sweden)

Dong Ding

2017-01-01

Full Text Available For the purpose of alleviating traffic congestion, this paper proposes a scheme to encourage travelers to carpool by traffic restriction. By a variational inequity we describe travelers’ mode (solo driving and carpooling and route choice under user equilibrium principle in the context of fixed demand and detect the performance of a simple network with various restriction links, restriction proportions, and carpooling costs. Then the optimal traffic restriction scheme aiming at minimal total travel cost is designed through a bilevel program and applied to a Sioux Fall network example with genetic algorithm. According to various requirements, optimal restriction regions and proportions for restricted automobiles are captured. From the results it is found that traffic restriction scheme is possible to enhance carpooling and alleviate congestion. However, higher carpooling demand is not always helpful to the whole network. The topology of network, OD demand, and carpooling cost are included in the factors influencing the performance of the traffic system.
Fluctuating interaction network and time-varying stability of a natural fish community

Science.gov (United States)

Ushio, Masayuki; Hsieh, Chih-Hao; Masuda, Reiji; Deyle, Ethan R.; Ye, Hao; Chang, Chun-Wei; Sugihara, George; Kondoh, Michio

2018-02-01

Ecological theory suggests that large-scale patterns such as community stability can be influenced by changes in interspecific interactions that arise from the behavioural and/or physiological responses of individual species varying over time. Although this theory has experimental support, evidence from natural ecosystems is lacking owing to the challenges of tracking rapid changes in interspecific interactions (known to occur on timescales much shorter than a generation time) and then identifying the effect of such changes on large-scale community dynamics. Here, using tools for analysing nonlinear time series and a 12-year-long dataset of fortnightly collected observations on a natural marine fish community in Maizuru Bay, Japan, we show that short-term changes in interaction networks influence overall community dynamics. Among the 15 dominant species, we identify 14 interspecific interactions to construct a dynamic interaction network. We show that the strengths, and even types, of interactions change with time; we also develop a time-varying stability measure based on local Lyapunov stability for attractor dynamics in non-equilibrium nonlinear systems. We use this dynamic stability measure to examine the link between the time-varying interaction network and community stability. We find seasonal patterns in dynamic stability for this fish community that broadly support expectations of current ecological theory. Specifically, the dominance of weak interactions and higher species diversity during summer months are associated with higher dynamic stability and smaller population fluctuations. We suggest that interspecific interactions, community network structure and community stability are dynamic properties, and that linking fluctuating interaction networks to community-level dynamic properties is key to understanding the maintenance of ecological communities in nature.
Supervised learning from human performance at the computationally hard problem of optimal traffic signal control on a network of junctions.

Science.gov (United States)

Box, Simon

2014-12-01

Optimal switching of traffic lights on a network of junctions is a computationally intractable problem. In this research, road traffic networks containing signallized junctions are simulated. A computer game interface is used to enable a human 'player' to control the traffic light settings on the junctions within the simulation. A supervised learning approach, based on simple neural network classifiers can be used to capture human player's strategies in the game and thus develop a human-trained machine control (HuTMaC) system that approaches human levels of performance. Experiments conducted within the simulation compare the performance of HuTMaC to two well-established traffic-responsive control systems that are widely deployed in the developed world and also to a temporal difference learning-based control method. In all experiments, HuTMaC outperforms the other control methods in terms of average delay and variance over delay. The conclusion is that these results add weight to the suggestion that HuTMaC may be a viable alternative, or supplemental method, to approximate optimization for some practical engineering control problems where the optimal strategy is computationally intractable.
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...
A novel stock forecasting model based on High-order-fuzzy-fluctuation Trends and Back Propagation Neural Network.

Science.gov (United States)

Guan, Hongjun; Dai, Zongli; Zhao, Aiwu; He, Jie

2018-01-01

In this paper, we propose a hybrid method to forecast the stock prices called High-order-fuzzy-fluctuation-Trends-based Back Propagation(HTBP)Neural Network model. First, we compare each value of the historical training data with the previous day's value to obtain a fluctuation trend time series (FTTS). On this basis, the FTTS blur into fuzzy time series (FFTS) based on the fluctuation of the increasing, equality, decreasing amplitude and direction. Since the relationship between FFTS and future wave trends is nonlinear, the HTBP neural network algorithm is used to find the mapping rules in the form of self-learning. Finally, the results of the algorithm output are used to predict future fluctuations. The proposed model provides some innovative features:(1)It combines fuzzy set theory and neural network algorithm to avoid overfitting problems existed in traditional models. (2)BP neural network algorithm can intelligently explore the internal rules of the actual existence of sequential data, without the need to analyze the influence factors of specific rules and the path of action. (3)The hybrid modal can reasonably remove noises from the internal rules by proper fuzzy treatment. This paper takes the TAIEX data set of Taiwan stock exchange as an example, and compares and analyzes the prediction performance of the model. The experimental results show that this method can predict the stock market in a very simple way. At the same time, we use this method to predict the Shanghai stock exchange composite index, and further verify the effectiveness and universality of the method.
A novel stock forecasting model based on High-order-fuzzy-fluctuation Trends and Back Propagation Neural Network.

Directory of Open Access Journals (Sweden)

Hongjun Guan

Full Text Available In this paper, we propose a hybrid method to forecast the stock prices called High-order-fuzzy-fluctuation-Trends-based Back Propagation(HTBPNeural Network model. First, we compare each value of the historical training data with the previous day's value to obtain a fluctuation trend time series (FTTS. On this basis, the FTTS blur into fuzzy time series (FFTS based on the fluctuation of the increasing, equality, decreasing amplitude and direction. Since the relationship between FFTS and future wave trends is nonlinear, the HTBP neural network algorithm is used to find the mapping rules in the form of self-learning. Finally, the results of the algorithm output are used to predict future fluctuations. The proposed model provides some innovative features:(1It combines fuzzy set theory and neural network algorithm to avoid overfitting problems existed in traditional models. (2BP neural network algorithm can intelligently explore the internal rules of the actual existence of sequential data, without the need to analyze the influence factors of specific rules and the path of action. (3The hybrid modal can reasonably remove noises from the internal rules by proper fuzzy treatment. This paper takes the TAIEX data set of Taiwan stock exchange as an example, and compares and analyzes the prediction performance of the model. The experimental results show that this method can predict the stock market in a very simple way. At the same time, we use this method to predict the Shanghai stock exchange composite index, and further verify the effectiveness and universality of the method.
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

Adaptive traffic signal control with actor-critic methods in a real-world traffic network with different traffic disruption events

NARCIS (Netherlands)

Aslani, Mohammad; Mesgari, Mohammad Saadi; Wiering, Marco

2017-01-01

The transportation demand is rapidly growing in metropolises, resulting in chronic traffic con-gestions in dense downtown areas. Adaptive traffic signal control as the principle part of in-telligent transportation systems has a primary role to effectively reduce traffic congestion by making a
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 ...
Efficient disk-to-disk copy through long-distance high-speed networks with background traffic

International Nuclear Information System (INIS)

Tanida, Naoki; Hiraki, Kei; Inaba, Mary

2010-01-01

We propose 'ICDC - InterContinental Disk Copy', a data sharing facility between distant places. ICDC aims to transfer huge amount of data files easily on Long Fat-pipe Networks with some background traffic. ICDC consists of commodity PCs and Solid State Drives and we apply Inter Packet Gap tuning technique to it. Using 'ICDC-1 Gbps model', we transferred data between Tokyo and Cadarache via New York. We attained about 860 Mbps, i.e., 86% usage of the network bottleneck bandwidth.
STUDY ON SUPPORTING FOR DRAWING UP THE BCP FOR URBAN EXPRESSWAY NETWORK USING BY TRAFFIC SIMULATION SYSTEM

Science.gov (United States)

Yamawaki, Masashi; Shiraki, Wataru; Inomo, Hitoshi; Yasuda, Keiichi

The urban expressway network is an important infrastructure to execute a disaster restoration. Therefore, it is necessary to draw up the BCP (Business Continuity Plan) to enable securing of road user's safety and restoration of facilities, etc. It is important that each urban expressway manager execute decision and improvement of effective BCP countermeasures when disaster occurs by assuming various disaster situations. Then, in this study, we develop the traffic simulation system that can reproduce various disaster situations and traffic actions, and examine some methods supporting for drawing up the BCP for an urban expressway network. For disaster outside assumption such as tsunami generated by a huge earthquake, we examine some approaches securing safety of users and cars on the Hanshin Expressway Network as well as on general roads. And, we aim to propose a tsunami countermeasure not considered in the current urban expressway BCP.
Exploiting Spatial Abstraction in Predictive Analytics of Vehicle Traffic

Directory of Open Access Journals (Sweden)

Natalia Andrienko

2015-04-01

Full Text Available By applying visual analytics techniques to vehicle traffic data, we found a way to visualize and study the relationships between the traffic intensity and movement speed on links of a spatially abstracted transportation network. We observed that the traffic intensities and speeds in an abstracted network are interrelated in the same way as they are in a detailed street network at the level of street segments. We developed interactive visual interfaces that support representing these interdependencies by mathematical models. To test the possibility of utilizing them for performing traffic simulations on the basis of abstracted transportation networks, we devised a prototypical simulation algorithm employing these dependency models. The algorithm is embedded in an interactive visual environment for defining traffic scenarios, running simulations, and exploring their results. Our research demonstrates a principal possibility of performing traffic simulations on the basis of spatially abstracted transportation networks using dependency models derived from real traffic data. This possibility needs to be comprehensively investigated and tested in collaboration with transportation domain specialists.
Self-Organized Criticality and $1/f$ Noise in Traffic

OpenAIRE

Paczuski, Maya; Nagel, Kai

1996-01-01

Phantom traffic jams may emerge ``out of nowhere'' from small fluctuations rather than being triggered by large, exceptional events. We show how phantom jams arise in a model of single lane highway traffic, which mimics human driving behavior. Surprisingly, the optimal state of highest efficiency, with the largest throughput, is a critical state with traffic jams of all sizes. We demonstrate that open systems self-organize to the most efficient state. In the model we study, this critical stat...
An efficient strategy for enhancing traffic capacity by removing links in scale-free networks

International Nuclear Information System (INIS)

Huang, Wei; Chow, Tommy W S

2010-01-01

An efficient link-removal strategy, called the variance-of-neighbor-degree-reduction (VNDR) strategy, for enhancing the traffic capacity of scale-free networks is proposed in this paper. The VNDR strategy, which considers the important role of hub nodes, balances the amounts of packets routed from each node to the node's neighbors. Compared against the outcomes of strategies that remove links among hub nodes, our results show that the traffic capacity can be greatly enhanced, especially under the shortest path routing strategy. It is also found that the average transport time is effectively reduced by using the VNDR strategy only under the shortest path routing strategy
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.
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.
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.
A Spatiotemporal Multi-View-Based Learning Method for Short-Term Traffic Forecasting

Directory of Open Access Journals (Sweden)

Shifen Cheng

2018-06-01

Full Text Available Short-term traffic forecasting plays an important part in intelligent transportation systems. Spatiotemporal k-nearest neighbor models (ST-KNNs have been widely adopted for short-term traffic forecasting in which spatiotemporal matrices are constructed to describe traffic conditions. The performance of the models is closely related to the spatial dependencies, the temporal dependencies, and the interaction of spatiotemporal dependencies. However, these models use distance functions and correlation coefficients to identify spatial neighbors and measure the temporal interaction by only considering the temporal closeness of traffic, which result in existing ST-KNNs that cannot fully reflect the essential features of road traffic. This study proposes an improved spatiotemporal k-nearest neighbor model for short-term traffic forecasting by utilizing a multi-view learning algorithm named MVL-STKNN that fully considers the spatiotemporal dependencies of traffic data. First, the spatial neighbors for each road segment are automatically determined using cross-correlation under different temporal dependencies. Three spatiotemporal views are built on the constructed spatiotemporal closeness, periodic, and trend matrices to represent spatially heterogeneous traffic states. Second, a spatiotemporal weighting matrix is introduced into the ST-KNN model to recognize similar traffic patterns in the three spatiotemporal views. Finally, the results of traffic pattern recognition under these three spatiotemporal views are aggregated by using a neural network algorithm to describe the interaction of spatiotemporal dependencies. Extensive experiments were conducted using real vehicular-speed datasets collected on city roads and expressways. In comparison with baseline methods, the results show that the MVL-STKNN model greatly improves short-term traffic forecasting by lowering the mean absolute percentage error between 28.24% and 46.86% for the city road dataset and
Property relationships of the physical infrastructure and the traffic flow networks

Science.gov (United States)

Zhou, Ta; Zou, Sheng-Rong; He, Da-Ren

2010-03-01

We studied both empirically and analytically the correlation between the degrees or the clustering coefficients, respectively, of the networks in the physical infrastructure and the traffic flow layers in three Chinese transportation systems. The systems are bus transportation systems in Beijing and Hangzhou, and the railway system in the mainland. It is found that the correlation between the degrees obey a linear function; while the correlation between the clustering coefficients obey a power law. A possible dynamic explanation on the rules is presented.
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...
Flow level performance approximations for elastic traffic integrated with prioritized stream traffic

NARCIS (Netherlands)

Malhotra, R.; Berg, J.L. van den

2007-01-01

Almost all traffic in todays networks can be classified as being either stream or elastic. The support of these two traffic types is possible either with a Differentiated (DiffServ) or an Integrated Services (IntServ) architecture. However, both DiffServ and IntServ rely on efficient scheduling
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.
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 ...
Understanding the T2 traffic in CMS during Run-1

Science.gov (United States)

T, Wildish

2015-12-01

In the run-up to Run-1 CMS was operating its facilities according to the MONARC model, where data-transfers were strictly hierarchical in nature. Direct transfers between Tier-2 nodes was excluded, being perceived as operationally intensive and risky in an era where the network was expected to be a major source of errors. By the end of Run-1 wide-area networks were more capable and stable than originally anticipated. The original data-placement model was relaxed, and traffic was allowed between Tier-2 nodes. Tier-2 to Tier-2 traffic in 2012 already exceeded the amount of Tier-2 to Tier-1 traffic, so it clearly has the potential to become important in the future. Moreover, while Tier-2 to Tier-1 traffic is mostly upload of Monte Carlo data, the Tier-2 to Tier-2 traffic represents data moved in direct response to requests from the physics analysis community. As such, problems or delays there are more likely to have a direct impact on the user community. Tier-2 to Tier-2 traffic may also traverse parts of the WAN that are at the 'edge' of our network, with limited network capacity or reliability compared to, say, the Tier-0 to Tier-1 traffic which goes the over LHCOPN network. CMS is looking to exploit technologies that allow us to interact with the network fabric so that it can manage our traffic better for us, this we hope to achieve before the end of Run-2. Tier-2 to Tier-2 traffic would be the most interesting use-case for such traffic management, precisely because it is close to the users' analysis and far from the 'core' network infrastructure. As such, a better understanding of our Tier-2 to Tier-2 traffic is important. Knowing the characteristics of our data-flows can help us place our data more intelligently. Knowing how widely the data moves can help us anticipate the requirements for network capacity, and inform the dynamic data placement algorithms we expect to have in place for Run-2. This paper presents an analysis of the CMS Tier-2 traffic during Run 1.
Noxious substances in the air - traffic planning measures - traffic of the future

