Directional virtual backbone based data aggregation scheme for Wireless Visual Sensor Networks.

PubMed

Zhang, Jing; Liu, Shi-Jian; Tsai, Pei-Wei; Zou, Fu-Min; Ji, Xiao-Rong

2018-01-01

Data gathering is a fundamental task in Wireless Visual Sensor Networks (WVSNs). Features of directional antennas and the visual data make WVSNs more complex than the conventional Wireless Sensor Network (WSN). The virtual backbone is a technique, which is capable of constructing clusters. The version associating with the aggregation operation is also referred to as the virtual backbone tree. In most of the existing literature, the main focus is on the efficiency brought by the construction of clusters that the existing methods neglect local-balance problems in general. To fill up this gap, Directional Virtual Backbone based Data Aggregation Scheme (DVBDAS) for the WVSNs is proposed in this paper. In addition, a measurement called the energy consumption density is proposed for evaluating the adequacy of results in the cluster-based construction problems. Moreover, the directional virtual backbone construction scheme is proposed by considering the local-balanced factor. Furthermore, the associated network coding mechanism is utilized to construct DVBDAS. Finally, both the theoretical analysis of the proposed DVBDAS and the simulations are given for evaluating the performance. The experimental results prove that the proposed DVBDAS achieves higher performance in terms of both the energy preservation and the network lifetime extension than the existing methods.

Network traffic anomaly prediction using Artificial Neural Network

NASA Astrophysics Data System (ADS)

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.

Predicting Information Flows in Network Traffic.

ERIC Educational Resources Information Center

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)

Transition Characteristic Analysis of Traffic Evolution Process for Urban Traffic Network

PubMed Central

Chen, Hong; Li, Yang

2014-01-01

The characterization of the dynamics of traffic states remains fundamental to seeking for the solutions of diverse traffic problems. To gain more insights into traffic dynamics in the temporal domain, this paper explored temporal characteristics and distinct regularity in the traffic evolution process of urban traffic network. We defined traffic state pattern through clustering multidimensional traffic time series using self-organizing maps and construct a pattern transition network model that is appropriate for representing and analyzing the evolution progress. The methodology is illustrated by an application to data flow rate of multiple road sections from Network of Shenzhen's Nanshan District, China. Analysis and numerical results demonstrated that the methodology permits extracting many useful traffic transition characteristics including stability, preference, activity, and attractiveness. In addition, more information about the relationships between these characteristics was extracted, which should be helpful in understanding the complex behavior of the temporal evolution features of traffic patterns. PMID:24982969

Spatiotemporal Recurrent Convolutional Networks for Traffic Prediction in Transportation Networks

PubMed Central

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

2017-01-01

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

Spatiotemporal Recurrent Convolutional Networks for Traffic Prediction in Transportation Networks.

PubMed

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.

Traffic Management for Satellite-ATM Networks

NASA Technical Reports Server (NTRS)

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

1998-01-01

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

Traffic placement policies for a multi-band network

NASA Technical Reports Server (NTRS)

Maly, Kurt J.; Foudriat, E. C.; Game, David; Mukkamala, R.; Overstreet, C. Michael

1990-01-01

Recently protocols were introduced that enable the integration of synchronous traffic (voice or video) and asynchronous traffic (data) and extend the size of local area networks without loss in speed or capacity. One of these is DRAMA, a multiband protocol based on broadband technology. It provides dynamic allocation of bandwidth among clusters of nodes in the total network. A number of traffic placement policies for such networks are proposed and evaluated. Metrics used for performance evaluation include average network access delay, degree of fairness of access among the nodes, and network throughput. The feasibility of the DRAMA protocol is established through simulation studies. DRAMA provides effective integration of synchronous and asychronous traffic due to its ability to separate traffic types. Under the suggested traffic placement policies, the DRAMA protocol is shown to handle diverse loads, mixes of traffic types, and numbers of nodes, as well as modifications to the network structure and momentary traffic overloads.

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

NASA Astrophysics Data System (ADS)

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.

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

NASA Astrophysics Data System (ADS)

Yang, Bin

2017-07-01

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

Congestion control strategy on complex network with privilege traffic

NASA Astrophysics Data System (ADS)

Li, Shi-Bao; He, Ya; Liu, Jian-Hang; Zhang, Zhi-Gang; Huang, Jun-Wei

The congestion control of traffic is one of the most important studies in complex networks. In the previous congestion algorithms, all the network traffic is assumed to have the same priority, and the privilege of traffic is ignored. In this paper, a privilege and common traffic congestion control routing strategy (PCR) based on the different priority of traffic is proposed, which can be devised to cope with the different traffic congestion situations. We introduce the concept of privilege traffic in traffic dynamics for the first time and construct a new traffic model which taking into account requirements with different priorities. Besides, a new factor Ui is introduced by the theoretical derivation to characterize the interaction between different traffic routing selection, furthermore, Ui is related to the network throughput. Since the joint optimization among different kinds of traffic is accomplished by PCR, the maximum value of Ui can be significantly reduced and the network performance can be improved observably. The simulation results indicate that the network throughput with PCR has a better performance than the other strategies. Moreover, the network capacity is improved by 25% at least. Additionally, the network throughput is also influenced by privilege traffic number and traffic priority.

Minimal-delay traffic grooming for WDM star networks

NASA Astrophysics Data System (ADS)

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

NASA Astrophysics Data System (ADS)

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.

A framework to find the logic backbone of a biological network.

PubMed

Maheshwari, Parul; Albert, Réka

2017-12-06

Cellular behaviors are governed by interaction networks among biomolecules, for example gene regulatory and signal transduction networks. An often used dynamic modeling framework for these networks, Boolean modeling, can obtain their attractors (which correspond to cell types and behaviors) and their trajectories from an initial state (e.g. a resting state) to the attractors, for example in response to an external signal. The existing methods however do not elucidate the causal relationships between distant nodes in the network. In this work, we propose a simple logic framework, based on categorizing causal relationships as sufficient or necessary, as a complement to Boolean networks. We identify and explore the properties of complex subnetworks that are distillable into a single logic relationship. We also identify cyclic subnetworks that ensure the stabilization of the state of participating nodes regardless of the rest of the network. We identify the logic backbone of biomolecular networks, consisting of external signals, self-sustaining cyclic subnetworks (stable motifs), and output nodes. Furthermore, we use the logic framework to identify crucial nodes whose override can drive the system from one steady state to another. We apply these techniques to two biological networks: the epithelial-to-mesenchymal transition network corresponding to a developmental process exploited in tumor invasion, and the network of abscisic acid induced stomatal closure in plants. We find interesting subnetworks with logical implications in these networks. Using these subgraphs and motifs, we efficiently reduce both networks to succinct backbone structures. The logic representation identifies the causal relationships between distant nodes and subnetworks. This knowledge can form the basis of network control or used in the reverse engineering of networks.

Traffic Profiling in Wireless Sensor Networks

DTIC Science & Technology

2006-12-01

components, that can be used for traffic profiling and monitoring of a wireless sensor network . The work demostrates how the IDS should capture and...observed and analyzed. Finally, initial indications from basic analysis of wireless sensor network traffic demonstrated a high degree of self-similarity.

Traffic Driven Analysis of Cellular and WiFi Networks

ERIC Educational Resources Information Center

Paul, Utpal Kumar

2012-01-01

Since the days Internet traffic proliferated, measurement, monitoring and analysis of network traffic have been critical to not only the basic understanding of large networks, but also to seek improvements in resource management, traffic engineering and security. At the current times traffic in wireless local and wide area networks are facing…

Nonuniform traffic spots (NUTS) in multistage interconnection networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lang, T.; Kurisaki, L.

1990-09-01

The performance of multistage interconnection networks for multiprocessors is degraded when the traffic pattern produces nonuniform congestion in the blocking switches, that is, when there exist nonuniform traffic spots. For some specific patterns the authors evaluate this degradation in performance and propose modifications to the network organization and operation to reduce the degradation. Successful modifications are the use of diverting switches and the extension of the network with additional links. The use of these modifications makes the network more effective for a larger variety of traffic patterns. The authors also consider the case in which the network carries the superpositionmore » of two types of traffic. One type is the high throughput data and instruction traffic, while the other consists of control and I/O packets which are of low throughput but have severe real-time constraints. The authors conclude that diverting switches and networks with additional links are also suitable for assuring low latency for the real-time traffic, especially when using the displacing mode.« less

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

PubMed Central

Artuñedo, Antonio; del Toro, Raúl M.; Haber, Rodolfo E.

2017-01-01

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. PMID:28445398

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

PubMed

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.

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

PubMed

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.

Fine-granularity inference and estimations to network traffic for SDN

PubMed Central

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. PMID:29718913

Network Traffic Generator for Low-rate Small Network Equipment Software

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lanzisera, Steven

2013-05-28

Application that uses the Python low-level socket interface to pass network traffic between devices on the local side of a NAT router and the WAN side of the NAT router. This application is designed to generate traffic that complies with the Energy Star Small Network Equipment Test Method.

Network traffic behaviour near phase transition point

NASA Astrophysics Data System (ADS)

Lawniczak, A. T.; Tang, X.

2006-03-01

We explore packet traffic dynamics in a data network model near phase transition point from free flow to congestion. The model of data network is an abstraction of the Network Layer of the OSI (Open Systems Interconnect) Reference Model of packet switching networks. The Network Layer is responsible for routing packets across the network from their sources to their destinations and for control of congestion in data networks. Using the model we investigate spatio-temporal packets traffic dynamics near the phase transition point for various network connection topologies, and static and adaptive routing algorithms. We present selected simulation results and analyze them.

An efficient coordination protocol for wireless sensor networks

NASA Astrophysics Data System (ADS)

Paruchuri, Vamsi; Durresi, Arjan; Durresi, Mimoza; Barolli, Leonard

2005-10-01

Backbones infrastructures in wireless sensor networks reduce the communication overhead and energy consumption. In this paper, we present BackBone Routing (BBR), a fully distributed protocol for construction and rotation of backbone networks. BBR reduces energy consumption without significantly diminishing the capacity or connectivity of the network. Another key feature of BBR is its energy balancing nature by distributing the role of being Backbone Node among all the nodes. BBR builds on the observation that when a region of a shared-channel wireless network has a sufficient density of nodes, only a small number of them need be on at any time to forward traffic for active connections. Improvement in system lifetime due to BBR increases as the ratio of idle-to-sleep energy consumption increases, and increases as the density of the network increases. Our experiments show that BBR is more efficient in saving energy and extending network life without deteriorating network performance when compared with geographical shortest path routing.

Sonification of network traffic flow for monitoring and situational awareness

PubMed Central

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.

PubMed

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.

Effects of traffic generation patterns on the robustness of complex networks

NASA Astrophysics Data System (ADS)

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.

PubMed

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.

Forecasting short-term data center network traffic load with convolutional neural networks

PubMed Central

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

Queuing theory models for computer networks

NASA Technical Reports Server (NTRS)

Galant, David C.

1989-01-01

A set of simple queuing theory models which can model the average response of a network of computers to a given traffic load has been implemented using a spreadsheet. The impact of variations in traffic patterns and intensities, channel capacities, and message protocols can be assessed using them because of the lack of fine detail in the network traffic rates, traffic patterns, and the hardware used to implement the networks. A sample use of the models applied to a realistic problem is included in appendix A. Appendix B provides a glossary of terms used in this paper. This Ames Research Center computer communication network is an evolving network of local area networks (LANs) connected via gateways and high-speed backbone communication channels. Intelligent planning of expansion and improvement requires understanding the behavior of the individual LANs as well as the collection of networks as a whole.

Using OpenSSH to secure mobile LAN network traffic

NASA Astrophysics Data System (ADS)

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.

Design of real-time voice over internet protocol system under bandwidth network

NASA Astrophysics Data System (ADS)

Zhang, Li; Gong, Lina

2017-04-01

With the increasing bandwidth of the network and network convergence accelerating, VoIP means of communication across the network is becoming increasingly popular phenomenon. The real-time identification and analysis for VOIP flow over backbone network become the urgent needs and research hotspot of network operations management. Based on this, the paper proposes a VoIP business management system over backbone network. The system first filters VoIP data stream over backbone network and further resolves the call signaling information and media voice. The system can also be able to design appropriate rules to complete real-time reduction and presentation of specific categories of calls. Experimental results show that the system can parse and process real-time backbone of the VoIP call, and the results are presented accurately in the management interface, VoIP-based network traffic management and maintenance provide the necessary technical support.

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

PubMed

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.

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

PubMed Central

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

2017-01-01

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. PMID:28394270

Relationship between microscopic dynamics in traffic flow and complexity in networks.

PubMed

Li, Xin-Gang; Gao, Zi-You; Li, Ke-Ping; Zhao, Xiao-Mei

2007-07-01

Complex networks are constructed in the evolution process of traffic flow, and the states of traffic flow are represented by nodes in the network. The traffic dynamics can then be studied by investigating the statistical properties of those networks. According to Kerner's three-phase theory, there are two different phases in congested traffic, synchronized flow and wide moving jam. In the framework of this theory, we study different properties of synchronized flow and moving jam in relation to complex network. Scale-free network is constructed in stop-and-go traffic, i.e., a sequence of moving jams [Chin. Phys. Lett. 10, 2711 (2005)]. In this work, the networks generated in synchronized flow are investigated in detail. Simulation results show that the degree distribution of the networks constructed in synchronized flow has two power law regions, so the distinction in topological structure can really reflect the different dynamics in traffic flow. Furthermore, the real traffic data are investigated by this method, and the results are consistent with the simulations.

Price of anarchy on heterogeneous traffic-flow networks.

PubMed

Rose, A; O'Dea, R; Hopcraft, K I

2016-09-01

The efficiency of routing traffic through a network, comprising nodes connected by links whose cost of traversal is either fixed or varies in proportion to volume of usage, can be measured by the "price of anarchy." This is the ratio of the cost incurred by agents who act to minimize their individual expenditure to the optimal cost borne by the entire system. As the total traffic load and the network variability-parameterized by the proportion of variable-cost links in the network-changes, the behaviors that the system presents can be understood with the introduction of a network of simpler structure. This is constructed from classes of nonoverlapping paths connecting source to destination nodes that are characterized by the number of variable-cost edges they contain. It is shown that localized peaks in the price of anarchy occur at critical traffic volumes at which it becomes beneficial to exploit ostensibly more expensive paths as the network becomes more congested. Simulation results verifying these findings are presented for the variation of the price of anarchy with the network's size, aspect ratio, variability, and traffic load.

Rethinking Traffic Management: Design of Optimizable Networks

DTIC Science & Technology

2008-06-01

Though this paper used optimization theory to design and analyze DaVinci , op- timization theory is one of many possible tools to enable a grounded...dynamically allocate bandwidth shares. The distributed protocols can be implemented using DaVinci : Dynamically Adaptive VIrtual Networks for a Customized...Internet. In DaVinci , each virtual network runs traffic-management protocols optimized for a traffic class, and link bandwidth is dynamically allocated

Cooperative Learning for Distributed In-Network Traffic Classification

NASA Astrophysics Data System (ADS)

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.

Surveying traffic congestion based on the concept of community structure of complex networks

NASA Astrophysics Data System (ADS)

Ma, Lili; Zhang, Zhanli; Li, Meng

2016-07-01

In this paper, taking the traffic of Beijing city as an instance, we study city traffic states, especially traffic congestion, based on the concept of network community structure. Concretely, using the floating car data (FCD) information of vehicles gained from the intelligent transport system (ITS) of the city, we construct a new traffic network model which is with floating cars as network nodes and time-varying. It shows that this traffic network has Gaussian degree distributions at different time points. Furthermore, compared with free traffic situations, our simulations show that the traffic network generally has more obvious community structures with larger values of network fitness for congested traffic situations, and through the GPSspg web page, we show that all of our results are consistent with the reality. Then, it indicates that network community structure should be an available way for investigating city traffic congestion problems.

Price of anarchy on heterogeneous traffic-flow networks

NASA Astrophysics Data System (ADS)

Rose, A.; O'Dea, R.; Hopcraft, K. I.

2016-09-01

The efficiency of routing traffic through a network, comprising nodes connected by links whose cost of traversal is either fixed or varies in proportion to volume of usage, can be measured by the "price of anarchy." This is the ratio of the cost incurred by agents who act to minimize their individual expenditure to the optimal cost borne by the entire system. As the total traffic load and the network variability—parameterized by the proportion of variable-cost links in the network—changes, the behaviors that the system presents can be understood with the introduction of a network of simpler structure. This is constructed from classes of nonoverlapping paths connecting source to destination nodes that are characterized by the number of variable-cost edges they contain. It is shown that localized peaks in the price of anarchy occur at critical traffic volumes at which it becomes beneficial to exploit ostensibly more expensive paths as the network becomes more congested. Simulation results verifying these findings are presented for the variation of the price of anarchy with the network's size, aspect ratio, variability, and traffic load.

Capacity-constrained traffic assignment in networks with residual queues

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lam, W.H.K.; Zhang, Y.

2000-04-01

This paper proposes a capacity-constrained traffic assignment model for strategic transport planning in which the steady-state user equilibrium principle is extended for road networks with residual queues. Therefore, the road-exit capacity and the queuing effects can be incorporated into the strategic transport model for traffic forecasting. The proposed model is applicable to the congested network particularly when the traffic demands exceeds the capacity of the network during the peak period. An efficient solution method is proposed for solving the steady-state traffic assignment problem with residual queues. Then a simple numerical example is employed to demonstrate the application of the proposedmore » model and solution method, while an example of a medium-sized arterial highway network in Sioux Falls, South Dakota, is used to test the applicability of the proposed solution to real problems.« less

Behavioral Profiling of Scada Network Traffic Using Machine Learning Algorithms

DTIC Science & Technology

2014-03-27

BEHAVIORAL PROFILING OF SCADA NETWORK TRAFFIC USING MACHINE LEARNING ALGORITHMS THESIS Jessica R. Werling, Captain, USAF AFIT-ENG-14-M-81 DEPARTMENT...subject to copyright protection in the United States. AFIT-ENG-14-M-81 BEHAVIORAL PROFILING OF SCADA NETWORK TRAFFIC USING MACHINE LEARNING ...AFIT-ENG-14-M-81 BEHAVIORAL PROFILING OF SCADA NETWORK TRAFFIC USING MACHINE LEARNING ALGORITHMS Jessica R. Werling, B.S.C.S. Captain, USAF Approved

High-cost, high-capacity backbone for global brain communication.

PubMed

van den Heuvel, Martijn P; Kahn, René S; Goñi, Joaquín; Sporns, Olaf

2012-07-10

Network studies of human brain structural connectivity have identified a specific set of brain regions that are both highly connected and highly central. Recent analyses have shown that these putative hub regions are mutually and densely interconnected, forming a "rich club" within the human brain. Here we show that the set of pathways linking rich club regions forms a central high-cost, high-capacity backbone for global brain communication. Diffusion tensor imaging (DTI) data of two sets of 40 healthy subjects were used to map structural brain networks. The contributions to network cost and communication capacity of global cortico-cortical connections were assessed through measures of their topology and spatial embedding. Rich club connections were found to be more costly than predicted by their density alone and accounted for 40% of the total communication cost. Furthermore, 69% of all minimally short paths between node pairs were found to travel through the rich club and a large proportion of these communication paths consisted of ordered sequences of edges ("path motifs") that first fed into, then traversed, and finally exited the rich club, while passing through nodes of increasing and then decreasing degree. The prevalence of short paths that follow such ordered degree sequences suggests that neural communication might take advantage of strategies for dynamic routing of information between brain regions, with an important role for a highly central rich club. Taken together, our results show that rich club connections make an important contribution to interregional signal traffic, forming a central high-cost, high-capacity backbone for global brain communication.

Traffic sign recognition by color segmentation and neural network

NASA Astrophysics Data System (ADS)

Surinwarangkoon, Thongchai; Nitsuwat, Supot; Moore, Elvin J.

2011-12-01

An algorithm is proposed for traffic sign detection and identification based on color filtering, color segmentation and neural networks. Traffic signs in Thailand are classified by color into four types: namely, prohibitory signs (red or blue), general warning signs (yellow) and construction area warning signs (amber). A color filtering method is first used to detect traffic signs and classify them by type. Then color segmentation methods adapted for each color type are used to extract inner features, e.g., arrows, bars etc. Finally, neural networks trained to recognize signs in each color type are used to identify any given traffic sign. Experiments show that the algorithm can improve the accuracy of traffic sign detection and recognition for the traffic signs used in Thailand.

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

PubMed

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

2016-10-27

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

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

PubMed Central

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

2016-01-01

To obtain adequate traffic information, the density of traffic sensors should be sufficiently high to cover the entire transportation network. However, deploying sensors densely over the entire network may not be realistic for practical applications due to the budgetary constraints of traffic management agencies. This paper describes several possible spatial distributions of traffic information credibility and proposes corresponding different sensor information credibility functions to describe these spatial distribution properties. A maximum benefit model and its simplified model are proposed to solve the traffic sensor location problem. The relationships between the benefit and the number of sensors are formulated with different sensor information credibility functions. Next, expanding models and algorithms in analytic results are performed. For each case, the maximum benefit, the optimal number and spacing of sensors are obtained and the analytic formulations of the optimal sensor locations are derived as well. Finally, a numerical example is proposed to verify the validity and availability of the proposed models for solving a network sensor location problem. The results show that the optimal number of sensors of segments with different model parameters in an entire freeway network can be calculated. Besides, it can also be concluded that the optimal sensor spacing is independent of end restrictions but dependent on the values of model parameters that represent the physical conditions of sensors and roads. PMID:27801794

Traffic Management in ATM Networks Over Satellite Links

NASA Technical Reports Server (NTRS)

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

1999-01-01

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

Efficiency gain from elastic optical networks

NASA Astrophysics Data System (ADS)

Morea, Annalisa; Rival, Olivier

2011-12-01

We compare the cost-efficiency of optical networks based on mixed datarates (10, 40, 100Gb/s) and datarateelastic technologies. A European backbone network is examined under various traffic assumptions (volume of transported data per demand and total number of demands) to better understand the impact of traffic characteristics on cost-efficiency. Network dimensioning is performed for static and restorable networks (resilient to one-link failure). In this paper we will investigate the trade-offs between price of interfaces, reach and reconfigurability, showing that elastic solutions can be more cost-efficient than mixed-rate solutions because of the better compatibility between different datarates, increased reach of channels and simplified wavelength allocation.

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

NASA Astrophysics Data System (ADS)

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.

Traffic engineering and regenerator placement in GMPLS networks with restoration

NASA Astrophysics Data System (ADS)

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

NASA Astrophysics Data System (ADS)

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.

Protein backbone and sidechain torsion angles predicted from NMR chemical shifts using artificial neural networks

PubMed Central

Shen, Yang; Bax, Ad

2013-01-01

A new program, TALOS-N, is introduced for predicting protein backbone torsion angles from NMR chemical shifts. The program relies far more extensively on the use of trained artificial neural networks than its predecessor, TALOS+. Validation on an independent set of proteins indicates that backbone torsion angles can be predicted for a larger, ≥ 90% fraction of the residues, with an error rate smaller than ca 3.5%, using an acceptance criterion that is nearly two-fold tighter than that used previously, and a root mean square difference between predicted and crystallographically observed (φ,ψ) torsion angles of ca 12°. TALOS-N also reports sidechain χ1 rotameric states for about 50% of the residues, and a consistency with reference structures of 89%. The program includes a neural network trained to identify secondary structure from residue sequence and chemical shifts. PMID:23728592

Traffic prediction using wireless cellular networks : final report.

DOT National Transportation Integrated Search

2016-03-01

The major objective of this project is to obtain traffic information from existing wireless : infrastructure. : In this project freeway traffic is identified and modeled using data obtained from existing : wireless cellular networks. Most of the prev...

Switching performance of OBS network model under prefetched real traffic

NASA Astrophysics Data System (ADS)

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.

Modeling the coevolution of topology and traffic on weighted technological networks

NASA Astrophysics Data System (ADS)

Xie, Yan-Bo; Wang, Wen-Xu; Wang, Bing-Hong

2007-02-01

For many technological networks, the network structures and the traffic taking place on them mutually interact. The demands of traffic increment spur the evolution and growth of the networks to maintain their normal and efficient functioning. In parallel, a change of the network structure leads to redistribution of the traffic. In this paper, we perform an extensive numerical and analytical study, extending results of Wang [Phys. Rev. Lett. 94, 188702 (2005)]. By introducing a general strength-coupling interaction driven by the traffic increment between any pair of vertices, our model generates networks of scale-free distributions of strength, weight, and degree. In particular, the obtained nonlinear correlation between vertex strength and degree, and the disassortative property demonstrate that the model is capable of characterizing weighted technological networks. Moreover, the generated graphs possess both dense clustering structures and an anticorrelation between vertex clustering and degree, which are widely observed in real-world networks. The corresponding theoretical predictions are well consistent with simulation results.

Statistical Traffic Anomaly Detection in Time-Varying Communication Networks

DTIC Science & Technology

2015-02-01

methods perform better than their vanilla counterparts, which assume that normal traffic is stationary. Statistical Traffic Anomaly Detection in Time...our methods perform better than their vanilla counterparts, which assume that normal traffic is stationary. Index Terms—Statistical anomaly detection...anomaly detection but also for understanding the normal traffic in time-varying networks. C. Comparison with vanilla stochastic methods For both types

Statistical Traffic Anomaly Detection in Time Varying Communication Networks

DTIC Science & Technology

2015-02-01

methods perform better than their vanilla counterparts, which assume that normal traffic is stationary. Statistical Traffic Anomaly Detection in Time...our methods perform better than their vanilla counterparts, which assume that normal traffic is stationary. Index Terms—Statistical anomaly detection...anomaly detection but also for understanding the normal traffic in time-varying networks. C. Comparison with vanilla stochastic methods For both types

An efficient routing strategy for traffic dynamics on two-layer complex networks

NASA Astrophysics Data System (ADS)

Ma, Jinlong; Wang, Huiling; Zhang, Zhuxi; Zhang, Yi; Duan, Congwen; Qi, Zhaohui; Liu, Yu

2018-05-01

In order to alleviate traffic congestion on multilayer networks, designing an efficient routing strategy is one of the most important ways. In this paper, a novel routing strategy is proposed to reduce traffic congestion on two-layer networks. In the proposed strategy, the optimal paths in the physical layer are chosen by comprehensively considering the roles of nodes’ degrees of the two layers. Both numerical and analytical results indicate that our routing strategy can reasonably redistribute the traffic load of the physical layer, and thus the traffic capacity of two-layer complex networks are significantly enhanced compared with the shortest path routing (SPR) and the global awareness routing (GAR) strategies. This study may shed some light on the optimization of networked traffic dynamics.

LINEBACkER: Bio-inspired Data Reduction Toward Real Time Network Traffic Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Teuton, Jeremy R.; Peterson, Elena S.; Nordwall, Douglas J.

