IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v604y2022ics0378437122004484.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437122004484
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

    File URL: https://libkey.io/10.1016/j.physa.2022.127668?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Lu, Qing-Chang & Zhang, Lei & Xu, Peng-Cheng & Cui, Xin & Li, Jing, 2022. "Modeling network vulnerability of urban rail transit under cascading failures: A Coupled Map Lattices approach," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    2. Shen, Yi & Yang, Huang & Xie, Yuangcheng & Liu, Yang & Ren, Gang, 2023. "Adaptive robustness optimization against network cascading congestion induced by fluctuant load via a bilateral-adaptive strategy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 630(C).
    3. Zhang, Mengyao & Huang, Tao & Guo, Zhaoxia & He, Zhenggang, 2022. "Complex-network-based traffic network analysis and dynamics: A comprehensive review," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).
    4. Yangyang Meng & Xiaofei Zhao & Jianzhong Liu & Qingjie Qi, 2023. "Dynamic Influence Analysis of the Important Station Evolution on the Resilience of Complex Metro Network," Sustainability, MDPI, vol. 15(12), pages 1-15, June.
    5. Xueguo Xu & Chen Xu & Wenxin Zhang, 2022. "Research on the Destruction Resistance of Giant Urban Rail Transit Network from the Perspective of Vulnerability," Sustainability, MDPI, vol. 14(12), pages 1-26, June.
    6. Jinxiao Duan & Guanwen Zeng & Nimrod Serok & Daqing Li & Efrat Blumenfeld Lieberthal & Hai-Jun Huang & Shlomo Havlin, 2023. "Spatiotemporal dynamics of traffic bottlenecks yields an early signal of heavy congestions," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    7. Amitrajeet A. Batabyal & Hamid Beladi, 2022. "Commuting to work in cities: Bus, car, or train?," Regional Science Policy & Practice, Wiley Blackwell, vol. 14(3), pages 599-609, June.
    8. Dui, Hongyan & Chen, Shuanshuan & Wang, Jia, 2021. "Failure-oriented maintenance analysis of nodes and edges in network systems," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    9. Jin, Kun & Wang, Wei & Li, Xinran & Chen, Siyuan & Qin, Shaoyang & Hua, Xuedong, 2023. "Cascading failure in urban rail transit network considering demand variation and time delay," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 630(C).
    10. Zhang, Jianhua & Wang, Ziqi & Wang, Shuliang & Shao, Wenchao & Zhao, Xun & Liu, Weizhi, 2021. "Vulnerability assessments of weighted urban rail transit networks with integrated coupled map lattices," Reliability Engineering and System Safety, Elsevier, vol. 214(C).
    11. Zhang, Lin & Xu, Min & Wang, Shuaian, 2023. "Quantifying bus route service disruptions under interdependent cascading failures of a multimodal public transit system based on an improved coupled map lattice model," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    12. Sun, Lina & Huang, Ning & Li, Ruiying & Bai, Yanan, 2019. "A new fractal reliability model for networks with node fractal growth and no-loop," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 699-707.
    13. Zhang, Kaimin & Bai, Libiao & Xie, Xiaoyan & Wang, Chenshuo, 2023. "Modeling of risk cascading propagation in project portfolio network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 612(C).
    14. Wang, Wei & Cova, Gregorio & Zio, Enrico, 2022. "A clustering-based framework for searching vulnerabilities in the operation dynamics of Cyber-Physical Energy Systems," Reliability Engineering and System Safety, Elsevier, vol. 222(C).
    15. Zhou, Jian & Tsianikas, Stamatis & Birnie, Dunbar P. & Coit, David W., 2019. "Economic and resilience benefit analysis of incorporating battery storage to photovoltaic array generation," Renewable Energy, Elsevier, vol. 135(C), pages 652-662.
    16. Chen, Daqiang & Sun, Danzhi & Yin, Yunqiang & Dhamotharan, Lalitha & Kumar, Ajay & Guo, Yihan, 2022. "The resilience of logistics network against node failures," International Journal of Production Economics, Elsevier, vol. 244(C).
    17. Eugene Furman & Adam Diamant & Murat Kristal, 2021. "Customer Acquisition and Retention: A Fluid Approach for Staffing," Production and Operations Management, Production and Operations Management Society, vol. 30(11), pages 4236-4257, November.
    18. Sindy Martínez-Marín & Nataly Puello-Pereira & David Ovallos-Gazabon, 2020. "Cluster Competitiveness Modeling: An Approach with Systems Dynamics," Social Sciences, MDPI, vol. 9(2), pages 1-18, February.
    19. Tsianikas, Stamatis & Yousefi, Nooshin & Zhou, Jian & Rodgers, Mark D. & Coit, David, 2021. "A storage expansion planning framework using reinforcement learning and simulation-based optimization," Applied Energy, Elsevier, vol. 290(C).
    20. Lam, C.Y. & Tai, K., 2020. "Network topological approach to modeling accident causations and characteristics: Analysis of railway incidents in Japan," Reliability Engineering and System Safety, Elsevier, vol. 193(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:604:y:2022:i:c:s0378437122004484. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.