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Modeling congestion considering sequential coupling applications: A network-cell-based method

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  • Zhang, Xin
  • Huang, Ning
  • Sun, Lina
  • Zheng, Xiangyu
  • Guo, Ziyue

Abstract

Sequential coupling of applications is the major cause of traffic congestion and low application quality. Modeling traffic congestion under sequential coupling applications is the primary means to explore congestion mechanism, which can further support application design and adjustment to improve application quality. Existing congestion models concentrate more on traffic flow modeling based on network components, with little consideration of the influence of network application and its coupling. This paper proposes a network-cell-based congestion model for describing dynamics of congestion propagation under sequential coupling multi-applications. First, the basic characteristics of network applications are analyzed, and network applications are abstracted into network cells as functional units, which is specifically described from three perspectives: Structure, function and connection. The dynamic process of network can be modeled as intracellular reaction (single application function behavior) and intercellular interaction (coupling behavior of multi-applications). Furthermore, a network-cell-based metric to evaluate application quality is presented, and the implementation algorithm of the model is also given. Numerical simulations are implemented with comparison of typical information flow model to verify the model. Moreover, the proposed model is applied to Chengdu Metro system case to show the applicability. Furthermore, the influence of sequential coupling on congestion is further investigated, and the results show that the larger coupling strength corresponds to less congestion in peak period. This study provides guidance for application design and management to improve application quality of transportation networks.

Suggested Citation

  • Zhang, Xin & Huang, Ning & Sun, Lina & Zheng, Xiangyu & Guo, Ziyue, 2022. "Modeling congestion considering sequential coupling applications: A network-cell-based method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 604(C).
    • Handle: RePEc:eee:phsmap:v:604:y:2022:i:c:s0378437122004484
    DOI: 10.1016/j.physa.2022.127668
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    References listed on IDEAS

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    1. Jincheng Jiang & Nico Dellaert & Tom Van Woensel & Lixin Wu, 2020. "Modelling traffic flows and estimating road travel times in transportation network under dynamic disturbances," Transportation, Springer, vol. 47(6), pages 2951-2980, December.
    2. Yin, Rong-Rong & Yuan, Huaili & Wang, Jing & Zhao, Ning & Liu, Lei, 2021. "Modeling and analyzing cascading dynamics of the urban road traffic network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 566(C).
    3. Meead Saberi & Homayoun Hamedmoghadam & Mudabber Ashfaq & Seyed Amir Hosseini & Ziyuan Gu & Sajjad Shafiei & Divya J. Nair & Vinayak Dixit & Lauren Gardner & S. Travis Waller & Marta C. González, 2020. "A simple contagion process describes spreading of traffic jams in urban networks," Nature Communications, Nature, vol. 11(1), pages 1-9, December.
    4. William A. Massey & Jamol Pender, 2018. "Dynamic rate Erlang-A queues," Queueing Systems: Theory and Applications, Springer, vol. 89(1), pages 127-164, June.
    5. Zhou, Jian & Huang, Ning & Coit, David W. & Felder, Frank A., 2018. "Combined effects of load dynamics and dependence clusters on cascading failures in network systems," Reliability Engineering and System Safety, Elsevier, vol. 170(C), pages 116-126.
    6. Shen, Yi & Song, Guohao & Xu, Huangliang & Xie, Yuancheng, 2020. "Model of node traffic recovery behavior and cascading congestion analysis in networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    7. Yi Shen & Gang Ren & Bin Ran, 2021. "Cascading failure analysis and robustness optimization of metro networks based on coupled map lattices: a case study of Nanjing, China," Transportation, Springer, vol. 48(2), pages 537-553, April.
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    Cited by:

    1. Zheng, Xiangyu & Huang, Ning & Bai, Ya-nan & Zhang, Xin, 2023. "A traffic-fractal-element-based congestion model considering the uneven distribution of road traffic," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 632(P1).

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