Abstract—One essential component of resilient cyber applications is the ability to detect adversaries and protect systems with the same flexibility adversaries will use to achieve their goals. Current detection techniques do not enable this degree of flexibility because most existing applications are built using exact or regular-expression matching to libraries of rule sets. Further, network traffic defies traditional cyber security approaches that focus on limiting access based on the use of passwords and examination of lists of installed or downloaded programs. These approaches do not readily apply to network traffic occurring beyond the access control point, and when the datamore » in question are combined control and payload data of ever increasing speed and volume. Manual analysis of network traffic is not normally possible because of the magnitude of the data that is being exchanged and the length of time that this analysis takes. At the same time, using an exact matching scheme to identify malicious traffic in real time often fails because the lists against which such searches must operate grow too large. In this work, we introduce an alternative method for cyber network detection based on similarity-measuring algorithms for gene sequence analysis. These methods are ideal because they were designed to identify similar but nonidentical sequences. We demonstrate that our method is generally applicable to the problem of network traffic analysis by illustrating its use in two different areas both based on different attributes of network traffic. Our approach provides a logical framework for organizing large collections of network data, prioritizing traffic of interest to human analysts, and makes it possible to discover traffic signatures without the bias introduced by expert-directed signature generation. Pattern recognition on reduced representations of network traffic offers a fast, efficient, and more robust way to detect anomalies.« less

General Dynamics of Topology and Traffic on Weighted Technological Networks

NASA Astrophysics Data System (ADS)

Wang, Wen-Xu; Wang, Bing-Hong; Hu, Bo; Yan, Gang; Ou, Qing

2005-05-01

For most technical networks, the interplay of dynamics, traffic, and topology is assumed crucial to their evolution. In this Letter, we propose a traffic-driven evolution model of weighted technological networks. By introducing a general strength-coupling mechanism under which the traffic and topology mutually interact, the model gives power-law distributions of degree, weight, and strength, as confirmed in many real networks. Particularly, depending on a parameter W that controls the total weight growth of the system, the nontrivial clustering coefficient C, degree assortativity coefficient r, and degree-strength correlation are all consistent with empirical evidence.

Backbone of complex networks of corporations: the flow of control.

PubMed

Glattfelder, J B; Battiston, S

2009-09-01

We present a methodology to extract the backbone of complex networks based on the weight and direction of links, as well as on nontopological properties of nodes. We show how the methodology can be applied in general to networks in which mass or energy is flowing along the links. In particular, the procedure enables us to address important questions in economics, namely, how control and wealth are structured and concentrated across national markets. We report on the first cross-country investigation of ownership networks, focusing on the stock markets of 48 countries around the world. On the one hand, our analysis confirms results expected on the basis of the literature on corporate control, namely, that in Anglo-Saxon countries control tends to be dispersed among numerous shareholders. On the other hand, it also reveals that in the same countries, control is found to be highly concentrated at the global level, namely, lying in the hands of very few important shareholders. Interestingly, the exact opposite is observed for European countries. These results have previously not been reported as they are not observable without the kind of network analysis developed here.

Backbone of complex networks of corporations: The flow of control

NASA Astrophysics Data System (ADS)

Glattfelder, J. B.; Battiston, S.

2009-09-01

We present a methodology to extract the backbone of complex networks based on the weight and direction of links, as well as on nontopological properties of nodes. We show how the methodology can be applied in general to networks in which mass or energy is flowing along the links. In particular, the procedure enables us to address important questions in economics, namely, how control and wealth are structured and concentrated across national markets. We report on the first cross-country investigation of ownership networks, focusing on the stock markets of 48 countries around the world. On the one hand, our analysis confirms results expected on the basis of the literature on corporate control, namely, that in Anglo-Saxon countries control tends to be dispersed among numerous shareholders. On the other hand, it also reveals that in the same countries, control is found to be highly concentrated at the global level, namely, lying in the hands of very few important shareholders. Interestingly, the exact opposite is observed for European countries. These results have previously not been reported as they are not observable without the kind of network analysis developed here.

Remote consultation and diagnosis in medical imaging using a global PACS backbone network

NASA Astrophysics Data System (ADS)

Martinez, Ralph; Sutaria, Bijal N.; Kim, Jinman; Nam, Jiseung

1993-10-01

A Global PACS is a national network which interconnects several PACS networks at medical and hospital complexes using a national backbone network. A Global PACS environment enables new and beneficial operations between radiologists and physicians, when they are located in different geographical locations. One operation allows the radiologist to view the same image folder at both Local and Remote sites so that a diagnosis can be performed. The paper describes the user interface, database management, and network communication software which has been developed in the Computer Engineering Research Laboratory and Radiology Research Laboratory. Specifically, a design for a file management system in a distributed environment is presented. In the remote consultation and diagnosis operation, a set of images is requested from the database archive system and sent to the Local and Remote workstation sites on the Global PACS network. Viewing the same images, the radiologists use pointing overlay commands, or frames to point out features on the images. Each workstation transfers these frames, to the other workstation, so that an interactive session for diagnosis takes place. In this phase, we use fixed frames and variable size frames, used to outline an object. The data pockets for these frames traverses the national backbone in real-time. We accomplish this feature by using TCP/IP protocol sockets for communications. The remote consultation and diagnosis operation has been tested in real-time between the University Medical Center and the Bowman Gray School of Medicine at Wake Forest University, over the Internet. In this paper, we show the feasibility of the operation in a Global PACS environment. Future improvements to the system will include real-time voice and interactive compressed video scenarios.

Routing protocol for wireless quantum multi-hop mesh backbone network based on partially entangled GHZ state

NASA Astrophysics Data System (ADS)

Xiong, Pei-Ying; Yu, Xu-Tao; Zhang, Zai-Chen; Zhan, Hai-Tao; Hua, Jing-Yu

2017-08-01

Quantum multi-hop teleportation is important in the field of quantum communication. In this study, we propose a quantum multi-hop communication model and a quantum routing protocol with multihop teleportation for wireless mesh backbone networks. Based on an analysis of quantum multi-hop protocols, a partially entangled Greenberger-Horne-Zeilinger (GHZ) state is selected as the quantum channel for the proposed protocol. Both quantum and classical wireless channels exist between two neighboring nodes along the route. With the proposed routing protocol, quantum information can be transmitted hop by hop from the source node to the destination node. Based on multi-hop teleportation based on the partially entangled GHZ state, a quantum route established with the minimum number of hops. The difference between our routing protocol and the classical one is that in the former, the processes used to find a quantum route and establish quantum channel entanglement occur simultaneously. The Bell state measurement results of each hop are piggybacked to quantum route finding information. This method reduces the total number of packets and the magnitude of air interface delay. The deduction of the establishment of a quantum channel between source and destination is also presented here. The final success probability of quantum multi-hop teleportation in wireless mesh backbone networks was simulated and analyzed. Our research shows that quantum multi-hop teleportation in wireless mesh backbone networks through a partially entangled GHZ state is feasible.

Toward a Scalable Visualization System for Network Traffic Monitoring

NASA Astrophysics Data System (ADS)

Malécot, Erwan Le; Kohara, Masayoshi; Hori, Yoshiaki; Sakurai, Kouichi

With the multiplication of attacks against computer networks, system administrators are required to monitor carefully the traffic exchanged by the networks they manage. However, that monitoring task is increasingly laborious because of the augmentation of the amount of data to analyze. And that trend is going to intensify with the explosion of the number of devices connected to computer networks along with the global rise of the available network bandwidth. So system administrators now heavily rely on automated tools to assist them and simplify the analysis of the data. Yet, these tools provide limited support and, most of the time, require highly skilled operators. Recently, some research teams have started to study the application of visualization techniques to the analysis of network traffic data. We believe that this original approach can also allow system administrators to deal with the large amount of data they have to process. In this paper, we introduce a tool for network traffic monitoring using visualization techniques that we developed in order to assist the system administrators of our corporate network. We explain how we designed the tool and some of the choices we made regarding the visualization techniques to use. The resulting tool proposes two linked representations of the network traffic and activity, one in 2D and the other in 3D. As 2D and 3D visualization techniques have different assets, we resulted in combining them in our tool to take advantage of their complementarity. We finally tested our tool in order to evaluate the accuracy of our approach.

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Hong; Aziz, H M Abdul; Young, Stan

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.more » 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.« less

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

PubMed

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.

Traffic Signal Synchronization in the Saturated High-Density Grid Road Network

PubMed Central

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. PMID:25663835

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

NASA Astrophysics Data System (ADS)

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

Traffic off-balancing algorithm for energy efficient networks

NASA Astrophysics Data System (ADS)

Kim, Junhyuk; Lee, Chankyun; Rhee, June-Koo Kevin

2011-12-01

Physical layer of high-end network system uses multiple interface arrays. Under the load-balancing perspective, light load can be distributed to multiple interfaces. However, it can cause energy inefficiency in terms of the number of poor utilization interfaces. To tackle this energy inefficiency, traffic off-balancing algorithm for traffic adaptive interface sleep/awake is investigated. As a reference model, 40G/100G Ethernet is investigated. We report that suggested algorithm can achieve energy efficiency while satisfying traffic transmission requirement.

From Cellular Attractor Selection to Adaptive Signal Control for Traffic Networks.

PubMed

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.

A new traffic control design method for large networks with signalized intersections

NASA Technical Reports Server (NTRS)

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.

PubMed

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.

Optimized Sensor Network and Multi-Agent Decision Support for Smart Traffic Light Management

PubMed Central

2018-01-01

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. PMID:29393884

Implementation of a tactical voice/data network over FDDI. [Fiber Distributed Data Interface

NASA Technical Reports Server (NTRS)

Bergman, L. A.; Halloran, F.; Martinez, J.

1988-01-01

An asynchronous high-speed fiber-optic local-area network is described that simultaneously supports packet data traffic with synchronous TI voice traffic over a standard asynchronous FDDI (fiber distributed data interface) token-ring channel. A voice interface module was developed that parses, buffers, and resynchronizes the voice data to the packet network. The technique is general, however, and can be applied to any deterministic class of networks, including multitier backbones. In addition, the higher layer packet data protocols may operate independently of those for the voice, thereby permitting great flexibility in reconfiguring the network. Voice call setup and switching functions are performed external to the network with PABX equipment.

Congestion transition in air traffic networks.

PubMed

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.

Effects of Sampling and Spatio/Temporal Granularity in Traffic Monitoring on Anomaly Detectability

NASA Astrophysics Data System (ADS)

Ishibashi, Keisuke; Kawahara, Ryoichi; Mori, Tatsuya; Kondoh, Tsuyoshi; Asano, Shoichiro

We quantitatively evaluate how sampling and spatio/temporal granularity in traffic monitoring affect the detectability of anomalous traffic. Those parameters also affect the monitoring burden, so network operators face a trade-off between the monitoring burden and detectability and need to know which are the optimal paramter values. We derive equations to calculate the false positive ratio and false negative ratio for given values of the sampling rate, granularity, statistics of normal traffic, and volume of anomalies to be detected. Specifically, assuming that the normal traffic has a Gaussian distribution, which is parameterized by its mean and standard deviation, we analyze how sampling and monitoring granularity change these distribution parameters. This analysis is based on observation of the backbone traffic, which exhibits spatially uncorrelated and temporally long-range dependence. Then we derive the equations for detectability. With those equations, we can answer the practical questions that arise in actual network operations: what sampling rate to set to find the given volume of anomaly, or, if the sampling is too high for actual operation, what granularity is optimal to find the anomaly for a given lower limit of sampling rate.

Traffic on complex networks: Towards understanding global statistical properties from microscopic density fluctuations

NASA Astrophysics Data System (ADS)

Tadić, Bosiljka; Thurner, Stefan; Rodgers, G. J.

2004-03-01

We study the microscopic time fluctuations of traffic load and the global statistical properties of a dense traffic of particles on scale-free cyclic graphs. For a wide range of driving rates R the traffic is stationary and the load time series exhibits antipersistence due to the regulatory role of the superstructure associated with two hub nodes in the network. We discuss how the superstructure affects the functioning of the network at high traffic density and at the jamming threshold. The degree of correlations systematically decreases with increasing traffic density and eventually disappears when approaching a jamming density Rc. Already before jamming we observe qualitative changes in the global network-load distributions and the particle queuing times. These changes are related to the occurrence of temporary crises in which the network-load increases dramatically, and then slowly falls back to a value characterizing free flow.

From Cellular Attractor Selection to Adaptive Signal Control for Traffic Networks

PubMed Central

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

2016-01-01

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. PMID:26972968

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

NASA Astrophysics Data System (ADS)

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

DOEpatents

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.

An adaptable neural-network model for recursive nonlinear traffic prediction and modeling of MPEG video sources.

PubMed

Doulamis, A D; Doulamis, N D; Kollias, S D

2003-01-01

Multimedia services and especially digital video is expected to be the major traffic component transmitted over communication networks [such as internet protocol (IP)-based networks]. For this reason, traffic characterization and modeling of such services are required for an efficient network operation. The generated models can be used as traffic rate predictors, during the network operation phase (online traffic modeling), or as video generators for estimating the network resources, during the network design phase (offline traffic modeling). In this paper, an adaptable neural-network architecture is proposed covering both cases. The scheme is based on an efficient recursive weight estimation algorithm, which adapts the network response to current conditions. In particular, the algorithm updates the network weights so that 1) the network output, after the adaptation, is approximately equal to current bit rates (current traffic statistics) and 2) a minimal degradation over the obtained network knowledge is provided. It can be shown that the proposed adaptable neural-network architecture simulates a recursive nonlinear autoregressive model (RNAR) similar to the notation used in the linear case. The algorithm presents low computational complexity and high efficiency in tracking traffic rates in contrast to conventional retraining schemes. Furthermore, for the problem of offline traffic modeling, a novel correlation mechanism is proposed for capturing the burstness of the actual MPEG video traffic. The performance of the model is evaluated using several real-life MPEG coded video sources of long duration and compared with other linear/nonlinear techniques used for both cases. The results indicate that the proposed adaptable neural-network architecture presents better performance than other examined techniques.

Comparison of classical statistical methods and artificial neural network in traffic noise prediction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nedic, Vladimir, E-mail: vnedic@kg.ac.rs; Despotovic, Danijela, E-mail: ddespotovic@kg.ac.rs; Cvetanovic, Slobodan, E-mail: slobodan.cvetanovic@eknfak.ni.ac.rs

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. Themore » 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.« less

Network-constrained spatio-temporal clustering analysis of traffic collisions in Jianghan District of Wuhan, China

PubMed Central

Fan, Yaxin; Zhu, Xinyan; Guo, Wei; Guo, Tao

2018-01-01

The analysis of traffic collisions is essential for urban safety and the sustainable development of the urban environment. Reducing the road traffic injuries and the financial losses caused by collisions is the most important goal of traffic management. In addition, traffic collisions are a major cause of traffic congestion, which is a serious issue that affects everyone in the society. Therefore, traffic collision analysis is essential for all parties, including drivers, pedestrians, and traffic officers, to understand the road risks at a finer spatio-temporal scale. However, traffic collisions in the urban context are dynamic and complex. Thus, it is important to detect how the collision hotspots evolve over time through spatio-temporal clustering analysis. In addition, traffic collisions are not isolated events in space. The characteristics of the traffic collisions and their surrounding locations also present an influence of the clusters. This work tries to explore the spatio-temporal clustering patterns of traffic collisions by combining a set of network-constrained methods. These methods were tested using the traffic collision data in Jianghan District of Wuhan, China. The results demonstrated that these methods offer different perspectives of the spatio-temporal clustering patterns. The weighted network kernel density estimation provides an intuitive way to incorporate attribute information. The network cross K-function shows that there are varying clustering tendencies between traffic collisions and different types of POIs. The proposed network differential Local Moran’s I and network local indicators of mobility association provide straightforward and quantitative measures of the hotspot changes. This case study shows that these methods could help researchers, practitioners, and policy-makers to better understand the spatio-temporal clustering patterns of traffic collisions. PMID:29672551

Routing optimization in networks based on traffic gravitational field model

NASA Astrophysics Data System (ADS)

Liu, Longgeng; Luo, Guangchun

2017-04-01

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

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

NASA Astrophysics Data System (ADS)

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.

Betweenness centrality and its applications from modeling traffic flows to network community detection

NASA Astrophysics Data System (ADS)

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

Efficient traffic grooming in SONET/WDM BLSR Networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

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

2004-04-02

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

A fiber optic tactical voice/data network based on FDDI

NASA Technical Reports Server (NTRS)

Bergman, L. A.; Hartmayer, R.; Marelid, S.; Wu, W. H.; Edgar, G.; Cassell, P.; Mancini, R.; Kiernicki, J.; Paul, L. J.; Jeng, J.

1988-01-01

An asynchronous high-speed fiber optic local area network is described that supports ordinary data packet traffic simultaneously with synchronous Tl voice traffic over a common FDDI token ring channel. A voice interface module was developed that parses, buffers, and resynchronizes the voice data to the packet network. The technique is general, however, and can be applied to any deterministic class of networks, including multi-tier backbones. A conventional single token access protocol was employed at the lowest layer, with fixed packet sizes for voice and variable for data. In addition, the higher layer packet data protocols are allowed to operate independently of those for the voice thereby permitting great flexibility in reconfiguring the network. Voice call setup and switching functions were performed external to the network with PABX equipment.

Spatial distribution of traffic in a cellular mobile data network

NASA Astrophysics Data System (ADS)

Linnartz, J. P. M. G.

1987-02-01

The use of integral transforms of the probability density function for the received power to analyze the relation between the spatial distributions of offered and throughout packet traffic in a mobile radio network with Rayleigh fading channels and ALOHA multiple access was assessed. A method to obtain the spatial distribution of throughput traffic from a prescribed spatial distribution of offered traffic is presented. Incoherent and coherent addition of interference signals is considered. The channel behavior for heavy traffic loads is studied. In both the incoherent and coherent case, the spatial distribution of offered traffic required to ensure a prescribed spatially uniform throughput is synthesized numerically.

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

NASA Astrophysics Data System (ADS)

Li, Yan; Dai, Shifang; Wu, Weiwei

2016-12-01

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

A Wavelet Neural Network Optimal Control Model for Traffic-Flow Prediction in Intelligent Transport Systems

NASA Astrophysics Data System (ADS)

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.

Variable speed limit strategies analysis with mesoscopic traffic flow model based on complex networks

NASA Astrophysics Data System (ADS)

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.

Traffic sign recognition based on deep convolutional neural network

NASA Astrophysics Data System (ADS)

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.

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

DOT National Transportation Integrated Search

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...

Traffic-driven epidemic spreading on scale-free networks with tunable degree distribution

NASA Astrophysics Data System (ADS)

Yang, Han-Xin; Wang, Bing-Hong

2016-04-01

We study the traffic-driven epidemic spreading on scale-free networks with tunable degree distribution. The heterogeneity of networks is controlled by the exponent γ of power-law degree distribution. It is found that the epidemic threshold is minimized at about γ=2.2. Moreover, we find that nodes with larger algorithmic betweenness are more likely to be infected. We expect our work to provide new insights in to the effect of network structures on traffic-driven epidemic spreading.

Traffic handling capability of a broadband indoor wireless network using CDMA multiple access

NASA Astrophysics Data System (ADS)

Zhang, Chang G.; Hafez, H. M.; Falconer, David D.

1994-05-01

CDMA (code division multiple access) may be an attractive technique for wireless access to broadband services because of its multiple access simplicity and other appealing features. In order to investigate traffic handling capabilities of a future network providing a variety of integrated services, this paper presents a study of a broadband indoor wireless network supporting high-speed traffic using CDMA multiple access. The results are obtained through the simulation of an indoor environment and the traffic capabilities of the wireless access to broadband 155.5 MHz ATM-SONET networks using the mm-wave band. A distributed system architecture is employed and the system performance is measured in terms of call blocking probability and dropping probability. The impacts of the base station density, traffic load, average holding time, and variable traffic sources on the system performance are examined. The improvement of system performance by implementing various techniques such as handoff, admission control, power control and sectorization are also investigated.

Fiber optic voice/data network

NASA Technical Reports Server (NTRS)

Bergman, Larry A. (Inventor)

1989-01-01

An asynchronous, high-speed, fiber optic local area network originally developed for tactical environments with additional benefits for other environments such as spacecraft, and the like. The network supports ordinary data packet traffic simultaneously with synchronous T1 voice traffic over a common token ring channel; however, the techniques and apparatus of this invention can be applied to any deterministic class of packet data networks, including multitier backbones, that must transport stream data (e.g., video, SAR, sensors) as well as data. A voice interface module parses, buffers, and resynchronizes the voice data to the packet network employing elastic buffers on both the sending and receiving ends. Voice call setup and switching functions are performed external to the network with ordinary PABX equipment. Clock information is passed across network boundaries in a token passing ring by preceeding the token with an idle period of non-transmission which allows the token to be used to re-establish a clock synchronized to the data. Provision is made to monitor and compensate the elastic receiving buffers so as to prevent them from overflowing or going empty.

Architectural impact of FDDI network on scheduling hard real-time traffic

NASA Technical Reports Server (NTRS)

Agrawal, Gopal; Chen, Baio; Zhao, Wei; Davari, Sadegh

1991-01-01

The architectural impact on guaranteeing synchronous message deadlines in FDDI (Fiber Distributed Data Interface) token ring networks is examined. The FDDI network does not have facility to support (global) priority arbitration which is a useful facility for scheduling hard real time activities. As a result, it was found that the worst case utilization of synchronous traffic in an FDDI network can be far less than that in a centralized single processor system. Nevertheless, it is proposed and analyzed that a scheduling method can guarantee deadlines of synchronous messages having traffic utilization up to 33 pct., the highest to date.

Quantification of Road Network Vulnerability and Traffic Impacts to Regional Landslide Hazards.

NASA Astrophysics Data System (ADS)

Postance, Benjamin; Hillier, John; Dixon, Neil; Dijkstra, Tom

2015-04-01

Slope instability represents a prevalent hazard to transport networks. In the UK regional road networks are frequently disrupted by multiple slope failures triggered during intense precipitation events; primarily due to a degree of regional homogeneity of slope materials, geomorphology and weather conditions. It is of interest to examine how different locations and combinations of slope failure impact road networks, particularly in the context of projected climate change and a 40% increase in UK road demand by 2040. In this study an extensive number (>50 000) of multiple failure event scenarios are simulated within a dynamic micro simulation to assess traffic impacts during peak flow (7 - 10 AM). Possible failure locations are selected within the county of Gloucestershire (3150 km2) using historic failure sites and British Geological Survey GeoSure data. Initial investigations employ a multiple linear regression analyses to consider the severity of traffic impacts, as measured by time, in respect of spatial and topographical network characteristics including connectivity, density and capacity in proximity to failure sites; the network distance between disruptions in multiple failure scenarios is used to consider the effects of spatial clustering. The UK Department of Transport road travel demand and UKCP09 weather projection data to 2080 provide a suitable basis for traffic simulations and probabilistic slope stability assessments. Future work will thus focus on the development of a catastrophe risk model to simulate traffic impacts under various narratives of future travel demand and slope instability under climatic change. The results of this investigation shall contribute to the understanding of road network vulnerabilities and traffic impacts from climate driven slope hazards.

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

NASA Astrophysics Data System (ADS)

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.

A model of traffic signs recognition with convolutional neural network

NASA Astrophysics Data System (ADS)

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

2016-10-01

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

Universal model for collective access patterns in the Internet traffic dynamics: A superstatistical approach

NASA Astrophysics Data System (ADS)

Tamazian, A.; Nguyen, V. D.; Markelov, O. A.; Bogachev, M. I.

2016-07-01

We suggest a universal phenomenological description for the collective access patterns in the Internet traffic dynamics both at local and wide area network levels that takes into account erratic fluctuations imposed by cooperative user behaviour. Our description is based on the superstatistical approach and leads to the q-exponential inter-session time and session size distributions that are also in perfect agreement with empirical observations. The validity of the proposed description is confirmed explicitly by the analysis of complete 10-day traffic traces from the WIDE backbone link and from the local campus area network downlink from the Internet Service Provider. Remarkably, the same functional forms have been observed in the historic access patterns from single WWW servers. The suggested approach effectively accounts for the complex interplay of both “calm” and “bursty” user access patterns within a single-model setting. It also provides average sojourn time estimates with reasonable accuracy, as indicated by the queuing system performance simulation, this way largely overcoming the failure of Poisson modelling of the Internet traffic dynamics.

A Learning System for Discriminating Variants of Malicious Network Traffic

DOE Office of Scientific and Technical Information (OSTI.GOV)

Beaver, Justin M; Symons, Christopher T; Gillen, Rob

Modern computer network defense systems rely primarily on signature-based intrusion detection tools, which generate alerts when patterns that are pre-determined to be malicious are encountered in network data streams. Signatures are created reactively, and only after in-depth manual analysis of a network intrusion. There is little ability for signature-based detectors to identify intrusions that are new or even variants of an existing attack, and little ability to adapt the detectors to the patterns unique to a network environment. Due to these limitations, the need exists for network intrusion detection techniques that can more comprehensively address both known unknown networkbased attacksmore » and can be optimized for the target environment. This work describes a system that leverages machine learning to provide a network intrusion detection capability that analyzes behaviors in channels of communication between individual computers. Using examples of malicious and non-malicious traffic in the target environment, the system can be trained to discriminate between traffic types. The machine learning provides insight that would be difficult for a human to explicitly code as a signature because it evaluates many interdependent metrics simultaneously. With this approach, zero day detection is possible by focusing on similarity to known traffic types rather than mining for specific bit patterns or conditions. This also reduces the burden on organizations to account for all possible attack variant combinations through signatures. The approach is presented along with results from a third-party evaluation of its performance.« less

Traffic routing for multicomputer networks with virtual cut-through capability

NASA Technical Reports Server (NTRS)

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.

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

NASA Technical Reports Server (NTRS)

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

2017-01-01

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

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

PubMed

Nellore, Kapileswar; Hancke, Gerhard P

2016-01-27

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

A Survey on Urban Traffic Management System Using Wireless Sensor Networks

PubMed Central

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.

PubMed

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.

Energy conservation in ad hoc multimedia networks using traffic-shaping mechanisms

NASA Astrophysics Data System (ADS)

Chandra, Surendar

2003-12-01

In this work, we explore network traffic shaping mechanisms that deliver packets at pre-determined intervals; allowing the network interface to transition to a lower power consuming sleep state. We focus our efforts on commodity devices, IEEE 802.11b ad hoc mode and popular streaming formats. We argue that factors such as the lack of scheduling clock phase synchronization among the participants and scheduling delays introduced by back ground tasks affect the potential energy savings. Increasing the periodic transmission delays to transmit data infrequently can offset some of these effects at the expense of flooding the wireless channel for longer periods of time; potentially increasing the time to acquire the channel for non-multimedia traffic. Buffering mechanisms built into media browsers can mitigate the effects of these added delays from being mis-interpreted as network congestion. We show that practical implementations of such traffic shaping mechanisms can offer significant energy savings.

