相互依存的网络
相互依存
稳健性(进化)
依赖关系(UML)
渗流理论
渗透(认知心理学)
巨型组件
计算机科学
级联故障
复杂网络
分布式计算
拓扑(电路)
理论计算机科学
数学
人工智能
随机图
心理学
组合数学
万维网
图形
神经科学
基因
化学
生物化学
法学
政治学
作者
Weifei Zang,Xinsheng Ji,Shuxin Liu,Ying-Le Li
出处
期刊:International Journal of Modern Physics C
[World Scientific]
日期:2021-12-31
标识
DOI:10.1142/s0129183122500796
摘要
Traditional research studies on interdependent networks with groups ignore the relationship between nodes in dependency groups. In real-world networks, nodes in the same group may support each other through cooperation and tend to fail or survive together. In this paper, based on the framework of group percolation, a cascading failure model on interdependent networks with cooperative dependency groups under targeted attacks is proposed, and the effect of group size distributions on the robustness of interdependent networks is investigated. The mutually giant component and phase transition point of networks with different group size distributions are analyzed. The effectiveness of the theory is verified through simulations. Results show that the robustness of interdependent networks with cooperative dependency groups can be enhanced by increasing the heterogeneity between groups under targeted attacks. The theory can well predict the numerical simulation results. This model provides some theoretical guidance for designing robust interdependent systems in real world.
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