Energy Technology Data Exchange (ETDEWEB)

Koestenberger, H

1985-01-01

Necessary bundle of measures: Extension of public transport and restriction of individual traffic, extension and activation of large main roads (by-passes) to unload inhabited areas, building garages, creation of residential streets, pedestrian precincts and cycle paths. The best possible traffic system can only be achieved if all means of transport are used efficiently. It is the duty of traffic planners to develop an overall traffic system with the aims of benefiting the whole community. Due to wrong slowing down of traffic, the reduction of emitted quantities of noxious substances from private cars can be counteracted by general slowing down of traffic; frequent braking and restarting. The functional separation of residential areas for living, areas for working, supply, education and leisure pursuits which has been aimed at in recent decades must be slowly changed. This could reduce the traffic and mobility (mixed functions). The aims for traffic of the future are: suitability for the environment, economy, safety and capacity. In an integrated road network, the traffic must take over the correct purpose of traffic. (orig.).
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.
Spatial correlation analysis of urban traffic state under a perspective of community detection

Science.gov (United States)

Yang, Yanfang; Cao, Jiandong; Qin, Yong; Jia, Limin; Dong, Honghui; Zhang, Aomuhan

2018-05-01

Understanding the spatial correlation of urban traffic state is essential for identifying the evolution patterns of urban traffic state. However, the distribution of traffic state always has characteristics of large spatial span and heterogeneity. This paper adapts the concept of community detection to the correlation network of urban traffic state and proposes a new perspective to identify the spatial correlation patterns of traffic state. In the proposed urban traffic 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 correlation of traffic state. Further, the process of community detection in the urban traffic network (named GWPA-K-means) is applied to analyze the spatial dependency of traffic state. The proposed method extends the traditional K-means algorithm in two steps: (i) redefines the initial cluster centers by two properties of nodes (the GWPA value and the minimum shortest path length); (ii) utilizes the weight signal propagation process to transfer the topological information of the urban traffic network into a node similarity matrix. Finally, numerical experiments are conducted on a simple network and a real urban road network in Beijing. The results show that GWPA-K-means algorithm is valid in spatial correlation analysis of traffic state. The network science and community structure analysis perform well in describing the spatial heterogeneity of traffic state on a large spatial scale.

Deep Neural Network for Structural Prediction and Lane Detection in Traffic Scene.

Science.gov (United States)

Li, Jun; Mei, Xue; Prokhorov, Danil; Tao, Dacheng

2017-03-01

Hierarchical neural networks have been shown to be effective in learning representative image features and recognizing object classes. However, most existing networks combine the low/middle level cues for classification without accounting for any spatial structures. For applications such as understanding a scene, how the visual cues are spatially distributed in an image becomes essential for successful analysis. This paper extends the framework of deep neural networks by accounting for the structural cues in the visual signals. In particular, two kinds of neural networks have been proposed. First, we develop a multitask deep convolutional network, which simultaneously detects the presence of the target and the geometric attributes (location and orientation) of the target with respect to the region of interest. Second, a recurrent neuron layer is adopted for structured visual detection. The recurrent neurons can deal with the spatial distribution of visible cues belonging to an object whose shape or structure is difficult to explicitly define. Both the networks are demonstrated by the practical task of detecting lane boundaries in traffic scenes. The multitask convolutional neural network provides auxiliary geometric information to help the subsequent modeling of the given lane structures. The recurrent neural network automatically detects lane boundaries, including those areas containing no marks, without any explicit prior knowledge or secondary modeling.
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.
Towards Scalable Distributed Framework for Urban Congestion Traffic Patterns Warehousing

Directory of Open Access Journals (Sweden)

A. Boulmakoul

2015-01-01

Full Text Available We put forward architecture of a framework for integration of data from moving objects related to urban transportation network. Most of this research refers to the GPS outdoor geolocation technology and uses distributed cloud infrastructure with big data NoSQL database. A network of intelligent mobile sensors, distributed on urban network, produces congestion traffic patterns. Congestion predictions are based on extended simulation model. This model provides traffic indicators calculations, which fuse with the GPS data for allowing estimation of traffic states across the whole network. The discovery process of congestion patterns uses semantic trajectories metamodel given in our previous works. The challenge of the proposed solution is to store patterns of traffic, which aims to ensure the surveillance and intelligent real-time control network to reduce congestion and avoid its consequences. The fusion of real-time data from GPS-enabled smartphones integrated with those provided by existing traffic systems improves traffic congestion knowledge, as well as generating new information for a soft operational control and providing intelligent added value for transportation systems deployment.
On balancing between minimum energy and minimum delay with radio diversity for wireless sensor networks

DEFF Research Database (Denmark)

Moad, Sofiane; Hansen, Morten Tranberg; Jurdak, RajA

2012-01-01

The expected number of transmissions (ETX) metric represents the link quality in wireless sensor networks, which is highly variable for a specific radio and it can influence dramatically both of the delay and the energy. To adapt to these fluctuations, radio diversity has been recently introduced...... to improve the delivery rate but at the cost of increases in energy for wireless sensor networks. In this paper, we propose a scheme for radio diversity that can balance, depending on the traffic nature in the network, between minimizing the energy consumption or minimizing the end-to-end delay. The proposed...... scheme combines the benefit of two metrics, which aim separately to minimize the energy consumption, and to minimize delay when delivering packets to the end-user. We show by both analysis and simulation that our proposed scheme can adapt to the type of traffic that can occur in a network so...
Traffic speed data imputation method based on tensor completion.

Science.gov (United States)

Ran, Bin; Tan, Huachun; Feng, Jianshuai; Liu, Ying; Wang, Wuhong

2015-01-01

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.
Value of Information for Optimal Adaptive Routing in Stochastic Time-Dependent Traffic Networks: Algorithms and Computational Tools

Science.gov (United States)

2010-10-25

Real-time information is important for travelers' routing decisions in uncertain networks by enabling online adaptation to revealed traffic conditions. Usually there are spatial and/or temporal limitations in traveler information. In this research, a...
Research on Congestion Pricing in Multimode Traffic considering Delay and Emission

Directory of Open Access Journals (Sweden)

Hongna Dai

2015-01-01

Full Text Available Rapid development of urbanization and automation has resulted in serious urban traffic congestion and air pollution problems in many Chinese cities recently. As a traffic demand management strategy, congestion pricing is acknowledged to be effective in alleviating the traffic congestion and improving the efficiency of traffic system. This paper proposes an urban traffic congestion pricing model based on the consideration of transportation network efficiency and environment effects. First, the congestion pricing problem under multimode (i.e., car mode and bus mode urban traffic network condition is investigated. Second, a traffic congestion pricing model based on bilevel programming is formulated for a dual-mode urban transportation network, in which the delay and emission of vehicles are considered. Third, an improved mathematical algorithm combining successive average method with the genetic algorithm is proposed to solve the bilevel programming problem. Finally, a numerical experiment based on a hypothetical network is performed to validate the proposed congestion pricing model and algorithm.
Accurate Traffic Flow Prediction in Heterogeneous Vehicular Networks in an Intelligent Transport System Using a Supervised Non-Parametric Classifier

Directory of Open Access Journals (Sweden)

Hesham El-Sayed

2018-05-01

Full Text Available Heterogeneous vehicular networks (HETVNETs evolve from vehicular ad hoc networks (VANETs, which allow vehicles to always be connected so as to obtain safety services within intelligent transportation systems (ITSs. The services and data provided by HETVNETs should be neither interrupted nor delayed. Therefore, Quality of Service (QoS improvement of HETVNETs is one of the topics attracting the attention of researchers and the manufacturing community. Several methodologies and frameworks have been devised by researchers to address QoS-prediction service issues. In this paper, to improve QoS, we evaluate various traffic characteristics of HETVNETs and propose a new supervised learning model to capture knowledge on all possible traffic patterns. This model is a refinement of support vector machine (SVM kernels with a radial basis function (RBF. The proposed model produces better results than SVMs, and outperforms other prediction methods used in a traffic context, as it has lower computational complexity and higher prediction accuracy.
Removing Ambiguities of IP Telephony Traffic Using Protocol Scrubbers

Directory of Open Access Journals (Sweden)

Bazara I. A. Barry

2012-10-01

Full Text Available Network intrusion detection systems (NIDSs face the serious challenge of attacks such as insertion and evasion attacks that are caused by ambiguous network traffic. Such ambiguity comes as a result of the nature of network traffic which includes protocol implementation variations and errors alongside legitimate network traffic. Moreover, attackers can intentionally introduce further ambiguities in the traffic. Consequently, NIDSs need to be aware of these ambiguities when detection is performed and make sure to differentiate between true attacks and protocol implementation variations or errors; otherwise, detection accuracy can be affected negatively. In this paper we present the design and implementation of tools that are called protocol scrubbers whose main functionality is to remove ambiguities from network traffic before it is presented to the NIDS. The proposed protocol scrubbers are designed for session initiation and data transfer protocols in IP telephony systems. They guarantee that the traffic presented to NIDSs is unambiguous by eliminating ambiguous behaviors of protocols using well-designed protocol state machines, and walking through packet headers of protocols to make sure packets will be interpreted in the desired way by the NIDS. The experimental results shown in this paper demonstrate the good quality and applicability of the introduced scrubbers.
Urban Road Traffic Simulation Techniques

Directory of Open Access Journals (Sweden)

Ana Maria Nicoleta Mocofan

2011-09-01

Full Text Available For achieving a reliable traffic control system it is necessary to first establish a network parameter evaluation system and also a simulation system for the traffic lights plan. In 40 years of history, the computer aided traffic simulation has developed from a small research group to a large scale technology for traffic systems planning and development. In the following thesis, a presentation of the main modeling and simulation road traffic applications will be provided, along with their utility, as well as the practical application of one of the models in a case study.
Survivable Impairment-Aware Traffic Grooming

NARCIS (Netherlands)

Beshir, A.; Nuijts, R.; Malhotra, R.; Kuipers, F.

2011-01-01

Traffic grooming allows efficient utilization of network capacity by aggregating several independent traffic streams into a wavelength. In addition, survivability and impairment-awareness (i.e., taking into account the effect of physical impairments) are two important issues that have gained a lot
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
Road safety and bicycle usage impacts of unbundling vehicular and cycle traffic in Dutch urban networks.

NARCIS (Netherlands)

Schepers, P. Heinen, E. Methorst, R. & Wegman, F.

2015-01-01

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
On the Impact of Zero-padding in Network Coding Efficiency with Internet Traffic and Video Traces

DEFF Research Database (Denmark)

Taghouti, Maroua; Roetter, Daniel Enrique Lucani; Pedersen, Morten Videbæk

2016-01-01

Random Linear Network Coding (RLNC) theoretical results typically assume that packets have equal sizes while in reality, data traffic presents a random packet size distribution. Conventional wisdom considers zero-padding of original packets as a viable alternative, but its effect can reduce the e...
Deformation and concentration fluctuations under stretching in a polymer network with free chains. The ''butterfly'' effect

International Nuclear Information System (INIS)

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
Scalable data-driven short-term traffic prediction

NARCIS (Netherlands)

Friso, K.; Wismans, L. J.J.; Tijink, M. B.

2017-01-01

Short-term traffic prediction has a lot of potential for traffic management. However, most research has traditionally focused on either traffic models-which do not scale very well to large networks, computationally-or on data-driven methods for freeways, leaving out urban arterials completely. Urban
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.
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.
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.
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.

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

DEFF Research Database (Denmark)

Bujlow, Tomasz; Pedersen, Jens Myrup

Learning Algorithms (MLAs) require good quality training data, which are difficult to obtain. MLAs usually cannot properly deal with other types of traffic, than they are trained to work with -- such traffic is identified as the most probable class, instead of being left unclassified. Another drawback...... Learning Algorithm. Finally, content and service provider levels are identified based on IP addresses. The training data for the statistical classifier and the mappings between the different types of content and the IP addresses are created based on the data collected by Volunteer-Based System, while...... 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...
Fluctuations and pseudo long range dependence in network flows: A non-stationary Poisson process model

International Nuclear Information System (INIS)

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

2009-01-01

In the study of complex networks (systems), the scaling phenomenon of flow fluctuations refers to a certain power-law between the mean flux (activity) (F i ) of the i-th node and its variance σ i as σ i α (F i ) α . Such scaling laws are found to be prevalent both in natural and man-made network systems, but the understanding of their origins still remains limited. This paper proposes a non-stationary Poisson process model to give an analytical explanation of the non-universal scaling phenomenon: the exponent α varies between 1/2 and 1 depending on the size of sampling time window and the relative strength of the external/internal driven forces of the systems. The crossover behaviour and the relation of fluctuation scaling with pseudo long range dependence are also accounted for by the model. Numerical experiments show that the proposed model can recover the multi-scaling phenomenon. (general)
Intelligent Traffic Quantification System

Science.gov (United States)

Mohanty, Anita; Bhanja, Urmila; Mahapatra, Sudipta

2017-08-01

Currently, city traffic monitoring and controlling is a big issue in almost all cities worldwide. Vehicular ad-hoc Network (VANET) technique is an efficient tool to minimize this problem. Usually, different types of on board sensors are installed in vehicles to generate messages characterized by different vehicle parameters. In this work, an intelligent system based on fuzzy clustering technique is developed to reduce the number of individual messages by extracting important features from the messages of a vehicle. Therefore, the proposed fuzzy clustering technique reduces the traffic load of the network. The technique also reduces congestion and quantifies congestion.
Simulation of traffic control signal systems

Science.gov (United States)

Connolly, P. J.; Concannon, P. A.; Ricci, R. C.