Near real-time traffic routing

NASA Technical Reports Server (NTRS)

Yang, Chaowei (Inventor); Xie, Jibo (Inventor); Zhou, Bin (Inventor); Cao, Ying (Inventor)

2012-01-01

A near real-time physical transportation network routing system comprising: a traffic simulation computing grid and a dynamic traffic routing service computing grid. The traffic simulator produces traffic network travel time predictions for a physical transportation network using a traffic simulation model and common input data. The physical transportation network is divided into a multiple sections. Each section has a primary zone and a buffer zone. The traffic simulation computing grid includes multiple of traffic simulation computing nodes. The common input data includes static network characteristics, an origin-destination data table, dynamic traffic information data and historical traffic data. The dynamic traffic routing service computing grid includes multiple dynamic traffic routing computing nodes and generates traffic route(s) using the traffic network travel time predictions.

Evaluation Study of a Wireless Multimedia Traffic-Oriented Network Model

NASA Astrophysics Data System (ADS)

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

2008-11-01

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

Inside the Mechanics of Network Development: How Competition and Strategy Reorganize European Air Traffic

NASA Technical Reports Server (NTRS)

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.

Dynamic traffic grooming with Spectrum Engineering (TG-SE) in flexible grid optical networks

NASA Astrophysics Data System (ADS)

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.

The multiscale backbone of the human phenotype network based on biological pathways.

PubMed

Darabos, Christian; White, Marquitta J; Graham, Britney E; Leung, Derek N; Williams, Scott M; Moore, Jason H

2014-01-25

Networks are commonly used to represent and analyze large and complex systems of interacting elements. In systems biology, human disease networks show interactions between disorders sharing common genetic background. We built pathway-based human phenotype network (PHPN) of over 800 physical attributes, diseases, and behavioral traits; based on about 2,300 genes and 1,200 biological pathways. Using GWAS phenotype-to-genes associations, and pathway data from Reactome, we connect human traits based on the common patterns of human biological pathways, detecting more pleiotropic effects, and expanding previous studies from a gene-centric approach to that of shared cell-processes. The resulting network has a heavily right-skewed degree distribution, placing it in the scale-free region of the network topologies spectrum. We extract the multi-scale information backbone of the PHPN based on the local densities of the network and discarding weak connection. Using a standard community detection algorithm, we construct phenotype modules of similar traits without applying expert biological knowledge. These modules can be assimilated to the disease classes. However, we are able to classify phenotypes according to shared biology, and not arbitrary disease classes. We present examples of expected clinical connections identified by PHPN as proof of principle. We unveil a previously uncharacterized connection between phenotype modules and discuss potential mechanistic connections that are obvious only in retrospect. The PHPN shows tremendous potential to become a useful tool both in the unveiling of the diseases' common biology, and in the elaboration of diagnosis and treatments.

Novel Schemes for Local Area Network Emulation in Passive Optical Networks With RF Subcarrier Multiplexed Customer Traffic

NASA Astrophysics Data System (ADS)

Nadarajah, Nishaanthan; Attygalle, Manik; Wong, Elaine; Nirmalathas, Ampalavanapillai

2005-10-01

This paper proposes two novel optical layer schemes for intercommunication between customers in a passive optical network (PON). The proposed schemes use radio frequency (RF) subcarrier multiplexed transmission for intercommunication between customers in conjunction with upstream access to the central office (CO) at baseband. One scheme employs a narrowband fiber Bragg grating (FBG) placed close to the star coupler in the feeder fiber of the PON, while the other uses an additional short-length distribution fiber from the star coupler to each customer unit for the redirection of customer traffic. In both schemes, only one optical transmitter is required at each optical network unit (ONU) for the transmission of customer traffic and upstream access traffic. Moreover, downstream bandwidth is not consumed by customer traffic unlike in previously reported techniques. The authors experimentally verify the feasibility of both schemes with 1.25 Gb/s upstream baseband transmission to the CO and 155 Mb/s customer data transmission on the RF carrier. The experimental results obtained from both schemes are compared, and the power budgets are calculated to analyze the scalability of each scheme. Further, the proposed schemes were discussed in terms of upgradability of the transmission bit rates for the upstream access traffic, bandwidth requirements at the customer premises, dispersion tolerance, and stability issues for the practical implementations of the network.

Adaptive route choice modeling in uncertain traffic networks with real-time information.

DOT National Transportation Integrated Search

2013-03-01

The objective of the research is to study travelers' route choice behavior in uncertain traffic networks : with real-time information. The research is motivated by two observations of the traffic system: 1) : the system is inherently uncertain with r...

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

NASA Astrophysics Data System (ADS)

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

2017-05-01

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

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

NASA Astrophysics Data System (ADS)

Lämmer, Stefan; Helbing, Dirk

2008-04-01

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

Traffic sharing algorithms for hybrid mobile networks

NASA Technical Reports Server (NTRS)

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.

Hydrodynamically induced oscillations and traffic dynamics in 1D microfludic networks

NASA Astrophysics Data System (ADS)

Bartolo, Denis; Jeanneret, Raphael

2011-03-01

We report on the traffic dynamics of particles driven through a minimal microfluidic network. Even in the minimal network consisting in a single loop, the traffic dynamics has proven to yield complex temporal patterns, including periodic, multi-periodic or chaotic sequences. This complex dynamics arises from the strongly nonlinear hydrodynamic interactions between the particles, that takes place at a junction. To better understand the consequences of this nontrivial coupling, we combined theoretical, numerical and experimental efforts and solved the 3-body problem in a 1D loop network. This apparently simple dynamical system revealed a rich and unexpected dynamics, including coherent spontaneous oscillations along closed orbits. Striking similarities between Hamiltonian systems and this driven dissipative system will be explained.

Packet Traffic Dynamics Near Onset of Congestion in Data Communication Network Model

NASA Astrophysics Data System (ADS)

Lawniczak, A. T.; Tang, X.

2006-05-01

The dominant technology of data communication networks is the Packet Switching Network (PSN). It is a complex technology organized as various hierarchical layers according to the International Standard Organization (ISO) Open Systems Interconnect (OSI) Reference Model. The Network Layer of the ISO OSI Reference Model is responsible for delivering packets from their sources to their destinations and for dealing with congestion if it arises in a network. Thus, we focus on this layer and present an abstraction of the Network Layer of the ISO OSI Reference Model. Using this abstraction we investigate how onset of traffic congestion is affected for various routing algorithms by changes in network connection topology. We study how aggregate measures of network performance depend on network connection topology and routing. We explore packets traffic spatio-temporal dynamics near the phase transition point from free flow to congestion for various network connection topologies and routing algorithms. We consider static and adaptive routings. We present selected simulation results.

Achieving QoS for TCP Traffic in Satellite Networks with Differentiated Services

NASA Technical Reports Server (NTRS)

Durresi, Arjan; Kota, Sastri; Goyal, Mukul; Jain, Raj; Bharani, Venkata

2001-01-01

Satellite networks play an indispensable role in providing global Internet access and electronic connectivity. To achieve such a global communications, provisioning of quality of service (QoS) within the advanced satellite systems is the main requirement. One of the key mechanisms of implementing the quality of service is traffic management. Traffic management becomes a crucial factor in the case of satellite network because of the limited availability of their resources. Currently, Internet Protocol (IP) only has minimal traffic management capabilities and provides best effort services. In this paper, we presented a broadband satellite network QoS model and simulated performance results. In particular, we discussed the TCP flow aggregates performance for their good behavior in the presence of competing UDP flow aggregates in the same assured forwarding. We identified several factors that affect the performance in the mixed environments and quantified their effects using a full factorial design of experiment methodology.

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

NASA Technical Reports Server (NTRS)

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.

Capacity planning of a wide-sense nonblocking generalized survivable network

NASA Astrophysics Data System (ADS)

Ho, Kwok Shing; Cheung, Kwok Wai

2006-06-01

Generalized survivable networks (GSNs) have two interesting properties that are essential attributes for future backbone networks--full survivability against link failures and support for dynamic traffic demands. GSNs incorporate the nonblocking network concept into the survivable network models. Given a set of nodes and a topology that is at least two-edge connected, a certain minimum capacity is required for each edge to form a GSN. The edge capacity is bounded because each node has an input-output capacity limit that serves as a constraint for any allowable traffic demand matrix. The GSN capacity planning problem is nondeterministic polynomial time (NP) hard. We first give a rigorous mathematical framework; then we offer two different solution approaches. The two-phase approach is fast, but the joint optimization approach yields a better bound. We carried out numerical computations for eight networks with different topologies and found that the cost of a GSN is only a fraction (from 52% to 89%) more than that of a static survivable network.

Traffic sign classification with dataset augmentation and convolutional neural network

NASA Astrophysics Data System (ADS)

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.

Strategic parameter-driven routing models for multidestination traffic in telecommunication networks.

PubMed

Lee, Y; Tien, J M

2001-01-01

We present mathematical models that determine the optimal parameters for strategically routing multidestination traffic in an end-to-end network setting. Multidestination traffic refers to a traffic type that can be routed to any one of a multiple number of destinations. A growing number of communication services is based on multidestination routing. In this parameter-driven approach, a multidestination call is routed to one of the candidate destination nodes in accordance with predetermined decision parameters associated with each candidate node. We present three different approaches: (1) a link utilization (LU) approach, (2) a network cost (NC) approach, and (3) a combined parametric (CP) approach. The LU approach provides the solution that would result in an optimally balanced link utilization, whereas the NC approach provides the least expensive way to route traffic to destinations. The CP approach, on the other hand, provides multiple solutions that help leverage link utilization and cost. The LU approach has in fact been implemented by a long distance carrier resulting in a considerable efficiency improvement in its international direct services, as summarized.

Communication efficiency and congestion of signal traffic in large-scale brain networks.

PubMed

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.

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

PubMed

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

2012-08-01

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

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

NASA Astrophysics Data System (ADS)

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.

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

PubMed

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.

Communication Efficiency and Congestion of Signal Traffic in Large-Scale Brain Networks

PubMed Central

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. PMID:24415931

XUNET experimental high-speed network testbed CRADA 1136, DOE TTI No. 92-MULT-020-B2

DOE Office of Scientific and Technical Information (OSTI.GOV)

Palmer, R.E.

1996-04-01

XUNET is a research program with AT&T and other partners to study high-speed wide area communication between local area networks over a backbone using Asynchronous Transfer Mode (ATM) switches. Important goals of the project are to develop software techniques for network control and management, and applications for high-speed networks. The project entails building a testbed between member sites to explore performance issues for mixed network traffic such as congestion control, multimedia communications protocols, segmentation and reassembly of ATM cells, and overall data throughput rates.

Cooperation and information replication in wireless networks.

PubMed

Poularakis, Konstantinos; Tassiulas, Leandros

2016-03-06

A significant portion of today's network traffic is due to recurring downloads of a few popular contents. It has been observed that replicating the latter in caches installed at network edges-close to users-can drastically reduce network bandwidth usage and improve content access delay. Such caching architectures are gaining increasing interest in recent years as a way of dealing with the explosive traffic growth, fuelled further by the downward slope in storage space price. In this work, we provide an overview of caching with a particular emphasis on emerging network architectures that enable caching at the radio access network. In this context, novel challenges arise due to the broadcast nature of the wireless medium, which allows simultaneously serving multiple users tuned into a multicast stream, and the mobility of the users who may be frequently handed off from one cell tower to another. Existing results indicate that caching at the wireless edge has a great potential in removing bottlenecks on the wired backbone networks. Taking into consideration the schedule of multicast service and mobility profiles is crucial to extract maximum benefit in network performance. © 2016 The Author(s).

Modeling and simulation of the data communication network at the ASRM Facility

NASA Technical Reports Server (NTRS)

Nirgudkar, R. P.; Moorhead, R. J.; Smith, W. D.

1994-01-01

This paper describes the modeling and simulation of the communication network for the NASA Advanced Solid Rocket Motor (ASRM) facility under construction at Yellow Creek near Luka, Mississippi. Manufacturing, testing, and operations at the ASRM site will be performed in different buildings scattered over an 1800 acre site. These buildings are interconnected through a local area network (LAN), which will contain one logical Fiber Distributed Data Interface (FDDI) ring acting as a backbone for the whole complex. The network contains approximately 700 multi-vendor workstations, 22 multi-vendor workcells, and 3 VAX clusters interconnected via Ethernet and FDDI. The different devices produce appreciably different traffic patterns, each pattern will be highly variable, and some patterns will be very bursty. Most traffic is between the VAX clusters and the other devices. Comdisco's Block Oriented Network Simulator (BONeS) has been used for network simulation. The two primary evaluation parameters used to judge the expected network performance are throughput and delay.

Traffic flow collection wireless sensor network node for intersection light control

NASA Astrophysics Data System (ADS)

Li, Xu; Li, Xue

2011-10-01

Wireless sensor network (WSN) is expected to be deployed in intersection to monitor the traffic flow continuously, and the monitoring datum can be used as the foundation of traffic light control. In this paper, a WSN based on ZigBee protocol for monitoring traffic flow is proposed. Structure, hardware and work flow of WSN nodes are designed. CC2431 from Texas Instrument is chosen as the main computational and transmission unit, and CC2591 as the amplification unit. The stability experiment and the actual environment experiment are carried out in the last of the paper. The results of experiments show that WSN has the ability to collect traffic flow information quickly and transmit the datum to the processing center in real time.

Encapsulating urban traffic rhythms into road networks.

PubMed

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

2014-02-20

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

An improved network model for railway traffic

NASA Astrophysics Data System (ADS)

Li, Keping; Ma, Xin; Shao, Fubo

In railway traffic, safety analysis is a key issue for controlling train operation. Here, the identification and order of key factors are very important. In this paper, a new network model is constructed for analyzing the railway safety, in which nodes are regarded as causation factors and links represent possible relationships among those factors. Our aim is to give all these nodes an importance order, and to find the in-depth relationship among these nodes including how failures spread among them. Based on the constructed network model, we propose a control method to ensure the safe state by setting each node a threshold. As the results, by protecting the Hub node of the constructed network, the spreading of railway accident can be controlled well. The efficiency of such a method is further tested with the help of numerical example.

Encapsulating Urban Traffic Rhythms into Road Networks

PubMed Central

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

2014-01-01

Using road GIS (geographical information systems) data and travel demand data for two U.S. urban areas, the dynamical driver sources of each road segment were located. A method to target road clusters closely related to urban traffic congestion was then developed to improve road network efficiency. The targeted road clusters show different spatial distributions at different times of a day, indicating that our method can encapsulate dynamical travel demand information into the road networks. As a proof of concept, when we lowered the speed limit or increased the capacity of road segments in the targeted road clusters, we found that both the number of congested roads and extra travel time were effectively reduced. In addition, the proposed modeling framework provided new insights on the optimization of transport efficiency in any infrastructure network with a specific supply and demand distribution. PMID:24553203

Heterogeneous delivering capability promotes traffic efficiency in complex networks

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

Uganda's National Transmission Backbone Infrastructure Project: Technical Challenges and the Way Forward

NASA Astrophysics Data System (ADS)

Bulega, T.; Kyeyune, A.; Onek, P.; Sseguya, R.; Mbabazi, D.; Katwiremu, E.

2011-10-01

Several publications have identified technical challenges facing Uganda's National Transmission Backbone Infrastructure project. This research addresses the technical limitations of the National Transmission Backbone Infrastructure project, evaluates the goals of the project, and compares the results against the technical capability of the backbone. The findings of the study indicate a bandwidth deficit, which will be addressed by using dense wave division multiplexing repeaters, leasing bandwidth from private companies. Microwave links for redundancy, a Network Operation Center for operation and maintenance, and deployment of wireless interoperability for microwave access as a last-mile solution are also suggested.

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

PubMed

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

2015-01-01

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

How Travel Demand Affects Detection of Non-Recurrent Traffic Congestion on Urban Road Networks

NASA Astrophysics Data System (ADS)

Anbaroglu, B.; Heydecker, B.; Cheng, T.

2016-06-01

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

PubMed Central

Zhang, Jisheng; Jia, Limin; Niu, Shuyun; Zhang, Fan; Tong, Lu; Zhou, Xuesong

2015-01-01

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. PMID:26076404

An optimal general type-2 fuzzy controller for Urban Traffic Network.

PubMed

Khooban, Mohammad Hassan; Vafamand, Navid; Liaghat, Alireza; Dragicevic, Tomislav

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 of input and output membership functions are optimized simultaneously by the novel heuristic algorithm MBSA. A comparison is made between the achieved results with those of optimal and conventional type-1 fuzzy logic controllers. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Fermi-Dirac statistics and traffic in complex networks.

PubMed

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.

Predicting backbone Cα angles and dihedrals from protein sequences by stacked sparse auto-encoder deep neural network.

PubMed

Lyons, James; Dehzangi, Abdollah; Heffernan, Rhys; Sharma, Alok; Paliwal, Kuldip; Sattar, Abdul; Zhou, Yaoqi; Yang, Yuedong

2014-10-30

Because a nearly constant distance between two neighbouring Cα atoms, local backbone structure of proteins can be represented accurately by the angle between C(αi-1)-C(αi)-C(αi+1) (θ) and a dihedral angle rotated about the C(αi)-C(αi+1) bond (τ). θ and τ angles, as the representative of structural properties of three to four amino-acid residues, offer a description of backbone conformations that is complementary to φ and ψ angles (single residue) and secondary structures (>3 residues). Here, we report the first machine-learning technique for sequence-based prediction of θ and τ angles. Predicted angles based on an independent test have a mean absolute error of 9° for θ and 34° for τ with a distribution on the θ-τ plane close to that of native values. The average root-mean-square distance of 10-residue fragment structures constructed from predicted θ and τ angles is only 1.9Å from their corresponding native structures. Predicted θ and τ angles are expected to be complementary to predicted ϕ and ψ angles and secondary structures for using in model validation and template-based as well as template-free structure prediction. The deep neural network learning technique is available as an on-line server called Structural Property prediction with Integrated DEep neuRal network (SPIDER) at http://sparks-lab.org. Copyright © 2014 Wiley Periodicals, Inc.

Building a Multivariable Linear Regression Model of On-road Traffic for Creation of High Resolution Emission Inventories

NASA Astrophysics Data System (ADS)

Powell, James Eckhardt

Emissions inventories are an important tool, often built by governments, and used to manage emissions. To build an inventory of urban CO2 emissions and other fossil fuel combustion products in the urban atmosphere, an inventory of on-road traffic is required. In particular, a high resolution inventory is necessary to capture the local characteristics of transport emissions. These emissions vary widely due to the local nature of the fleet, fuel, and roads. Here we show a new model of ADT for the Portland, OR metropolitan region. The backbone is traffic counter recordings made by the Portland Bureau of Transportation at 7,767 sites over 21 years (1986-2006), augmented with PORTAL (The Portland Regional Transportation Archive Listing) freeway traffic count data. We constructed a regression model to fill in traffic network gaps using GIS data such as road class and population density. An EPA-supplied emissions factor was used to estimate transportation CO2 emissions, which is compared to several other estimates for the city's CO2 footprint.

Route guidance strategies revisited: Comparison and evaluation in an asymmetric two-route traffic network

NASA Astrophysics Data System (ADS)

He, Zhengbing; Chen, Bokui; Jia, Ning; Guan, Wei; Lin, Benchuan; Wang, Binghong

2014-12-01

To alleviate traffic congestion, a variety of route guidance strategies have been proposed for intelligent transportation systems. A number of strategies are introduced and investigated on a symmetric two-route traffic network over the past decade. To evaluate the strategies in a more general scenario, this paper conducts eight prevalent strategies on an asymmetric two-route traffic network with different slowdown behaviors on alternative routes. The results show that only mean velocity feedback strategy (MVFS) is able to equalize travel time, i.e. approximate user optimality (UO); while the others fail due to incapability of establishing relations between the feedback parameters and travel time. The paper helps better understand these strategies, and suggests MVFS if the authority intends to achieve user optimality.

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

PubMed

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

2016-01-01

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

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

PubMed Central

Al-Shargabi, Mohammed A.; Ismail, Abdulsamad S.

2016-01-01

Optical burst switching (OBS) networks have been attracting much consideration as a promising approach to build the next generation optical Internet. A solution for enhancing the Quality of Service (QoS) for high priority real time traffic over OBS with the fairness among the traffic types is absent in current OBS’ QoS schemes. In this paper we present a novel Real Time Quality of Service with Fairness Ratio (RT-QoSFR) scheme that can adapt the burst assembly parameters according to the traffic QoS needs in order to enhance the real time traffic QoS requirements and to ensure the fairness for other traffic. The results show that RT-QoSFR scheme is able to fulfill the real time traffic requirements (end to end delay, and loss rate) ensuring the fairness for other traffics under various conditions such as the type of real time traffic and traffic load. RT-QoSFR can guarantee that the delay of the real time traffic packets does not exceed the maximum packets transfer delay value. Furthermore, it can reduce the real time traffic packets loss, at the same time guarantee the fairness for non real time traffic packets by determining the ratio of real time traffic inside the burst to be 50–60%, 30–40%, and 10–20% for high, normal, and low traffic loads respectively. PMID:27583557

Advanced Models and Algorithms for Self-Similar IP Network Traffic Simulation and Performance Analysis

NASA Astrophysics Data System (ADS)

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.

Traffic protection in MPLS networks using an off-line flow optimization model

NASA Astrophysics Data System (ADS)

Krzesinski, Anthony E.; Muller, Karen E.

2002-07-01

MPLS-based recovery is intended to effect rapid and complete restoration of traffic affected by a fault in an MPLS network. Two MPLS-based recovery models have been proposed: IP re-routing which establishes recovery paths on demand, and protection switching which works with pre-established recovery paths. IP re-routing is robust and frugal since no resources are pre-committed but is inherently slower than protection switching which is intended to offer high reliability to premium services where fault recovery takes place at the 100 ms time scale. We present a model of protection switching in MPLS networks. A variant of the flow deviation method is used to find and capacitate a set of optimal label switched paths. The traffic is routed over a set of working LSPs. Global repair is implemented by reserving a set of pre-established recovery LSPs. An analytic model is used to evaluate the MPLS-based recovery mechanisms in response to bi-directional link failures. A simulation model is used to evaluate the MPLS recovery cycle in terms of the time needed to restore the traffic after a uni-directional link failure. The models are applied to evaluate the effectiveness of protection switching in networks consisting of between 20 and 100 nodes.

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sossoe, K.S., E-mail: kwami.sossoe@irt-systemx.fr; Lebacque, J-P., E-mail: jean-patrick.lebacque@ifsttar.fr

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 schememore » is introduced to numerically approximate the model’s flow equations.« less

From trees to forest: relational complexity network and workload of air traffic controllers.

PubMed

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.

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Keim, Daniel; Pras, Aiko; Schonwalder, Jurgen

2011-01-26

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

Effects of packet retransmission with finite packet lifetime on traffic capacity in scale-free networks

NASA Astrophysics Data System (ADS)

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.

Traffic Generator (TrafficGen) Version 1.4.2: Users Guide

DTIC Science & Technology

2016-06-01

events, the user has to enter them manually . We will research and implement a way to better define and organize the multicast addresses so they can be...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

Betweenness centrality in a weighted network

NASA Astrophysics Data System (ADS)

Wang, Huijuan; Hernandez, Javier Martin; van Mieghem, Piet

2008-04-01

When transport in networks follows the shortest paths, the union of all shortest path trees G∪SPT can be regarded as the “transport overlay network.” Overlay networks such as peer-to-peer networks or virtual private networks can be considered as a subgraph of G∪SPT . The traffic through the network is examined by the betweenness Bl of links in the overlay G∪SPT . The strength of disorder can be controlled by, e.g., tuning the extreme value index α of the independent and identically distributed polynomial link weights. In the strong disorder limit (α→0) , all transport flows over a critical backbone, the minimum spanning tree (MST). We investigate the betweenness distributions of wide classes of trees, such as the MST of those well-known network models and of various real-world complex networks. All these trees with different degree distributions (e.g., uniform, exponential, or power law) are found to possess a power law betweenness distribution Pr[Bl=j]˜j-c . The exponent c seems to be positively correlated with the degree variance of the tree and to be insensitive of the size N of a network. In the weak disorder regime, transport in the network traverses many links. We show that a link with smaller link weight tends to carry more traffic. This negative correlation between link weight and betweenness depends on α and the structure of the underlying topology.

Using mobile probes to inform and measure the effectiveness of traffic control strategies on urban networks.

DOT National Transportation Integrated Search

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

NASA Astrophysics Data System (ADS)

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.

Designing area optimized application-specific network-on-chip architectures while providing hard QoS guarantees.

PubMed

Khawaja, Sajid Gul; Mushtaq, Mian Hamza; Khan, Shoab A; Akram, M Usman; Jamal, Habib Ullah

2015-01-01

With the increase of transistors' density, popularity of System on Chip (SoC) has increased exponentially. As a communication module for SoC, Network on Chip (NoC) framework has been adapted as its backbone. In this paper, we propose a methodology for designing area-optimized application specific NoC while providing hard Quality of Service (QoS) guarantees for real time flows. The novelty of the proposed system lies in derivation of a Mixed Integer Linear Programming model which is then used to generate a resource optimal Network on Chip (NoC) topology and architecture while considering traffic and QoS requirements. We also present the micro-architectural design features used for enabling traffic and latency guarantees and discuss how the solution adapts for dynamic variations in the application traffic. The paper highlights the effectiveness of proposed method by generating resource efficient NoC solutions for both industrial and benchmark applications. The area-optimized results are generated in few seconds by proposed technique, without resorting to heuristics, even for an application with 48 traffic flows.

Designing Area Optimized Application-Specific Network-On-Chip Architectures while Providing Hard QoS Guarantees

PubMed Central

Khawaja, Sajid Gul; Mushtaq, Mian Hamza; Khan, Shoab A.; Akram, M. Usman; Jamal, Habib ullah

2015-01-01

With the increase of transistors' density, popularity of System on Chip (SoC) has increased exponentially. As a communication module for SoC, Network on Chip (NoC) framework has been adapted as its backbone. In this paper, we propose a methodology for designing area-optimized application specific NoC while providing hard Quality of Service (QoS) guarantees for real time flows. The novelty of the proposed system lies in derivation of a Mixed Integer Linear Programming model which is then used to generate a resource optimal Network on Chip (NoC) topology and architecture while considering traffic and QoS requirements. We also present the micro-architectural design features used for enabling traffic and latency guarantees and discuss how the solution adapts for dynamic variations in the application traffic. The paper highlights the effectiveness of proposed method by generating resource efficient NoC solutions for both industrial and benchmark applications. The area-optimized results are generated in few seconds by proposed technique, without resorting to heuristics, even for an application with 48 traffic flows. PMID:25898016

Fiber fault location utilizing traffic signal in optical network.

PubMed

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.

