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Research on invulnerability of the random scale-free network against cascading failure

Author

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  • Yin, Rong-Rong
  • Liu, Bin
  • Liu, Hao-Ran
  • Li, Ya-Qian

Abstract

The effect of structure parameters of random scale-free network on the network invulnerability for cascading failure is investigated by establishing a cascading failure model of random scale-free network based on node degree and analyzing the effect of node capacity on the cascading failure. The node capacity threshold is thus obtained. Furthermore, the relationship between the threshold of node capacity and the structure parameters of the network (the number of added edges per time slot and the power exponent) is established. The experimental results show that the structure parameters of the network are positively correlated with the network invulnerability for cascading failure. The more the number of added edges at a time and higher the power exponent, the stronger the network invulnerability for cascading failure.

Suggested Citation

  • Yin, Rong-Rong & Liu, Bin & Liu, Hao-Ran & Li, Ya-Qian, 2016. "Research on invulnerability of the random scale-free network against cascading failure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 458-465.
    • Handle: RePEc:eee:phsmap:v:444:y:2016:i:c:p:458-465
    DOI: 10.1016/j.physa.2015.08.017
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    Citations

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    Cited by:

    1. Li Li & Haifen Lin & Yibo Lyu, 2022. "Technology cluster coupling and invulnerability of industrial innovation networks: the role of centralized structure and technological turbulence," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(3), pages 1209-1231, March.
    2. Nguyen, Win P.V. & Nof, Shimon Y., 2020. "Strategic lines of collaboration in response to disruption propagation (CRDP) through cyber-physical systems," International Journal of Production Economics, Elsevier, vol. 230(C).
    3. 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.
    4. Zhou, Lin & Qi, Xiaogang & Liu, Lifang, 2023. "Robustness of networks with dependency groups considering fluctuating loads and recovery behaviors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 613(C).
    5. Chen, Lei & Kou, Yingxin & Li, Zhanwu & Xu, An & Wu, Cheng, 2018. "Empirical research on complex networks modeling of combat SoS based on data from real war-game, Part I: Statistical characteristics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 754-773.
    6. Fu, Chaoqi & Wang, Ying & Gao, Yangjun & Wang, Xiaoyang, 2017. "Complex networks repair strategies: Dynamic models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 401-406.

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