1974-01-01

In recent years there has been considerable interest in the development and testing of control strategies for networks of urban traffic signal systems by simulation. Simulation is an inexpensive and timely method for evaluating the effect of these traffic control strategies since traffic phenomena are too complex to be defined by analytical models and since a controlled experiment may be hazardous, expensive, and slow in producing meaningful results. This paper describes the application of an urban traffic corridor program, to evaluate the effectiveness of different traffic control strategies for the Massachusetts Avenue TOPICS Project.
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
Traffic Congestion Detection and Avoidance using Vehicular Communication

Directory of Open Access Journals (Sweden)

Ajay Narendrabhai Upadhyaya

2015-01-01

Full Text Available Traffic congestion is a serious problem in big cities. With the number of vehicles increasing rapidly, especially in cities whose economy is booming, the situation is getting even worse. Drivers, unaware of congestion ahead eventually join it and increase the severity of it. The ability of a driver to know the traffic conditions on the roads ahead enables him/her to seek alternate routes through which time and fuel can be saved. Due to recent advancements in vehicular technologies, vehicular communication has emerged. The objective of this work is to check feasibility of using infrastructure based vehicular communication for detecting and avoiding traffic congestion. In this paper we propose a Signal Agent (SA and Car Agent(CAbased approach for detecting and avoiding traffic congestion. We analyze performance of the proposed approach for two different road network scenarios using simulations: structured grid network (like Gandhinagar City of Gujarat, India and apart of typical city road network ( Tiwan city. With the proposed approach we get reduction of 10.05% in trip duration of vehicles, reduction of 10.08% in number of vehicles in entire traffic road network and 9.82% in heavy traffic area. In an accident scenario, about 72.63% vehicles changed their route due to awareness of congestion. Error in trip time estimation and vehicle count estimation is observed to be less than 1%.
Nuclear traffic and peloton formation in fungal networks

Science.gov (United States)

Roper, Marcus; Hickey, Patrick; Lewkiewicz, Stephanie; Dressaire, Emilie; Read, Nick

2013-11-01

Hyphae, the network of microfluidic pipes that make up a growing fungal cell, must balance their function as conduits for the transport of nuclei with other cellular functions including secretion and growth. Constant flow of nuclei may interfere with the protein traffic that enables other functions to be performed. Live-cell imaging reveals that nuclear flows are anti-congestive; that groups of nuclei flow faster than single nuclei, and that nuclei sweep through the colony in dense clumps. We call these clumps pelotons, after the term used to describe groups of cycle racers slip-streaming off each other. Because of the pelotons, individual hyphae transport nuclei only intermittently, producing long intervals in which hyphae can perform their other functions. Modeling reveals how pelotons are created by interactions between nuclei and the hyphal cytoskeleton, and reveal the control that the fungus enjoys over peloton assembly and timing.
Discovering urban mobility patterns with PageRank based traffic modeling and prediction

Science.gov (United States)

Wang, Minjie; Yang, Su; Sun, Yi; Gao, Jun

2017-11-01

Urban transportation system can be viewed as complex network with time-varying traffic flows as links to connect adjacent regions as networked nodes. By computing urban traffic evolution on such temporal complex network with PageRank, it is found that for most regions, there exists a linear relation between the traffic congestion measure at present time and the PageRank value of the last time. Since the PageRank measure of a region does result from the mutual interactions of the whole network, it implies that the traffic state of a local region does not evolve independently but is affected by the evolution of the whole network. As a result, the PageRank values can act as signatures in predicting upcoming traffic congestions. We observe the aforementioned laws experimentally based on the trajectory data of 12000 taxies in Beijing city for one month.
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.
Characterization of YouTube Video Streaming Traffic

OpenAIRE

Ravattu, Radha; Balasetty, Prudhviraj

2013-01-01

Online digital videos have made a revolutionary evolution since the social networking sites such as YouTube and Hulu have emerged. These websites facilitate video accessable and only a click away. Ever increasing internet traffic and a very significant increase in the use of videos in social networking has led to the problem of network congestion. Consequently, it becomes essential and imperative to analyze the traffic flow and comprehend how it is being delivered from the server. If the flow...
Traffic Flow Prediction Using MI Algorithm and Considering Noisy and Data Loss Conditions: An Application to Minnesota Traffic Flow Prediction

Directory of Open Access Journals (Sweden)

Seyed Hadi Hosseini

2014-10-01

Full Text Available Traffic flow forecasting is useful for controlling traffic flow, traffic lights, and travel times. This study uses a multi-layer perceptron neural network and the mutual information (MI technique to forecast traffic flow and compares the prediction results with conventional traffic flow forecasting methods. The MI method is used to calculate the interdependency of historical traffic data and future traffic flow. In numerical case studies, the proposed traffic flow forecasting method was tested against data loss, changes in weather conditions, traffic congestion, and accidents. The outcomes were highly acceptable for all cases and showed the robustness of the proposed flow forecasting method.
The research on optimization of auto supply chain network robust model under macroeconomic fluctuations

International Nuclear Information System (INIS)

Guo, Chunxiang; Liu, Xiaoli; Jin, Maozhu; Lv, Zhihan

2016-01-01

Considering the uncertainty of the macroeconomic environment, the robust optimization method is studied for constructing and designing the automotive supply chain network, and based on the definition of robust solution a robust optimization model is built for integrated supply chain network design that consists of supplier selection problem and facility location–distribution problem. The tabu search algorithm is proposed for supply chain node configuration, analyzing the influence of the level of uncertainty on robust results, and by comparing the performance of supply chain network design through the stochastic programming model and robustness optimize model, on this basis, determining the rational layout of supply chain network under macroeconomic fluctuations. At last the contrastive test result validates that the performance of tabu search algorithm is outstanding on convergence and computational time. Meanwhile it is indicated that the robust optimization model can reduce investment risks effectively when it is applied to supply chain network design.
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.
A Survey of Congestion Control Techniques and Data Link Protocols in Satellite Networks

OpenAIRE

Fahmy, Sonia; Jain, Raj; Lu, Fang; Kalyanaraman, Shivkumar

1998-01-01

Satellite communication systems are the means of realizing a global broadband integrated services digital network. Due to the statistical nature of the integrated services traffic, the resulting rate fluctuations and burstiness render congestion control a complicated, yet indispensable function. The long propagation delay of the earth-satellite link further imposes severe demands and constraints on the congestion control schemes, as well as the media access control techniques and retransmissi...
An Improved Car-Following Model in Vehicle Networking Based on Network Control

Directory of Open Access Journals (Sweden)

D. Y. Kong

2014-01-01

Full Text Available Vehicle networking is a system to realize information interoperability between vehicles and people, vehicles and roads, vehicles and vehicles, and cars and transport facilities, through the network information exchange, in order to achieve the effective monitoring of the vehicle and traffic flow. Realizing information interoperability between vehicles and vehicles, which can affect the traffic flow, is an important application of network control system (NCS. In this paper, a car-following model using vehicle networking theory is established, based on network control principle. The car-following model, which is an improvement of the traditional traffic model, describes the traffic in vehicle networking condition. The impact that vehicle networking has on the traffic flow is quantitatively assessed in a particular scene of one-way, no lane changing highway. The examples show that the capacity of the road is effectively enhanced by using vehicle networking.
Scaling law of resistance fluctuations in stationary random resistor networks

Science.gov (United States)

Pennetta; Trefan; Reggiani

2000-12-11

In a random resistor network we consider the simultaneous evolution of two competing random processes consisting in breaking and recovering the elementary resistors with probabilities W(D) and W(R). The condition W(R)>W(D)/(1+W(D)) leads to a stationary state, while in the opposite case, the broken resistor fraction reaches the percolation threshold p(c). We study the resistance noise of this system under stationary conditions by Monte Carlo simulations. The variance of resistance fluctuations is found to follow a scaling law |p-p(c)|(-kappa(0)) with kappa(0) = 5.5. The proposed model relates quantitatively the defectiveness of a disordered media with its electrical and excess-noise characteristics.
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.
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.
McMAC: Towards a MAC Protocol with Multi-Constrained QoS Provisioning for Diverse Traffic in Wireless Body Area Networks

OpenAIRE

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

2012-01-01

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 de...
Quality of Service Model on Data Link Layer for Mission Critical Traffic on IEEE 802.11g Networks in Infrastructure Mode

Directory of Open Access Journals (Sweden)

Gerald B. Fuenmayor-Rivadeneira

2013-11-01

Full Text Available This article presents a synthesized review as state of the art of the study of QoS for mission-critical traffic in wireless local area networks that use the IEEE 802.11g protocol. This is to highlight previous research for their contribution will constitute a reference to guide a proposed new approach to ensuring the quality of service for this type of traffic using the above protocol. The review is based on academic and business items made during the current five years. As a result of this review it is evident that there have been many efforts to address the issue but there are still gaps in the characterization of mission-critical traffic and ensuring quality of service for the same, due the new applications and the large host of WiFi networks in business and government, which has led to increased demand for access channels and, therefore, a challenge to the progress already known, such as IEEE 802.1q.

Application of machine learning methods for traffic signs recognition

Science.gov (United States)

Filatov, D. V.; Ignatev, K. V.; Deviatkin, A. V.; Serykh, E. V.

2018-02-01

This paper focuses on solving a relevant and pressing safety issue on intercity roads. Two approaches were considered for solving the problem of traffic signs recognition; the approaches involved neural networks to analyze images obtained from a camera in the real-time mode. The first approach is based on a sequential image processing. At the initial stage, with the help of color filters and morphological operations (dilatation and erosion), the area containing the traffic sign is located on the image, then the selected and scaled fragment of the image is analyzed using a feedforward neural network to determine the meaning of the found traffic sign. Learning of the neural network in this approach is carried out using a backpropagation method. The second approach involves convolution neural networks at both stages, i.e. when searching and selecting the area of the image containing the traffic sign, and when determining its meaning. Learning of the neural network in the second approach is carried out using the intersection over union function and a loss function. For neural networks to learn and the proposed algorithms to be tested, a series of videos from a dash cam were used that were shot under various weather and illumination conditions. As a result, the proposed approaches for traffic signs recognition were analyzed and compared by key indicators such as recognition rate percentage and the complexity of neural networks’ learning process.
GIS-based methods for establishing the datafoundation for traffic models

DEFF Research Database (Denmark)

Nielsen, Otto Anker

1997-01-01

Traffic models demand large amounts of data - some of which are: Traffic network topology, traffic network data, zone-data and trip matrices. GIS is a natural tool for handling most of these data as it can ease the work process and improve the quality control. However, traffic models demand a com......-plex topology not very well covered by the traditional GIS-topology. The paper describes a number of applications where ARC/INFO and ArcView have been used to automate the process of building a traffic network topology. The methodology has been used on a number of full-scale models, from medium sized urban...... areas to metropolitan areas (Copenhagen, Denmark and Bandung, Indonesia). The paper covers key subjects in the work process which has been eased considerably by using AML and Avenue scripts or by using the information from ARC/INFO in external applications:· Semi-automatic procedures for attaching zones...
Modelling of road traffic for traffic flow optimization of modern regional center as an example of Odessa

Directory of Open Access Journals (Sweden)

S.V. Myronenko

2016-12-01

Full Text Available At present sharply there is a problem of traffic management especially in big cities. The increase in the number of vehicles, both personal and public, led to congestion of city roads, many hours of traffic jams, difficulty of movement of pedestrians, increase the number of accidents, etc. Aim: The aim of the study is to evaluate the possibility of using simulation models to solve problems of analysis and optimization of traffic flows. To achieve this goal in a simulation environment the data base of the transport network will be developed. Materials and Methods: The problem of analysis and optimization of traffic flow is considered by the example of the city of Odessa (Ukraine, the results and recommendations can be easily adapted for other cities of Ukraine, and for the cities of most countries of the former socialist bloc. Features of transport systems make it impossible to build an adequate analytical model to explore options for the management of the system and its characteristic in different conditions. At the same time simulation modelling as a method to study such objects is a promising for the solution to this problem. As a simulation environment an OmniTRANS package as a universal tool for modeling of discrete, continuous and hybrid systems. Results: With OmniTRANS programs the model of traffic in Odessa was derived and the intensity of the traffic flow. B first approximation the transport network of the central district of the city was considered and built; without calibration and simulation it was developed a database of elements of the transport network and shown how it can be used to solve problems of analysis and optimization of traffic flows. Models constructed from elements of created database, allows you to change the level of detail of the simulated objects and phenomena, thereby obtaining models as macro and micro level.
Analysis of Malicious Traffic in Modbus/TCP Communications

Science.gov (United States)

Kobayashi, Tiago H.; Batista, Aguinaldo B.; Medeiros, João Paulo S.; Filho, José Macedo F.; Brito, Agostinho M.; Pires, Paulo S. Motta

This paper presents the results of our analysis about the influence of Information Technology (IT) malicious traffic on an IP-based automation environment. We utilized a traffic generator, called MACE (Malicious trAffic Composition Environment), to inject malicious traffic in a Modbus/TCP communication system and a sniffer to capture and analyze network traffic. The realized tests show that malicious traffic represents a serious risk to critical information infrastructures. We show that this kind of traffic can increase latency of Modbus/TCP communication and that, in some cases, can put Modbus/TCP devices out of communication.
An LTE implementation based on a road traffic density model

OpenAIRE

Attaullah, Muhammad

2013-01-01

The increase in vehicular traffic has created new challenges in determining the behavior of performance of data and safety measures in traffic. Hence, traffic signals on intersection used as cost effective and time saving tools for traffic management in urban areas. But on the other hand the signalized intersections in congested urban areas are the key source of high traffic density and slow traffic. High traffic density causes the slow network traffic data rate between vehicle to vehicle and...
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
Forecasting energy market indices with recurrent neural networks: Case study of crude oil price fluctuations

International Nuclear Information System (INIS)

Wang, Jie; Wang, Jun

2016-01-01

In an attempt to improve the forecasting accuracy of crude oil price fluctuations, a new neural network architecture is established in this work which combines Multilayer perception and ERNN (Elman recurrent neural networks) with stochastic time effective function. ERNN is a time-varying predictive control system and is developed with the ability to keep memory of recent events in order to predict future output. The stochastic time effective function represents that the recent information has a stronger effect for the investors than the old information. With the established model the empirical research has a good performance in testing the predictive effects on four different time series indices. Compared to other models, the present model is possible to evaluate data from 1990s to today with extreme accuracy and speedy. The applied CID (complexity invariant distance) analysis and multiscale CID analysis, are provided as the new useful measures to evaluate a better predicting ability of the proposed model than other traditional models. - Highlights: • A new forecasting model is developed by a random Elman recurrent neural network. • The forecasting accuracy of crude oil price fluctuations is improved by the model. • The forecasting results of the proposed model are more accurate than compared models. • Two new distance analysis methods are applied to confirm the predicting results.
Traffic-aware energy saving scheme with modularization supporting in TWDM-PON

Science.gov (United States)

Xiong, Yu; Sun, Peng; Liu, Chuanbo; Guan, Jianjun

2017-01-01

Time and wavelength division multiplexed passive optical network (TWDM-PON) is considered to be a primary solution for next-generation passive optical network stage 2 (NG-PON2). Due to the feature of multi-wavelength transmission of TWDM-PON, some of the transmitters/receivers at the optical line terminal (OLT) could be shut down to reduce the energy consumption. Therefore, a novel scheme called traffic-aware energy saving scheme with modularization supporting is proposed. Through establishing the modular energy consumption model of OLT, the wavelength transmitters/receivers at OLT could be switched on or shut down adaptively depending on sensing the status of network traffic load, thus the energy consumption of OLT will be effectively reduced. Furthermore, exploring the technology of optical network unit (ONU) modularization, each module of ONU could be switched to sleep or active mode independently in order to reduce the energy consumption of ONU. Simultaneously, the polling sequence of ONU could be changed dynamically via sensing the packet arrival time. In order to guarantee the delay performance of network traffic, the sub-cycle division strategy is designed to transmit the real-time traffic preferentially. Finally, simulation results verify that the proposed scheme is able to reduce the energy consumption of the network while maintaining the traffic delay performance.
The deployment of carbon monoxide wireless sensor network (CO-WSN) for ambient air monitoring.