Quantitative Assessment of Transportation Network Vulnerability with Dynamic Traffic Simulation Methods

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shekar, Venkateswaran; Fiondella, Lance; Chatterjee, Samrat

Transportation networks are critical to the social and economic function of nations. Given the continuing increase in the populations of cities throughout the world, the criticality of transportation infrastructure is expected to increase. Thus, it is ever more important to mitigate congestion as well as to assess the impact disruptions would have on individuals who depend on transportation for their work and livelihood. Moreover, several government organizations are responsible for ensuring transportation networks are available despite the constant threat of natural disasters and terrorist activities. Most of the previous transportation network vulnerability research has been performed in the context ofmore » static traffic models, many of which are formulated as traditional optimization problems. However, transportation networks are dynamic because their usage varies over time. Thus, more appropriate methods to characterize the vulnerability of transportation networks should consider their dynamic properties. This paper presents a quantitative approach to assess the vulnerability of a transportation network to disruptions with methods from traffic simulation. Our approach can prioritize the critical links over time and is generalizable to the case where both link and node disruptions are of concern. We illustrate the approach through a series of examples. Our results demonstrate that the approach provides quantitative insight into the time varying criticality of links. Such an approach could be used as the objective function of less traditional optimization methods that use simulation and other techniques to evaluate the relative utility of a particular network defense to reduce vulnerability and increase resilience.« less

Self-Learning Intelligent Agents for Dynamic Traffic Routing on Transportation Networks

NASA Astrophysics Data System (ADS)

Sadek, Add; Basha, Nagi

Intelligent Transportation Systems (ITS) are designed to take advantage of recent advances in communications, electronics, and Information Technology in improving the efficiency and safety of transportation systems. Among the several ITS applications is the notion of Dynamic Traffic Routing (DTR), which involves generating "optimal" routing recommendations to drivers with the aim of maximizing network utilizing. In this paper, we demonstrate the feasibility of using a self-learning intelligent agent to solve the DTR problem to achieve traffic user equilibrium in a transportation network. The core idea is to deploy an agent to a simulation model of a highway. The agent then learns by itself by interacting with the simulation model. Once the agent reaches a satisfactory level of performance, it can then be deployed to the real-world, where it would continue to learn how to refine its control policies over time. To test this concept in this paper, the Cell Transmission Model (CTM) developed by Carlos Daganzo of the University of California at Berkeley is used to simulate a simple highway with two main alternative routes. With the model developed, a Reinforcement Learning Agent (RLA) is developed to learn how to best dynamically route traffic, so as to maximize the utilization of existing capacity. Preliminary results obtained from our experiments are promising. RL, being an adaptive online learning technique, appears to have a great potential for controlling a stochastic dynamic systems such as a transportation system. Furthermore, the approach is highly scalable and applicable to a variety of networks and roadways.

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

PubMed

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

2015-01-01

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

An Enhanced Backbone-Assisted Reliable Framework for Wireless Sensor Networks

PubMed Central

Tufail, Ali; Khayam, Syed Ali; Raza, Muhammad Taqi; Ali, Amna; Kim, Ki-Hyung

2010-01-01

An extremely reliable source to sink communication is required for most of the contemporary WSN applications especially pertaining to military, healthcare and disaster-recovery. However, due to their intrinsic energy, bandwidth and computational constraints, Wireless Sensor Networks (WSNs) encounter several challenges in reliable source to sink communication. In this paper, we present a novel reliable topology that uses reliable hotlines between sensor gateways to boost the reliability of end-to-end transmissions. This reliable and efficient routing alternative reduces the number of average hops from source to the sink. We prove, with the help of analytical evaluation, that communication using hotlines is considerably more reliable than traditional WSN routing. We use reliability theory to analyze the cost and benefit of adding gateway nodes to a backbone-assisted WSN. However, in hotline assisted routing some scenarios where source and the sink are just a couple of hops away might bring more latency, therefore, we present a Signature Based Routing (SBR) scheme. SBR enables the gateways to make intelligent routing decisions, based upon the derived signature, hence providing lesser end-to-end delay between source to the sink communication. Finally, we evaluate our proposed hotline based topology with the help of a simulation tool and show that the proposed topology provides manifold increase in end-to-end reliability. PMID:22294890

Dynamic segment shared protection for multicast traffic in meshed wavelength-division-multiplexing optical networks

NASA Astrophysics Data System (ADS)

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.

Achieving End-to-End QoS in the Next Generation Internet: Integrated Services Over Differentiated Service Networks

NASA Technical Reports Server (NTRS)

Bai, Haowei; Atiquzzaman, Mohammed; Ivancic, William

2001-01-01

Currently there are two approaches to provide Quality of Service (QoS) in the next generation Internet: An early one is the Integrated Services (IntServ) with the goal of allowing end-to-end QoS to be provided to applications; the other one is the Differentiated Services (DiffServ) architecture providing QoS in the backbone. In this context, a DiffServ network may be viewed as a network element in the total end-to-end path. The objective of this paper is to investigate the possibility of providing end-to-end QoS when IntServ runs over DiffServ backbone in the next generation Internet. Our results show that the QoS requirements of IntServ applications can be successfully achieved when IntServ traffic is mapped to the DiffServ domain in next generation Internet.

Achieving End-to-End QoS in the Next Generation Internet: Integrated Services over Differentiated Service Networks

NASA Technical Reports Server (NTRS)

Bai, Haowei; Atiquzzaman, Mohammed; Ivancic, William

2001-01-01

Currently there are two approaches to provide Quality of Service (QoS) in the next generation Internet: An early one is the Integrated Services (IntServ) with the goal of allowing end-to-end QoS to be provided to applications; the other one is the Differentiated Services (DiffServ) architecture providing QoS in the backbone. In this context, a DiffServ network may be viewed as a network element in the total end-to-end path. The objective of this paper is to investigate the possibility of providing end-to-end QoS when IntServ runs over DiffServ backbone in the next generation Internet. Our results show that the QoS requirements of IntServ applications can be successfully achieved when IntServ traffic is mapped to the DiffServ domain in next generation Internet.

Optical RRH working in an all-optical fronthaul network

NASA Astrophysics Data System (ADS)

Zakrzewski, Zbigniew

2017-12-01

The paper presents an example of an optical RRH (Remote Radio Head) design, which is equipped with photonic components for direct connection to an all-optical network. The features that can be fulfilled by an all-optical network are indicated to support future 5G mobile networks. The demand for optical bandwidth in fronthaul/midhaul distribution network links, working in D-RoF and A-RoF formats was performed. The increase in demand is due to the very large traffic generated by the Optical Massive-MIMO RRH/RRU will work in format of an Active-Distributed Antenna System (A-DAS). An exemplary next-generation mobile network that will utilize O-RRH and an all-optical backbone is presented. All components of presented network will work in the Centralized/Cloud Radio Access Network (C-RAN) architecture, which is achievable by control with the use of the OpenFlow (OF).

Framework for waveband switching in multigranular optical networks: part I-multigranular cross-connect architectures [Invited

NASA Astrophysics Data System (ADS)

Cao, Xiaojun; Anand, Vishal; Qiao, Chunming

2006-12-01

Optical networks using wavelength-division multiplexing (WDM) are the foremost solution to the ever-increasing traffic in the Internet backbone. Rapid advances in WDM technology will enable each fiber to carry hundreds or even a thousand wavelengths (using dense-WDM, or DWDM, and ultra-DWDM) of traffic. This, coupled with worldwide fiber deployment, will bring about a tremendous increase in the size of the optical cross-connects, i.e., the number of ports of the wavelength switching elements. Waveband switching (WBS), wherein wavelengths are grouped into bands and switched as a single entity, can reduce the cost and control complexity of switching nodes by minimizing the port count. This paper presents a detailed study on recent advances and open research issues in WBS networks. In this study, we investigate in detail the architecture for various WBS cross-connects and compare them in terms of the number of ports and complexity and also in terms of how flexible they are in adjusting to dynamic traffic. We outline various techniques for grouping wavelengths into bands for the purpose of WBS and show how traditional wavelength routing is different from waveband routing and why techniques developed for wavelength-routed networks (WRNs) cannot be simply applied to WBS networks. We also outline how traffic grooming of subwavelength traffic can be done in WBS networks. In part II of this study [Cao , submitted to J. Opt. Netw.], we study the effect of wavelength conversion on the performance of WBS networks with reconfigurable MG-OXCs. We present an algorithm for waveband grouping in wavelength-convertible networks and evaluate its performance. We also investigate issues related to survivability in WBS networks and show how waveband and wavelength conversion can be used to recover from failures in WBS networks.

Using mobile probes to inform and measure the effectiveness of macroscopic traffic control strategies on urban networks.

DOT National Transportation Integrated Search

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

NASA Astrophysics Data System (ADS)

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.

TCP throughput adaptation in WiMax networks using replicator dynamics.

PubMed

Anastasopoulos, Markos P; Petraki, Dionysia K; Kannan, Rajgopal; Vasilakos, Athanasios V

2010-06-01

The high-frequency segment (10-66 GHz) of the IEEE 802.16 standard seems promising for the implementation of wireless backhaul networks carrying large volumes of Internet traffic. In contrast to wireline backbone networks, where channel errors seldom occur, the TCP protocol in IEEE 802.16 Worldwide Interoperability for Microwave Access networks is conditioned exclusively by wireless channel impairments rather than by congestion. This renders a cross-layer design approach between the transport and physical layers more appropriate during fading periods. In this paper, an adaptive coding and modulation (ACM) scheme for TCP throughput maximization is presented. In the current approach, Internet traffic is modulated and coded employing an adaptive scheme that is mathematically equivalent to the replicator dynamics model. The stability of the proposed ACM scheme is proven, and the dependence of the speed of convergence on various physical-layer parameters is investigated. It is also shown that convergence to the strategy that maximizes TCP throughput may be further accelerated by increasing the amount of information from the physical layer.

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

NASA Astrophysics Data System (ADS)

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.

Noise-Assisted Concurrent Multipath Traffic Distribution in Ad Hoc Networks

PubMed Central

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

Visualization of Traffic Accidents

NASA Technical Reports Server (NTRS)

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.

Information transmission on hybrid networks

NASA Astrophysics Data System (ADS)

Chen, Rongbin; Cui, Wei; Pu, Cunlai; Li, Jie; Ji, Bo; Gakis, Konstantinos; Pardalos, Panos M.

2018-01-01

Many real-world communication networks often have hybrid nature with both fixed nodes and moving modes, such as the mobile phone networks mainly composed of fixed base stations and mobile phones. In this paper, we discuss the information transmission process on the hybrid networks with both fixed and mobile nodes. The fixed nodes (base stations) are connected as a spatial lattice on the plane forming the information-carrying backbone, while the mobile nodes (users), which are the sources and destinations of information packets, connect to their current nearest fixed nodes respectively to deliver and receive information packets. We observe the phase transition of traffic load in the hybrid network when the packet generation rate goes from below and then above a critical value, which measures the network capacity of packets delivery. We obtain the optimal speed of moving nodes leading to the maximum network capacity. We further improve the network capacity by rewiring the fixed nodes and by considering the current load of fixed nodes during packets transmission. Our purpose is to optimize the network capacity of hybrid networks from the perspective of network science, and provide some insights for the construction of future communication infrastructures.

A Wireless Sensor Network for Urban Traffic Characterization and Trend Monitoring

PubMed Central

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

2015-01-01

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. PMID:26501278

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

PubMed

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.

Triazine-Based Sequence-Defined Polymers with Side-Chain Diversity and Backbone-Backbone Interaction Motifs.

PubMed

Grate, Jay W; Mo, Kai-For; Daily, Michael D

2016-03-14

Sequence control in polymers, well-known in nature, encodes structure and functionality. Here we introduce a new architecture, based on the nucleophilic aromatic substitution chemistry of cyanuric chloride, that creates a new class of sequence-defined polymers dubbed TZPs. Proof of concept is demonstrated with two synthesized hexamers, having neutral and ionizable side chains. Molecular dynamics simulations show backbone-backbone interactions, including H-bonding motifs and pi-pi interactions. This architecture is arguably biomimetic while differing from sequence-defined polymers having peptide bonds. The synthetic methodology supports the structural diversity of side chains known in peptides, as well as backbone-backbone hydrogen-bonding motifs, and will thus enable new macromolecules and materials with useful functions. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

PubMed Central

Sajeel, Muhammad; Bashir, Faisal; Asfand-e-yar, Muhammad; Tauqir, Muhammad

2017-01-01

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 (CAP)with 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). PMID:28832495

Automatic detection and recognition of traffic signs in stereo images based on features and probabilistic neural networks

NASA Astrophysics Data System (ADS)

Sheng, Yehua; Zhang, Ka; Ye, Chun; Liang, Cheng; Li, Jian

2008-04-01

Considering the problem of automatic traffic sign detection and recognition in stereo images captured under motion conditions, a new algorithm for traffic sign detection and recognition based on features and probabilistic neural networks (PNN) is proposed in this paper. Firstly, global statistical color features of left image are computed based on statistics theory. Then for red, yellow and blue traffic signs, left image is segmented to three binary images by self-adaptive color segmentation method. Secondly, gray-value projection and shape analysis are used to confirm traffic sign regions in left image. Then stereo image matching is used to locate the homonymy traffic signs in right image. Thirdly, self-adaptive image segmentation is used to extract binary inner core shapes of detected traffic signs. One-dimensional feature vectors of inner core shapes are computed by central projection transformation. Fourthly, these vectors are input to the trained probabilistic neural networks for traffic sign recognition. Lastly, recognition results in left image are compared with recognition results in right image. If results in stereo images are identical, these results are confirmed as final recognition results. The new algorithm is applied to 220 real images of natural scenes taken by the vehicle-borne mobile photogrammetry system in Nanjing at different time. Experimental results show a detection and recognition rate of over 92%. So the algorithm is not only simple, but also reliable and high-speed on real traffic sign detection and recognition. Furthermore, it can obtain geometrical information of traffic signs at the same time of recognizing their types.

Competition between Local Collisions and Collective Hydrodynamic Feedback Controls Traffic Flows in Microfluidic Networks

NASA Astrophysics Data System (ADS)

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.

Design and implementation of priority and time-window based traffic scheduling and routing-spectrum allocation mechanism in elastic optical networks

NASA Astrophysics Data System (ADS)

Wang, Honghuan; Xing, Fangyuan; Yin, Hongxi; Zhao, Nan; Lian, Bizhan

2016-02-01

With the explosive growth of network services, the reasonable traffic scheduling and efficient configuration of network resources have an important significance to increase the efficiency of the network. In this paper, an adaptive traffic scheduling policy based on the priority and time window is proposed and the performance of this algorithm is evaluated in terms of scheduling ratio. The routing and spectrum allocation are achieved by using the Floyd shortest path algorithm and establishing a node spectrum resource allocation model based on greedy algorithm, which is proposed by us. The fairness index is introduced to improve the capability of spectrum configuration. The results show that the designed traffic scheduling strategy can be applied to networks with multicast and broadcast functionalities, and makes them get real-time and efficient response. The scheme of node spectrum configuration improves the frequency resource utilization and gives play to the efficiency of the network.

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

NASA Astrophysics Data System (ADS)

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

DOT National Transportation Integrated Search

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...

Data communication network at the ASRM facility

NASA Astrophysics Data System (ADS)

Moorhead, Robert J., II; Smith, Wayne D.

1993-08-01

This report describes the simulation of the overall communication network structure for the Advanced Solid Rocket Motor (ASRM) facility being built at Yellow Creek near Iuka, Mississippi as of today. The report is compiled using information received from NASA/MSFC, LMSC, AAD, and RUST Inc. As per the information gathered, the overall network structure will have one logical FDDI ring acting as a backbone for the whole complex. The buildings will be grouped into two categories viz. manufacturing intensive and manufacturing non-intensive. The manufacturing intensive buildings will be connected via FDDI to the Operational Information System (OIS) in the main computing center in B_1000. The manufacturing non-intensive buildings will be connected by 10BASE-FL to the OIS through the Business Information System (BIS) hub in the main computing center. All the devices inside B_1000 will communicate with the BIS. The workcells will be connected to the Area Supervisory Computers (ASCs) through the nearest manufacturing intensive hub and one of the OIS hubs. Comdisco's Block Oriented Network Simulator (BONeS) has been used to simulate the performance of the network. BONeS models a network topology, traffic, data structures, and protocol functions using a graphical interface. The main aim of the simulations was to evaluate the loading of the OIS, the BIS, and the ASCs, and the network links by the traffic generated by the workstations and workcells throughout the site.

Data communication network at the ASRM facility

NASA Technical Reports Server (NTRS)

Moorhead, Robert J., II; Smith, Wayne D.

1993-01-01

This report describes the simulation of the overall communication network structure for the Advanced Solid Rocket Motor (ASRM) facility being built at Yellow Creek near Iuka, Mississippi as of today. The report is compiled using information received from NASA/MSFC, LMSC, AAD, and RUST Inc. As per the information gathered, the overall network structure will have one logical FDDI ring acting as a backbone for the whole complex. The buildings will be grouped into two categories viz. manufacturing intensive and manufacturing non-intensive. The manufacturing intensive buildings will be connected via FDDI to the Operational Information System (OIS) in the main computing center in B_1000. The manufacturing non-intensive buildings will be connected by 10BASE-FL to the OIS through the Business Information System (BIS) hub in the main computing center. All the devices inside B_1000 will communicate with the BIS. The workcells will be connected to the Area Supervisory Computers (ASCs) through the nearest manufacturing intensive hub and one of the OIS hubs. Comdisco's Block Oriented Network Simulator (BONeS) has been used to simulate the performance of the network. BONeS models a network topology, traffic, data structures, and protocol functions using a graphical interface. The main aim of the simulations was to evaluate the loading of the OIS, the BIS, and the ASCs, and the network links by the traffic generated by the workstations and workcells throughout the site.

Fixed Point Learning Based Intelligent Traffic Control System

NASA Astrophysics Data System (ADS)

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.

PubMed

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

TrafficGen Architecture Document

DTIC Science & Technology

2016-01-01

sequence diagram ....................................................5 Fig. 5 TrafficGen traffic flows viewed in SDT3D...Scripts contain commands to have the network node listen on specific ports and flows describing the start time, stop time, and specific traffic ...arranged vertically and time presented horizontally. Individual traffic flows are represented by horizontal bars indicating the start time, stop time

Impairment assessment of orthogonal frequency division multiplexing over dispersion-managed links in backbone and backhaul networks

NASA Astrophysics Data System (ADS)

Tamilarasan, Ilavarasan; Saminathan, Brindha; Murugappan, Meenakshi

2016-04-01

The past decade has seen the phenomenal usage of orthogonal frequency division multiplexing (OFDM) in the wired as well as wireless communication domains, and it is also proposed in the literature as a future proof technique for the implementation of flexible resource allocation in cognitive optical networks. Fiber impairment assessment and adaptive compensation becomes critical in such implementations. A comprehensive analytical model for impairments in OFDM-based fiber links is developed. The proposed model includes the combined impact of laser phase fluctuations, fiber dispersion, self phase modulation, cross phase modulation, four-wave mixing, the nonlinear phase noise due to the interaction of amplified spontaneous emission with fiber nonlinearities, and the photodetector noises. The bit error rate expression for the proposed model is derived based on error vector magnitude estimation. The performance analysis of the proposed model is presented and compared for dispersion compensated and uncompensated backbone/backhaul links. The results suggest that OFDM would perform better for uncompensated links than the compensated links due to the negligible FWM effects and there is a need for flexible compensation. The proposed model can be employed in cognitive optical networks for accurate assessment of fiber-related impairments.

A QoS Framework with Traffic Request in Wireless Mesh Network

NASA Astrophysics Data System (ADS)

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.

Traffic-engineering-aware shortest-path routing and its application in IP-over-WDM networks [Invited

NASA Astrophysics Data System (ADS)

Lee, Youngseok; Mukherjee, Biswanath

2004-03-01

Single shortest-path routing is known to perform poorly for Internet traffic engineering (TE) where the typical optimization objective is to minimize the maximum link load. Splitting traffic uniformly over equal-cost multiple shortest paths in open shortest path first and intermediate system-intermediate system protocols does not always minimize the maximum link load when multiple paths are not carefully selected for the global traffic demand matrix. However, a TE-aware shortest path among all the equal-cost multiple shortest paths between each ingress-egress pair can be selected such that the maximum link load is significantly reduced. IP routers can use the globally optimal TE-aware shortest path without any change to existing routing protocols and without any serious configuration overhead. While calculating TE-aware shortest paths, the destination-based forwarding constraint at a node should be satisfied, because an IP router will forward a packet to the next hop toward the destination by looking up the destination prefix. We present a mathematical problem formulation for finding a set of TE-aware shortest paths for the given network as an integer linear program, and we propose a simple heuristic for solving large instances of the problem. Then we explore the usage of our proposed algorithm for the integrated TE method in IP-over-WDM networks. The proposed algorithm is evaluated through simulations in IP networks as well as in IP-over-WDM networks.

Conservation of high-flux backbone in alternate optimal and near-optimal flux distributions of metabolic networks.

PubMed

Samal, Areejit

2008-12-01

Constraint-based flux balance analysis (FBA) has proven successful in predicting the flux distribution of metabolic networks in diverse environmental conditions. FBA finds one of the alternate optimal solutions that maximizes the biomass production rate. Almaas et al. have shown that the flux distribution follows a power law, and it is possible to associate with most metabolites two reactions which maximally produce and consume a given metabolite, respectively. This observation led to the concept of high-flux backbone (HFB) in metabolic networks. In previous work, the HFB has been computed using a particular optima obtained using FBA. In this paper, we investigate the conservation of HFB of a particular solution for a given medium across different alternate optima and near-optima in metabolic networks of E. coli and S. cerevisiae. Using flux variability analysis (FVA), we propose a method to determine reactions that are guaranteed to be in HFB regardless of alternate solutions. We find that the HFB of a particular optima is largely conserved across alternate optima in E. coli, while it is only moderately conserved in S. cerevisiae. However, the HFB of a particular near-optima shows a large variation across alternate near-optima in both organisms. We show that the conserved set of reactions in HFB across alternate near-optima has a large overlap with essential reactions and reactions which are both uniquely consuming (UC) and uniquely producing (UP). Our findings suggest that the structure of the metabolic network admits a high degree of redundancy and plasticity in near-optimal flow patterns enhancing system robustness for a given environmental condition.

Ontology-Based Architecture for Intelligent Transportation Systems Using a Traffic Sensor Network.

PubMed

Fernandez, Susel; Hadfi, Rafik; Ito, Takayuki; Marsa-Maestre, Ivan; Velasco, Juan R

2016-08-15

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.

Ontology-Based Architecture for Intelligent Transportation Systems Using a Traffic Sensor Network

PubMed Central

Fernandez, Susel; Hadfi, Rafik; Ito, Takayuki; Marsa-Maestre, Ivan; Velasco, Juan R.

2016-01-01

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. PMID:27537878

Extracting the Information Backbone in Online System

PubMed Central

Zhang, Qian-Ming; Zeng, An; Shang, Ming-Sheng

2013-01-01

Information overload is a serious problem in modern society and many solutions such as recommender system have been proposed to filter out irrelevant information. In the literature, researchers have been mainly dedicated to improving the recommendation performance (accuracy and diversity) of the algorithms while they have overlooked the influence of topology of the online user-object bipartite networks. In this paper, we find that some information provided by the bipartite networks is not only redundant but also misleading. With such “less can be more” feature, we design some algorithms to improve the recommendation performance by eliminating some links from the original networks. Moreover, we propose a hybrid method combining the time-aware and topology-aware link removal algorithms to extract the backbone which contains the essential information for the recommender systems. From the practical point of view, our method can improve the performance and reduce the computational time of the recommendation system, thus improving both of their effectiveness and efficiency. PMID:23690946

Monitor Network Traffic with Packet Capture (pcap) on an Android Device

DTIC Science & Technology

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

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

NASA Astrophysics Data System (ADS)

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.

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

NASA Technical Reports Server (NTRS)

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.

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

PubMed Central

Kerkhove, Dwight; Tian, Le; Munteanu, Adrian; De Poorter, Eli

2018-01-01

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

Bayesian networks for maritime traffic accident prevention: benefits and challenges.

PubMed

Hänninen, Maria

2014-12-01

Bayesian networks are quantitative modeling tools whose applications to the maritime traffic safety context are becoming more popular. This paper discusses the utilization of Bayesian networks in maritime safety modeling. Based on literature and the author's own experiences, the paper studies what Bayesian networks can offer to maritime accident prevention and safety modeling and discusses a few challenges in their application to this context. It is argued that the capability of representing rather complex, not necessarily causal but uncertain relationships makes Bayesian networks an attractive modeling tool for the maritime safety and accidents. Furthermore, as the maritime accident and safety data is still rather scarce and has some quality problems, the possibility to combine data with expert knowledge and the easy way of updating the model after acquiring more evidence further enhance their feasibility. However, eliciting the probabilities from the maritime experts might be challenging and the model validation can be tricky. It is concluded that with the utilization of several data sources, Bayesian updating, dynamic modeling, and hidden nodes for latent variables, Bayesian networks are rather well-suited tools for the maritime safety management and decision-making. Copyright © 2014 Elsevier Ltd. All rights reserved.

Resource optimization scheme for multimedia-enabled wireless mesh networks.

PubMed

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

2014-08-08

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

Resource Optimization Scheme for Multimedia-Enabled Wireless Mesh Networks

PubMed Central

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

2014-01-01

Wireless mesh networking is a promising technology that can support numerous multimedia applications. Multimedia applications have stringent quality of service (QoS) requirements, i.e., bandwidth, delay, jitter, and packet loss ratio. Enabling such QoS-demanding applications over wireless mesh networks (WMNs) require QoS provisioning routing protocols that lead to the network resource underutilization problem. Moreover, random topology deployment leads to have some unused network resources. Therefore, resource optimization is one of the most critical design issues in multi-hop, multi-radio WMNs enabled with multimedia applications. Resource optimization has been studied extensively in the literature for wireless Ad Hoc and sensor networks, but existing studies have not considered resource underutilization issues caused by QoS provisioning routing and random topology deployment. Finding a QoS-provisioned path in wireless mesh networks is an NP complete problem. In this paper, we propose a novel Integer Linear Programming (ILP) optimization model to reconstruct the optimal connected mesh backbone topology with a minimum number of links and relay nodes which satisfies the given end-to-end QoS demands for multimedia traffic and identification of extra resources, while maintaining redundancy. We further propose a polynomial time heuristic algorithm called Link and Node Removal Considering Residual Capacity and Traffic Demands (LNR-RCTD). Simulation studies prove that our heuristic algorithm provides near-optimal results and saves about 20% of resources from being wasted by QoS provisioning routing and random topology deployment. PMID:25111241

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

DOT National Transportation Integrated Search

2014-04-01

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

Traffic intensity monitoring using multiple object detection with traffic surveillance cameras

NASA Astrophysics Data System (ADS)

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.

An Architectural Concept for Intrusion Tolerance in Air Traffic Networks

NASA Technical Reports Server (NTRS)

Maddalon, Jeffrey M.; Miner, Paul S.

