Accurate traffic prediction is crucial for an intelligent traffic system (ITS). However, the excessive non-linearity and complexity of the spatial-temporal correlation in traffic flow severely limit the prediction acc...Accurate traffic prediction is crucial for an intelligent traffic system (ITS). However, the excessive non-linearity and complexity of the spatial-temporal correlation in traffic flow severely limit the prediction accuracy of most existing models, which simply stack temporal and spatial modules and fail to capture spatial-temporal features effectively. To improve the prediction accuracy, a multi-head attention spatial-temporal graph neural network (MSTNet) is proposed in this paper. First, the traffic data is decomposed into unique time spans that conform to positive rules, and valuable traffic node attributes are mined through an adaptive graph structure. Second, time and spatial features are captured using a multi-head attention spatial-temporal module. Finally, a multi-step prediction module is used to achieve future traffic condition prediction. Numerical experiments were conducted on an open-source dataset, and the results demonstrate that MSTNet performs well in spatial-temporal feature extraction and achieves more positive forecasting results than the baseline methods.展开更多
Call Admission Control (CAC) is one of the key traffic management mechanisms that must be deployed in order to meet the strict requirements for dependability imposed on the services provided by modern wireless network...Call Admission Control (CAC) is one of the key traffic management mechanisms that must be deployed in order to meet the strict requirements for dependability imposed on the services provided by modern wireless networks. In this paper, we develop an executable top-down hierarchical Colored Petri Net (CPN) model for multi-traffic CAC in Orthogonal Frequency Division Multiple Access (OFDMA) system. By theoretic analysis and CPN simulation, it is demonstrated that the CPN model is isomorphic to Markov Chain (MC) assuming that each data stream follows Poisson distribution and the corresponding arrival time interval is an exponential random variable, and it breaks through MC's explicit limitation, which includes MC's memoryless property and proneness to state space explosion in evaluating CAC process. Moreover, we present four CAC schemes based on CPN model taking into account call-level and packet-level Quality of Service (QoS). The simulation results show that CPN offers significant advantages over MC in modeling CAC strategies and evaluating their performance with less computational complexity in addition to its flexibility and adaptability to different scenarios.展开更多
Aiming at the deficiency of conventional traffic control method, this paper proposes a new method based on multi-agent technology for traffic control. Different from many existing methods, this paper distinguishes tra...Aiming at the deficiency of conventional traffic control method, this paper proposes a new method based on multi-agent technology for traffic control. Different from many existing methods, this paper distinguishes traffic control on the basis of the agent technology from conventional traffic control method. The composition and structure of a multi-agent system （MAS） is first discussed. Then, the step-coordination strategies of intersection-agent, segment-agent, and area-agent are put forward. The advantages of the algorithm are demonstrated by a simulation study.展开更多
Multipath Protocol Label Switching (MPLS) is a routing mechanism (technology) used in modern telecommunication networks, which is built as a multi-service network with a certain Quality of Service (QoS). To maintain t...Multipath Protocol Label Switching (MPLS) is a routing mechanism (technology) used in modern telecommunication networks, which is built as a multi-service network with a certain Quality of Service (QoS). To maintain the required QoS in such complicated networks, the Traffic Engineering (TE) should be equipped with optimum traffic management, routing mechanism, and switching operations, which are what this paper tackles, where the TE is identified as the optimal distribution of flows in the existing network. In this paper, an effective multipath routing mathematical model is developed based on several previous mechanisms to ensure the guaranteed desired QoS and loading balance according to the Telecommunication Network Systems (TCS) resources, to achieve the optimum TE, and hence improving the network usage efficiency. Moreover, the obtained mathematical optimization algorithm results are provided through the relative equations. Indeed the developed routing mathematical model in this paper is suitable for the dynamic distribution of information flows, which is the main improvement in the TE achieved in this work.展开更多
While Internet traffic is currently dominated by elastic data transfers, it is anticipated that streaming applications will rapidly develop and contribute a significant amount of traffic in the near future. Therefore,...While Internet traffic is currently dominated by elastic data transfers, it is anticipated that streaming applications will rapidly develop and contribute a significant amount of traffic in the near future. Therefore, it is essential to understand and capture the relation between streaming and elastic traffic behavior. In this paper, we focus on developing simple yet effective approximations to capture this relationship. We study, then, an analytical model to evaluate the end-to-end performance of elastic traffic under multi-queuing system. This model is based on the fluid flow approximation. We assume that network architecture gives the head of priority to real time traffic and shares the remaining capacity between the elastic ongoing flows according to a specific weight.展开更多