Science.gov (United States)

Chaiwatpongsakorn, Chaichana; Lu, Mingming; Keener, Tim C; Khang, Soon-Jai

2014-06-16

Wireless sensor networks are becoming increasingly important as an alternative solution for environment monitoring because they can reduce cost and complexity. Also, they can improve reliability and data availability in places where traditional monitoring methods are difficult to site. In this study, a carbon monoxide wireless sensor network (CO-WSN) was developed to measure carbon monoxide concentrations at a major traffic intersection near the University of Cincinnati main campus. The system has been deployed over two weeks during Fall 2010, and Summer 2011-2012, traffic data was also recorded by using a manual traffic counter and a video camcorder to characterize vehicles at the intersection 24 h, particularly, during the morning and evening peak hour periods. According to the field test results, the 1 hr-average CO concentrations were found to range from 0.1-1.0 ppm which is lower than the National Ambient Air Quality Standards (NAAQS) 35 ppm on a one-hour averaging period. During rush hour periods, the traffic volume at the intersection varied from 2,067 to 3,076 vehicles per hour with 97% being passenger vehicles. Furthermore, the traffic volume based on a 1-h average showed good correlation (R2 = 0.87) with the 1-h average CO-WSN concentrations for morning and evening peak time periods whereas CO-WSN results provided a moderate correlation (R2 = 0.42) with 24 hours traffic volume due to fluctuated changes of meteorological conditions. It is concluded that the performance and the reliability of wireless ambient air monitoring networks can be used as an alternative method for real time air monitoring.
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
The Optimization of the Data Packet Length in Adaptive Radio Networks

Directory of Open Access Journals (Sweden)

Anatolii P. Voiter

2017-10-01

Full Text Available Background. Development of methods and means of the adaptive management of the radio networks bandwidth with competitive access to the radio channel. Objective. The aim of the paper is to determine the packet length effect on the effective radio networks transmission rate with taking into account the parameters, formats, and procedures of the physical and link levels at using the MAC protocol with a rigid strategy of competitive access to the radio channel. Methods. The goal is achieved by creating and analyzing the mathematical model of the effective transmission rate in radio networks. The model is described by the equation for the effective transmission rate, which is the function of both the probability of the conflict-free transmission of the MAC protocol and the coefficient of the data packet size deviation from the optimal for LLC protocol. Results. It is proved that there is the optimal deviation of the data packet length for each MAC protocol traffic intensity value, which provides the most effective transfer rate. This makes the possibility for adaptive management of the radio bandwidth by applying a pre-calculated deviation of the data packet size in dependence on the traffic intensity. Conclusions. The proposed mathematical model is the tool for calculation of both the radio bandwidth network capacity and the optimal deviation of the data packet length at adaptive management of competitive access to a radio channel with a rigid strategy at conditions of the significant fluctuation in traffic intensity.
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.
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.
Distributed Dynamic Traffic Modeling and Implementation Oriented Different Levels of Induced Travelers

Directory of Open Access Journals (Sweden)

Yan Liu

2015-01-01

Full Text Available In order to respond to the variable state of traffic network in time, a distributed dynamic traffic assignment strategy is proposed which can improve the intelligent traffic management. The proposed dynamic assignment method is based on utility theory and is oriented to different levels of induced users. A distributed model based on the marginal utility is developed which combines the advantages of both decentralized paradigm and traveler preference, so as to provide efficient and robust dynamic traffic assignment solutions under uncertain network conditions. Then, the solution algorithm including subroute update and subroute calculation is proposed. To testify the effectiveness of the proposed model in optimizing traffic network operation and minimizing traveler’s cost on different induced levels, a sequence numerical experiment is conducted. In the experiment, there are two test environments: one is in different network load conditions and the other is in different deployment coverage of local agents. The numerical results show that the proposed model not only can improve the running efficiency of road network but also can significantly decrease the average travel time.
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....... If the spikes arrive at random times the changes in synaptic conductance are therefore stochastic and rapid during intense network activity. In comparison, sub-threshold intrinsic conductances vary smoothly in time. In the present study this discrepancy is investigated using two conductance-based models: a (1...... 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...
Detection of Botnet Command and Control Traffic by the Multistage Trust Evaluation of Destination Identifiers

Directory of Open Access Journals (Sweden)

Pieter Burghouwt

2015-10-01

Full Text Available Network-based detection of botnet Command and Control communication is a difficult task if the traffic has a relatively low volume and if popular protocols, such as HTTP, are used to resemble normal traffic. We present a new network-based detection approach that is capable of detecting this type of Command and Control traffic in an enterprise network by estimating the trustworthiness of the traffic destinations. If the destination identifier of a traffic flow origins directly from: human input, prior traffic from a trusted destination, or a defined set of legitimate applications, the destination is trusted and its associated traffic is classified as normal. Advantages of this approach are: the ability of zero day malicious traffic detection, low exposure to malware by passive host-external traffic monitoring, and the applicability for real-time filtering. Experimental evaluation demonstrates successful detection of diverse types of Command and Control Traffic.
Modelling computer networks

International Nuclear Information System (INIS)

Max, G

2011-01-01

Traffic models in computer networks can be described as a complicated system. These systems show non-linear features and to simulate behaviours of these systems are also difficult. Before implementing network equipments users wants to know capability of their computer network. They do not want the servers to be overloaded during temporary traffic peaks when more requests arrive than the server is designed for. As a starting point for our study a non-linear system model of network traffic is established to exam behaviour of the network planned. The paper presents setting up a non-linear simulation model that helps us to observe dataflow problems of the networks. This simple model captures the relationship between the competing traffic and the input and output dataflow. In this paper, we also focus on measuring the bottleneck of the network, which was defined as the difference between the link capacity and the competing traffic volume on the link that limits end-to-end throughput. We validate the model using measurements on a working network. The results show that the initial model estimates well main behaviours and critical parameters of the network. Based on this study, we propose to develop a new algorithm, which experimentally determines and predict the available parameters of the network modelled.
Smart Traffic Management Protocol Based on VANET architecture

Directory of Open Access Journals (Sweden)

Amilcare Francesco Santamaria

2014-01-01

Full Text Available Nowadays one of the hottest theme in wireless environments research is the application of the newest technologies to road safety problems and traffic management exploiting the (VANET architecture. In this work, a novel protocol that aims to achieve a better traffic management is proposed. The overal system is able to reduce traffic level inside the city exploiting inter-communication among vehicles and support infrastructures also known as (V2V and (V2I communications. We design a network protocol called (STMP that takes advantages of IEEE 802.11p standard. On each road several sensors system are placed and they are responsible of monitoring. Gathered data are spread in the network exploiting ad-hoc protocol messages. The increasing knowledge about environment conditions make possible to take preventive actions. Moreover, having a realtime monitoring of the lanes it is possible to reveal roads and city blocks congestions in a shorter time. An external entity to the (VANET is responsible to manage traffic and rearrange traffic along the lanes of the city avoiding huge traffic levels.
Dynamic traffic assignment based trailblazing guide signing for major traffic generator.

Science.gov (United States)

2009-11-01

The placement of guide signs and the display of dynamic massage signs greatly affect drivers : understanding of the network and therefore their route choices. Most existing dynamic traffic assignment : models assume that drivers heading to a Major...
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.

Traveler oriented traffic performance metrics using real time traffic data from the Midtown-in-Motion (MIM) project in Manhattan, NY.

Science.gov (United States)

2013-10-01

In a congested urban street network the average traffic speed is an inadequate metric for measuring : speed changes that drivers can perceive from changes in traffic control strategies. : A driver oriented metric is needed. Stop frequency distrib...
Order and disorder in traffic and self-driven many-particle systems

Science.gov (United States)

Helbing, Dirk

2002-07-01

During the last decade, physicists have identified various spatio-temporal patterns of motion in vehicle and pedestrian traffic. Moreover, by applying and extending methods from statistical physics and non-linear dynamics, these have been successfully explained by means of self-driven many-particle models. Some of the questions now understood are the following: Why are vehicles sometimes stopped by so-called "phantom traffic jams," although they all like to drive fast? What are the mechanisms behind stop-and-go traffic? Why are there several different kinds of congestion, and how are they related? Why do most traffic jams occur considerably before the road capacity is reached? Can a temporary reduction of the traffic volume cause a lasting traffic jam? What is the origin of fluctuations in traffic systems and which consequences do they have? Why do pedestrians moving in opposite directions normally organize in lanes, while nervous crowds are "freezing by heating?" Why do panicking pedestrians produce dangerous deadlocks?
Traffic Congestion Detection System through Connected Vehicles and Big Data

Directory of Open Access Journals (Sweden)

Néstor Cárdenas-Benítez

2016-04-01

Full Text Available This article discusses the simulation and evaluation of a traffic congestion detection system which combines inter-vehicular communications, fixed roadside infrastructure and infrastructure-to-infrastructure connectivity and big data. The system discussed in this article permits drivers to identify traffic congestion and change their routes accordingly, thus reducing the total emissions of CO2 and decreasing travel time. This system monitors, processes and stores large amounts of data, which can detect traffic congestion in a precise way by means of a series of algorithms that reduces localized vehicular emission by rerouting vehicles. To simulate and evaluate the proposed system, a big data cluster was developed based on Cassandra, which was used in tandem with the OMNeT++ discreet event network simulator, coupled with the SUMO (Simulation of Urban MObility traffic simulator and the Veins vehicular network framework. The results validate the efficiency of the traffic detection system and its positive impact in detecting, reporting and rerouting traffic when traffic events occur.
Traffic Congestion Detection System through Connected Vehicles and Big Data.

Science.gov (United States)

Cárdenas-Benítez, Néstor; Aquino-Santos, Raúl; Magaña-Espinoza, Pedro; Aguilar-Velazco, José; Edwards-Block, Arthur; Medina Cass, Aldo

2016-04-28

This article discusses the simulation and evaluation of a traffic congestion detection system which combines inter-vehicular communications, fixed roadside infrastructure and infrastructure-to-infrastructure connectivity and big data. The system discussed in this article permits drivers to identify traffic congestion and change their routes accordingly, thus reducing the total emissions of CO₂ and decreasing travel time. This system monitors, processes and stores large amounts of data, which can detect traffic congestion in a precise way by means of a series of algorithms that reduces localized vehicular emission by rerouting vehicles. To simulate and evaluate the proposed system, a big data cluster was developed based on Cassandra, which was used in tandem with the OMNeT++ discreet event network simulator, coupled with the SUMO (Simulation of Urban MObility) traffic simulator and the Veins vehicular network framework. The results validate the efficiency of the traffic detection system and its positive impact in detecting, reporting and rerouting traffic when traffic events occur.
Automated Big Traffic Analytics for Cyber Security

OpenAIRE

Miao, Yuantian; Ruan, Zichan; Pan, Lei; Wang, Yu; Zhang, Jun; Xiang, Yang

2018-01-01

Network traffic analytics technology is a cornerstone for cyber security systems. We demonstrate its use through three popular and contemporary cyber security applications in intrusion detection, malware analysis and botnet detection. However, automated traffic analytics faces the challenges raised by big traffic data. In terms of big data's three characteristics --- volume, variety and velocity, we review three state of the art techniques to mitigate the key challenges including real-time tr...
Correlations of stock price fluctuations under multi-scale and multi-threshold scenarios

Science.gov (United States)

Sui, Guo; Li, Huajiao; Feng, Sida; Liu, Xueyong; Jiang, Meihui

2018-01-01

The multi-scale method is widely used in analyzing time series of financial markets and it can provide market information for different economic entities who focus on different periods. Through constructing multi-scale networks of price fluctuation correlation in the stock market, we can detect the topological relationship between each time series. Previous research has not addressed the problem that the original fluctuation correlation networks are fully connected networks and more information exists within these networks that is currently being utilized. Here we use listed coal companies as a case study. First, we decompose the original stock price fluctuation series into different time scales. Second, we construct the stock price fluctuation correlation networks at different time scales. Third, we delete the edges of the network based on thresholds and analyze the network indicators. Through combining the multi-scale method with the multi-threshold method, we bring to light the implicit information of fully connected networks.
Traffic modelling for Big Data backed telecom cloud

OpenAIRE

Via Baraldés, Anna

2016-01-01

The objective of this project is to provide traffic models based on new services characteristics. Specifically, we focus on modelling the traffic between origin-destination node pairs (also known as OD pairs) in a telecom network. Two use cases are distinguished: i) traffic generation in the context of simulation, and ii) traffic modelling for prediction in the context of big-data backed telecom cloud systems. To this aim, several machine learning and statistical models and technics are studi...
Field-theoretic approach to fluctuation effects in neural networks

International Nuclear Information System (INIS)

Buice, Michael A.; Cowan, Jack D.

2007-01-01

A well-defined stochastic theory for neural activity, which permits the calculation of arbitrary statistical moments and equations governing them, is a potentially valuable tool for theoretical neuroscience. We produce such a theory by analyzing the dynamics of neural activity using field theoretic methods for nonequilibrium statistical processes. Assuming that neural network activity is Markovian, we construct the effective spike model, which describes both neural fluctuations and response. This analysis leads to a systematic expansion of corrections to mean field theory, which for the effective spike model is a simple version of the Wilson-Cowan equation. We argue that neural activity governed by this model exhibits a dynamical phase transition which is in the universality class of directed percolation. More general models (which may incorporate refractoriness) can exhibit other universality classes, such as dynamic isotropic percolation. Because of the extremely high connectivity in typical networks, it is expected that higher-order terms in the systematic expansion are small for experimentally accessible measurements, and thus, consistent with measurements in neocortical slice preparations, we expect mean field exponents for the transition. We provide a quantitative criterion for the relative magnitude of each term in the systematic expansion, analogous to the Ginsburg criterion. Experimental identification of dynamic universality classes in vivo is an outstanding and important question for neuroscience
Modeling Road Traffic Using Service Center

Directory of Open Access Journals (Sweden)

HARAGOS, I.-M.

