Cascading failure in multilayer networks with dynamic dependency groups

doi:10.1088/1674-1056/27/9/098901

中国物理B ›› 2018, Vol. 27 ›› Issue (9): 98901-098901.doi: 10.1088/1674-1056/27/9/098901

• INTERDISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY • 上一篇下一篇

Cascading failure in multilayer networks with dynamic dependency groups

Lei Jin(金磊), Xiaojuan Wang(王小娟), Yong Zhang(张勇), Jingwen You(由婧文)

Beijing University of Posts and Telecommunications, Beijing 100876, China

收稿日期:2018-05-11 修回日期:2018-07-04 出版日期:2018-09-05 发布日期:2018-09-05
通讯作者: Xiaojuan Wang E-mail:wj2718@163.com
基金资助:
Project supported by the National Natural Science Foundation of China (Grant No. 61601053).

Cascading failure in multilayer networks with dynamic dependency groups

Lei Jin(金磊), Xiaojuan Wang(王小娟), Yong Zhang(张勇), Jingwen You(由婧文)

Beijing University of Posts and Telecommunications, Beijing 100876, China

Received:2018-05-11 Revised:2018-07-04 Online:2018-09-05 Published:2018-09-05
Contact: Xiaojuan Wang E-mail:wj2718@163.com
Supported by:
Project supported by the National Natural Science Foundation of China (Grant No. 61601053).

摘要/Abstract

摘要：

The cascading failure often occurs in real networks. It is significant to analyze the cascading failure in the complex network research. The dependency relation can change over time. Therefore, in this study, we investigate the cascading failure in multilayer networks with dynamic dependency groups. We construct a model considering the recovery mechanism. In our model, two effects between layers are defined. Under Effect 1, the dependent nodes in other layers will be disabled as long as one node does not belong to the largest connected component in one layer. Under Effect 2, the dependent nodes in other layers will recover when one node belongs to the largest connected component. The theoretical solution of the largest component is deduced and the simulation results verify our theoretical solution. In the simulation, we analyze the influence factors of the network robustness, including the fraction of dependent nodes and the group size, in our model. It shows that increasing the fraction of dependent nodes and the group size will enhance the network robustness under Effect 1. On the contrary, these will reduce the network robustness under Effect 2. Meanwhile, we find that the tightness of the network connection will affect the robustness of networks. Furthermore, setting the average degree of network as 8 is enough to keep the network robust.

关键词: cascading failure, dependency group, multilayer network

Abstract:

Key words: cascading failure, dependency group, multilayer network

中图分类号: (Structures and organization in complex systems)

89.75.Fb

05.10.-a (Computational methods in statistical physics and nonlinear dynamics)

金磊, 王小娟, 张勇, 由婧文. Cascading failure in multilayer networks with dynamic dependency groups[J]. 中国物理B, 2018, 27(9): 98901-098901.

Lei Jin(金磊), Xiaojuan Wang(王小娟), Yong Zhang(张勇), Jingwen You(由婧文). Cascading failure in multilayer networks with dynamic dependency groups[J]. Chin. Phys. B, 2018, 27(9): 98901-098901.

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Cascading failure in multilayer networks with dynamic dependency groups

Cascading failure in multilayer networks with dynamic dependency groups

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