The rapid development of mobile network brings opportunities for researchers to analyze user behaviors based on largescale network traffic data. It is important for Internet Service Providers(ISP) to optimize resource...The rapid development of mobile network brings opportunities for researchers to analyze user behaviors based on largescale network traffic data. It is important for Internet Service Providers(ISP) to optimize resource allocation and provide customized services to users. The first step of analyzing user behaviors is to extract information of user actions from HTTP traffic data by multi-pattern URL matching. However, the efficiency is a huge problem when performing this work on massive network traffic data. To solve this problem, we propose a novel and accurate algorithm named Multi-Pattern Parallel Matching(MPPM) that takes advantage of HashMap in data searching for extracting user behaviors from big network data more effectively. Extensive experiments based on real-world traffic data prove the ability of MPPM algorithm to deal with massive HTTP traffic with better performance on accuracy, concurrency and efficiency. We expect the proposed algorithm and it parallelized implementation would be a solid base to build a high-performance analysis engine of user behavior based on massive HTTP traffic data processing.展开更多
In order to estimate vehicular queue length at signalized intersections accurately and overcome the shortcomings and restrictions of existing studies especially those based on shockwave theory,a new methodology is pre...In order to estimate vehicular queue length at signalized intersections accurately and overcome the shortcomings and restrictions of existing studies especially those based on shockwave theory,a new methodology is presented for estimating vehicular queue length using data from both point detectors and probe vehicles. The methodology applies the shockwave theory to model queue evolution over time and space. Using probe vehicle locations and times as well as point detector measured traffic states,analytical formulations for calculating the maximum and minimum( residual) queue length are developed. The proposed methodology is verified using ground truth data collected from numerical experiments conducted in Shanghai,China. It is found that the methodology has a mean absolute percentage error of 17. 09%,which is reasonably effective in estimating the queue length at traffic signalized intersections. Limitations of the proposed models and algorithms are also discussed in the paper.展开更多
文摘Accurate traffic prediction is crucial for an intelligent traffic system (ITS). However, the excessive non-linearity and complexity of the spatial-temporal correlation in traffic flow severely limit the prediction accuracy of most existing models, which simply stack temporal and spatial modules and fail to capture spatial-temporal features effectively. To improve the prediction accuracy, a multi-head attention spatial-temporal graph neural network (MSTNet) is proposed in this paper. First, the traffic data is decomposed into unique time spans that conform to positive rules, and valuable traffic node attributes are mined through an adaptive graph structure. Second, time and spatial features are captured using a multi-head attention spatial-temporal module. Finally, a multi-step prediction module is used to achieve future traffic condition prediction. Numerical experiments were conducted on an open-source dataset, and the results demonstrate that MSTNet performs well in spatial-temporal feature extraction and achieves more positive forecasting results than the baseline methods.
基金Supported by the National Natural Science Foundation of China (No. 61271421)the Education Department of Henan Province (No. 2011GGJS-002 and No. 12A510023)
文摘Call Admission Control (CAC) is one of the key traffic management mechanisms that must be deployed in order to meet the strict requirements for dependability imposed on the services provided by modern wireless networks. In this paper, we develop an executable top-down hierarchical Colored Petri Net (CPN) model for multi-traffic CAC in Orthogonal Frequency Division Multiple Access (OFDMA) system. By theoretic analysis and CPN simulation, it is demonstrated that the CPN model is isomorphic to Markov Chain (MC) assuming that each data stream follows Poisson distribution and the corresponding arrival time interval is an exponential random variable, and it breaks through MC's explicit limitation, which includes MC's memoryless property and proneness to state space explosion in evaluating CAC process. Moreover, we present four CAC schemes based on CPN model taking into account call-level and packet-level Quality of Service (QoS). The simulation results show that CPN offers significant advantages over MC in modeling CAC strategies and evaluating their performance with less computational complexity in addition to its flexibility and adaptability to different scenarios.