2012-05-01

Full Text Available Transport systems have an essential role in modern society because they facilitate access to natural resources and they stimulate trade. Current studies aimed at improving transport networks by developing new methods for optimization. Because of the increase in the global number of cars, one of the most common problems facing the transport network is congestion. By creating traffic models and simulate them, we can avoid this problem and find appropriate solutions. In this paper we propose a new method for modeling traffic. This method considers road intersections as being service centers. A service center represents a set consisting of a queue followed by one or multiple servers. This model was used to simulate real situations in an urban traffic area. Based on this simulation, we have successfully determined the optimal functioning and we have computed the performance measures.
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
McMAC: Towards a MAC Protocol with Multi-Constrained QoS Provisioning for Diverse Traffic in Wireless Body Area Networks

Directory of Open Access Journals (Sweden)

Muhammad Mostafa Monowar

2012-11-01

Full Text Available The emergence of heterogeneous applications with diverse requirements forresource-constrained Wireless Body Area Networks (WBANs poses significant challengesfor provisioning Quality of Service (QoS with multi-constraints (delay and reliability whilepreserving energy efficiency. To address such challenges, this paper proposes McMAC,a MAC protocol with multi-constrained QoS provisioning for diverse traffic classes inWBANs. McMAC classifies traffic based on their multi-constrained QoS demands andintroduces a novel superframe structure based on the "transmit-whenever-appropriate"principle, which allows diverse periods for diverse traffic classes according to their respectiveQoS requirements. Furthermore, a novel emergency packet handling mechanism is proposedto ensure packet delivery with the least possible delay and the highest reliability. McMACis also modeled analytically, and extensive simulations were performed to evaluate itsperformance. The results reveal that McMAC achieves the desired delay and reliabilityguarantee according to the requirements of a particular traffic class while achieving energyefficiency.
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.
A novel grooming algorithm with the adaptive weight and load balancing for dynamic holding-time-aware traffic in optical networks

Science.gov (United States)

Xu, Zhanqi; Huang, Jiangjiang; Zhou, Zhiqiang; Ding, Zhe; Ma, Tao; Wang, Junping

2013-10-01

To maximize the resource utilization of optical networks, the dynamic traffic grooming, which could efficiently multiplex many low-speed services arriving dynamically onto high-capacity optical channels, has been studied extensively and used widely. However, the link weights in the existing research works can be improved since they do not adapt to the network status and load well. By exploiting the information on the holding times of the preexisting and new lightpaths, and the requested bandwidth of a user service, this paper proposes a grooming algorithm using Adaptively Weighted Links for Holding-Time-Aware (HTA) (abbreviated as AWL-HTA) traffic, especially in the setup process of new lightpath(s). Therefore, the proposed algorithm can not only establish a lightpath that uses network resource efficiently, but also achieve load balancing. In this paper, the key issues on the link weight assignment and procedure within the AWL-HTA are addressed in detail. Comprehensive simulation and experimental results show that the proposed algorithm has a much lower blocking ratio and latency than other existing algorithms.
Remotely Accessed Vehicle Traffic Management System

Science.gov (United States)

Al-Alawi, Raida

2010-06-01

The ever increasing number of vehicles in most metropolitan cities around the world and the limitation in altering the transportation infrastructure, led to serious traffic congestion and an increase in the travelling time. In this work we exploit the emergence of novel technologies such as the internet, to design an intelligent Traffic Management System (TMS) that can remotely monitor and control a network of traffic light controllers located at different sites. The system is based on utilizing Embedded Web Servers (EWS) technology to design a web-based TMS. The EWS located at each intersection uses IP technology for communicating remotely with a Central Traffic Management Unit (CTMU) located at the traffic department authority. Friendly GUI software installed at the CTMU will be able to monitor the sequence of operation of the traffic lights and the presence of traffic at each intersection as well as remotely controlling the operation of the signals. The system has been validated by constructing a prototype that resembles the real application.
A Comparison of Traffic Operations among Beijing and Several International Megacities

Directory of Open Access Journals (Sweden)

Yuanzhou Yang

2011-12-01

Full Text Available High-Efficient traffic system is very important for economy and society of cities. Previous studies on the traffic comparison mostly took a city as a whole, but ignored the differences among areas inside the city. But in fact, the traffic congestion in different areas with a city is mostly different. Taking typical mega cities like Beijing, London, New York, and Tokyo as objects, this paper makes cross-comparison in the traffic operation and performance based on intelligent algorithm. Transportation infrastructure and travel demand data are discussed and unbalanced transport system is found in Beijing because of the conflict between too much traffic demand and defect road networks. From the aspects of traffic load, operational efficiency and safety, indexes including traffic v/c ratio, average vehicle speed and accident rate are selected to assess the performance of road traffic. It is concluded that road networks of Beijing have the worst performance compared with other three mega-cities and the primary reasons are the inappropriate distribution of utilization rate among the freeways, arterials, and local streets, and the high traffic concentration in urban area. So, several measures are recommended to improve the operation efficiency of traffic in Beijing especially for the green intelligent traffic system. Keywords: Traffic operation; Operational efficiency; Intelligent traffic system (ITS; Traffic load; traffic safety; Intelligent algorithm.
Detecting bots using multi-level traffic analysis

DEFF Research Database (Denmark)

Stevanovic, Matija; Pedersen, Jens Myrup

2016-01-01

introduces a novel multi-level botnet detection approach that performs network traffic analysis of three protocols widely considered as the main carriers of botnet Command and Control (C&C) and attack traffic, i.e. TCP, UDP and DNS. The proposed method relies on supervised machine learning for identifying...
Self-organized natural roads for predicting traffic flow: a sensitivity study

International Nuclear Information System (INIS)

Jiang, Bin; Zhao, Sijian; Yin, Junjun

2008-01-01

In this paper, we extended road-based topological analysis to both nationwide and urban road networks, and concentrated on a sensitivity study with respect to the formation of self-organized natural roads based on the Gestalt principle of good continuity. Both annual average daily traffic (AADT) and global positioning system (GPS) data were used to correlate with a series of ranking metrics including five centrality-based metrics and two PageRank metrics. It was found that there exists a tipping point from segment-based to road-based network topology in terms of correlation between ranking metrics and their traffic. To our great surprise, (1) this correlation is significantly improved if a selfish rather than utopian strategy is adopted in forming the self-organized natural roads, and (2) point-based metrics assigned by summation into individual roads tend to have a much better correlation with traffic flow than line-based metrics. These counter-intuitive surprising findings constitute emergent properties of self-organized natural roads, which are intelligent enough for predicting traffic flow, thus shedding substantial light on the understanding of road networks and their traffic from the perspective of complex networks
Simulation of logical traffic isolation using differentiated services

CSIR Research Space (South Africa)

Dlamini, I

2009-06-01

Full Text Available This paper extends work on a forensic model for traffic isolation based on Differentiated Services (DiffServ) and measures its performance by using a simulation. The simulated model has four basic components: traffic generators, the DiffServ network...
A Comprehensive Real-Time Traffic Map for Geographic Routing in VANETs

Directory of Open Access Journals (Sweden)

Chi-Fu Huang

2017-01-01

Full Text Available Vehicular Ad Hoc Networks (VANETs have attracted a lot of attention during the last decade. VANETs can not only improve driving safety, but also convenience, and support most future Intelligent Transportation System (ITS. Due to the highly dynamic network topology of VANETs, many geographic routing protocols have been proposed and use real-time traffic information as an important metric to select a reliable forwarding path. However, most of the existing works do not describe how to gather real-time traffic. They either assume this information is already available, or can query an existing traffic center. Few studies have noticed this issue but the proposed solutions only consider a small region. In this paper, we propose a Comprehensive Real-Time Traffic Map (CRT Map to collect wide-ranging real-time traffic information with low overhead. In the design of a CRT Map, the concept of Crowdsensing is adopted. Vehicles cooperatively gather traffic information and share it with each other to construct an overview of the whole road network traffic. In addition, we design a CRT Map Based Routing (CBR, which takes into account the connectivity of consecutive roads in routing decisions. Simulation results show that the CBR can achieve a lower end-to-end delay and a higher packet delivery ratio.
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.

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
Analysis of Wireless Traffic Data through Machine Learning

Directory of Open Access Journals (Sweden)

Muhammad Ahsan Latif

2017-06-01

Full Text Available The paper presents an analytical study on a wireless traffic dataset carried out under the different approaches of machine learning including the backpropagation feedforward neural network, the time-series NARX network, the self-organizing map and the principal component analyses. These approaches are well-known for their usefulness in the modeling and in transforming a high dimensional data into a more convenient form to make the understanding and the analysis of the trends, the patterns within the data easy. We witness to an exponential rise in the volume of the wireless traffic data in the recent decade and it is increasingly becoming a problem for the service providers to ensure the QoS for the end-users given the limited resources as the demand for a larger bandwidth almost always exist. The inception of the next generation wireless networks (3G/4G somehow provide such services to meet the amplified capacity, higher data rates, seamless mobile connectivity as well as the dynamic ability of reconfiguration and the self-organization. Nevertheless, having an intelligent base-station able to perceive the demand well before the actual need may assist in the management of the traffic data. The outcome of the analysis conducted in this paper may be considered in designing an efficient and an intelligent base-station for better resource management for wireless network traffic.
computer networks

Directory of Open Access Journals (Sweden)

N. U. Ahmed

2002-01-01

Full Text Available In this paper, we construct a new dynamic model for the Token Bucket (TB algorithm used in computer networks and use systems approach for its analysis. This model is then augmented by adding a dynamic model for a multiplexor at an access node where the TB exercises a policing function. In the model, traffic policing, multiplexing and network utilization are formally defined. Based on the model, we study such issues as (quality of service QoS, traffic sizing and network dimensioning. Also we propose an algorithm using feedback control to improve QoS and network utilization. Applying MPEG video traces as the input traffic to the model, we verify the usefulness and effectiveness of our model.
Anomalous Traffic Detection and Self-Similarity Analysis in the Environment of ATMSim

Directory of Open Access Journals (Sweden)

Hae-Duck J. Jeong

2017-12-01

Full Text Available Internet utilisation has steadily increased, predominantly due to the rapid recent development of information and communication networks and the widespread distribution of smartphones. As a result of this increase in Internet consumption, various types of services, including web services, social networking services (SNS, Internet banking, and remote processing systems have been created. These services have significantly enhanced global quality of life. However, as a negative side-effect of this rapid development, serious information security problems have also surfaced, which has led to serious to Internet privacy invasions and network attacks. In an attempt to contribute to the process of addressing these problems, this paper proposes a process to detect anomalous traffic using self-similarity analysis in the Anomaly Teletraffic detection Measurement analysis Simulator (ATMSim environment as a research method. Simulations were performed to measure normal and anomalous traffic. First, normal traffic for each attack, including the Address Resolution Protocol (ARP and distributed denial-of-service (DDoS was measured for 48 h over 10 iterations. Hadoop was used to facilitate processing of the large amount of collected data, after which MapReduce was utilised after storing the data in the Hadoop Distributed File System (HDFS. A new platform on Hadoop, the detection system ATMSim, was used to identify anomalous traffic after which a comparative analysis of the normal and anomalous traffic was performed through a self-similarity analysis. There were four categories of collected traffic that were divided according to the attack methods used: normal local area network (LAN traffic, DDoS attack, and ARP spoofing, as well as DDoS and ARP attack. ATMSim, the anomaly traffic detection system, was used to determine if real attacks could be identified effectively. To achieve this, the ATMSim was used in simulations for each scenario to test its ability to
Traffic characterization and Internet usage in rural Africa

CSIR Research Space (South Africa)

Johnson, D

2011-03-01

Full Text Available significantly from the developed world. We observe dominance of web-based traffic, as opposed to peer-to-peer traffic common in urban areas. Application-wise, online social networks are the most popular, while the majority of bandwidth is consumed by large...
Directing Traffic: Managing Internet Bandwidth Fairly

Science.gov (United States)

Paine, Thomas A.; Griggs, Tyler J.

2008-01-01

Educational institutions today face budgetary restraints and scarce resources, complicating the decision of how to allot bandwidth for campus network users. Additionally, campus concerns over peer-to-peer networking (specifically outbound Internet traffic) have increased because of bandwidth and copyright issues. In this article, the authors…
Predictive Abuse Detection for a PLC Smart Lighting Network Based on Automatically Created Models of Exponential Smoothing

Directory of Open Access Journals (Sweden)

Tomasz Andrysiak

2017-01-01

Full Text Available One of the basic elements of a Smart City is the urban infrastructure management system, in particular, systems of intelligent street lighting control. However, for their reliable operation, they require special care for the safety of their critical communication infrastructure. This article presents solutions for the detection of different kinds of abuses in network traffic of Smart Lighting infrastructure, realized by Power Line Communication technology. Both the structure of the examined Smart Lighting network and its elements are described. The article discusses the key security problems which have a direct impact on the correct performance of the Smart Lighting critical infrastructure. In order to detect an anomaly/attack, we proposed the usage of a statistical model to obtain forecasting intervals. Then, we calculated the value of the differences between the forecast in the estimated traffic model and its real variability so as to detect abnormal behavior (which may be symptomatic of an abuse attempt. Due to the possibility of appearance of significant fluctuations in the real network traffic, we proposed a procedure of statistical models update which is based on the criterion of interquartile spacing. The results obtained during the experiments confirmed the effectiveness of the presented misuse detection method.
Lagrangian generic second order traffic flow models for node

Directory of Open Access Journals (Sweden)

Asma Khelifi

2018-02-01

Full Text Available This study sheds light on higher order macroscopic traffic flow modeling on road networks, thanks to the generic second order models (GSOM family which embeds a myriad of traffic models. It has been demonstrated that such higher order models are easily solved in Lagrangian coordinates which are compatible with both microscopic and macroscopic descriptions. The generalized GSOM model is reformulated in the Lagrangian coordinate system to develop a more efficient numerical method. The difficulty in applying this approach on networks basically resides in dealing with node dynamics. Traffic flow characteristics at node are different from that on homogeneous links. Different geometry features can lead to different critical research issues. For instance, discontinuity in traffic stream can be an important issue for traffic signal operations, while capacity drop may be crucial for lane-merges. The current paper aims to establish and analyze a new adapted node model for macroscopic traffic flow models by applying upstream and downstream boundary conditions on the Lagrangian coordinates in order to perform simulations on networks of roads, and accompanying numerical method. The internal node dynamics between upstream and downstream links are taken into account of the node model. Therefore, a numerical example is provided to underscore the efficiency of this approach. Simulations show that the discretized node model yields accurate results. Additional kinematic waves and contact discontinuities are induced by the variation of the driver attribute.
Cytoskeleton dynamics: Fluctuations within the network

International Nuclear Information System (INIS)

Bursac, Predrag; Fabry, Ben; Trepat, Xavier; Lenormand, Guillaume; Butler, James P.; Wang, Ning; Fredberg, Jeffrey J.; An, Steven S.

