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Robustness of complex networks with an improved breakdown probability against cascading failures

Author

Listed:
  • Liu, Jun
  • Xiong, Qingyu
  • Shi, Xin
  • Wang, Kai
  • Shi, Weiren

Abstract

The robustness of complex network is a core issue in complex network research. We agree that not all overload nodes will be removed from the network in real networks because some effective measures can be taken to protect them. But only a few researches consider this issue. Based on previous researches, we propose a cascading model with an improved breakdown probability. Different from previous breakdown probability model, the current model brings in some parameters to explore the optimal distribution strategy of the protection resources. Furthermore, we quantify the allocation of the protection resources. We explore the relationship between the parameters of our cascading model and the robustness of three networks (two typical networks and one real network), based on which we find out the optimal value of the parameter. It in turn helps us to quantify the allocation of protection resources and form an optimal protection strategy. Our work may be helpful for improving the robustness of complex networks.

Suggested Citation

  • Liu, Jun & Xiong, Qingyu & Shi, Xin & Wang, Kai & Shi, Weiren, 2016. "Robustness of complex networks with an improved breakdown probability against cascading failures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 456(C), pages 302-309.
    • Handle: RePEc:eee:phsmap:v:456:y:2016:i:c:p:302-309
    DOI: 10.1016/j.physa.2016.03.040
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    Citations

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    Cited by:

    1. Yushu Sun & Xisheng Tang & Guowei Zhang & Fufeng Miao & Ping Wang, 2017. "Dynamic Power Flow Cascading Failure Analysis of Wind Power Integration with Complex Network Theory," Energies, MDPI, vol. 11(1), pages 1-15, December.
    2. Yang, Guizhen & Qi, Xiaogang & Liu, Lifang, 2020. "Research on network robustness based on different deliberate attack methods," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    3. Li, Dongyan & Wang, Xingyuan & Huang, Penghe, 2017. "A fractal growth model: Exploring the connection pattern of hubs in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 200-211.
    4. Qi, Xiaogang & Yang, Guizhen & Liu, Lifang, 2020. "Robustness analysis of the networks in cascading failures with controllable parameters," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 539(C).
    5. Hao, Yucheng & Jia, Limin & Wang, Yanhui, 2020. "Robustness of weighted networks with the harmonic closeness against cascading failures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 541(C).

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