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Effects of mutual traffic redistribution on robustness of interdependent networks to cascading failures under fluctuant load

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  • Shen, Yi
  • Ren, Gang
  • Zhang, Ning
  • Song, Guohao
  • Wang, Qin
  • Ran, Bin

Abstract

Failure in real interdependent networks can be induced by temporal and fluctuant overload on nodes. Moreover, failure of nodes will lead to loss of flow to some extent due to the decline of system delivery ability. In this paper, we propose a cascading failure model of interdependent networks based on mutual traffic redistribution under fluctuant load. In the model, the flow loss that is correlated with network existing resource is considered by defining a traffic loss parameter. The interdependence between coupled layers is realized by mutual traffic redistribution. Different types of artificial interdependent networks and a Bus-Metro network example are investigated. The results show larger node tolerance and larger traffic loss parameter can lead to higher network robustness. Moreover, cascading time synchronization of different layers induced by mutual traffic redistribution is observed. Although the interdependence usually makes the entire systems fragile, the optimal mutual flow redistribution rules that are beneficial to the whole network robustness can be obtained by our model. The model and results in this paper can provide some references on robust traffic flow assignment and network topology design for real interdependent systems.

Suggested Citation

  • Shen, Yi & Ren, Gang & Zhang, Ning & Song, Guohao & Wang, Qin & Ran, Bin, 2020. "Effects of mutual traffic redistribution on robustness of interdependent networks to cascading failures under fluctuant load," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 560(C).
  • Handle: RePEc:eee:phsmap:v:560:y:2020:i:c:s0378437120305951
    DOI: 10.1016/j.physa.2020.125138
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    References listed on IDEAS

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    Cited by:

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    3. 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).
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    5. Ma, Shan & Shen, Binda & Ma, Junfeng & Hu, Wenfeng & Peng, Tao, 2023. "Improvement of network robustness against cascading failures based on the min–max edge-adding strategy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 611(C).
    6. 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).
    7. Lu, Qing-Chang & Xu, Peng-Cheng & Zhao, Xiangmo & Zhang, Lei & Li, Xiaoling & Cui, Xin, 2022. "Measuring network interdependency between dependent networks: A supply-demand-based approach," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
    8. Yang, Qihui & Scoglio, Caterina M. & Gruenbacher, Don M., 2021. "Robustness of supply chain networks against underload cascading failures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 563(C).
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    10. 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).

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