2007-01-01

Out-of-equilibrium systems, such as the dynamics of a living cytoskeleton (CSK), are inherently noisy with fluctuations arising from the stochastic nature of the underlying biochemical and molecular events. Recently, such fluctuations within the cell were characterized by observing spontaneous nano-scale motions of an RGD-coated microbead bound to the cell surface [Bursac et al., Nat. Mater. 4 (2005) 557-561]. While these reported anomalous bead motions represent a molecular level reorganization (remodeling) of microstructures in contact with the bead, a precise nature of these cytoskeletal constituents and forces that drive their remodeling dynamics are largely unclear. Here, we focused upon spontaneous motions of an RGD-coated bead and, in particular, assessed to what extent these motions are attributable to (i) bulk cell movement (cell crawling), (ii) dynamics of focal adhesions, (iii) dynamics of lipid membrane, and/or (iv) dynamics of the underlying actin CSK driven by myosin motors
A scaling law for random walks on networks

Science.gov (United States)

Perkins, Theodore J.; Foxall, Eric; Glass, Leon; Edwards, Roderick

2014-10-01

The dynamics of many natural and artificial systems are well described as random walks on a network: the stochastic behaviour of molecules, traffic patterns on the internet, fluctuations in stock prices and so on. The vast literature on random walks provides many tools for computing properties such as steady-state probabilities or expected hitting times. Previously, however, there has been no general theory describing the distribution of possible paths followed by a random walk. Here, we show that for any random walk on a finite network, there are precisely three mutually exclusive possibilities for the form of the path distribution: finite, stretched exponential and power law. The form of the distribution depends only on the structure of the network, while the stepping probabilities control the parameters of the distribution. We use our theory to explain path distributions in domains such as sports, music, nonlinear dynamics and stochastic chemical kinetics.
Rerouting algorithms solving the air traffic congestion

Science.gov (United States)

Adacher, Ludovica; Flamini, Marta; Romano, Elpidio

2017-06-01

Congestion in the air traffic network is a problem with an increasing relevance for airlines costs as well as airspace safety. One of the major issue is the limited operative capacity of the air network. In this work an Autonomous Agent approach is proposed to solve in real time the problem of air traffic congestion. The air traffic infrastructures are modeled with a graph and are considered partitioned in different sectors. Each sector has its own decision agent dealing with the air traffic control involved in it. Each agent sector imposes a real time aircraft scheduling to respect both delay and capacity constrains. When a congestion is predicted, a new aircraft scheduling is computed. Congestion is solved when the capacity constrains are satisfied once again. This can be done by delaying on ground aircraft or/and rerouting aircraft and/or postponing the congestion. We have tested two different algorithms that calculate K feasible paths for each aircraft involved in the congestion. Some results are reported on North Italian air space.
Early Obstacle Detection and Avoidance for All to All Traffic Pattern in Wireless Sensor Networks

Science.gov (United States)

Huc, Florian; Jarry, Aubin; Leone, Pierre; Moraru, Luminita; Nikoletseas, Sotiris; Rolim, Jose

This paper deals with early obstacles recognition in wireless sensor networks under various traffic patterns. In the presence of obstacles, the efficiency of routing algorithms is increased by voluntarily avoiding some regions in the vicinity of obstacles, areas which we call dead-ends. In this paper, we first propose a fast convergent routing algorithm with proactive dead-end detection together with a formal definition and description of dead-ends. Secondly, we present a generalization of this algorithm which improves performances in all to many and all to all traffic patterns. In a third part we prove that this algorithm produces paths that are optimal up to a constant factor of 2π + 1. In a fourth part we consider the reactive version of the algorithm which is an extension of a previously known early obstacle detection algorithm. Finally we give experimental results to illustrate the efficiency of our algorithms in different scenarios.
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...
Recurrent network models for perfect temporal integration of fluctuating correlated inputs.

Directory of Open Access Journals (Sweden)

Hiroshi Okamoto

2009-06-01

Full Text Available Temporal integration of input is essential to the accumulation of information in various cognitive and behavioral processes, and gradually increasing neuronal activity, typically occurring within a range of seconds, is considered to reflect such computation by the brain. Some psychological evidence suggests that temporal integration by the brain is nearly perfect, that is, the integration is non-leaky, and the output of a neural integrator is accurately proportional to the strength of input. Neural mechanisms of perfect temporal integration, however, remain largely unknown. Here, we propose a recurrent network model of cortical neurons that perfectly integrates partially correlated, irregular input spike trains. We demonstrate that the rate of this temporal integration changes proportionately to the probability of spike coincidences in synaptic inputs. We analytically prove that this highly accurate integration of synaptic inputs emerges from integration of the variance of the fluctuating synaptic inputs, when their mean component is kept constant. Highly irregular neuronal firing and spike coincidences are the major features of cortical activity, but they have been separately addressed so far. Our results suggest that the efficient protocol of information integration by cortical networks essentially requires both features and hence is heterotic.
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

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......Although many countries only now begin to invest in deployment of GSM-Railways (GSM-R) networks, this technology is already obsolete and reveals its significant shortcomings. The most troublesome one is the insufficient number of communication channels offered by GSM-R. This is a major problem...... 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...
Investigating the relationship between jobs-housing balance and traffic safety.

Science.gov (United States)

Xu, Chengcheng; Li, Haojie; Zhao, Jingya; Chen, Jun; Wang, Wei

2017-10-01

This study aimed to investigate the effects of jobs-housing balance on traffic safety. The crash, demographic characteristics, employment, road network, household characteristics and traffic data were collected from the Los Angeles in 2010. One-way ANOVA tests indicated that the jobs-housing ratio significantly affects traffic safety in terms of crash frequency at traffic analysis zone (TAZ). To quantify the safety impacts of jobs-housing balance, the semi-parametric geographically weighted Poisson regression (S-GWPR) was further used to link crash frequency at TAZ with jobs-housing ratio and other contributing factors. The S-GWPR provides better fitness to the data than do the generalized linear regression, as the S-GWPR accounts for the spatial heterogeneity. The S-GWPR results showed that the jobs-housing relationship has a significant association with crash frequency at TAZ when the factors of traffic, network, and household characteristics are controlled. Crash frequency at TAZ level increases with an increase in the jobs-housing ratio. To further investigate the interactive effects between jobs-housing ratio and other factors, a comparative analysis was conducted to compare the variable elasticities under different jobs-housing ratios. The results indicate considerable interactive effects that traffic conditions and road network characteristics have different effects on crash frequency under various jobs-housing ratios. Copyright © 2017 Elsevier Ltd. All rights reserved.
On Applicability of Network Coding Technique for 6LoWPAN-based Sensor Networks.

Science.gov (United States)

Amanowicz, Marek; Krygier, Jaroslaw

2018-05-26

In this paper, the applicability of the network coding technique in 6LoWPAN-based sensor multihop networks is examined. The 6LoWPAN is one of the standards proposed for the Internet of Things architecture. Thus, we can expect the significant growth of traffic in such networks, which can lead to overload and decrease in the sensor network lifetime. The authors propose the inter-session network coding mechanism that can be implemented in resource-limited sensor motes. The solution reduces the overall traffic in the network, and in consequence, the energy consumption is decreased. Used procedures take into account deep header compressions of the native 6LoWPAN packets and the hop-by-hop changes of the header structure. Applied simplifications reduce signaling traffic that is typically occurring in network coding deployments, keeping the solution usefulness for the wireless sensor networks with limited resources. The authors validate the proposed procedures in terms of end-to-end packet delay, packet loss ratio, traffic in the air, total energy consumption, and network lifetime. The solution has been tested in a real wireless sensor network. The results confirm the efficiency of the proposed technique, mostly in delay-tolerant sensor networks.
A better understanding of long-range temporal dependence of traffic flow time series

Science.gov (United States)

Feng, Shuo; Wang, Xingmin; Sun, Haowei; Zhang, Yi; Li, Li

2018-02-01

Long-range temporal dependence is an important research perspective for modelling of traffic flow time series. Various methods have been proposed to depict the long-range temporal dependence, including autocorrelation function analysis, spectral analysis and fractal analysis. However, few researches have studied the daily temporal dependence (i.e. the similarity between different daily traffic flow time series), which can help us better understand the long-range temporal dependence, such as the origin of crossover phenomenon. Moreover, considering both types of dependence contributes to establishing more accurate model and depicting the properties of traffic flow time series. In this paper, we study the properties of daily temporal dependence by simple average method and Principal Component Analysis (PCA) based method. Meanwhile, we also study the long-range temporal dependence by Detrended Fluctuation Analysis (DFA) and Multifractal Detrended Fluctuation Analysis (MFDFA). The results show that both the daily and long-range temporal dependence exert considerable influence on the traffic flow series. The DFA results reveal that the daily temporal dependence creates crossover phenomenon when estimating the Hurst exponent which depicts the long-range temporal dependence. Furthermore, through the comparison of the DFA test, PCA-based method turns out to be a better method to extract the daily temporal dependence especially when the difference between days is significant.
Fluctuation microscopy analysis of amorphous silicon models

Energy Technology Data Exchange (ETDEWEB)

Gibson, J.M., E-mail: jmgibson@fsu.edu [Northeastern University, Department of Physics, Boston MA 02115 (United States); FAMU/FSU Joint College of Engineering, 225 Pottsdamer Street, Tallahassee, FL 32310 (United States); Treacy, M.M.J. [Arizona State University, Department of Physics, Tempe AZ 85287 (United States)

2017-05-15

Highlights: • Studied competing computer models for amorphous silicon and simulated fluctuation microscopy data. • Show that only paracrystalline/random network composite can fit published data. • Specifically show that pure random network or random network with void models do not fit available data. • Identify a new means to measure volume fraction of ordered material. • Identify unreported limitations of the Debye model for simulating fluctuation microscopy data. - Abstract: Using computer-generated models we discuss the use of fluctuation electron microscopy (FEM) to identify the structure of amorphous silicon. We show that a combination of variable resolution FEM to measure the correlation length, with correlograph analysis to obtain the structural motif, can pin down structural correlations. We introduce the method of correlograph variance as a promising means of independently measuring the volume fraction of a paracrystalline composite. From comparisons with published data, we affirm that only a composite material of paracrystalline and continuous random network that is substantially paracrystalline could explain the existing experimental data, and point the way to more precise measurements on amorphous semiconductors. The results are of general interest for other classes of disordered materials.
Fluctuation microscopy analysis of amorphous silicon models

International Nuclear Information System (INIS)

Gibson, J.M.; Treacy, M.M.J.

2017-01-01

Highlights: • Studied competing computer models for amorphous silicon and simulated fluctuation microscopy data. • Show that only paracrystalline/random network composite can fit published data. • Specifically show that pure random network or random network with void models do not fit available data. • Identify a new means to measure volume fraction of ordered material. • Identify unreported limitations of the Debye model for simulating fluctuation microscopy data. - Abstract: Using computer-generated models we discuss the use of fluctuation electron microscopy (FEM) to identify the structure of amorphous silicon. We show that a combination of variable resolution FEM to measure the correlation length, with correlograph analysis to obtain the structural motif, can pin down structural correlations. We introduce the method of correlograph variance as a promising means of independently measuring the volume fraction of a paracrystalline composite. From comparisons with published data, we affirm that only a composite material of paracrystalline and continuous random network that is substantially paracrystalline could explain the existing experimental data, and point the way to more precise measurements on amorphous semiconductors. The results are of general interest for other classes of disordered materials.

Functional Connectivity with Distinct Neural Networks Tracks Fluctuations in Gain/Loss Framing Susceptibility

Science.gov (United States)

Smith, David V.; Sip, Kamila E.; Delgado, Mauricio R.

2016-01-01

Multiple large-scale neural networks orchestrate a wide range of cognitive processes. For example, interoceptive processes related to self-referential thinking have been linked to the default-mode network (DMN); whereas exteroceptive processes related to cognitive control have been linked to the executive-control network (ECN). Although the DMN and ECN have been postulated to exert opposing effects on cognition, it remains unclear how connectivity with these spatially overlapping networks contribute to fluctuations in behavior. While previous work has suggested the medial prefrontal cortex (MPFC) is involved in behavioral change following feedback, these observations could be linked to interoceptive processes tied to DMN or exteroceptive processes tied to ECN because MPFC is positioned in both networks. To address this problem, we employed independent component analysis combined with dual-regression functional connectivity analysis. Participants made a series of financial decisions framed as monetary gains or losses. In some sessions, participants received feedback from a peer observing their choices; in other sessions, feedback was not provided. Following feedback, framing susceptibility—indexed as the increase in gambling behavior in loss frames compared to gain frames—was heightened in some participants and diminished in others. We examined whether these individual differences were linked to differences in connectivity by contrasting sessions containing feedback against those that did not contain feedback. We found two key results. As framing susceptibility increased, the MPFC increased connectivity with DMN; in contrast, temporal-parietal junction decreased connectivity with the ECN. Our results highlight how functional connectivity patterns with distinct neural networks contribute to idiosyncratic behavioral changes. PMID:25858445
Automatic, time-interval traffic counts for recreation area management planning

Science.gov (United States)

D. L. Erickson; C. J. Liu; H. K. Cordell

1980-01-01

Automatic, time-interval recorders were used to count directional vehicular traffic on a multiple entry/exit road network in the Red River Gorge Geological Area, Daniel Boone National Forest. Hourly counts of entering and exiting traffic differed according to recorder location, but an aggregated distribution showed a delayed peak in exiting traffic thought to be...
Simplified management of ATM traffic

Science.gov (United States)

Luoma, Marko; Ilvesmaeki, Mika

1997-10-01

ATM has been under a thorough standardization process for more than ten years. Looking at it now, what have we achieved during this time period? Originally ATM was meant to be an easy and efficient protocol enabling varying services over a single network. What it is turning to be it `yet another ISDN'--network full of hopes and promises but too difficult to implement and expensive to market. The fact is that more and more `nice features' are implemented on the cost of overloading network with hard management procedures. Therefore we need to adopt a new approach. This approach keeps a strong reminder on `what is necessary.' This paper presents starting points for an alternative approach to the traffic management. We refer to this approach as `the minimum management principle.' Choosing of the suitable service classes for the ATM network is made difficult by the fact that the more services one implements the more management he needs. This is especially true for the variable bit rate connections that are usually treated based on the stochastic models. Stochastic model, at its best, can only reveal momentary characteristics in the traffic stream not the long range behavior of it. Our assumption is that ATM will move towards Internet in the sense that strict values for quality make little or no sense in the future. Therefore stochastic modeling of variable bit rate connections seems to be useless. Nevertheless we see that some traffic needs to have strict guarantees and that the only economic way of doing so is to use PCR allocation.
Adaptive Traffic Signal Control: Deep Reinforcement Learning Algorithm with Experience Replay and Target Network

OpenAIRE

Gao, Juntao; Shen, Yulong; Liu, Jia; Ito, Minoru; Shiratori, Norio

2017-01-01

Adaptive traffic signal control, which adjusts traffic signal timing according to real-time traffic, has been shown to be an effective method to reduce traffic congestion. Available works on adaptive traffic signal control make responsive traffic signal control decisions based on human-crafted features (e.g. vehicle queue length). However, human-crafted features are abstractions of raw traffic data (e.g., position and speed of vehicles), which ignore some useful traffic information and lead t...
Traffic control and intelligent vehicle highway systems: a survey

NARCIS (Netherlands)

Baskar, L.D.; Schutter, B. de; Hellendoorn, J.; Papp, Z.

2011-01-01

Traffic congestion in highway networks is one of the main issues to be addressed by today's traffic management schemes. Automation combined with the increasing market penetration of on-line communication, navigation and advanced driver assistance systems will ultimately result in intelligent vehicle
Metro manila transport and traffic management plan (1993-1998)

Energy Technology Data Exchange (ETDEWEB)

Cal, P.C.