2003-01-01

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

Supervised learning from human performance at the computationally hard problem of optimal traffic signal control on a network of junctions

PubMed Central

Box, Simon

2014-01-01

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. PMID:26064570

Supervised learning from human performance at the computationally hard problem of optimal traffic signal control on a network of junctions.

PubMed

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.

Traffic-Sensitive Live Migration of Virtual Machines

DOE Office of Scientific and Technical Information (OSTI.GOV)

Deshpande, Umesh; Keahey, Kate

2015-01-01

In this paper we address the problem of network contention between the migration traffic and the VM application traffic for the live migration of co-located Virtual Machines (VMs). When VMs are migrated with pre-copy, they run at the source host during the migration. Therefore the VM applications with predominantly outbound traffic contend with the outgoing migration traffic at the source host. Similarly, during post-copy migration, the VMs run at the destination host. Therefore the VM applications with predominantly inbound traffic contend with the incoming migration traffic at the destination host. Such a contention increases the total migration time of themore » VMs and degrades the performance of VM application. Here, we propose traffic-sensitive live VM migration technique to reduce the contention of migration traffic with the VM application traffic. It uses a combination of pre-copy and post-copy techniques for the migration of the co-located VMs, instead of relying upon any single pre-determined technique for the migration of all the VMs. We base the selection of migration techniques on VMs' network traffic profiles so that the direction of migration traffic complements the direction of the most VM application traffic. We have implemented a prototype of traffic-sensitive migration on the KVM/QEMU platform. In the evaluation, we compare traffic-sensitive migration against the approaches that use only pre-copy or only post-copy for VM migration. We show that our approach minimizes the network contention for migration, thus reducing the total migration time and the application degradation.« less

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

DOT National Transportation Integrated Search

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...

Cyber-physical networking for wireless mesh infrastructures

NASA Astrophysics Data System (ADS)

Mannweiler, C.; Lottermann, C.; Klein, A.; Schneider, J.; Schotten, H. D.

2012-09-01

This paper presents a novel approach for cyber-physical network control. "Cyber-physical" refers to the inclusion of different parameters and information sources, ranging from physical sensors (e.g. energy, temperature, light) to conventional network information (bandwidth, delay, jitter, etc.) to logical data providers (inference systems, user profiles, spectrum usage databases). For a consistent processing, collected data is represented in a uniform way, analyzed, and provided to dedicated network management functions and network services, both internally and, through an according API, to third party services. Specifically, in this work, we outline the design of sophisticated energy management functionalities for a hybrid wireless mesh network (WLAN for both backhaul traffic and access, GSM for access only), disposing of autonomous energy supply, in this case solar power. Energy consumption is optimized under the presumption of fluctuating power availability and considerable storage constraints, thus influencing, among others, handover and routing decisions. Moreover, advanced situation-aware auto-configuration and self-adaptation mechanisms are introduced for an autonomous operation of the network. The overall objective is to deploy a robust wireless access and backbone infrastructure with minimal operational cost and effective, cyber-physical control mechanisms, especially dedicated for rural or developing regions.

Towards Scalable Cost-Effective Service and Survivability Provisioning in Ultra High Speed Networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bin Wang

Optical transport networks based on wavelength division multiplexing (WDM) are considered to be the most appropriate choice for future Internet backbone. On the other hand, future DOE networks are expected to have the ability to dynamically provision on-demand survivable services to suit the needs of various high performance scientific applications and remote collaboration. Since a failure in aWDMnetwork such as a cable cut may result in a tremendous amount of data loss, efficient protection of data transport in WDM networks is therefore essential. As the backbone network is moving towards GMPLS/WDM optical networks, the unique requirement to support DOE’s sciencemore » mission results in challenging issues that are not directly addressed by existing networking techniques and methodologies. The objectives of this project were to develop cost effective protection and restoration mechanisms based on dedicated path, shared path, preconfigured cycle (p-cycle), and so on, to deal with single failure, dual failure, and shared risk link group (SRLG) failure, under different traffic and resource requirement models; to devise efficient service provisioning algorithms that deal with application specific network resource requirements for both unicast and multicast; to study various aspects of traffic grooming in WDM ring and mesh networks to derive cost effective solutions while meeting application resource and QoS requirements; to design various diverse routing and multi-constrained routing algorithms, considering different traffic models and failure models, for protection and restoration, as well as for service provisioning; to propose and study new optical burst switched architectures and mechanisms for effectively supporting dynamic services; and to integrate research with graduate and undergraduate education. All objectives have been successfully met. This report summarizes the major accomplishments of this project. The impact of the project manifests in many aspects

STUDY ON SUPPORTING FOR DRAWING UP THE BCP FOR URBAN EXPRESSWAY NETWORK USING BY TRAFFIC SIMULATION SYSTEM

NASA Astrophysics Data System (ADS)

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.

Uncovering the essential links in online commercial networks

NASA Astrophysics Data System (ADS)

Zeng, Wei; Fang, Meiling; Shao, Junming; Shang, Mingsheng

2016-09-01

Recommender systems are designed to effectively support individuals' decision-making process on various web sites. It can be naturally represented by a user-object bipartite network, where a link indicates that a user has collected an object. Recently, research on the information backbone has attracted researchers' interests, which is a sub-network with fewer nodes and links but carrying most of the relevant information. With the backbone, a system can generate satisfactory recommenda- tions while saving much computing resource. In this paper, we propose an enhanced topology-aware method to extract the information backbone in the bipartite network mainly based on the information of neighboring users and objects. Our backbone extraction method enables the recommender systems achieve more than 90% of the accuracy of the top-L recommendation, however, consuming only 20% links. The experimental results show that our method outperforms the alternative backbone extraction methods. Moreover, the structure of the information backbone is studied in detail. Finally, we highlight that the information backbone is one of the most important properties of the bipartite network, with which one can significantly improve the efficiency of the recommender system.

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

PubMed Central

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

2010-01-01

Energy conservation is one of the striking research issues now-a-days for power constrained wireless sensor networks (WSNs) and hence, several duty-cycle based MAC protocols have been devised for WSNs in the last few years. However, assimilation of diverse applications with different QoS requirements (i.e., delay and reliability) within the same network also necessitates in devising a generic duty-cycle based MAC protocol that can achieve both the delay and reliability guarantee, termed as multi-constrained QoS, while preserving the energy efficiency. To address this, in this paper, we propose a Multi-constrained QoS-aware duty-cycle MAC for heterogeneous traffic in WSNs (MQ-MAC). MQ-MAC classifies the traffic based on their multi-constrained QoS demands. Through extensive simulation using ns-2 we evaluate the performance of MQ-MAC. MQ-MAC provides the desired delay and reliability guarantee according to the nature of the traffic classes as well as achieves energy efficiency. PMID:22163439

Property relationships of the physical infrastructure and the traffic flow networks

NASA Astrophysics Data System (ADS)

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.

Network Characteristics of Video Streaming Traffic

DTIC Science & Technology

2011-11-01

Silverlight, Flash, or HTML5 ) used for video streaming. In particular, we identify three different streaming strategies that produce traffic... HTML5 , Flash. 1. INTRODUCTION The popularity of video streaming has considerably increased in the last decade. Indeed, recent studies have shown...applications for mobile devices), and the container (Flash [10], HTML5 [18], Silverlight [4]), on the charac- teristics of the traffic between the

A knowledge-based system for controlling automobile traffic

NASA Technical Reports Server (NTRS)

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.

A junction-tree based learning algorithm to optimize network wide traffic control: A coordinated multi-agent framework

DOE PAGES

Zhu, Feng; Aziz, H. M. Abdul; Qian, Xinwu; ...

2015-01-31

Our study develops a novel reinforcement learning algorithm for the challenging coordinated signal control problem. Traffic signals are modeled as intelligent agents interacting with the stochastic traffic environment. The model is built on the framework of coordinated reinforcement learning. The Junction Tree Algorithm (JTA) based reinforcement learning is proposed to obtain an exact inference of the best joint actions for all the coordinated intersections. Moreover, the algorithm is implemented and tested with a network containing 18 signalized intersections in VISSIM. Finally, our results show that the JTA based algorithm outperforms independent learning (Q-learning), real-time adaptive learning, and fixed timing plansmore » in terms of average delay, number of stops, and vehicular emissions at the network level.« less

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

PubMed

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

2012-09-01

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

Community structure in traffic zones based on travel demand

NASA Astrophysics Data System (ADS)

Sun, Li; Ling, Ximan; He, Kun; Tan, Qian

2016-09-01

Large structure in complex networks can be studied by dividing it into communities or modules. Urban traffic system is one of the most critical infrastructures. It can be abstracted into a complex network composed of tightly connected groups. Here, we analyze community structure in urban traffic zones based on the community detection method in network science. Spectral algorithm using the eigenvectors of matrices is employed. Our empirical results indicate that the traffic communities are variant with the travel demand distribution, since in the morning the majority of the passengers are traveling from home to work and in the evening they are traveling a contrary direction. Meanwhile, the origin-destination pairs with large number of trips play a significant role in urban traffic network's community division. The layout of traffic community in a city also depends on the residents' trajectories.

Optimizing automatic traffic recorders network in Minnesota.

DOT National Transportation Integrated Search

2016-01-01

Accurate traffic counts are important for budgeting, traffic planning, and roadway design. With thousands of : centerline miles of roadways, it is not possible to install continuous counters at all locations of interest (e.g., : intersections). There...

An Improved Response Surface Methodology Algorithm with an Application to Traffic Signal Optimization for Urban Networks

DOT National Transportation Integrated Search

1995-01-01

Prepared ca. 1995. This paper illustrates the use of the simulation-optimization technique of response surface methodology (RSM) in traffic signal optimization of urban networks. It also quantifies the gains of using the common random number (CRN) va...

Understanding the T2 traffic in CMS during Run-1

NASA Astrophysics Data System (ADS)

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.

Cost-effectiveness analysis of dolutegravir plus backbone compared with raltegravir plus backbone, darunavir+ritonavir plus backbone and efavirenz/tenofovir/emtricitabine in treatment naïve and experienced HIV-positive patients.

PubMed

Restelli, Umberto; Rizzardini, Giuliano; Antinori, Andrea; Lazzarin, Adriano; Bonfanti, Marzia; Bonfanti, Paolo; Croce, Davide

2017-01-01

In January 2014, the European Medicines Agency issued a marketing authorization for dolutegravir (DTG), a second-generation integrase strand transfer inhibitor for HIV treatment. The study aimed at determining the incremental cost-effectiveness ratio (ICER) of the use of DTG+backbone compared with raltegravir (RAL)+backbone, darunavir (DRV)+ritonavir(r)+backbone and efavirenz/tenofovir/emtricitabine (EFV/TDF/FTC) in HIV-positive treatment-naïve patients and compared with RAL+backbone in treatment-experienced patients, from the Italian National Health Service's point of view. A published Monte Carlo Individual Simulation Model (ARAMIS-DTG model) was used to perform the analysis. Patients pass through mutually exclusive health states (defined in terms of diagnosis of HIV with or without opportunistic infections [OIs] and cardiovascular disease [CVD]) and successive lines of therapy. The model considers costs (2014) and quality of life per monthly cycle in a lifetime horizon. Costs and quality-adjusted life years (QALYs) are dependent on OI, CVD, AIDS events, adverse events and antiretroviral therapies. In treatment-naïve patients, DTG dominates RAL; compared with DRV/r, the ICER obtained is of 38,586 €/QALY (6,170 €/QALY in patients with high viral load) and over EFV/TDF/FTC, DTG generates an ICER of 33,664 €/QALY. In treatment-experienced patients, DTG compared to RAL leads to an ICER of 12,074 €/QALY. The use of DTG+backbone may be cost effective in treatment-naïve and treatment-experienced patients compared with RAL+backbone and in treatment-naïve patients compared with DRV/r+backbone and EFV/TDF/FTC considering a threshold of 40,000 €/QALY.

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

NASA Technical Reports Server (NTRS)

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

NASA Astrophysics Data System (ADS)

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.

PubMed

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.

Dynamics of traffic flow with real-time traffic information

NASA Astrophysics Data System (ADS)

Yokoya, Yasushi

2004-01-01

We studied dynamics of traffic flow with real-time information provided. Provision of the real-time traffic information based on advancements in telecommunication technology is expected to facilitate the efficient utilization of available road capacity. This system has a potentiality of not only engineering for road usage but also the science of complexity series. In the system, the information plays a role of feedback connecting microscopic and macroscopic phenomena beyond the hierarchical structure of statistical physics. In this paper, we tried to clarify how the information works in a network of traffic flow from the perspective of statistical physics. The dynamical feature of the traffic flow is abstracted by a contrastive study between the nonequilibrium statistical physics and a computer simulation based on cellular automaton. We found that the information disrupts the local equilibrium of traffic flow by a characteristic dissipation process due to interaction between the information and individual vehicles. The dissipative structure was observed in the time evolution of traffic flow driven far from equilibrium as a consequence of the breakdown of the local-equilibrium hypothesis.

Traffic Adaptive Energy Efficient and Low Latency Medium Access Control for Wireless Sensor Networks

NASA Astrophysics Data System (ADS)

Yadav, Rajesh; Varma, Shirshu; Malaviya, N.

2008-05-01

Medium access control for wireless sensor networks has been a very active research area in the recent years. The traditional wireless medium access control protocol such as IEEE 802.11 is not suitable for the sensor network application because these are battery powered. The recharging of these sensor nodes is expensive and also not possible. The most of the literature in the medium access for the sensor network focuses on the energy efficiency. The proposed MAC protocol solves the energy inefficiency caused by idle listening, control packet overhead and overhearing taking nodes latency into consideration based on the network traffic. Simulation experiments have been performed to demonstrate the effectiveness of the proposed approach. The validation of the simulation results of the proposed MAC has been done by comparing it with the analytical model. This protocol has been simulated in Network Simulator ns-2.

Architectures and Design for Next-Generation Hybrid Circuit/Packet Networks

NASA Astrophysics Data System (ADS)

Vadrevu, Sree Krishna Chaitanya

Internet traffic is increasing rapidly at an annual growth rate of 35% with aggregate traffic exceeding several Exabyte's per month. The traffic is also becoming heterogeneous in bandwidth and quality-of-service (QoS) requirements with growing popularity of cloud computing, video-on-demand (VoD), e-science, etc. Hybrid circuit/packet networks which can jointly support circuit and packet services along with the adoption of high-bit-rate transmission systems form an attractive solution to address the traffic growth. 10 Gbps and 40 Gbps transmission systems are widely deployed in telecom backbone networks such as Comcast, AT&T, etc., and network operators are considering migration to 100 Gbps and beyond. This dissertation proposes robust architectures, capacity migration strategies, and novel service frameworks for next-generation hybrid circuit/packet architectures. In this dissertation, we study two types of hybrid circuit/packet networks: a) IP-over-WDM networks, in which the packet (IP) network is overlaid on top of the circuit (optical WDM) network and b) Hybrid networks in which the circuit and packet networks are deployed side by side such as US DoE's ESnet. We investigate techniques to dynamically migrate capacity between the circuit and packet sections by exploiting traffic variations over a day, and our methods show that significant bandwidth savings can be obtained with improved reliability of services. Specifically, we investigate how idle backup circuit capacity can be used to support packet services in IP-over-WDM networks, and similarly, excess capacity in packet network to support circuit services in ESnet. Control schemes that enable our mechanisms are also discussed. In IP-over-WDM networks, with upcoming 100 Gbps and beyond, dedicated protection will induce significant under-utilization of backup resources. We investigate design strategies to loan idle circuit backup capacity to support IP/packet services. However, failure of backup circuits will

Cost-effectiveness analysis of dolutegravir plus backbone compared with raltegravir plus backbone, darunavir+ritonavir plus backbone and efavirenz/tenofovir/emtricitabine in treatment naïve and experienced HIV-positive patients

PubMed Central

Restelli, Umberto; Rizzardini, Giuliano; Antinori, Andrea; Lazzarin, Adriano; Bonfanti, Marzia; Bonfanti, Paolo; Croce, Davide

2017-01-01

Background In January 2014, the European Medicines Agency issued a marketing authorization for dolutegravir (DTG), a second-generation integrase strand transfer inhibitor for HIV treatment. The study aimed at determining the incremental cost-effectiveness ratio (ICER) of the use of DTG+backbone compared with raltegravir (RAL)+backbone, darunavir (DRV)+ritonavir(r)+backbone and efavirenz/tenofovir/emtricitabine (EFV/TDF/FTC) in HIV-positive treatment-naïve patients and compared with RAL+backbone in treatment-experienced patients, from the Italian National Health Service’s point of view. Materials and methods A published Monte Carlo Individual Simulation Model (ARAMIS-DTG model) was used to perform the analysis. Patients pass through mutually exclusive health states (defined in terms of diagnosis of HIV with or without opportunistic infections [OIs] and cardiovascular disease [CVD]) and successive lines of therapy. The model considers costs (2014) and quality of life per monthly cycle in a lifetime horizon. Costs and quality-adjusted life years (QALYs) are dependent on OI, CVD, AIDS events, adverse events and antiretroviral therapies. Results In treatment-naïve patients, DTG dominates RAL; compared with DRV/r, the ICER obtained is of 38,586 €/QALY (6,170 €/QALY in patients with high viral load) and over EFV/TDF/FTC, DTG generates an ICER of 33,664 €/QALY. In treatment-experienced patients, DTG compared to RAL leads to an ICER of 12,074 €/QALY. Conclusion The use of DTG+backbone may be cost effective in treatment-naïve and treatment-experienced patients compared with RAL+backbone and in treatment-naïve patients compared with DRV/r+backbone and EFV/TDF/FTC considering a threshold of 40,000 €/QALY. PMID:28721059

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

DOT National Transportation Integrated Search

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...

Accurate Traffic Flow Prediction in Heterogeneous Vehicular Networks in an Intelligent Transport System Using a Supervised Non-Parametric Classifier.

PubMed

El-Sayed, Hesham; Sankar, Sharmi; Daraghmi, Yousef-Awwad; Tiwari, Prayag; Rattagan, Ekarat; Mohanty, Manoranjan; Puthal, Deepak; Prasad, Mukesh

2018-05-24

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.

Bridging the gap between peak and average loads on science networks

DOE PAGES

Nickolay, Sam; Jung, Eun -Sung; Kettimuthu, Rajkumar; ...

2017-05-12

Backbone networks are typically overprovisioned in order to support peak loads. Research and education networks (RENs), for example, are often designed to operate at 20–30% of capacity. Thus, Internet2 upgrades its backbone interconnects when the weekly 95th-percentile load is reliably above 30% of link capacity, and analysis of ESnet traffic between major laboratories shows a substantial gap between peak and average utilization. As science data volumes increase exponentially, it is unclear whether this overprovisioning trend can continue into the future. Even if overprovisioning is possible, it may not be the most cost-effective (and desirable) approach going forward. Under the currentmore » mode of free access to RENs, traffic at peak load may include both flows that need to be transferred in near-real time–for example, for computation and instrument monitoring and steering–and flows that are less time-critical, for example, archival and storage replication operations. Thus, peak load does not necessarily indicate the capacity that is absolutely required at that moment. We thus examine how data transfers are impacted when the average network load is increased while the network capacity is kept at the current levels. We also classify data transfers into on-demand (time-critical) and best-effort (less time-critical) and study the impact on both classes for different proportions of both the number of on-demand transfers and amount of bandwidth allocated for on-demand transfers. For our study, we use real transfer logs from production GridFTP servers to do simulation-based experiments as well as real experiments on a testbed. We find that when the transfer load is doubled and the network capacity is fixed at the current level, the gap between peak and average throughput decreases by an average of 18% in the simulation experiments and 16% in the testbed experiments, and the average slowdown experienced by the data transfers is under 1.5×. Moreover, when

Bridging the gap between peak and average loads on science networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nickolay, Sam; Jung, Eun -Sung; Kettimuthu, Rajkumar

Backbone networks are typically overprovisioned in order to support peak loads. Research and education networks (RENs), for example, are often designed to operate at 20–30% of capacity. Thus, Internet2 upgrades its backbone interconnects when the weekly 95th-percentile load is reliably above 30% of link capacity, and analysis of ESnet traffic between major laboratories shows a substantial gap between peak and average utilization. As science data volumes increase exponentially, it is unclear whether this overprovisioning trend can continue into the future. Even if overprovisioning is possible, it may not be the most cost-effective (and desirable) approach going forward. Under the currentmore » mode of free access to RENs, traffic at peak load may include both flows that need to be transferred in near-real time–for example, for computation and instrument monitoring and steering–and flows that are less time-critical, for example, archival and storage replication operations. Thus, peak load does not necessarily indicate the capacity that is absolutely required at that moment. We thus examine how data transfers are impacted when the average network load is increased while the network capacity is kept at the current levels. We also classify data transfers into on-demand (time-critical) and best-effort (less time-critical) and study the impact on both classes for different proportions of both the number of on-demand transfers and amount of bandwidth allocated for on-demand transfers. For our study, we use real transfer logs from production GridFTP servers to do simulation-based experiments as well as real experiments on a testbed. We find that when the transfer load is doubled and the network capacity is fixed at the current level, the gap between peak and average throughput decreases by an average of 18% in the simulation experiments and 16% in the testbed experiments, and the average slowdown experienced by the data transfers is under 1.5×. Moreover, when

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

PubMed Central

Niu, Qiang; Yang, Xu; Gao, Shouwan; Chen, Pengpeng; Chan, Shibing

2016-01-01

Localization is crucial for the monitoring applications of cities, such as road monitoring, environment surveillance, vehicle tracking, etc. In urban road sensor networks, sensors are often sparely deployed due to the hardware cost. Under this sparse deployment, sensors cannot communicate with each other via ranging hardware or one-hop connectivity, rendering the existing localization solutions ineffective. To address this issue, this paper proposes a novel Traffic Lights Schedule-based localization algorithm (TLS), which is built on the fact that vehicles move through the intersection with a known traffic light schedule. We can first obtain the law by binary vehicle detection time stamps and describe the law as a matrix, called a detection matrix. At the same time, we can also use the known traffic light information to construct the matrices, which can be formed as a collection called a known matrix collection. The detection matrix is then matched in the known matrix collection for identifying where sensors are located on urban roads. We evaluate our algorithm by extensive simulation. The results show that the localization accuracy of intersection sensors can reach more than 90%. In addition, we compare it with a state-of-the-art algorithm and prove that it has a wider operational region. PMID:27735871

Evaluation of LADOTD traffic load data for determination of traffic load equivalency factors : technical summary.

DOT National Transportation Integrated Search

2002-04-01

Louisianan has established a traffic monitoring program, compliant with FHWA incentives, that is designed to collect and manage the traffic data needed for the design and management of LADOTD's network of current and future highways. In the early 198...

The CARFAX road traffic information system

NASA Astrophysics Data System (ADS)

Sandell, R. S.

1984-02-01

A description of the development work and field trials which led to the completion of the dedicated traffic information service "CARFAX' is presented. The system employs a single medium frequency channel, and involves a network of low powered transmitters that operate in time division multiplex to provide traffic announcements. A description of the network distribution, equipment test, results and future system utilization is included.

High-resolution protein design with backbone freedom.

PubMed

Harbury, P B; Plecs, J J; Tidor, B; Alber, T; Kim, P S

1998-11-20

Recent advances in computational techniques have allowed the design of precise side-chain packing in proteins with predetermined, naturally occurring backbone structures. Because these methods do not model protein main-chain flexibility, they lack the breadth to explore novel backbone conformations. Here the de novo design of a family of alpha-helical bundle proteins with a right-handed superhelical twist is described. In the design, the overall protein fold was specified by hydrophobic-polar residue patterning, whereas the bundle oligomerization state, detailed main-chain conformation, and interior side-chain rotamers were engineered by computational enumerations of packing in alternate backbone structures. Main-chain flexibility was incorporated through an algebraic parameterization of the backbone. The designed peptides form alpha-helical dimers, trimers, and tetramers in accord with the design goals. The crystal structure of the tetramer matches the designed structure in atomic detail.

Recovery Act: Energy Efficiency of Data Networks through Rate Adaptation (EEDNRA) - Final Technical Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Matthew Andrews; Spyridon Antonakopoulos; Steve Fortune

2011-07-12

This Concept Definition Study focused on developing a scientific understanding of methods to reduce energy consumption in data networks using rate adaptation. Rate adaptation is a collection of techniques that reduce energy consumption when traffic is light, and only require full energy when traffic is at full provisioned capacity. Rate adaptation is a very promising technique for saving energy: modern data networks are typically operated at average rates well below capacity, but network equipment has not yet been designed to incorporate rate adaptation. The Study concerns packet-switching equipment, routers and switches; such equipment forms the backbone of the modern Internet.more » The focus of the study is on algorithms and protocols that can be implemented in software or firmware to exploit hardware power-control mechanisms. Hardware power-control mechanisms are widely used in the computer industry, and are beginning to be available for networking equipment as well. Network equipment has different performance requirements than computer equipment because of the very fast rate of packet arrival; hence novel power-control algorithms are required for networking. This study resulted in five published papers, one internal report, and two patent applications, documented below. The specific technical accomplishments are the following: • A model for the power consumption of switching equipment used in service-provider telecommunication networks as a function of operating state, and measured power-consumption values for typical current equipment. • An algorithm for use in a router that adapts packet processing rate and hence power consumption to traffic load while maintaining performance guarantees on delay and throughput. • An algorithm that performs network-wide traffic routing with the objective of minimizing energy consumption, assuming that routers have less-than-ideal rate adaptivity. • An estimate of the potential energy savings in service

Realistic Data-Driven Traffic Flow Animation Using Texture Synthesis.

PubMed

Chao, Qianwen; Deng, Zhigang; Ren, Jiaping; Ye, Qianqian; Jin, Xiaogang

2018-02-01

We present a novel data-driven approach to populate virtual road networks with realistic traffic flows. Specifically, given a limited set of vehicle trajectories as the input samples, our approach first synthesizes a large set of vehicle trajectories. By taking the spatio-temporal information of traffic flows as a 2D texture, the generation of new traffic flows can be formulated as a texture synthesis process, which is solved by minimizing a newly developed traffic texture energy. The synthesized output captures the spatio-temporal dynamics of the input traffic flows, and the vehicle interactions in it strictly follow traffic rules. After that, we position the synthesized vehicle trajectory data to virtual road networks using a cage-based registration scheme, where a few traffic-specific constraints are enforced to maintain each vehicle's original spatial location and synchronize its motion in concert with its neighboring vehicles. Our approach is intuitive to control and scalable to the complexity of virtual road networks. We validated our approach through many experiments and paired comparison user studies.

Computational protein design with backbone plasticity

PubMed Central

MacDonald, James T.; Freemont, Paul S.