文摘Aiming at the deficiency of conventional traffic control method, this paper proposes a new method based on multi-agent technology for traffic control. Different from many existing methods, this paper distinguishes traffic control on the basis of the agent technology from conventional traffic control method. The composition and structure of a multi-agent system （MAS） is first discussed. Then, the step-coordination strategies of intersection-agent, segment-agent, and area-agent are put forward. The advantages of the algorithm are demonstrated by a simulation study.
文摘Multipath Protocol Label Switching (MPLS) is a routing mechanism (technology) used in modern telecommunication networks, which is built as a multi-service network with a certain Quality of Service (QoS). To maintain the required QoS in such complicated networks, the Traffic Engineering (TE) should be equipped with optimum traffic management, routing mechanism, and switching operations, which are what this paper tackles, where the TE is identified as the optimal distribution of flows in the existing network. In this paper, an effective multipath routing mathematical model is developed based on several previous mechanisms to ensure the guaranteed desired QoS and loading balance according to the Telecommunication Network Systems (TCS) resources, to achieve the optimum TE, and hence improving the network usage efficiency. Moreover, the obtained mathematical optimization algorithm results are provided through the relative equations. Indeed the developed routing mathematical model in this paper is suitable for the dynamic distribution of information flows, which is the main improvement in the TE achieved in this work.
文摘While Internet traffic is currently dominated by elastic data transfers, it is anticipated that streaming applications will rapidly develop and contribute a significant amount of traffic in the near future. Therefore, it is essential to understand and capture the relation between streaming and elastic traffic behavior. In this paper, we focus on developing simple yet effective approximations to capture this relationship. We study, then, an analytical model to evaluate the end-to-end performance of elastic traffic under multi-queuing system. This model is based on the fluid flow approximation. We assume that network architecture gives the head of priority to real time traffic and shares the remaining capacity between the elastic ongoing flows according to a specific weight.
基金supported in part by National Natural Science Foundation of China(61671078)the Director Funds of Beijing Key Laboratory of Network System Architecture and Convergence(2017BKL-NSACZJ-06)
文摘The rapid development of mobile network brings opportunities for researchers to analyze user behaviors based on largescale network traffic data. It is important for Internet Service Providers(ISP) to optimize resource allocation and provide customized services to users. The first step of analyzing user behaviors is to extract information of user actions from HTTP traffic data by multi-pattern URL matching. However, the efficiency is a huge problem when performing this work on massive network traffic data. To solve this problem, we propose a novel and accurate algorithm named Multi-Pattern Parallel Matching(MPPM) that takes advantage of HashMap in data searching for extracting user behaviors from big network data more effectively. Extensive experiments based on real-world traffic data prove the ability of MPPM algorithm to deal with massive HTTP traffic with better performance on accuracy, concurrency and efficiency. We expect the proposed algorithm and it parallelized implementation would be a solid base to build a high-performance analysis engine of user behavior based on massive HTTP traffic data processing.
基金Sponsored by the National Natural Science Foundation of China(Grant No.51138003)
文摘In order to estimate vehicular queue length at signalized intersections accurately and overcome the shortcomings and restrictions of existing studies especially those based on shockwave theory,a new methodology is presented for estimating vehicular queue length using data from both point detectors and probe vehicles. The methodology applies the shockwave theory to model queue evolution over time and space. Using probe vehicle locations and times as well as point detector measured traffic states,analytical formulations for calculating the maximum and minimum( residual) queue length are developed. The proposed methodology is verified using ground truth data collected from numerical experiments conducted in Shanghai,China. It is found that the methodology has a mean absolute percentage error of 17. 09%,which is reasonably effective in estimating the queue length at traffic signalized intersections. Limitations of the proposed models and algorithms are also discussed in the paper.