1995-12-31

In 1988, former President Corazon Aquino created the Presidential Task Force on Traffic Management to formulate plans and programs to improve the traffic situation in Metro Manila and to address the emerging problem of air pollution and concern on renewable energy sources for transportation. The Task Force formulated the Metro Manila Traffic Improvement Plan (TRIP) which was approved by President Aquino for implementation. TRIP called for the development of a mass urban transport system, which included the expansion of the light rail transit system and the construction and improvement of the Metro Manila road network. Culled mainly from the TRIP proposals, the Updated Transport and Traffic Management Plan for Metro Manila (1993-1998) was developed through interagency discussions, public consultations, data collation and research work. This plan is directed towards the development of a more responsive public transport system, expansion of road network capacity, and improvement of traffic management and enforcement. Constraints may be present along the way but opportunities and potentials exist for the deliverance of daily commuters struggling to make a living.
Stability of synchrony against local intermittent fluctuations in tree-like power grids

Science.gov (United States)

Auer, Sabine; Hellmann, Frank; Krause, Marie; Kurths, Jürgen

2017-12-01

90% of all Renewable Energy Power in Germany is installed in tree-like distribution grids. Intermittent power fluctuations from such sources introduce new dynamics into the lower grid layers. At the same time, distributed resources will have to contribute to stabilize the grid against these fluctuations in the future. In this paper, we model a system of distributed resources as oscillators on a tree-like, lossy power grid and its ability to withstand desynchronization from localized intermittent renewable infeed. We find a remarkable interplay of the network structure and the position of the node at which the fluctuations are fed in. An important precondition for our findings is the presence of losses in distribution grids. Then, the most network central node splits the network into branches with different influence on network stability. Troublemakers, i.e., nodes at which fluctuations are especially exciting the grid, tend to be downstream branches with high net power outflow. For low coupling strength, we also find branches of nodes vulnerable to fluctuations anywhere in the network. These network regions can be predicted at high confidence using an eigenvector based network measure taking the turbulent nature of perturbations into account. While we focus here on tree-like networks, the observed effects also appear, albeit less pronounced, for weakly meshed grids. On the other hand, the observed effects disappear for lossless power grids often studied in the complex system literature.
Quantifying fluctuations in reversible enzymatic cycles and clocks

Science.gov (United States)

Wierenga, Harmen; ten Wolde, Pieter Rein; Becker, Nils B.

2018-04-01

Biochemical reactions are fundamentally noisy at a molecular scale. This limits the precision of reaction networks, but it also allows fluctuation measurements that may reveal the structure and dynamics of the underlying biochemical network. Here, we study nonequilibrium reaction cycles, such as the mechanochemical cycle of molecular motors, the phosphorylation cycle of circadian clock proteins, or the transition state cycle of enzymes. Fluctuations in such cycles may be measured using either of two classical definitions of the randomness parameter, which we show to be equivalent in general microscopically reversible cycles. We define a stochastic period for reversible cycles and present analytical solutions for its moments. Furthermore, we associate the two forms of the randomness parameter with the thermodynamic uncertainty relation, which sets limits on the timing precision of the cycle in terms of thermodynamic quantities. Our results should prove useful also for the study of temporal fluctuations in more general networks.
Modeling Erlang's Ideal Grading with Multirate BPP Traffic

Directory of Open Access Journals (Sweden)

Mariusz Glabowski

2012-01-01

Full Text Available This paper presents a complete methodology for modeling gradings (also called non-full-availability groups servicing single-service and multi-service traffic streams. The methodology worked out by the authors makes it possible to determine traffic characteristics of various types of gradings with state-dependent call arrival processes, including a new proposed structure of the Erlang’s Ideal Grading with the multirate links. The elaborated models of the gradings can be used for modeling different systems of modern networks, for example, the radio interfaces of the UMTS system, switching networks carrying a mixture of different multirate traffic streams, and video-on-demand systems. The results of the analytical calculations are compared with the results of the simulation data for selected gradings, which confirm high accuracy of the proposed methodology.
Enhancing traffic performance in hierarchical DHT system by exploiting network proximity

Science.gov (United States)

Zhong, Haifeng; Wu, Wei; Pei, Canhao; Zhang, Chengfeng

2009-08-01

Nowadays P2P systems have become increasingly popular for object distribution and file sharing, and the majority of Internet traffic is generated by P2P file sharing applications. However, those applications usually ignored the underlying proximity of physical nodes and regionalization of file accessing. As a result, they generate a large amount of unnecessary interdomain transit traffic and increase response latency. In this paper, we proposed a new traffic control approach to enhance p2p traffic locality and reduce the cross-group transfer. Using analysis, we show that the method substantially improves node transfer efficiency and significantly reduces file access latency compared with native P2P applications.
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.)
Epidemic metapopulation model with traffic routing in scale-free networks

International Nuclear Information System (INIS)

Huang, Wei; Chen, Shengyong

2011-01-01

In this paper, we propose a model incorporating both the traffic routing dynamics and the virus prevalence dynamics. In this model, each packet may be isolated from the network on its transporting path, which means that the packet cannot be successfully delivered to its destination. In contrast, a successful transport means that a packet can be delivered from source to destination without being isolated. The effects of model parameters on the delivery success rate and the delivery failure rate are intensively studied and analyzed. Several routing strategies are performed for our model. Results show that the shortest path routing strategy is the most effective for enhancing the delivery success rate, especially when each packet is only allowed to be delivered to the neighbor with the lowest degree along the shortest path. We also find that, by minimizing the sum of the nodes' degree along the transporting path, we can also obtain a satisfactory delivery success rate
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.
On the Design of Energy Efficient Optical Networks with Software Defined Networking Control Across Core and Access Networks

DEFF Research Database (Denmark)

Wang, Jiayuan; Yan, Ying; Dittmann, Lars

2013-01-01

This paper presents a Software Defined Networking (SDN) control plane based on an overlay GMPLS control model. The SDN control platform manages optical core networks (WDM/DWDM networks) and the associated access networks (GPON networks), which makes it possible to gather global information...... and enable wider areas' energy efficiency networking. The energy related information of the networks and the types of the traffic flows are collected and utilized for the end-to-end QoS provision. Dynamic network simulation results show that by applying different routing algorithms according to the type...... of traffic in the core networks, the energy efficiency of the network is improved without compromising the quality of service....
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.
MODELS OF AIR TRAFFIC CONTROLLERS ERRORS PREVENTION IN TERMINAL CONTROL AREAS UNDER UNCERTAINTY CONDITIONS

Directory of Open Access Journals (Sweden)

Volodymyr Kharchenko

2017-03-01

Full Text Available Purpose: the aim of this study is to research applied models of air traffic controllers’ errors prevention in terminal control areas (TMA under uncertainty conditions. In this work the theoretical framework descripting safety events and errors of air traffic controllers connected with the operations in TMA is proposed. Methods: optimisation of terminal control area formal description based on the Threat and Error management model and the TMA network model of air traffic flows. Results: the human factors variables associated with safety events in work of air traffic controllers under uncertainty conditions were obtained. The Threat and Error management model application principles to air traffic controller operations and the TMA network model of air traffic flows were proposed. Discussion: Information processing context for preventing air traffic controller errors, examples of threats in work of air traffic controllers, which are relevant for TMA operations under uncertainty conditions.
Phase transition in traffic jam experiment on a circuit

International Nuclear Information System (INIS)

Tadaki, Shin-ichi; Kikuchi, Macoto; Fukui, Minoru; Yosida, Taturu; Nakayama, Akihiro; Nishinari, Katsuhiro; Shibata, Akihiro; Sugiyama, Yuki; Yukawa, Satoshi

2013-01-01

The emergence of a traffic jam is considered to be a dynamical phase transition in a physics point of view; traffic flow becomes unstable and changes phase into a traffic jam when the car density exceeds a critical value. In order to verify this view, we have been performing a series of circuit experiments. In our previous work (2008 New J. Phys. 10 033001), we demonstrated that a traffic jam emerges even in the absence of bottlenecks at a certain high density. In this study, we performed a larger indoor circuit experiment in the Nagoya Dome in which the positions of cars were observed using a high-resolution laser scanner. Over a series of sessions at various values of density, we found that jammed flow occurred at high densities, whereas free flow was conserved at low densities. We also found indications of metastability at an intermediate density. The critical density is estimated by analyzing the fluctuations in speed and the density–flow relation. The value of this critical density is consistent with that observed on real expressways. This experiment provides strong support for physical interpretations of the emergence of traffic jams as a dynamical phase transition. (paper)
Phase transition in traffic jam experiment on a circuit

Science.gov (United States)

Tadaki, Shin-ichi; Kikuchi, Macoto; Fukui, Minoru; Nakayama, Akihiro; Nishinari, Katsuhiro; Shibata, Akihiro; Sugiyama, Yuki; Yosida, Taturu; Yukawa, Satoshi

2013-10-01

The emergence of a traffic jam is considered to be a dynamical phase transition in a physics point of view; traffic flow becomes unstable and changes phase into a traffic jam when the car density exceeds a critical value. In order to verify this view, we have been performing a series of circuit experiments. In our previous work (2008 New J. Phys. 10 033001), we demonstrated that a traffic jam emerges even in the absence of bottlenecks at a certain high density. In this study, we performed a larger indoor circuit experiment in the Nagoya Dome in which the positions of cars were observed using a high-resolution laser scanner. Over a series of sessions at various values of density, we found that jammed flow occurred at high densities, whereas free flow was conserved at low densities. We also found indications of metastability at an intermediate density. The critical density is estimated by analyzing the fluctuations in speed and the density-flow relation. The value of this critical density is consistent with that observed on real expressways. This experiment provides strong support for physical interpretations of the emergence of traffic jams as a dynamical phase transition.
Development and Evaluation of a Control System for Regional Traffic Management

Directory of Open Access Journals (Sweden)

John L. McLin

2011-01-01

Full Text Available Traffic congestion is a worsening problem in metropolitan areas which will require integrated regional traffic control systems to improve traffic conditions. This paper presents a regional traffic control system which can detect incident conditions and provide integrated traffic management during nonrecurrent congestion events. The system combines advanced artificial intelligence techniques with a traffic performance model based on HCM equations. Preliminary evaluation of the control system using traffic microsimulation demonstrates that it has the potential to improve system conditions during traffic incidents. In addition, several enhancements were identified which will make the system more robust in a real traffic control setting. An assessment of the control system elements indicates that there are no substantial technical barriers in implementing this system in a large traffic network.
Identifying MMORPG Bots: A Traffic Analysis Approach

Science.gov (United States)

Chen, Kuan-Ta; Jiang, Jhih-Wei; Huang, Polly; Chu, Hao-Hua; Lei, Chin-Laung; Chen, Wen-Chin

2008-12-01

Massively multiplayer online role playing games (MMORPGs) have become extremely popular among network gamers. Despite their success, one of MMORPG's greatest challenges is the increasing use of game bots, that is, autoplaying game clients. The use of game bots is considered unsportsmanlike and is therefore forbidden. To keep games in order, game police, played by actual human players, often patrol game zones and question suspicious players. This practice, however, is labor-intensive and ineffective. To address this problem, we analyze the traffic generated by human players versus game bots and propose general solutions to identify game bots. Taking Ragnarok Online as our subject, we study the traffic generated by human players and game bots. We find that their traffic is distinguishable by 1) the regularity in the release time of client commands, 2) the trend and magnitude of traffic burstiness in multiple time scales, and 3) the sensitivity to different network conditions. Based on these findings, we propose four strategies and two ensemble schemes to identify bots. Finally, we discuss the robustness of the proposed methods against countermeasures of bot developers, and consider a number of possible ways to manage the increasingly serious bot problem.

Identifying MMORPG Bots: A Traffic Analysis Approach

Directory of Open Access Journals (Sweden)

Wen-Chin Chen

2008-11-01

Full Text Available Massively multiplayer online role playing games (MMORPGs have become extremely popular among network gamers. Despite their success, one of MMORPG's greatest challenges is the increasing use of game bots, that is, autoplaying game clients. The use of game bots is considered unsportsmanlike and is therefore forbidden. To keep games in order, game police, played by actual human players, often patrol game zones and question suspicious players. This practice, however, is labor-intensive and ineffective. To address this problem, we analyze the traffic generated by human players versus game bots and propose general solutions to identify game bots. Taking Ragnarok Online as our subject, we study the traffic generated by human players and game bots. We find that their traffic is distinguishable by 1 the regularity in the release time of client commands, 2 the trend and magnitude of traffic burstiness in multiple time scales, and 3 the sensitivity to different network conditions. Based on these findings, we propose four strategies and two ensemble schemes to identify bots. Finally, we discuss the robustness of the proposed methods against countermeasures of bot developers, and consider a number of possible ways to manage the increasingly serious bot problem.
The Thouless-Anderson-Palmer equation for an analogue neural network with temporally fluctuating white synaptic noise

International Nuclear Information System (INIS)

Ichiki, Akihisa; Shiino, Masatoshi

2007-01-01

Effects of synaptic noise on the retrieval process of associative memory neural networks are studied from the viewpoint of neurobiological and biophysical understanding of information processing in the brain. We investigate the statistical mechanical properties of stochastic analogue neural networks with temporally fluctuating synaptic noise, which is assumed to be white noise. Such networks, in general, defy the use of the replica method, since they have no energy concept. The self-consistent signal-to-noise analysis (SCSNA), which is an alternative to the replica method for deriving a set of order parameter equations, requires no energy concept and thus becomes available in studying networks without energy functions. Applying the SCSNA to stochastic networks requires the knowledge of the Thouless-Anderson-Palmer (TAP) equation which defines the deterministic networks equivalent to the original stochastic ones. The study of the TAP equation which is of particular interest for the case without energy concept is very less, while it is closely related to the SCSNA in the case with energy concept. This paper aims to derive the TAP equation for networks with synaptic noise together with a set of order parameter equations by a hybrid use of the cavity method and the SCSNA
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.
Locating replenishment stations for electric vehicles: Application to Danish traffic data

DEFF Research Database (Denmark)

Wen, Min; Laporte, Gilbert; Madsen, Oli B.G.