2016-01-01

The computational algorithms used in the design of artificial proteins have become increasingly sophisticated in recent years, producing a series of remarkable successes. The most dramatic of these is the de novo design of artificial enzymes. The majority of these designs have reused naturally occurring protein structures as ‘scaffolds’ onto which novel functionality can be grafted without having to redesign the backbone structure. The incorporation of backbone flexibility into protein design is a much more computationally challenging problem due to the greatly increased search space, but promises to remove the limitations of reusing natural protein scaffolds. In this review, we outline the principles of computational protein design methods and discuss recent efforts to consider backbone plasticity in the design process. PMID:27911735

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

NASA Technical Reports Server (NTRS)

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.

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

PubMed Central

AsSadhan, Basil; Moura, José M.F.

2013-01-01

Botnets are large networks of bots (compromised machines) that are under the control of a small number of bot masters. They pose a significant threat to Internet’s communications and applications. A botnet relies on command and control (C2) communications channels traffic between its members for its attack execution. C2 traffic occurs prior to any attack; hence, the detection of botnet’s C2 traffic enables the detection of members of the botnet before any real harm happens. We analyze C2 traffic and find that it exhibits a periodic behavior. This is due to the pre-programmed behavior of bots that check for updates to download them every T seconds. We exploit this periodic behavior to detect C2 traffic. The detection involves evaluating the periodogram of the monitored traffic. Then applying Walker’s large sample test to the periodogram’s maximum ordinate in order to determine if it is due to a periodic component or not. If the periodogram of the monitored traffic contains a periodic component, then it is highly likely that it is due to a bot’s C2 traffic. The test looks only at aggregate control plane traffic behavior, which makes it more scalable than techniques that involve deep packet inspection (DPI) or tracking the communication flows of different hosts. We apply the test to two types of botnet, tinyP2P and IRC that are generated by SLINGbot. We verify the periodic behavior of their C2 traffic and compare it to the results we get on real traffic that is obtained from a secured enterprise network. We further study the characteristics of the test in the presence of injected HTTP background traffic and the effect of the duty cycle on the periodic behavior. PMID:25685512

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

PubMed Central

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

2017-01-01

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

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

PubMed

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.

Achieving QoS for Aeronautical Telecommunication Networks Over Differentiated Services

NASA Technical Reports Server (NTRS)

Bai, Haowei; Atiquzzaman, Mohammed; Ivanic, William

2001-01-01

Aeronautical Telecommunication Network (ATN) has been developed by the International Civil Aviation Organization to integrate Air-Ground and Ground-Ground data communication for aeronautical applications into a single network serving Air Traffic Control and Aeronautical Operational Communications. To carry time critical information required for aeronautical applications, ATN provides different Quality of Services (QoS) to applications. ATN has therefore, been designed as a stand alone network which implies building an expensive separate network for ATN However, the cost of operating ATN can be reduced if it can be run over a public network such as the Internet. Although the current Internet does not provide QoS the next generation Internet is expected to provide QoS to applications. The objective of this paper is to investigate the possibility of providing QoS to ATN applications when it is run over the next generation Internet. Differentiated Services (DiffServ), one of the protocols proposed for the next generation Internet, will allow network service providers to offer different QoS to customers. Our results show that it is possible to provide QoS to ATN applications when they run over a DiffServ backbone.

Achieving QoS for Aeronautical Telecommunication Networks over Differentiated Services

NASA Technical Reports Server (NTRS)

Bai, Haowei; Atiquzzaman, Mohammed; Ivancic, William

2001-01-01

Aeronautical Telecommunication Network (ATN) has been developed by the International Civil Aviation Organization to integrate Air-Ground and Ground-Ground data communication for aeronautical applications into a single network serving Air Traffic Control and Aeronautical Operational Communications. To carry time critical information required for aeronautical applications, ATN provides different Quality of Services (QoS) to applications. ATN has therefore, been designed as a standalone network which implies building an expensive separate network for ATN. However, the cost of operating ATN can be reduced if it can be run over a public network such as the Internet. Although the current Internet does not provide QoS, the next generation Internet is expected to provide QoS to applications. The objective of this paper is to investigate the possibility of providing QoS to ATN applications when it is run over the next generation Internet. Differentiated Services (DiffServ), one of the protocols proposed for the next generation Internet, will allow network service providers to offer different QoS to customers. Our results show that it is possible to provide QoS to ATN applications when they run over a DiffServ backbone.

Intelligent Traffic Quantification System

NASA Astrophysics Data System (ADS)

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.

Application of Artificial Neural Networks and Singular-Spectral Analysis in Forecasting the Daily Traffic in the Moscow Metro

NASA Astrophysics Data System (ADS)

Ivanov, Victor; Osetrov, Evgenii

2018-02-01

In this paper, we investigate the possibility of applying various approaches to solving the problem of medium-term forecasting of daily passenger traffic volumes in the Moscow metro (MM): 1) on the basis of artificial neural networks (ANN); 2) using the singular-spectral analysis implemented in the package "Caterpillar"-SSA; 3) sharing the ANN and the "Caterpillar"-SSA approach. We demonstrate that the developed methods and algorithms allow us to conduct medium-term forecasting of passenger traffic in the MM with reasonable accuracy.

Simulation of traffic control signal systems

NASA Technical Reports Server (NTRS)

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.

The importance of antipersistence for traffic jams

NASA Astrophysics Data System (ADS)

Krause, Sebastian M.; Habel, Lars; Guhr, Thomas; Schreckenberg, Michael

2017-05-01

Universal characteristics of road networks and traffic patterns can help to forecast and control traffic congestion. The antipersistence of traffic flow time series has been found for many data sets, but its relevance for congestion has been overseen. Based on empirical data from motorways in Germany, we study how antipersistence of traffic flow time-series impacts the duration of traffic congestion on a wide range of time scales. We find a large number of short-lasting traffic jams, which implies a large risk for rear-end collisions.

Analysis of Traffic Signals on a Software-Defined Network for Detection and Classification of a Man-in-the-Middle Attack

DTIC Science & Technology

2017-09-01

unique characteristics of reported anomalies in the collected traffic signals to build a classification framework. Other cyber events, such as a...Furthermore, we identify unique characteristics of reported anomalies in the collected traffic signals to build a classification framework. Other cyber...2]. The applications build flow rules using network topology information provided by the control plane [1]. Since the control plane is able to

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

NASA Technical Reports Server (NTRS)

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

Criticism of generally accepted fundamentals and methodologies of traffic and transportation theory

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kerner, Boris S.

It is explained why the set of the fundamental empirical features of traffic breakdown (a transition from free flow to congested traffic) should be the empirical basis for any traffic and transportation theory that can be reliable used for control and optimization in traffic networks. It is shown that generally accepted fundamentals and methodologies of traffic and transportation theory are not consistent with the set of the fundamental empirical features of traffic breakdown at a highway bottleneck. To these fundamentals and methodologies of traffic and transportation theory belong (i) Lighthill-Whitham-Richards (LWR) theory, (ii) the General Motors (GM) model class (formore » example, Herman, Gazis et al. GM model, Gipps’s model, Payne’s model, Newell’s optimal velocity (OV) model, Wiedemann’s model, Bando et al. OV model, Treiber’s IDM, Krauß’s model), (iii) the understanding of highway capacity as a particular stochastic value, and (iv) principles for traffic and transportation network optimization and control (for example, Wardrop’s user equilibrium (UE) and system optimum (SO) principles). Alternatively to these generally accepted fundamentals and methodologies of traffic and transportation theory, we discuss three-phase traffic theory as the basis for traffic flow modeling as well as briefly consider the network breakdown minimization (BM) principle for the optimization of traffic and transportation networks with road bottlenecks.« less

Nuclear traffic and peloton formation in fungal networks

NASA Astrophysics Data System (ADS)

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.

Using Inspiration from Synaptic Plasticity Rules to Optimize Traffic Flow in Distributed Engineered Networks.

PubMed

Suen, Jonathan Y; Navlakha, Saket

2017-05-01

Controlling the flow and routing of data is a fundamental problem in many distributed networks, including transportation systems, integrated circuits, and the Internet. In the brain, synaptic plasticity rules have been discovered that regulate network activity in response to environmental inputs, which enable circuits to be stable yet flexible. Here, we develop a new neuro-inspired model for network flow control that depends only on modifying edge weights in an activity-dependent manner. We show how two fundamental plasticity rules, long-term potentiation and long-term depression, can be cast as a distributed gradient descent algorithm for regulating traffic flow in engineered networks. We then characterize, both by simulation and analytically, how different forms of edge-weight-update rules affect network routing efficiency and robustness. We find a close correspondence between certain classes of synaptic weight update rules derived experimentally in the brain and rules commonly used in engineering, suggesting common principles to both.

Discovering urban mobility patterns with PageRank based traffic modeling and prediction

NASA Astrophysics Data System (ADS)

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.

Inventory of system operations data collection and use in the Virginia Department of Transportation.

DOT National Transportation Integrated Search

2006-01-01

Accurate data describing the status of the transportation network is the backbone of system operations management. Without accurate data, traffic engineers cannot optimize signal phasing and timing, effective incident management cannot be undertaken,...

Percolation transition in dynamical traffic network with evolving critical bottlenecks.

PubMed

Li, Daqing; Fu, Bowen; Wang, Yunpeng; Lu, Guangquan; Berezin, Yehiel; Stanley, H Eugene; Havlin, Shlomo

2015-01-20

A critical phenomenon is an intrinsic feature of traffic dynamics, during which transition between isolated local flows and global flows occurs. However, very little attention has been given to the question of how the local flows in the roads are organized collectively into a global city flow. Here we characterize this organization process of traffic as "traffic percolation," where the giant cluster of local flows disintegrates when the second largest cluster reaches its maximum. We find in real-time data of city road traffic that global traffic is dynamically composed of clusters of local flows, which are connected by bottleneck links. This organization evolves during a day with different bottleneck links appearing in different hours, but similar in the same hours in different days. A small improvement of critical bottleneck roads is found to benefit significantly the global traffic, providing a method to improve city traffic with low cost. Our results may provide insights on the relation between traffic dynamics and percolation, which can be useful for efficient transportation, epidemic control, and emergency evacuation.

Analysis and Classification of Traffic in Wireless Sensor Network

DTIC Science & Technology

2007-03-01

34 1. Hurst Parameter ................................................................................35 2. Self-Similarity...traffic is self-similar, buffer size can be better designed from the forecasted traffic workload. 1. Hurst Parameter To determine the extent of self...similarity in WSN traffic, the Hurst parameter, H, is used. H also calculates the length of the long range dependence of a stochastic process. If H

Methods and systems for detecting abnormal digital traffic

DOEpatents

Goranson, Craig A [Kennewick, WA; Burnette, John R [Kennewick, WA

2011-03-22

Aspects of the present invention encompass methods and systems for detecting abnormal digital traffic by assigning characterizations of network behaviors according to knowledge nodes and calculating a confidence value based on the characterizations from at least one knowledge node and on weighting factors associated with the knowledge nodes. The knowledge nodes include a characterization model based on prior network information. At least one of the knowledge nodes should not be based on fixed thresholds or signatures. The confidence value includes a quantification of the degree of confidence that the network behaviors constitute abnormal network traffic.

Gel Permeation Chromatography Characterization of the Chain Length Distributions in Thiol-Acrylate Photopolymer Networks

PubMed Central

Rydholm, Amber E.; Held, Nicole L.; Bowman, Christopher N.; Anseth, Kristi S.

2008-01-01

Crosslinked, degradable networks formed from the photopolymerization of thiol and acrylate monomers are explored as potential biomaterials. The degradation behavior and material properties of these networks are influenced by the molecular weight of the nondegradable thiol-polyacrylate backbone chains that form during photopolymerization. Here, gel permeation chromatography was used to characterize the thiol-polyacrylate backbone chain lengths in degraded thiol-acrylate networks. Increasing thiol functionality from 1 to 4 increased the backbone molecular weight (M̄w = 2.3 ± 0.07 × 104 Da for monothiol and 3.6 ± 0.1 × 104 Da for tetrathiol networks). Decreasing thiol functional group concentration from 30 to 10 mol% also increased the backbone lengths (M̄w = 7.3 ± 1.1 × 104 Da for the networks containing 10 mol% thiol groups as compared to 3.6 ± 0.1 × 104 Da for 30 mol% thiol). Finally, the backbone chain lengths were probed at various stages of degradation and an increase in backbone molecular weight was observed as mass loss progressed from 10 to 70%. PMID:19079733

Application of machine learning methods for traffic signs recognition

NASA Astrophysics Data System (ADS)

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.

Data communication network at the ASRM facility

NASA Technical Reports Server (NTRS)

Moorhead, Robert J., II; Smith, Wayne D.; Nirgudkar, Ravi; Zhu, Zhifan; Robinson, Walter

1993-01-01

The main objective of the report is to present the overall communication network structure for the Advanced Solid Rocket Motor (ASRM) facility being built at Yellow Creek near Iuka, Mississippi. This report is compiled using information received from NASA/MSFC, LMSC, AAD, and RUST Inc. As per the information gathered, the overall network structure will have one logical FDDI ring acting as a backbone for the whole complex. The buildings will be grouped into two categories viz. manufacturing critical and manufacturing non-critical. The manufacturing critical buildings will be connected via FDDI to the Operational Information System (OIS) in the main computing center in B 1000. The manufacturing non-critical buildings will be connected by 10BASE-FL to the Business Information System (BIS) in the main computing center. The workcells will be connected to the Area Supervisory Computers (ASCs) through the nearest manufacturing critical hub and one of the OIS hubs. The network structure described in this report will be the basis for simulations to be carried out next year. The Comdisco's Block Oriented Network Simulator (BONeS) will be used for the network simulation. The main aim of the simulations will be to evaluate the loading of the OIS, the BIS, the ASCs, and the network links by the traffic generated by the workstations and workcells throughout the site.

Data communication network at the ASRM facility

NASA Astrophysics Data System (ADS)

Moorhead, Robert J., II; Smith, Wayne D.; Nirgudkar, Ravi; Zhu, Zhifan; Robinson, Walter

1993-02-01

The main objective of the report is to present the overall communication network structure for the Advanced Solid Rocket Motor (ASRM) facility being built at Yellow Creek near Iuka, Mississippi. This report is compiled using information received from NASA/MSFC, LMSC, AAD, and RUST Inc. As per the information gathered, the overall network structure will have one logical FDDI ring acting as a backbone for the whole complex. The buildings will be grouped into two categories viz. manufacturing critical and manufacturing non-critical. The manufacturing critical buildings will be connected via FDDI to the Operational Information System (OIS) in the main computing center in B 1000. The manufacturing non-critical buildings will be connected by 10BASE-FL to the Business Information System (BIS) in the main computing center. The workcells will be connected to the Area Supervisory Computers (ASCs) through the nearest manufacturing critical hub and one of the OIS hubs. The network structure described in this report will be the basis for simulations to be carried out next year. The Comdisco's Block Oriented Network Simulator (BONeS) will be used for the network simulation. The main aim of the simulations will be to evaluate the loading of the OIS, the BIS, the ASCs, and the network links by the traffic generated by the workstations and workcells throughout the site.

Analysis of Malicious Traffic in Modbus/TCP Communications

NASA Astrophysics Data System (ADS)

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.

Triazine-based sequence-defined polymers with side-chain diversity and backbone-backbone interaction motifs

DOE PAGES

Grate, Jay W.; Mo, Kai -For; Daily, Michael D.

2016-02-10

Sequence control in polymers, well-known in nature, encodes structure and functionality. Here we introduce a new architecture, based on the nucleophilic aromatic substitution chemistry of cyanuric chloride, that creates a new class of sequence-defined polymers dubbed TZPs. Proof of concept is demonstrated with two synthesized hexamers, having neutral and ionizable side chains. Molecular dynamics simulations show backbone–backbone interactions, including H-bonding motifs and pi–pi interactions. This architecture is arguably biomimetic while differing from sequence-defined polymers having peptide bonds. In conclusion, the synthetic methodology supports the structural diversity of side chains known in peptides, as well as backbone–backbone hydrogen-bonding motifs, and willmore » thus enable new macromolecules and materials with useful functions.« less

Triazine-based sequence-defined polymers with side-chain diversity and backbone-backbone interaction motifs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Grate, Jay W.; Mo, Kai -For; Daily, Michael D.

Sequence control in polymers, well-known in nature, encodes structure and functionality. Here we introduce a new architecture, based on the nucleophilic aromatic substitution chemistry of cyanuric chloride, that creates a new class of sequence-defined polymers dubbed TZPs. Proof of concept is demonstrated with two synthesized hexamers, having neutral and ionizable side chains. Molecular dynamics simulations show backbone–backbone interactions, including H-bonding motifs and pi–pi interactions. This architecture is arguably biomimetic while differing from sequence-defined polymers having peptide bonds. In conclusion, the synthetic methodology supports the structural diversity of side chains known in peptides, as well as backbone–backbone hydrogen-bonding motifs, and willmore » thus enable new macromolecules and materials with useful functions.« less

Traffic-aware energy saving scheme with modularization supporting in TWDM-PON

NASA Astrophysics Data System (ADS)

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.

Dynamic traffic assignment based trailblazing guide signing for major traffic generator.

DOT National Transportation Integrated Search

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.

PubMed

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.

DOT National Transportation Integrated Search

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...

Traffic Congestion Detection System through Connected Vehicles and Big Data

PubMed Central

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

2016-01-01

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. PMID:27136548

Traffic Congestion Detection System through Connected Vehicles and Big Data.

PubMed

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.

Hybrid Optimization in Urban Traffic Networks

DOT National Transportation Integrated Search

1979-04-01

The hybrid optimization problem is formulated to provide a general theoretical framework for the analysis of a class of traffic control problems which takes into account the role of individual drivers as independent decisionmakers. Different behavior...

Effect of Liquid-Crystalline Epoxy Backbone Structure on Thermal Conductivity of Epoxy-Alumina Composites

NASA Astrophysics Data System (ADS)

Giang, Thanhkieu; Kim, Jinhwan

2017-01-01

In a series of papers published recently, we clearly demonstrated that the most important factor governing the thermal conductivity of epoxy-Al2O3 composites is the backbone structure of the epoxy. In this study, three more epoxies based on diglycidyl ester-terminated liquid-crystalline epoxy (LCE) have been synthesized to draw conclusions regarding the effect of the epoxy backbone structure on the thermal conductivity of epoxy-alumina composites. The synthesized structures were characterized by proton nuclear magnetic resonance (1H-NMR) and Fourier-transform infrared (FT-IR) spectroscopy. Differential scanning calorimetry, thermogravimetric analysis, and optical microscopy were also employed to examine the thermal and optical properties of the synthesized LCEs and the cured composites. All three LCE resins exhibited typical liquid-crystalline behaviors: clear solid crystalline state below the melting temperature ( T m), sharp crystalline melting at T m, and transition to nematic phase above T m with consequent isotropic phase above the isotropic temperature ( T i). The LCE resins displayed distinct nematic liquid-crystalline phase over a wide temperature range and retained liquid-crystalline phase after curing, with high thermal conductivity of the resulting composite. The thermal conductivity values ranged from 3.09 W/m-K to 3.89 W/m-K for LCE-Al2O3 composites with 50 vol.% filler loading. The steric effect played a governing role in the difference. The neat epoxy resin thermal conductivity was obtained as 0.35 W/m-K to 0.49 W/m-K based on analysis using the Agari-Uno model. The results clearly support the objective of this study in that the thermal conductivity of the LCE-containing networks strongly depended on the epoxy backbone structure and the degree of ordering in the cured network.

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

PubMed

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

2017-01-01

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

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

PubMed Central

Zhang, Wenyi; Guan, Wei; Ma, Rui

2017-01-01

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

Multilane Traffic Flow Modeling Using Cellular Automata Theory

NASA Astrophysics Data System (ADS)

Chechina, Antonina; Churbanova, Natalia; Trapeznikova, Marina

2018-02-01

The paper deals with the mathematical modeling of traffic flows on urban road networks using microscopic approach. The model is based on the cellular automata theory and presents a generalization of the Nagel-Schreckenberg model to a multilane case. The created program package allows to simulate traffic on various types of road fragments (T or X type intersection, strait road elements, etc.) and on road networks that consist of these elements. Besides that, it allows to predict the consequences of various decisions regarding road infrastructure changes, such as: number of lanes increasing/decreasing, putting new traffic lights into operation, building new roads, entrances/exits, road junctions.

McMAC: Towards a MAC Protocol with Multi-Constrained QoS Provisioning for Diverse Traffic in Wireless Body Area Networks

PubMed Central

Monowar, Muhammad Mostafa; Hassan, Mohammad Mehedi; 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 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 proposed to 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. PMID:23202224

Propagation of Disturbances in Traffic Flow

DOT National Transportation Integrated Search

1977-09-01

The system-optimized static traffic-assignment problem in a freeway corridor network is the problem of choosing a distribution of vehicles in the network to minimize average travel time. It is of interest to know how sensitive the optimal steady-stat...

Remotely Accessed Vehicle Traffic Management System

NASA Astrophysics Data System (ADS)

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.

Protein-Backbone Thermodynamics across the Membrane Interface.

PubMed

Bereau, Tristan; Kremer, Kurt

2016-07-07

The thermodynamics of insertion of a protein in a membrane depends on the fine interplay between backbone and side-chain contributions interacting with the lipid environment. Using computer simulations, we probe how different descriptions of the backbone glycyl unit affect the thermodynamics of insertion of individual residues, dipeptides, and entire transmembrane helices. Due to the lack of reference data, we first introduce an efficient methodology to estimate atomistic potential of mean force (PMF) curves from a series of representative and uncorrelated coarse-grained (CG) snapshots. We find strong discrepancies between two CG models, Martini and PLUM, against reference atomistic PMFs and experiments. Atomistic simulations suggest a weak free energy of insertion between water and a POPC membrane for the glycyl unit, in overall agreement with experimental results despite severe assumptions in our calculations. We show that refining the backbone contribution in PLUM significantly improves the PMF of insertion of the WALP16 transmembrane peptide. An improper balance between the glycyl backbone and the attached side chain will lead to energetic artifacts, rationalizing Martini's overstabilization of WALP's adsorbed interfacial state. It illustrates difficulties associated with free-energy-based parametrizations of single-residue models, as the relevant free energy of partitioning used for force-field parametrization does not arise from the entire residue but rather the solvent-accessible chemical groups.

Inferring the background traffic arrival process in the Internet.

PubMed

Hága, Péter; Csabai, István; Vattay, Gábor

2009-12-01

Phase transition has been found in many complex interactivity systems. Complex networks are not exception either but there are quite few real systems where we can directly understand the emergence of this nontrivial behavior from the microscopic view. In this paper, we present the emergence of the phase transition between the congested and uncongested phases of a network link. We demonstrate a method to infer the background traffic arrival process, which is one of the key state parameters of the Internet traffic. The traffic arrival process in the Internet has been investigated in several studies, since the recognition of its self-similar nature. The statistical properties of the traffic arrival process are very important since they are fundamental in modeling the dynamical behavior. Here, we demonstrate how the widely used packet train technique can be used to determine the main properties of the traffic arrival process. We show that the packet train dispersion is sensitive to the congestion on the network path. We introduce the packet train stretch as an order parameter to describe the phase transition between the congested and uncongested phases of the bottleneck link in the path. We find that the distribution of the background traffic arrival process can be determined from the average packet train dispersion at the critical point of the system.

Using temporal detrending to observe the spatial correlation of traffic.

PubMed

Ermagun, Alireza; Chatterjee, Snigdhansu; Levinson, David

2017-01-01

This empirical study sheds light on the spatial correlation of traffic links under different traffic regimes. We mimic the behavior of real traffic by pinpointing the spatial correlation between 140 freeway traffic links in a major sub-network of the Minneapolis-St. Paul freeway system with a grid-like network topology. This topology enables us to juxtapose the positive and negative correlation between links, which has been overlooked in short-term traffic forecasting models. To accurately and reliably measure the correlation between traffic links, we develop an algorithm that eliminates temporal trends in three dimensions: (1) hourly dimension, (2) weekly dimension, and (3) system dimension for each link. The spatial correlation of traffic links exhibits a stronger negative correlation in rush hours, when congestion affects route choice. Although this correlation occurs mostly in parallel links, it is also observed upstream, where travelers receive information and are able to switch to substitute paths. Irrespective of the time-of-day and day-of-week, a strong positive correlation is witnessed between upstream and downstream links. This correlation is stronger in uncongested regimes, as traffic flow passes through consecutive links more quickly and there is no congestion effect to shift or stall traffic. The extracted spatial correlation structure can augment the accuracy of short-term traffic forecasting models.

Evaluation of traffic responsive control on the Reston Parkway arterial network.

DOT National Transportation Integrated Search

2009-01-01

Traffic responsive plan selection (TRPS) control is considered an effective operational mode in traffic signal systems. Its efficiency stems from the fact that it can capture variations in traffic patterns and switch timing plans based on existing tr...

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

PubMed Central

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

Thin Films Formed from Conjugated Polymers with Ionic, Water-Soluble Backbones.

PubMed

Voortman, Thomas P; Chiechi, Ryan C

2015-12-30

This paper compares the morphologies of films of conjugated polymers in which the backbone (main chain) and pendant groups are varied between ionic/hydrophilic and aliphatic/hydrophobic. We observe that conjugated polymers in which the pendant groups and backbone are matched, either ionic-ionic or hydrophobic-hydrophobic, form smooth, structured, homogeneous films from water (ionic) or tetrahydrofuran (hydrophobic). Mismatched conjugated polymers, by contrast, form inhomogeneous films with rough topologies. The polymers with ionic backbone chains are conjugated polyions (conjugated polymers with closed-shell charges in the backbone), which are semiconducting materials with tunable bad-gaps, not unlike uncharged conjugated polymers.

Effect of Backbone Design on Hybridization Thermodynamics of Oligo-nucleic Acids: A Coarse-Grained Molecular Dynamics Simulation Study

NASA Astrophysics Data System (ADS)

Ghobadi, Ahmadreza F.; Jayaraman, Arthi

DNA hybridization is the basis of various bio-nano technologies, such as DNA origami and assembly of DNA-functionalized nanoparticles. A hybridized double stranded (ds) DNA is formed when complementary nucleobases on hybridizing strands exhibit specific and directional hydrogen bonds through canonical Watson-Crick base-pairing interactions. In recent years, the need for cheaper alternatives and significant synthetic advances have driven design of DNA mimics with new backbone chemistries. However, a fundamental understanding of how these backbone modifications in the oligo-nucleic acids impact the hybridization and melting behavior of the duplex is still lacking. In this talk, we present our recent findings on impact of varying backbone chemistry on hybridization of oligo-nucleic acid duplexes. We use coarse-grained molecular dynamics simulations to isolate the effect of strand flexibility, electrostatic interactions and nucleobase spacing on the melting curves for duplexes with various strand sequences and concentrations. Since conjugation of oligo-nucleic acids with polymers serve as building blocks for thermo-responsive polymer networks and gels, we also present the effect of such conjugation on hybridization thermodynamics and polymer conformation.

