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Percolation of edge-coupled interdependent networks

Author

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  • Gao, YanLi
  • Chen, ShiMing
  • Zhou, Jie
  • Stanley, H.E.
  • Gao, Jianxi

Abstract

The study of the robustness of interdependent networks has attracted enormous attention from researchers of diverse fields. For this topic, the node-dependent scheme is most widely adopted to describe the interdependency between different network layers, where nodes in one layer are interdependent with nodes in other layers. However, this scheme may not well reflect many realistic scenarios, since many real systems are actually based on a edge-coupled interdependency, that is edges in one layer are interdependent with edges in other layer. In this paper, we propose an edge-coupled interdependent networks (EIN) model to address this kind of interdependency. A mathematic framework based on a set of self-consistent equations is developed to characterize the robustness of EIN, which is further verified by extensive simulations over different kinds of network structures. It is shown that the EIN also possesses the discontinuous phase transition behavior and the threshold of the phase transition is smaller than that of node-coupled interdependent networks (NIN), which suggests a stronger robustness of EIN. Moreover, as contrast to NIN, for EIN a broader degree distribution could enhance the robustness of EIN reflected by the reducing of the threshold of transition. Our findings could help deepening the understanding of interdependent networks that are coupled with the edge perspective and pertinent real world systems.

Suggested Citation

  • Gao, YanLi & Chen, ShiMing & Zhou, Jie & Stanley, H.E. & Gao, Jianxi, 2021. "Percolation of edge-coupled interdependent networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 580(C).
  • Handle: RePEc:eee:phsmap:v:580:y:2021:i:c:s037843712100409x
    DOI: 10.1016/j.physa.2021.126136
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    References listed on IDEAS

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    1. Gao, Yanli & Chen, Shiming & Zhou, Jie & Zhang, Jingjing & Stanley, H.E., 2020. "Multiple phase transition in the non-symmetrical interdependent networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 556(C).
    2. Wang, Yiqiao & Lu, Qiaoyi & Cao, Xianbin & Zhou, Xuesong & Latora, Vito & Tong, Lu Carol & Du, Wenbo, 2020. "Travel time analysis in the Chinese coupled aviation and high-speed rail network," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
    3. Ouyang, Min, 2014. "Review on modeling and simulation of interdependent critical infrastructure systems," Reliability Engineering and System Safety, Elsevier, vol. 121(C), pages 43-60.
    4. Fotouhi, Hossein & Moryadee, Seksun & Miller-Hooks, Elise, 2017. "Quantifying the resilience of an urban traffic-electric power coupled system," Reliability Engineering and System Safety, Elsevier, vol. 163(C), pages 79-94.
    5. Sergey V. Buldyrev & Roni Parshani & Gerald Paul & H. Eugene Stanley & Shlomo Havlin, 2010. "Catastrophic cascade of failures in interdependent networks," Nature, Nature, vol. 464(7291), pages 1025-1028, April.
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    Cited by:

    1. Zhao, Yanyan & Zhou, Jie & Zou, Yong & Guan, Shuguang & Gao, Yanli, 2022. "Characteristics of edge-based interdependent networks," Chaos, Solitons & Fractals, Elsevier, vol. 156(C).
    2. Zhou, Lili & Yin, Jun & Tan, Fei & Liao, Haibin, 2023. "Robustness analysis of edge-coupled interdependent networks under different attack strategies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 632(P1).
    3. Gao, Yanli & Liang, Chongsheng & Zhou, Jie & Chen, Shiming, 2023. "Robustness optimization of aviation-high-speed rail coupling network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 610(C).

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