2012-01-01

for electric vehicles on a traffic network with flow-based demand. The objective is to optimize the network performance, for example to maximize the flow covered by a prefixed number of stations, or to minimize the number of stations needed to cover traffic flows. Two mixed integer linear programming......Environment-friendly electric vehicles have gained substantial attention in governments, industry and universities. The deployment of a network of recharging stations is essential given their limited travel range. This paper considers the problem of locating electronic replenishment stations...
Serial Network Flow Monitor

Science.gov (United States)

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

2009-01-01

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

Directory of Open Access Journals (Sweden)

Ming Li

2012-01-01

Full Text Available Reliable distinguishing DDOS flood traffic from aggregated traffic is desperately desired by reliable prevention of DDOS attacks. By reliable distinguishing, we mean that flood traffic can be distinguished from aggregated one for a predetermined probability. The basis to reliably distinguish flood traffic from aggregated one is reliable detection of signs of DDOS flood attacks. As is known, reliably distinguishing DDOS flood traffic from aggregated traffic becomes a tough task mainly due to the effects of flash-crowd traffic. For this reason, this paper studies reliable detection in the underlying DiffServ network to use static-priority schedulers. In this network environment, we present a method for reliable detection of signs of DDOS flood attacks for a given class with a given priority. There are two assumptions introduced in this study. One is that flash-crowd traffic does not have all priorities but some. The other is that attack traffic has all priorities in all classes, otherwise an attacker cannot completely achieve its DDOS goal. Further, we suppose that the protected site is equipped with a sensor that has a signature library of the legitimate traffic with the priorities flash-crowd traffic does not have. Based on those, we are able to reliably distinguish attack traffic from aggregated traffic with the priorities that flash-crowd traffic does not have according to a given detection probability.
Analysis of jitter due to call-level fluctuations

NARCIS (Netherlands)

M.R.H. Mandjes (Michel)

2005-01-01

textabstractIn communication networks used by constant bit rate applications, call-level dynamics (i.e., entering and leaving calls) lead to fluctuations in the load, and therefore also fluctuations in the delay (jitter). By intentionally delaying the packets at the destination, one can transform
Environment Aware Cellular Networks

KAUST Repository

Ghazzai, Hakim

2015-02-01

The unprecedented rise of mobile user demand over the years have led to an enormous growth of the energy consumption of wireless networks as well as the greenhouse gas emissions which are estimated currently to be around 70 million tons per year. This significant growth of energy consumption impels network companies to pay huge bills which represent around half of their operating expenditures. Therefore, many service providers, including mobile operators, are looking for new and modern green solutions to help reduce their expenses as well as the level of their CO2 emissions. Base stations are the most power greedy element in cellular networks: they drain around 80% of the total network energy consumption even during low traffic periods. Thus, there is a growing need to develop more energy-efficient techniques to enhance the green performance of future 4G/5G cellular networks. Due to the problem of traffic load fluctuations in cellular networks during different periods of the day and between different areas (shopping or business districts and residential areas), the base station sleeping strategy has been one of the main popular research topics in green communications. In this presentation, we present several practical green techniques that provide significant gains for mobile operators. Indeed, combined with the base station sleeping strategy, these techniques achieve not only a minimization of the fossil fuel consumption but also an enhancement of mobile operator profits. We start with an optimized cell planning method that considers varying spatial and temporal user densities. We then use the optimal transport theory in order to define the cell boundaries such that the network total transmit power is reduced. Afterwards, we exploit the features of the modern electrical grid, the smart grid, as a new tool of power management for cellular networks and we optimize the energy procurement from multiple energy retailers characterized by different prices and pollutant
Analysis of Traffic Noise along Oyemekun - Oba-Adesida Road Akure Ondo State Nigeria

Directory of Open Access Journals (Sweden)

O. J Oyedepo

2013-03-01

Full Text Available The primary aim of the research is to quantify and analyze the traffic noise emissions along Oba-Adesida –Oyemekun Road. Measurements of noise were recorded in decibel (dBA using digital sound level meters (IEC651 Type 2. While, the traffic volume and spot speed were obtained using cine –camera at six selected locations namely Alagbaka(L1, Biological Garden(L2, Adegbola(L3, Ondo Bye Pass(L4, Ilesha Garage(L5 and FUTA junction(L6 along ObaAdesida- Oyemekun road during the peak period(7:30am -8:30 am & 4:00pm-5:00pm and off peak period(11:30pm- 12:30pm, repeated 3-5 times to account for time-fluctuation of these variables. All measurements were taken on a weighting frequency network, at a height of about 1.5m from the ground level. The vehicles were divided into five categories namely Cars, buses, motorcycles,2-axle load, and 3-axle loads; and were converted into “Passenger Car Units” (PCU by multiplying with recommended factors in accordance with Nigerian Federal Highway Capacity Manual 2006.The average L10(dBA are 72.8, 73.8, 73.4, 74.4, 73.9, and 75.0dBA ; while average combine sound pressure level(SPL in dBA are 76, 77, 78, 78, 77, and 78dBA for L1, L2, L3, L4, L5,and L6 respectively. Findings indicated that traffic generated noise pollution is at or above, the standard outdoor limits in most locations and area can adversely affect the welfare activities. The present study revealed that the study area is getting noisier due to high traffic density and lack of traffic management, practical action to limit and control the exposure to environmental noise are essential. However, road traffic noise by treatments at source (such as to reduce engine noise, exhaust pipe noise etc. is to be encouraged as the principal method of control. The techniques include road design, the management of traffic flow and the use of screens and barriers.
Resistive transition of superconducting-wire networks. Influence of pinning and fluctuations

International Nuclear Information System (INIS)

Giroud, M.; Buisson, O.; Wang, Y.Y.; Pannetier, B.; Mailly, D.

1992-01-01

The authors studied the resistive transition of several 2-D superconducting-wire networks of various coupling strengths, which they characterize in terms of the Kosterlitz-Thouless transition temperature and the ratio ξ/a of the coherence length to the array period. In the extreme strong-coupling limit where the mesh size is of the order of the zero-temperature coherence length, the superconducting behavior is well described by the mean-field properties of the superconducting wave function. Extending to 2-D array, the 1-D phase-slippage model explains the dissipative regime observed above the Ginzburg-Landau depairing critical current. On the other hand, when the coupling is weak, phase fluctuations below the Ginzburg-Landau transition and vortex depinning dominate the resistive behavior. An activated dissipation is observed even below the depairing critical current. Results obtained in this regime for critical temperature, magnetoresistance, or critical current versus temperature, and magnetic field are shown; their periodic oscillations are discussed in terms of depinning of vortices on the array. A simple periodic pinning potential for a vortex in a wire network is calculated, and compared with the case of pinning in Josephson junction arrays. It is shown that this model explains qualitatively the experimental results observed for small ξ/a
Distributed traffic signal control using fuzzy logic

Science.gov (United States)

Chiu, Stephen

1992-01-01

We present a distributed approach to traffic signal control, where the signal timing parameters at a given intersection are adjusted as functions of the local traffic condition and of the signal timing parameters at adjacent intersections. Thus, the signal timing parameters evolve dynamically using only local information to improve traffic flow. This distributed approach provides for a fault-tolerant, highly responsive traffic management system. The signal timing at an intersection is defined by three parameters: cycle time, phase split, and offset. We use fuzzy decision rules to adjust these three parameters based only on local information. The amount of change in the timing parameters during each cycle is limited to a small fraction of the current parameters to ensure smooth transition. We show the effectiveness of this method through simulation of the traffic flow in a network of controlled intersections.
Understanding the T2 traffic in CMS during Run-1

CERN Document Server

T, Wildish

2015-01-01

In the run-up to Run-1 CMS was operating its facilities according to the MONARC model, where data-transfers were strictly hierarchical in nature. Direct transfers between Tier-2 nodes was excluded, being perceived as operationally intensive and risky in an era where the network was expected to be a major source of errors. By the end of Run-1 wide-area networks were more capable and stable than originally anticipated. The original data-placement model was relaxed, and traffic was allowed between Tier-2 nodes.Tier-2 to Tier-2 traffic in 2012 already exceeded the amount of Tier-2 to Tier-1 traffic, so it clearly has the potential to become important in the future. Moreover, while Tier-2 to Tier-1 traffic is mostly upload of Monte Carlo data, the Tier-2 to Tier-2 traffic represents data moved in direct response to requests from the physics analysis community. As such, problems or delays there are more likely to have a direct impact on the user community.Tier-2 to Tier-2 traffic may also traverse parts of the WAN ...
PERFORMANCE ANALYSIS OF IPv4 AND IPv6 INTERNET TRAFFIC

Directory of Open Access Journals (Sweden)

Rupesh Jaiswal

2015-12-01

Full Text Available The gigantic growth of the internet communication technology has illustrated its value and benefits to private businesses, government organizations, worldwide professionals, academic institutes and individuals over the past few years. The size and range of computing devices connected to the internet, substantially increased because of IPv6 and offers the potential to establish a much more powerful internet compared to the IPv4. IPV6 developed by the IETF to deal with a shortage of IP addresses under IPv4. New features of IPv6 enhance packet processing speeds over routers, switches and end systems. These improved features will have different traffic characteristics than IPv4. The internet traffic which was earlier assumed as Poisson is now shown to have fractal characteristics as; heavy tailedness, self-similarity and long range dependency. Internet traffic showing above characteristics are found to have burstiness at multiple timescales. This behavior impacts network performance and degrades it substantially. It also increases complexity for network design and create difficulties to maintain desired QoS. IPv4 traffic has been well established as self-similar traffic. Nowadays, IPv6 forming a larger share of the internet traffic and it is pivotal to asses IPv6 with regards to fractal behavior. This will enable network designers to do necessary changes in the existing network to reconcile with IPv6. In this paper we compared IPv4 and IPv6 with respect to fractal behavioral characteristics. It is found that IPv6 shows higher degree of heavy tailedness, higher values of Hurst parameter values, higher fractal dimension values i.e. it is more self-similar, greater autocorrelation achieved even at larger lag and thus showing more burstiness.
THE METHODS OF TRAFFIC ENGINEERING’S OPTIMIZATION IN CASE OF DATA TRANSFER BY TWO ROUTS

Directory of Open Access Journals (Sweden)

Vera Petrovna Khoborova

2018-05-01

Full Text Available To prevent congestion in certain sections of multi-service networks, data flow management, which leads to a more proportional distribution of resources and improved network functioning, is implemented. The task of selecting routes for individual data streams (traffic class, taking into account requirements of QoS, is solved by the methods of traffic engineering. With the help of these methods, it is strived to load all the network resources maximally and balanced, so that the network, with a given level of service quality, has high total capacity as much as possible. However, at the present time, there are no rigorous well-founded solutions for the problem of distributing data flows between the selected routes, taking into account the possibility of additional control over their capacity. The article proposes a method for optimizing the distribution of data flows and the bandwidth of the channels (routes used in each separate information direction, with different coordination of control actions at adjacent levels of the network architecture. We consider scientific and technical proposals for the implementation of the developed method as part of the mechanisms that implement the traffic engineering in modern multiservice networks. Purpose: increasing the efficiency of the multiservice network by optimizing the traffic engineering. Methodology in article analytical methods for solving optimization problems with a non-linear objective function and linear constraints are used. Results: analytical expressions were obtained for the optimal distribution of data flows and bandwidth of the used channels, which provides the minimum values of delay indicators, and the use of these expressions in calculations in the mechanisms of traffic engineering was suggested. Practical implications: the obtained results should be used in modern multiservice networks, which are implemented data flow management through the traffic engineering in order to improve the
Application of Internet in Road Traffic Engineering

Directory of Open Access Journals (Sweden)

Ivan Dadić

2012-10-01

Full Text Available The paper deals with the implementation of Internet in trafficengineering with the purpose of improving the professionaland scientific research development of the traffic system in theRepublic of Croatia.Fast growth of the world computer network, Internet, andits applications in almost all the fields of human activities,change the picture of the modern world. The current exchangeof data in all their forms and the daily growth of the network,supplemented by almost incredible amounts of data that can bealmost instantly accessible, indicates that Internet is not just theinfomwtion technology revolution, but that it is a revolutionper se. More than 100 million computers are estimated to benetworked beginning of the 21" century.Internet seems almost as if it were created for the purposesof knowledge and expe1ience exchange in traffic, a relativelyyoung scientific branch. 11 can be concluded that the presenceof traffic engineers in Internet is today's reality and tomon·ow'snecessity.
Roads at risk: traffic detours from debris flows in southern Norway

Science.gov (United States)

Meyer, N. K.; Schwanghart, W.; Korup, O.; Nadim, F.

2015-05-01

Globalisation and interregional exchange of people, goods, and services has boosted the importance of and reliance on all kinds of transport networks. The linear structure of road networks is especially sensitive to natural hazards. In southern Norway, steep topography and extreme weather events promote frequent traffic disruption caused by debris flows. Topographic susceptibility and trigger frequency maps serve as input into a hazard appraisal at the scale of first-order catchments to quantify the impact of debris flows on the road network in terms of a failure likelihood of each link connecting two network vertices, e.g. road junctions. We compute total additional traffic loads as a function of traffic volume and excess distance, i.e. the extra length of an alternative path connecting two previously disrupted network vertices using a shortest-path algorithm. Our risk metric of link failure is the total additional annual traffic load, expressed as vehicle kilometres, because of debris-flow-related road closures. We present two scenarios demonstrating the impact of debris flows on the road network and quantify the associated path-failure likelihood between major cities in southern Norway. The scenarios indicate that major routes crossing the central and north-western part of the study area are associated with high link-failure risk. Yet options for detours on major routes are manifold and incur only little additional costs provided that drivers are sufficiently well informed about road closures. Our risk estimates may be of importance to road network managers and transport companies relying on speedy delivery of services and goods.
Call Admission Scheme for Multidimensional Traffic Assuming Finite Handoff User

Directory of Open Access Journals (Sweden)

Md. Baitul Al Sadi

2017-01-01

Full Text Available Usually, the number of users within a cell in a mobile cellular network is considered infinite; hence, M/M/n/k model is appropriate for new originated traffic, but the number of ongoing calls around a cell is always finite. Hence, the traffic model of handoff call will be M/M/n/k/N. In this paper, a K-dimensional traffic model of a mobile cellular network is proposed using the combination of limited and unlimited users case. A new call admission scheme (CAS is proposed based on both thinning scheme and fading condition. The fading condition of the wireless channel access to a handoff call is prioritized compared to newly originated calls.
Leveraging spatial abstraction in traffic analysis and forecasting with visual analytics

OpenAIRE

Andrienko, N.; Andrienko, G.; Rinzivillo, S.

2016-01-01

A spatially abstracted transportation network is a graph where nodes are territory compartments (areas in geographic space) and edges, or links, are abstract constructs, each link representing all possible paths between two neighboring areas. By applying visual analytics techniques to vehicle traffic data from different territories, we discovered that the traffic intensity (a.k.a. traffic flow or traffic flux) and the mean velocity are interrelated in a spatially abstracted transportation net...
Measurements and modelling of base station power consumption under real traffic loads.

Science.gov (United States)

Lorincz, Josip; Garma, Tonko; Petrovic, Goran

2012-01-01

Base stations represent the main contributor to the energy consumption of a mobile cellular network. Since traffic load in mobile networks significantly varies during a working or weekend day, it is important to quantify the influence of these variations on the base station power consumption. Therefore, this paper investigates changes in the instantaneous power consumption of GSM (Global System for Mobile Communications) and UMTS (Universal Mobile Telecommunications System) base stations according to their respective traffic load. The real data in terms of the power consumption and traffic load have been obtained from continuous measurements performed on a fully operated base station site. Measurements show the existence of a direct relationship between base station traffic load and power consumption. According to this relationship, we develop a linear power consumption model for base stations of both technologies. This paper also gives an overview of the most important concepts which are being proposed to make cellular networks more energy-efficient.

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