The Deep Impact Network Experiment Operations Center

NASA Technical Reports Server (NTRS)

Torgerson, J. Leigh; Clare, Loren; Wang, Shin-Ywan

2009-01-01

Delay/Disruption Tolerant Networking (DTN) promises solutions in solving space communications challenges arising from disconnections as orbiters lose line-of-sight with landers, long propagation delays over interplanetary links, and other phenomena. DTN has been identified as the basis for the future NASA space communications network backbone, and international standardization is progressing through both the Consultative Committee for Space Data Systems (CCSDS) and the Internet Engineering Task Force (IETF). JPL has developed an implementation of the DTN architecture, called the Interplanetary Overlay Network (ION). ION is specifically implemented for space use, including design for use in a real-time operating system environment and high processing efficiency. In order to raise the Technology Readiness Level of ION, the first deep space flight demonstration of DTN is underway, using the Deep Impact (DI) spacecraft. Called the Deep Impact Network (DINET), operations are planned for Fall 2008. An essential component of the DINET project is the Experiment Operations Center (EOC), which will generate and receive the test communications traffic as well as "out-of-DTN band" command and control of the DTN experiment, store DTN flight test information in a database, provide display systems for monitoring DTN operations status and statistics (e.g., bundle throughput), and support query and analyses of the data collected. This paper describes the DINET EOC and its value in the DTN flight experiment and potential for further DTN testing.

Adding signals to coordinated traffic signal systems.

DOT National Transportation Integrated Search

1983-08-01

The purpose of this research was to investigate the effect of adding or : removing traffic signals within a coordinated, signal-controlled street network. : The report includes a discussion of coordinated signal systems; arterial street : network con...

Traffic signal coordination and queue management in oversaturated intersection.

DOT National Transportation Integrated Search

2011-03-18

Traffic signal timing optimization when done properly, could significantly improve network : performance by reducing delay, increasing network throughput, reducing number of stops, or : increasing average speed in the network. The optimization can be...

Traffic signal coordination and queue management in oversaturated intersections.

DOT National Transportation Integrated Search

2011-03-18

Traffic signal timing optimization when done properly, could significantly improve network performance by reducing delay, increasing network throughput, reducing number of stops, or increasing average speed in the network. The optimization can become...

Directing Traffic: Managing Internet Bandwidth Fairly

ERIC Educational Resources Information Center

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…

Computer Simulations of Bottlebrush Melts and Soft Networks

NASA Astrophysics Data System (ADS)

Cao, Zhen; Carrillo, Jan-Michael; Sheiko, Sergei; Dobrynin, Andrey

We have studied dense bottlebrush systems in a melt and network state using a combination of the molecular dynamics simulations and analytical calculations. Our simulations show that the bottlebrush macromolecules in a melt behave as ideal chains with the effective Kuhn length bK. The bottlebrush induced bending rigidity is due to redistribution of the side chains upon backbone bending. Kuhn length of the bottlebrushes increases with increasing the side-chain degree of polymerization nsc as bK ~nsc0 . 46 . This model of bottlebrush macromolecules is extended to describe mechanical properties of bottlebrush networks in linear and nonlinear deformation regimes. In the linear deformation regime, the network shear modulus scales with the degree of polymerization of the side chains as G0 ~nsc + 1 - 1 as long as the ratio of the Kuhn length to the size of the fully extended bottlebrush backbone between crosslinks, Rmax, is smaller than unity, bK /Rmax < < 1 . Bottlebrush networks with bK /Rmax ~ 1 demonstrate behavior similar to that of networks of semiflexible chains with G0 ~nsc- 0 . 5 . In the nonlinear deformation regime, the deformation dependent shear modulus is a universal function of the first strain invariant I1 and bottlebrush backbone deformation ratio β describing stretching ability of the bottlebrush backbone between crosslinks. Nsf DMR-1409710 DMR-1436201.

Using temporal detrending to observe the spatial correlation of traffic

PubMed Central

2017-01-01

This empirical study sheds light on the spatial correlation of traffic links under different traffic regimes. We mimic the behavior of real traffic by pinpointing the spatial correlation between 140 freeway traffic links in a major sub-network of the Minneapolis—St. Paul freeway system with a grid-like network topology. This topology enables us to juxtapose the positive and negative correlation between links, which has been overlooked in short-term traffic forecasting models. To accurately and reliably measure the correlation between traffic links, we develop an algorithm that eliminates temporal trends in three dimensions: (1) hourly dimension, (2) weekly dimension, and (3) system dimension for each link. The spatial correlation of traffic links exhibits a stronger negative correlation in rush hours, when congestion affects route choice. Although this correlation occurs mostly in parallel links, it is also observed upstream, where travelers receive information and are able to switch to substitute paths. Irrespective of the time-of-day and day-of-week, a strong positive correlation is witnessed between upstream and downstream links. This correlation is stronger in uncongested regimes, as traffic flow passes through consecutive links more quickly and there is no congestion effect to shift or stall traffic. The extracted spatial correlation structure can augment the accuracy of short-term traffic forecasting models. PMID:28472093

Road Accident Prevention with Instant Emergency Warning Message Dissemination in Vehicular Ad-Hoc Network.

PubMed

Gokulakrishnan, P; Ganeshkumar, P

2015-01-01

A Road Accident Prevention (RAP) scheme based on Vehicular Backbone Network (VBN) structure is proposed in this paper for Vehicular Ad-hoc Network (VANET). The RAP scheme attempts to prevent vehicles from highway road traffic accidents and thereby reduces death and injury rates. Once the possibility of an emergency situation (i.e. an accident) is predicted in advance, instantly RAP initiates a highway road traffic accident prevention scheme. The RAP scheme constitutes the following activities: (i) the Road Side Unit (RSU) constructs a Prediction Report (PR) based on the status of the vehicles and traffic in the highway roads, (ii) the RSU generates an Emergency Warning Message (EWM) based on an abnormal PR, (iii) the RSU forms a VBN structure and (iv) the RSU disseminates the EWM to the vehicles that holds the high Risk Factor (RF) and travels in High Risk Zone (HRZ). These vehicles might reside either within the RSU's coverage area or outside RSU's coverage area (reached using VBN structure). The RAP scheme improves the performance of EWM dissemination in terms of increase in notification and decrease in end-to-end delay. The RAP scheme also reduces infrastructure cost (number of RSUs) by formulating and deploying the VBN structure. The RAP scheme with VBN structure improves notification by 19 percent and end-to-end delay by 14.38 percent for a vehicle density of 160 vehicles. It is also proved from the simulation experiment that the performance of RAP scheme is promising in 4-lane highway roads.

Road Accident Prevention with Instant Emergency Warning Message Dissemination in Vehicular Ad-Hoc Network

PubMed Central

P, Gokulakrishnan; P, Ganeshkumar

2015-01-01

A Road Accident Prevention (RAP) scheme based on Vehicular Backbone Network (VBN) structure is proposed in this paper for Vehicular Ad-hoc Network (VANET). The RAP scheme attempts to prevent vehicles from highway road traffic accidents and thereby reduces death and injury rates. Once the possibility of an emergency situation (i.e. an accident) is predicted in advance, instantly RAP initiates a highway road traffic accident prevention scheme. The RAP scheme constitutes the following activities: (i) the Road Side Unit (RSU) constructs a Prediction Report (PR) based on the status of the vehicles and traffic in the highway roads, (ii) the RSU generates an Emergency Warning Message (EWM) based on an abnormal PR, (iii) the RSU forms a VBN structure and (iv) the RSU disseminates the EWM to the vehicles that holds the high Risk Factor (RF) and travels in High Risk Zone (HRZ). These vehicles might reside either within the RSU’s coverage area or outside RSU’s coverage area (reached using VBN structure). The RAP scheme improves the performance of EWM dissemination in terms of increase in notification and decrease in end-to-end delay. The RAP scheme also reduces infrastructure cost (number of RSUs) by formulating and deploying the VBN structure. The RAP scheme with VBN structure improves notification by 19 percent and end-to-end delay by 14.38 percent for a vehicle density of 160 vehicles. It is also proved from the simulation experiment that the performance of RAP scheme is promising in 4-lane highway roads. PMID:26636576

Finding Cardinality Heavy-Hitters in Massive Traffic Data and Its Application to Anomaly Detection

NASA Astrophysics Data System (ADS)

Ishibashi, Keisuke; Mori, Tatsuya; Kawahara, Ryoichi; Hirokawa, Yutaka; Kobayashi, Atsushi; Yamamoto, Kimihiro; Sakamoto, Hitoaki; Asano, Shoichiro

We propose an algorithm for finding heavy hitters in terms of cardinality (the number of distinct items in a set) in massive traffic data using a small amount of memory. Examples of such cardinality heavy-hitters are hosts that send large numbers of flows, or hosts that communicate with large numbers of other hosts. Finding these hosts is crucial to the provision of good communication quality because they significantly affect the communications of other hosts via either malicious activities such as worm scans, spam distribution, or botnet control or normal activities such as being a member of a flash crowd or performing peer-to-peer (P2P) communication. To precisely determine the cardinality of a host we need tables of previously seen items for each host (e. g., flow tables for every host) and this may infeasible for a high-speed environment with a massive amount of traffic. In this paper, we use a cardinality estimation algorithm that does not require these tables but needs only a little information called the cardinality summary. This is made possible by relaxing the goal from exact counting to estimation of cardinality. In addition, we propose an algorithm that does not need to maintain the cardinality summary for each host, but only for partitioned addresses of a host. As a result, the required number of tables can be significantly decreased. We evaluated our algorithm using actual backbone traffic data to find the heavy-hitters in the number of flows and estimate the number of these flows. We found that while the accuracy degraded when estimating for hosts with few flows, the algorithm could accurately find the top-100 hosts in terms of the number of flows using a limited-sized memory. In addition, we found that the number of tables required to achieve a pre-defined accuracy increased logarithmically with respect to the total number of hosts, which indicates that our method is applicable for large traffic data for a very large number of hosts. We also

Early Obstacle Detection and Avoidance for All to All Traffic Pattern in Wireless Sensor Networks

NASA Astrophysics Data System (ADS)

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.

Investigating the relationship between jobs-housing balance and traffic safety.

PubMed

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.

Determination of backbone chain direction of PDA using FFM

NASA Astrophysics Data System (ADS)

Jo, Sadaharu; Okamoto, Kentaro; Takenaga, Mitsuru

2010-01-01

The effect of backbone chains on friction force was investigated on both Langmuir-Blodgett (LB) films of 10,12-heptacosadiynoic acid and the (0 1 0) surfaces of single crystals of 2,4-hexadiene-1,6-diol using friction force microscopy (FFM). It was observed that friction force decreased when the scanning direction was parallel to the [0 0 1] direction in both samples. Moreover, friction force decreased when the scanning direction was parallel to the crystallographic [1 0 2], [1 0 1], [1 0 0] and [1 0 1¯] directions in only the single crystals. For the LB films, the [0 0 1] direction corresponds to the backbone chain direction of 10,12-heptacosadiynoic acid. For the single crystals, both the [0 0 1] and [1 0 1] directions correspond to the backbone chain direction, and the [1 0 2], [1 0 0] and [1 0 1¯] directions correspond to the low-index crystallographic direction. In both the LB films and single crystals, the friction force was minimized when the directions of scanning and the backbone chain were parallel.

Identification of critical regulatory genes in cancer signaling network using controllability analysis

NASA Astrophysics Data System (ADS)

Ravindran, Vandana; Sunitha, V.; Bagler, Ganesh

2017-05-01

Cancer is characterized by a complex web of regulatory mechanisms which makes it difficult to identify features that are central to its control. Molecular integrative models of cancer, generated with the help of data from experimental assays, facilitate use of control theory to probe for ways of controlling the state of such a complex dynamic network. We modeled the human cancer signaling network as a directed graph and analyzed it for its controllability, identification of driver nodes and their characterization. We identified the driver nodes using the maximum matching algorithm and classified them as backbone, peripheral and ordinary based on their role in regulatory interactions and control of the network. We found that the backbone driver nodes were key to driving the regulatory network into cancer phenotype (via mutations) as well as for steering into healthy phenotype (as drug targets). This implies that while backbone genes could lead to cancer by virtue of mutations, they are also therapeutic targets of cancer. Further, based on their impact on the size of the set of driver nodes, genes were characterized as indispensable, dispensable and neutral. Indispensable nodes within backbone of the network emerged as central to regulatory mechanisms of control of cancer. In addition to probing the cancer signaling network from the perspective of control, our findings suggest that indispensable backbone driver nodes could be potentially leveraged as therapeutic targets. This study also illustrates the application of structural controllability for studying the mechanisms underlying the regulation of complex diseases.

On Applicability of Network Coding Technique for 6LoWPAN-based Sensor Networks.

PubMed

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.

Models for IP/MPLS routing performance: convergence, fast reroute, and QoS impact

NASA Astrophysics Data System (ADS)

Choudhury, Gagan L.

2004-09-01

We show how to model the black-holing and looping of traffic during an Interior Gateway Protocol (IGP) convergence event at an IP network and how to significantly improve both the convergence time and packet loss duration through IGP parameter tuning and algorithmic improvement. We also explore some congestion avoidance and congestion control algorithms that can significantly improve stability of networks in the face of occasional massive control message storms. Specifically we show the positive impacts of prioritizing Hello and Acknowledgement packets and slowing down LSA generation and retransmission generation on detecting congestion in the network. For some types of video, voice signaling and circuit emulation applications it is necessary to reduce traffic loss durations following a convergence event to below 100 ms and we explore that using Fast Reroute algorithms based on Multiprotocol Label Switching Traffic Engineering (MPLS-TE) that effectively bypasses IGP convergence. We explore the scalability of primary and backup MPLS-TE tunnels where MPLS-TE domain is in the backbone-only or edge-to-edge. We also show how much extra backbone resource is needed to support Fast Reroute and how can that be reduced by taking advantage of Constrained Shortest Path (CSPF) routing of MPLS-TE and by reserving less than 100% of primary tunnel bandwidth during Fast Reroute.

Automatic, time-interval traffic counts for recreation area management planning

Treesearch

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

NASA Astrophysics Data System (ADS)

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.

Visual traffic jam analysis based on trajectory data.

PubMed

Wang, Zuchao; Lu, Min; Yuan, Xiaoru; Zhang, Junping; van de Wetering, Huub

2013-12-01

In this work, we present an interactive system for visual analysis of urban traffic congestion based on GPS trajectories. For these trajectories we develop strategies to extract and derive traffic jam information. After cleaning the trajectories, they are matched to a road network. Subsequently, traffic speed on each road segment is computed and traffic jam events are automatically detected. Spatially and temporally related events are concatenated in, so-called, traffic jam propagation graphs. These graphs form a high-level description of a traffic jam and its propagation in time and space. Our system provides multiple views for visually exploring and analyzing the traffic condition of a large city as a whole, on the level of propagation graphs, and on road segment level. Case studies with 24 days of taxi GPS trajectories collected in Beijing demonstrate the effectiveness of our system.

Macroscopic modeling of freeway traffic using an artificial neural network

DOT National Transportation Integrated Search

1997-01-01

Traffic flow on freeways is a complex process that often is described by a set of highly nonlinear, dynamic equations in the form of a macroscopic traffic flow model. However, some of the existing macroscopic models have been found to exhibit instabi...

Fiber optic sensor for monitoring a density of road traffic

NASA Astrophysics Data System (ADS)

Nedoma, Jan; Fajkus, Marcel; Martinek, Radek; Mec, Pavel; Novak, Martin; Jargus, Jan; Vasinek, Vladimir

2017-10-01

Authors of this article have focused on the use of fiber-optic technology in the car traffic. The article describes the use of fiber-optic interferometer for the purpose of the dynamic calculation of traffic density and inclusion the vehicle into the traffic lane. The objective is to increase safety and traffic flow. Presented solution is characterized by the non-destructive character to the road - sensor no need built into the roadway. The sensor works with standard telecommunications fibers of the G.652 standard. Other hallmarks are immunity to electromagnetic interference (EMI) and passivity of concerning the power supply. The massive expansion of optical cables within telecommunication needs along roads offers the possibility of connecting to the existing telecommunications fiber-optic network without a converter. Information can be transmitted at distances of several km up to tens km by this fiber-optic network. Set of experimental measurements in real traffic flow verified the functionality of presented solution.

Fault tolerant high-performance PACS network design and implementation

NASA Astrophysics Data System (ADS)

Chimiak, William J.; Boehme, Johannes M.

1998-07-01

The Wake Forest University School of Medicine and the Wake Forest University/Baptist Medical Center (WFUBMC) are implementing a second generation PACS. The first generation PACS provided helpful information about the functional and temporal requirements of the system. It highlighted the importance of image retrieval speed, system availability, RIS/HIS integration, the ability to rapidly view images on any PACS workstation, network bandwidth, equipment redundancy, and the ability for the system to evolve using standards-based components. This paper deals with the network design and implementation of the PACS. The physical layout of the hospital areas served by the PACS, the choice of network equipment and installation issues encountered are addressed. Efforts to optimize fault tolerance are discussed. The PACS network is a gigabit, mixed-media network based on LAN emulation over ATM (LANE) with a rapid migration from LANE to Multiple Protocols Over ATM (MPOA) planned. Two fault-tolerant backbone ATM switches serve to distribute network accesses with two load-balancing 622 megabit per second (Mbps) OC-12 interconnections. The switch was sized to be upgradable to provide a 2.54 Gbps OC-48 interconnection with an OC-12 interconnection as a load-balancing backup. Modalities connect with legacy network interface cards to a switched-ethernet device. This device has two 155 Mbps OC-3 load-balancing uplinks to each of the backbone ATM switches of the PACS. This provides a fault-tolerant logical connection to the modality servers which pass verified DICOM images to the PACS servers and proper PACS diagnostic workstations. Where fiber pulls were prohibitively expensive, edge ATM switches were installed with an OC-12 uplink to a backbone ATM switches. The PACS and data base servers are fault-tolerant, hot-swappable Sun Enterprise Servers with an OC-12 connection to a backbone ATM switch and a fast-ethernet connection to a back-up network. The workstations come with 10

Performance Evaluation of FAST TCP Traffic-Flows in Multihomed MANETs

NASA Astrophysics Data System (ADS)

Mudassir, Mumajjed Ul; Akram, Adeel

In Mobile Ad hoc Networks (MANETs) an efficient communication protocol is required at the transport layer. Mobile nodes moving around will have temporary and rather short-lived connectivity with each other and the Internet, thus requiring efficient utilization of network resources. Moreover the problems arising due to high mobility, collision and congestion must also be considered. Multihoming allows higher reliability and enhancement of network throughput. FAST TCP is a new promising transport layer protocol developed for high-speed high-latency networks. In this paper, we have analyzed the performance of FAST TCP traffic flows in multihomed MANETs and compared it with standard TCP (TCP Reno) traffic flows in non-multihomed MANETs.

Di-Isocyanate Crosslinked Aerogels with 1, 6-Bis (Trimethoxysilyl) Hexane Incorporated in Silica Backbone

NASA Technical Reports Server (NTRS)

Vivod, Stephanie L.; Meador, Mary Ann B.; Nguyen, Baochau N.; Quade, Derek; Randall, Jason; Perry, Renee

2008-01-01

Silica aerogels are desirable materials for many applications that take advantage of their light weight and low thermal conductivity. Addition of a conformal polymer coating which bonds with the amine decorated surface of the silica network improves the strength of the aerogels by as much as 200 times. Even with vast improvement in strength they still tend to undergo brittle failure due to the rigid silica backbone. We hope to increase the flexibility and elastic recovery of the silica based aerogel by altering the silica back-bone by incorporation of more flexible hexane links. To this end, we investigated the use of 1,6-bis(trimethoxysilyl)hexane (BTMSH), a polysilsesquioxane precursor3, as an additional co-reactant to prepare silica gels which were subsequently cross-linked with di-isocyanate. Previously, this approach of adding flexibility by BTMSH incorporation was demonstrated with styrene cross-linked aerogels. In our study, we varied silane concentration, mol % of silicon from BTMSH and di-isocyanate concentration by weight percent to attempt to optimize both the flexibility and the strength of the aerogels.

Implementing and Simulating Dynamic Traffic Assignment with Intelligent Transportation Systems in Cube Avenue

NASA Technical Reports Server (NTRS)

Foytik, Peter; Robinson, Mike

2010-01-01

As urban populations and traffic congestion levels increase, effective use of information and communication tools and intelligent transportation systems as becoming increasingly important in order to maximize the efficiency of transportation networks. The appropriate placement and employment of these tools within a network is critical to their effectiveness. This presentation proposes and demonstrates the use of a commercial transportation simulation tool to simulate dynamic traffic assignment and rerouting to model route modifications as a result of traffic information.

Identifying MMORPG Bots: A Traffic Analysis Approach

NASA Astrophysics Data System (ADS)

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.

Current distribution in conducting nanowire networks

NASA Astrophysics Data System (ADS)

Kumar, Ankush; Vidhyadhiraja, N. S.; Kulkarni, Giridhar U.

2017-07-01

Conducting nanowire networks find diverse applications in solar cells, touch-screens, transparent heaters, sensors, and various related transparent conducting electrode (TCE) devices. The performances of these devices depend on effective resistance, transmittance, and local current distribution in these networks. Although, there have been rigorous studies addressing resistance and transmittance in TCE, not much attention is paid on studying the distribution of current. Present work addresses this compelling issue of understanding current distribution in TCE networks using analytical as well as Monte-Carlo approaches. We quantified the current carrying backbone region against isolated and dangling regions as a function of wire density (ranging from percolation threshold to many multiples of threshold) and compared the wired connectivity with those obtained from template-based methods. Further, the current distribution in the obtained backbone is studied using Kirchhoff's law, which reveals that a significant fraction of the backbone (which is believed to be an active current component) may not be active for end-to-end current transport due to the formation of intervening circular loops. The study shows that conducting wire based networks possess hot spots (extremely high current carrying regions) which can be potential sources of failure. The fraction of these hot spots is found to decrease with increase in wire density, while they are completely absent in template based networks. Thus, the present work discusses unexplored issues related to current distribution in conducting networks, which are necessary to choose the optimum network for best TCE applications.

Solution, solid phase and computational structures of apicidin and its backbone-reduced analogs.

PubMed

Kranz, Michael; Murray, Peter John; Taylor, Stephen; Upton, Richard J; Clegg, William; Elsegood, Mark R J

2006-06-01

The recently isolated broad-spectrum antiparasitic apicidin (1) is one of the few naturally occurring cyclic tetrapeptides (CTP). Depending on the solvent, the backbone of 1 exhibits two gamma-turns (in CH(2)Cl(2)) or a beta-turn (in DMSO), differing solely in the rotation of the plane of one of the amide bonds. In the X-ray crystal structure, the peptidic C==Os and NHs are on opposite sides of the backbone plane, giving rise to infinite stacks of cyclotetrapeptides connected by three intermolecular hydrogen bonds between the backbones. Conformational searches (Amber force field) on a truncated model system of 1 confirm all three backbone conformations to be low-energy states. The previously synthesized analogs of 1 containing a reduced amide bond exhibit the same backbone conformation as 1 in DMSO, which is confirmed further by the X-ray crystal structure of a model system of the desoxy analogs of 1. This similarity helps in explaining why the desoxy analogs retain some of the antiprotozoal activities of apicidin. The backbone-reduction approach designed to facilitate the cyclization step of the acyclic precursors of the CTPs seems to retain the conformational preferences of the parent peptide backbone.

Serial Network Flow Monitor

NASA Technical Reports Server (NTRS)

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.

Effects of disulfide bridges and backbone connectivity on water sorption by protein matrices.

PubMed

Kim, Sang Beom; Singh, Rakesh S; Paul, Prem K C; Debenedetti, Pablo G

2017-08-11

Understanding the water sorption behavior of protein powders is important in applications such as the preservation of protein-based pharmaceuticals. Most globular proteins exhibit a characteristic sigmoidal water adsorption isotherm at ambient conditions. However, it is not well understood how water sorption behavior is influenced by intrinsic factors that are related to structural properties of proteins. We investigate computationally how structural constraints on proteins influence the water sorption isotherms of amorphous protein powders. Specifically, we study the effects of non-local disulfide linkages and backbone connectivity using pheromone ER-23 and lysozyme as model proteins. We find that non-local disulfide linkages can significantly restrict structural changes during hydration and dehydration, and this in turn greatly reduces the extent of hysteresis between the adsorption and desorption branches. Upon removing the backbone connectivity by breaking all peptide bonds in lysozyme, we find that the hysteresis shifts towards the lower humidity regime, and the water uptake capacity is significantly enhanced. We attribute these changes to the higher aggregation propensity of the constraint-free amino acids in dehydrated condition, and the formation of a spanning water network at high hydration levels.

Distributed traffic signal control using fuzzy logic

NASA Technical Reports Server (NTRS)

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.

Roads at risk - traffic detours from debris flows in southern Norway

NASA Astrophysics Data System (ADS)

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

2014-10-01

Globalization 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 kilometers 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 northwestern 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 of speedy delivery of services and goods.

Roads at risk: traffic detours from debris flows in southern Norway

NASA Astrophysics Data System (ADS)

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.

Measurements and modelling of base station power consumption under real traffic loads.

PubMed

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.

Underestimated Halogen Bonds Forming with Protein Backbone in Protein Data Bank.

PubMed

Zhang, Qian; Xu, Zhijian; Shi, Jiye; Zhu, Weiliang

2017-07-24

Halogen bonds (XBs) are attracting increasing attention in biological systems. Protein Data Bank (PDB) archives experimentally determined XBs in biological macromolecules. However, no software for structure refinement in X-ray crystallography takes into account XBs, which might result in the weakening or even vanishing of experimentally determined XBs in PDB. In our previous study, we showed that side-chain XBs forming with protein side chains are underestimated in PDB on the basis of the phenomenon that the proportion of side-chain XBs to overall XBs decreases as structural resolution becomes lower and lower. However, whether the dominant backbone XBs forming with protein backbone are overlooked is still a mystery. Here, with the help of the ratio (R F ) of the observed XBs' frequency of occurrence to their frequency expected at random, we demonstrated that backbone XBs are largely overlooked in PDB, too. Furthermore, three cases were discovered possessing backbone XBs in high resolution structures while losing the XBs in low resolution structures. In the last two cases, even at 1.80 Å resolution, the backbone XBs were lost, manifesting the urgent need to consider XBs in the refinement process during X-ray crystallography study.

Traffic jam dynamics in stochastic cellular automata

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nagel, K.; Schreckenberg, M.

