Impact of core-periphery structure on cascading failures in interdependent scale-free networks

被引:16
|
作者
Dong, Zhengcheng [1 ]
Tian, Meng [2 ]
Lu, Yuxin [1 ]
Lai, Jingang [3 ]
Tang, Ruoli [4 ]
Li, Xin [4 ]
机构
[1] Wuhan Univ, Sch Elect Engn & Automat, Wuhan, Hubei, Peoples R China
[2] Wuhan Univ, Elect Informat Sch, Wuhan, Hubei, Peoples R China
[3] RMIT Univ, Sch Engn, Melbourne, Vic, Australia
[4] Wuhan Univ Technol, Sch Energy & Power Engn, Wuhan, Hubei, Peoples R China
基金
中国国家自然科学基金; 中国博士后科学基金;
关键词
Core-periphery structure; Interdependent scale-free networks; Evolution model; Coupling preference; INFLUENTIAL SPREADERS; VULNERABILITY; EMERGENCE;
D O I
10.1016/j.physleta.2018.12.042
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
Core-periphery structure is a typical meso-scale structure in networks. Previous studies on core-periphery structure mainly focus on the improvement of detection methods, while the research on the impact of core-periphery structure on cascading failures in interdependent networks is still missing. Therefore, we investigate the cascading failures of interdependent scale-free networks with different core-periphery structures and coupling preferences in the paper. First, we introduce an evaluation index to calculate the goodness of core-periphery structure. Second, we propose a new scale-free network evolution model, which can generate tunable core-periphery structures, and its degree distribution is analyzed mathematically. Finally, based on a degree-load-based cascading failure model, we mainly investigate the impact of goodness of core-periphery structure on cascading failures in both symmetrical and asymmetrical interdependent networks. Through numerical simulations, we find that with the same average degree, the networks with weak core-periphery structure will be more robust, while the initial load on node will influence the improvement of robustness. In addition, we also find that the inter-similarity coupling performs better than random coupling. These findings may be helpful for building resilient interdependent networks. (C) 2019 Elsevier B.V. All rights reserved.
引用
收藏
页码:607 / 616
页数:10
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