1995-09-01

Simple models for particles hopping on a grid (cellular automata) are used to simulate (single lane) traffic flow. Despite their simplicity, these models are astonishingly realistic in reproducing start-stop-waves and realistic fundamental diagrams. One can use these models to investigate traffic phenomena near maximum flow. A so-called phase transition at average maximum flow is visible in the life-times of jams. The resulting dynamic picture is consistent with recent fluid-dynamical results by Kuehne/Kerner/Konhaeuser, and with Treiterer`s hysteresis description. This places CA models between car-following models and fluid-dynamical models for traffic flow. CA models are tested in projects in Los Alamos (USA)more » and in NRW (Germany) for large scale microsimulations of network traffic.« less

Using Tensor Completion Method to Achieving Better Coverage of Traffic State Estimation from Sparse Floating Car Data

PubMed Central

Ran, Bin; Song, Li; Cheng, Yang; Tan, Huachun

2016-01-01

Traffic state estimation from the floating car system is a challenging problem. The low penetration rate and random distribution make available floating car samples usually cover part space and time points of the road networks. To obtain a wide range of traffic state from the floating car system, many methods have been proposed to estimate the traffic state for the uncovered links. However, these methods cannot provide traffic state of the entire road networks. In this paper, the traffic state estimation is transformed to solve a missing data imputation problem, and the tensor completion framework is proposed to estimate missing traffic state. A tensor is constructed to model traffic state in which observed entries are directly derived from floating car system and unobserved traffic states are modeled as missing entries of constructed tensor. The constructed traffic state tensor can represent spatial and temporal correlations of traffic data and encode the multi-way properties of traffic state. The advantage of the proposed approach is that it can fully mine and utilize the multi-dimensional inherent correlations of traffic state. We tested the proposed approach on a well calibrated simulation network. Experimental results demonstrated that the proposed approach yield reliable traffic state estimation from very sparse floating car data, particularly when dealing with the floating car penetration rate is below 1%. PMID:27448326

Using Tensor Completion Method to Achieving Better Coverage of Traffic State Estimation from Sparse Floating Car Data.

PubMed

Ran, Bin; Song, Li; Zhang, Jian; Cheng, Yang; Tan, Huachun

2016-01-01

Traffic state estimation from the floating car system is a challenging problem. The low penetration rate and random distribution make available floating car samples usually cover part space and time points of the road networks. To obtain a wide range of traffic state from the floating car system, many methods have been proposed to estimate the traffic state for the uncovered links. However, these methods cannot provide traffic state of the entire road networks. In this paper, the traffic state estimation is transformed to solve a missing data imputation problem, and the tensor completion framework is proposed to estimate missing traffic state. A tensor is constructed to model traffic state in which observed entries are directly derived from floating car system and unobserved traffic states are modeled as missing entries of constructed tensor. The constructed traffic state tensor can represent spatial and temporal correlations of traffic data and encode the multi-way properties of traffic state. The advantage of the proposed approach is that it can fully mine and utilize the multi-dimensional inherent correlations of traffic state. We tested the proposed approach on a well calibrated simulation network. Experimental results demonstrated that the proposed approach yield reliable traffic state estimation from very sparse floating car data, particularly when dealing with the floating car penetration rate is below 1%.

Cellular automata model for traffic flow at intersections in internet of vehicles

NASA Astrophysics Data System (ADS)

Zhao, Han-Tao; Liu, Xin-Ru; Chen, Xiao-Xu; Lu, Jian-Cheng

2018-03-01

Considering the effect of the front vehicle's speed, the influence of the brake light and the conflict of the traffic flow, we established a cellular automata model called CE-NS for traffic flow at the intersection in the non-vehicle networking environment. According to the information interaction of Internet of Vehicles (IoV), introducing parameters describing the congestion and the accurate speed of the front vehicle into the CE-NS model, we improved the rules of acceleration, deceleration and conflict, and finally established a cellular automata model for traffic flow at intersections of IoV. The relationship between traffic parameters such as vehicle speed, flow and average travel time is obtained by numerical simulation of two models. Based on this, we compared the traffic situation of the non-vehicle networking environment with conditions of IoV environment, and analyzed the influence of the different degree of IoV on the traffic flow. The results show that the traffic speed is increased, the travel time is reduced, the flux of intersections is increased and the traffic flow is more smoothly under IoV environment. After the vehicle which achieves IoV reaches a certain proportion, the operation effect of the traffic flow begins to improve obviously.

An ultra low-power and traffic-adaptive medium access control protocol for wireless body area network.

PubMed

Ullah, Sana; Kwak, Kyung Sup

2012-06-01

Wireless Body Area Network (WBAN) consists of low-power, miniaturized, and autonomous wireless sensor nodes that enable physicians to remotely monitor vital signs of patients and provide real-time feedback with medical diagnosis and consultations. It is the most reliable and cheaper way to take care of patients suffering from chronic diseases such as asthma, diabetes and cardiovascular diseases. Some of the most important attributes of WBAN is low-power consumption and delay. This can be achieved by introducing flexible duty cycling techniques on the energy constraint sensor nodes. Stated otherwise, low duty cycle nodes should not receive frequent synchronization and control packets if they have no data to send/receive. In this paper, we introduce a Traffic-adaptive MAC protocol (TaMAC) by taking into account the traffic information of the sensor nodes. The protocol dynamically adjusts the duty cycle of the sensor nodes according to their traffic-patterns, thus solving the idle listening and overhearing problems. The traffic-patterns of all sensor nodes are organized and maintained by the coordinator. The TaMAC protocol is supported by a wakeup radio that is used to accommodate emergency and on-demand events in a reliable manner. The wakeup radio uses a separate control channel along with the data channel and therefore it has considerably low power consumption requirements. Analytical expressions are derived to analyze and compare the performance of the TaMAC protocol with the well-known beacon-enabled IEEE 802.15.4 MAC, WiseMAC, and SMAC protocols. The analytical derivations are further validated by simulation results. It is shown that the TaMAC protocol outperforms all other protocols in terms of power consumption and delay.

The Graphical Representation of the Digital Astronaut Physiology Backbone

NASA Technical Reports Server (NTRS)

Briers, Demarcus

2010-01-01

This report summarizes my internship project with the NASA Digital Astronaut Project to analyze the Digital Astronaut (DA) physiology backbone model. The Digital Astronaut Project (DAP) applies integrated physiology models to support space biomedical operations, and to assist NASA researchers in closing knowledge gaps related to human physiologic responses to space flight. The DA physiology backbone is a set of integrated physiological equations and functions that model the interacting systems of the human body. The current release of the model is HumMod (Human Model) version 1.5 and was developed over forty years at the University of Mississippi Medical Center (UMMC). The physiology equations and functions are scripted in an XML schema specifically designed for physiology modeling by Dr. Thomas G. Coleman at UMMC. Currently it is difficult to examine the physiology backbone without being knowledgeable of the XML schema. While investigating and documenting the tags and algorithms used in the XML schema, I proposed a standard methodology for a graphical representation. This standard methodology may be used to transcribe graphical representations from the DA physiology backbone. In turn, the graphical representations can allow examination of the physiological functions and equations without the need to be familiar with the computer programming languages or markup languages used by DA modeling software.

Game theory and traffic assignment.

DOT National Transportation Integrated Search

2013-09-01

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

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

PubMed

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

2016-08-01

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

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

DOT National Transportation Integrated Search

2012-05-01

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

Transport Traffic Analysis for Abusive Infrastructure Characterization

DTIC Science & Technology

2012-12-14

Introduction Abusive traffic abounds on the Internet, in the form of email, malware, vulnerability scanners, worms, denial-of-service, drive-by-downloads, scam ...insight is two-fold. First, attackers have a basic requirement to source large amounts of data, be it denial-of-service, scam -hosting, spam, or other...the network core. This paper explores the power of transport-layer traffic analysis to detect and characterize scam hosting infrastructure, including

Improving the effectiveness of traffic monitoring based on wireless location technology.

DOT National Transportation Integrated Search

2004-01-01

A fundamental requirement for effectively monitoring and operating transportation facilities is reliable, accurate data on traffic flow. The current state of the practice is to use networks of point detectors to gather information on traffic flow at ...

Golden Ratio Genetic Algorithm Based Approach for Modelling and Analysis of the Capacity Expansion of Urban Road Traffic Network

PubMed Central

Zhang, Lun; Zhang, Meng; Yang, Wenchen; Dong, Decun

2015-01-01

This paper presents the modelling and analysis of the capacity expansion of urban road traffic network (ICURTN). Thebilevel programming model is first employed to model the ICURTN, in which the utility of the entire network is maximized with the optimal utility of travelers' route choice. Then, an improved hybrid genetic algorithm integrated with golden ratio (HGAGR) is developed to enhance the local search of simple genetic algorithms, and the proposed capacity expansion model is solved by the combination of the HGAGR and the Frank-Wolfe algorithm. Taking the traditional one-way network and bidirectional network as the study case, three numerical calculations are conducted to validate the presented model and algorithm, and the primary influencing factors on extended capacity model are analyzed. The calculation results indicate that capacity expansion of road network is an effective measure to enlarge the capacity of urban road network, especially on the condition of limited construction budget; the average computation time of the HGAGR is 122 seconds, which meets the real-time demand in the evaluation of the road network capacity. PMID:25802512

Adaptive Bloom Filter: A Space-Efficient Counting Algorithm for Unpredictable Network Traffic

NASA Astrophysics Data System (ADS)

Matsumoto, Yoshihide; Hazeyama, Hiroaki; Kadobayashi, Youki

The Bloom Filter (BF), a space-and-time-efficient hashcoding method, is used as one of the fundamental modules in several network processing algorithms and applications such as route lookups, cache hits, packet classification, per-flow state management or network monitoring. BF is a simple space-efficient randomized data structure used to represent a data set in order to support membership queries. However, BF generates false positives, and cannot count the number of distinct elements. A counting Bloom Filter (CBF) can count the number of distinct elements, but CBF needs more space than BF. We propose an alternative data structure of CBF, and we called this structure an Adaptive Bloom Filter (ABF). Although ABF uses the same-sized bit-vector used in BF, the number of hash functions employed by ABF is dynamically changed to record the number of appearances of a each key element. Considering the hash collisions, the multiplicity of a each key element on ABF can be estimated from the number of hash functions used to decode the membership of the each key element. Although ABF can realize the same functionality as CBF, ABF requires the same memory size as BF. We describe the construction of ABF and IABF (Improved ABF), and provide a mathematical analysis and simulation using Zipf's distribution. Finally, we show that ABF can be used for an unpredictable data set such as real network traffic.

Spatial-spectral flexible optical networking: enabling switching solutions for a simplified and efficient SDM network platform

NASA Astrophysics Data System (ADS)

Tomkos, I.; Zakynthinos, P.; Klonidis, D.; Marom, D.; Sygletos, S.; Ellis, A.; Salvadori, E.; Siracusa, D.; Angelou, M.; Papastergiou, G.; Psaila, N.; Ferran, J. F.; Ben-Ezra, S.; Jimenez, F.; Fernández-Palacios, J. P.

2013-12-01

The traffic carried by core optical networks grows at a steady but remarkable pace of 30-40% year-over-year. Optical transmissions and networking advancements continue to satisfy the traffic requirements by delivering the content over the network infrastructure in a cost and energy efficient manner. Such core optical networks serve the information traffic demands in a dynamic way, in response to requirements for shifting of traffics demands, both temporally (day/night) and spatially (business district/residential). However as we are approaching fundamental spectral efficiency limits of singlemode fibers, the scientific community is pursuing recently the development of an innovative, all-optical network architecture introducing the spatial degree of freedom when designing/operating future transport networks. Spacedivision- multiplexing through the use of bundled single mode fibers, and/or multi-core fibers and/or few-mode fibers can offer up to 100-fold capacity increase in future optical networks. The EU INSPACE project is working on the development of a complete spatial-spectral flexible optical networking solution, offering the network ultra-high capacity, flexibility and energy efficiency required to meet the challenges of delivering exponentially growing traffic demands in the internet over the next twenty years. In this paper we will present the motivation and main research activities of the INSPACE consortium towards the realization of the overall project solution.

Optimal topologies for maximizing network transmission capacity

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

Nonribosomal biosynthesis of backbone-modified peptides

NASA Astrophysics Data System (ADS)

Niquille, David L.; Hansen, Douglas A.; Mori, Takahiro; Fercher, David; Kries, Hajo; Hilvert, Donald

2018-03-01

Biosynthetic modification of nonribosomal peptide backbones represents a potentially powerful strategy to modulate the structure and properties of an important class of therapeutics. Using a high-throughput assay for catalytic activity, we show here that an L-Phe-specific module of an archetypal nonribosomal peptide synthetase can be reprogrammed to accept and process the backbone-modified amino acid (S)-β-Phe with near-native specificity and efficiency. A co-crystal structure with a non-hydrolysable aminoacyl-AMP analogue reveals the origins of the 40,000-fold α/β-specificity switch, illuminating subtle but precise remodelling of the active site. When the engineered catalyst was paired with downstream module(s), (S)-β-Phe-containing peptides were produced at preparative scale in vitro (~1 mmol) and high titres in vivo (~100 mg l-1), highlighting the potential of biosynthetic pathway engineering for the construction of novel nonribosomal β-frameworks.

Development of a Traffic Management Decision Support Tool for Freeway Incident Traffic Management (FITM) Plan Deployment

DOT National Transportation Integrated Search

2017-12-01

Traffic incidents have long been recognized as the main contributor to congestion in highway networks. Thus, contending with non-recurrent congestion has been a priority task for most highway agencies over the past decades. Under most incident scenar...

Computer Networks and Networking: A Primer.

ERIC Educational Resources Information Center

Collins, Mauri P.

1993-01-01

Provides a basic introduction to computer networks and networking terminology. Topics addressed include modems; the Internet; TCP/IP (Transmission Control Protocol/Internet Protocol); transmission lines; Internet Protocol numbers; network traffic; Fidonet; file transfer protocol (FTP); TELNET; electronic mail; discussion groups; LISTSERV; USENET;…

Analysis of the Chinese air route network as a complex network

NASA Astrophysics Data System (ADS)

Cai, Kai-Quan; Zhang, Jun; Du, Wen-Bo; Cao, Xian-Bin

2012-02-01

The air route network, which supports all the flight activities of the civil aviation, is the most fundamental infrastructure of air traffic management system. In this paper, we study the Chinese air route network (CARN) within the framework of complex networks. We find that CARN is a geographical network possessing exponential degree distribution, low clustering coefficient, large shortest path length and exponential spatial distance distribution that is obviously different from that of the Chinese airport network (CAN). Besides, via investigating the flight data from 2002 to 2010, we demonstrate that the topology structure of CARN is homogeneous, howbeit the distribution of flight flow on CARN is rather heterogeneous. In addition, the traffic on CARN keeps growing in an exponential form and the increasing speed of west China is remarkably larger than that of east China. Our work will be helpful to better understand Chinese air traffic systems.

Hybrid protection algorithms based on game theory in multi-domain optical networks

NASA Astrophysics Data System (ADS)

Guo, Lei; Wu, Jingjing; Hou, Weigang; Liu, Yejun; Zhang, Lincong; Li, Hongming

2011-12-01

With the network size increasing, the optical backbone is divided into multiple domains and each domain has its own network operator and management policy. At the same time, the failures in optical network may lead to a huge data loss since each wavelength carries a lot of traffic. Therefore, the survivability in multi-domain optical network is very important. However, existing survivable algorithms can achieve only the unilateral optimization for profit of either users or network operators. Then, they cannot well find the double-win optimal solution with considering economic factors for both users and network operators. Thus, in this paper we develop the multi-domain network model with involving multiple Quality of Service (QoS) parameters. After presenting the link evaluation approach based on fuzzy mathematics, we propose the game model to find the optimal solution to maximize the user's utility, the network operator's utility, and the joint utility of user and network operator. Since the problem of finding double-win optimal solution is NP-complete, we propose two new hybrid protection algorithms, Intra-domain Sub-path Protection (ISP) algorithm and Inter-domain End-to-end Protection (IEP) algorithm. In ISP and IEP, the hybrid protection means that the intelligent algorithm based on Bacterial Colony Optimization (BCO) and the heuristic algorithm are used to solve the survivability in intra-domain routing and inter-domain routing, respectively. Simulation results show that ISP and IEP have the similar comprehensive utility. In addition, ISP has better resource utilization efficiency, lower blocking probability, and higher network operator's utility, while IEP has better user's utility.

Computer Simulations of Bottle Brushes: From Melts to Soft Networks

DOE PAGES

Cao, Zhen; Carrillo, Jan-Michael Y.; Sheiko, Sergei S.; ...

2015-07-13

We use a combination of Molecular dynamics simulations and analytical calculations, and study dens bottle-brush systems in a melt and network State. Analysis of our simulation results shows that bottle-brush macromolecules in melt behave as ideal chains with effective Kuhn length b K. Simulations show that the bottle-brush-induced bending rigidity is due to an entropy decrease caused by redistribution of the side chains upon backbone bending. The Kuhn length of the bottle:brushes increases with increasing the side-chain degree of polymerization n sc as b K proportional to n sc 0.46. Moreover, this model of bottle brush macromolecules is extended tomore » describe mechanical properties of bottle brush networks in linear and nonlinear deformation regimes. In the linear deformation regime, the network shear modulus scales with the degree of polymerization of the side chains as G 0 proportional to (n sc + 1) -1 as long as the ratio of the Kuhn length, b K, to the size of the fully extended bottle-brush backbone between cross-links, R-max, is smaller than unity, b K/R max << 1. Bottle-brush networks With b K/R max proportional to 1 demonstrate behavior similar to that of networks Of semiflexible chains with G 0 proportional to n sc -0.5. Finally, in the nonlinear network deformation regime, the deformation-dependent shear modulus is a universal function of the first strain invariant I 1 and bottle-brush backbone deformation ratio beta describing stretching ability of the bottle-brush backbone between cross-links.« less

Neural network for control of rearrangeable Clos networks.

PubMed

Park, Y K; Cherkassky, V

1994-09-01

Rapid evolution in the field of communication networks requires high speed switching technologies. This involves a high degree of parallelism in switching control and routing performed at the hardware level. The multistage crossbar networks have always been attractive to switch designers. In this paper a neural network approach to controlling a three-stage Clos network in real time is proposed. This controller provides optimal routing of communication traffic requests on a call-by-call basis by rearranging existing connections, with a minimum length of rearrangement sequence so that a new blocked call request can be accommodated. The proposed neural network controller uses Paull's rearrangement algorithm, along with the special (least used) switch selection rule in order to minimize the length of rearrangement sequences. The functional behavior of our model is verified by simulations and it is shown that the convergence time required for finding an optimal solution is constant, regardless of the switching network size. The performance is evaluated for random traffic with various traffic loads. Simulation results show that applying the least used switch selection rule increases the efficiency in switch rearrangements, reducing the network convergence time. The implementation aspects are also discussed to show the feasibility of the proposed approach.

Onboard connectivity network for command-and-control aircraft

NASA Astrophysics Data System (ADS)

Artz, Timothy J.

1993-02-01

Command and control (C2) aircraft are host to an array of communications, information processing, and electronic control systems. The previous method of interconnecting this equipment involves point-to-point wiring harnesses between devices. A fiber optic broadband bus can be used to improve this situation by consolidating equipment connections on a shared medium. This network, known as the Onboard Connectivity Network (OCN), is being prototypes for application on the U.S. Government's Special Air Mission aircraft. Significant weight reduction and simplified future systems integration are the primary benefits of the OCN. The OCN design integrates voice, data, control, and video communications on a 3GHZ single mode fiber backbone. Communications within the aircraft use 500 MHz coaxial cable subnetworks connected to the backbone. The entire network is a dual redundant system for enhanced reliability. Node topologies are based on VMEbus to encourage use of commercial products and facilitate future evolution of the backbone topology. Network encryption technologies are being developed for OCN communications security. Automated workstations will be implemented to control and switch communications assets and to provide a technical control, test, and monitoring function.

Chemical characteristics and antithrombotic effect of chondroitin sulfates from sturgeon skull and sturgeon backbone.

PubMed

Gui, Meng; Song, Juyi; Zhang, Lu; Wang, Shun; Wu, Ruiyun; Ma, Changwei; Li, Pinglan

2015-06-05

Chondroitin sulfates (CSs) were extracted from sturgeon skull and backbone, and their chemical composition, anticoagulant, anti-platelet and thrombolysis activities were evaluated. The average molecular weights of CS from sturgeon skull and backbone were 38.5kDa and 49.2kDa, respectively. Disaccharide analysis indicated that the sturgeon backbone CS was primarily composed of disaccharide monosulfated in position four of the GalNAc (37.8%) and disaccharide monosulfated in position six of the GalNAc (59.6%) while sturgeon skull CS was primarily composed of nonsulfated disaccharide (74.2%). Sturgeon backbone CS showed stronger antithrombotic effect than sturgeon skull CS. Sturgeon backbone CS could significantly prolong activated partial thromboplastin time (APTT) and thrombin time (TT), inhibited ADP-induced platelet aggregation and dissolved platelet plasma clots in vitro. The results suggested that sturgeon backbone CS can be explored as a functional food with antithrombotic function. Copyright © 2015 Elsevier Ltd. All rights reserved.

Measurements and Modelling of Base Station Power Consumption under Real Traffic Loads †

PubMed Central

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. PMID:22666026

VSAT communications networks - An overview

NASA Astrophysics Data System (ADS)

Chakraborty, D.

1988-05-01

The very-small-aperture-terminal (VSAT) fixed satellite communication network is a star network in which many dispersed micro terminals attempt to send data in a packet form through a random access/time-division multiple-access (RA/TDMA) satellite channel with transmission delay. The basic concept of the VSAT and its service potential are discussed. Two classes of traffic are addressed, namely, business-oriented low-rate-data traffic and bulk data traffic of corporate networks. Satellite access, throughput, and delay are considered. The size of the network population that can be served in an RA/TDMA environment is calculated. User protocols are examined. A typical VSAT business scenario is described.

Modeling 15N NMR chemical shift changes in protein backbone with pressure

NASA Astrophysics Data System (ADS)

La Penna, Giovanni; Mori, Yoshiharu; Kitahara, Ryo; Akasaka, Kazuyuki; Okamoto, Yuko

2016-08-01

Nitrogen chemical shift is a useful parameter for determining the backbone three-dimensional structure of proteins. Empirical models for fast calculation of N chemical shift are improving their reliability, but there are subtle effects that cannot be easily interpreted. Among these, the effects of slight changes in hydrogen bonds, both intramolecular and with water molecules in the solvent, are particularly difficult to predict. On the other hand, these hydrogen bonds are sensitive to changes in protein environment. In this work, the change of N chemical shift with pressure for backbone segments in the protein ubiquitin is correlated with the change in the population of hydrogen bonds involving the backbone amide group. The different extent of interaction of protein backbone with the water molecules in the solvent is put in evidence.

Discrete Mathematical Approaches to Graph-Based Traffic Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Joslyn, Cliff A.; Cowley, Wendy E.; Hogan, Emilie A.

2014-04-01

Modern cyber defense and anlaytics requires general, formal models of cyber systems. Multi-scale network models are prime candidates for such formalisms, using discrete mathematical methods based in hierarchically-structured directed multigraphs which also include rich sets of labels. An exemplar of an application of such an approach is traffic analysis, that is, observing and analyzing connections between clients, servers, hosts, and actors within IP networks, over time, to identify characteristic or suspicious patterns. Towards that end, NetFlow (or more generically, IPFLOW) data are available from routers and servers which summarize coherent groups of IP packets flowing through the network. In thismore » paper, we consider traffic analysis of Netflow using both basic graph statistics and two new mathematical measures involving labeled degree distributions and time interval overlap measures. We do all of this over the VAST test data set of 96M synthetic Netflow graph edges, against which we can identify characteristic patterns of simulated ground-truth network attacks.« less

Neural networks for continuous online learning and control.

PubMed

Choy, Min Chee; Srinivasan, Dipti; Cheu, Ruey Long

2006-11-01

This paper proposes a new hybrid neural network (NN) model that employs a multistage online learning process to solve the distributed control problem with an infinite horizon. Various techniques such as reinforcement learning and evolutionary algorithm are used to design the multistage online learning process. For this paper, the infinite horizon distributed control problem is implemented in the form of real-time distributed traffic signal control for intersections in a large-scale traffic network. The hybrid neural network model is used to design each of the local traffic signal controllers at the respective intersections. As the state of the traffic network changes due to random fluctuation of traffic volumes, the NN-based local controllers will need to adapt to the changing dynamics in order to provide effective traffic signal control and to prevent the traffic network from becoming overcongested. Such a problem is especially challenging if the local controllers are used for an infinite horizon problem where online learning has to take place continuously once the controllers are implemented into the traffic network. A comprehensive simulation model of a section of the Central Business District (CBD) of Singapore has been developed using PARAMICS microscopic simulation program. As the complexity of the simulation increases, results show that the hybrid NN model provides significant improvement in traffic conditions when evaluated against an existing traffic signal control algorithm as well as a new, continuously updated simultaneous perturbation stochastic approximation-based neural network (SPSA-NN). Using the hybrid NN model, the total mean delay of each vehicle has been reduced by 78% and the total mean stoppage time of each vehicle has been reduced by 84% compared to the existing traffic signal control algorithm. This shows the efficacy of the hybrid NN model in solving large-scale traffic signal control problem in a distributed manner. Also, it indicates the

Laboratory Evaluation of Dynamic Traffic Assignment Systems: Requirements, Framework, and System Design

DOT National Transportation Integrated Search

1997-01-01

The success of Advanced Traveler Information Systems (ATIS) and Advanced Traffic Management Systems (ATMS) depends on the availability and dissemination of timely and accurate estimates of current and emerging traffic network conditions. Real-time Dy...

Synthesis of safety for traffic operations

DOT National Transportation Integrated Search

2003-03-01

Traffic operations practitioners are continually making decisions that impact on the safety performance of the transportation network. In order to make the best possible decisions the practitioner must be aware of the best available evidence on safet...

Dynamic baseline detection method for power data network service

NASA Astrophysics Data System (ADS)

Chen, Wei

2017-08-01

This paper proposes a dynamic baseline Traffic detection Method which is based on the historical traffic data for the Power data network. The method uses Cisco's NetFlow acquisition tool to collect the original historical traffic data from network element at fixed intervals. This method uses three dimensions information including the communication port, time, traffic (number of bytes or number of packets) t. By filtering, removing the deviation value, calculating the dynamic baseline value, comparing the actual value with the baseline value, the method can detect whether the current network traffic is abnormal.

Fuel efficient traffic signal operation and evaluation: Garden Grove Demonstration Project

DOE Office of Scientific and Technical Information (OSTI.GOV)

Not Available

1983-02-01

The procedures and results of a case study of fuel efficient traffic signal operation and evaluation in the City of Garden Grove, California are documented. Improved traffic signal timing was developed for a 70-intersection test network in Garden Grove using an optimization tool called the TRANSYT Version 8 computer program. Full-scale field testing of five alternative timing plans was conducted using two instrumented vehicles equipped to measure traffic performance characteristics and fuel consumption. The field tests indicated that significant improvements in traffic flow and fuel consumption result from the use of timing plans generated by the TRANSYT optimization model. Changingmore » from pre-existing to an optimized timing plan yields a networkwide 5 percent reduction in total travel time, more than 10 percent reduction in both the number of stops and stopped delay time, and 6 percent reduction in fuel consumption. Projections are made of the benefits and costs of implementing such a program at the 20,000 traffic signals in networks throughout the State of California.« less