Analysis of overload-based cascading failure in multilayer spatial networks

doi:10.1088/1674-1056/aba275

中国物理B ›› 2020, Vol. 29 ›› Issue (9): 96401-096401.doi: 10.1088/1674-1056/aba275

Analysis of overload-based cascading failure in multilayer spatial networks

Min Zhang(张敏), Xiao-Juan Wang(王小娟), Lei Jin(金磊), Mei Song(宋梅), Zhong-Hua Liao(廖中华)

1 School of Science, Beijing University of Posts and Telecommunications, Beijing 100876, China;
2 School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China;
3 Beijing Complex Product Advanced Manufacturing Engineering Research Center, Beijing Simulation Center, Beijing 100854, China;
4 State Key Laboratory of Intelligent Manufacturing System Technology, Beijing Institute of Electronic System Engineering, Beijing 100854, China

收稿日期:2020-05-07 修回日期:2020-06-28 接受日期:2020-07-03 出版日期:2020-09-05 发布日期:2020-09-05
通讯作者: Xiao-Juan Wang E-mail:wj2718@163.com
基金资助:
Project supported by the National Natural Science Foundation of China (Grant No. 61871046).

Analysis of overload-based cascading failure in multilayer spatial networks

Min Zhang(张敏)^1,2, Xiao-Juan Wang(王小娟)^2,3,4, Lei Jin(金磊)², Mei Song(宋梅)², Zhong-Hua Liao(廖中华)^3,4

1 School of Science, Beijing University of Posts and Telecommunications, Beijing 100876, China;
2 School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China;
3 Beijing Complex Product Advanced Manufacturing Engineering Research Center, Beijing Simulation Center, Beijing 100854, China;
4 State Key Laboratory of Intelligent Manufacturing System Technology, Beijing Institute of Electronic System Engineering, Beijing 100854, China

Received:2020-05-07 Revised:2020-06-28 Accepted:2020-07-03 Online:2020-09-05 Published:2020-09-05
Contact: Xiao-Juan Wang E-mail:wj2718@163.com
Supported by:
Project supported by the National Natural Science Foundation of China (Grant No. 61871046).

摘要/Abstract

摘要： Many complex networks in real life are embedded in space and most infrastructure networks are interdependent, such as the power system and the transport network. In this paper, we construct two cascading failure models on the multilayer spatial network. In our research, the distance l between nodes within the layer obeys the exponential distribution P(l)～exp(-l/ζ), and the length r of dependency link between layers is defined according to node position. An entropy approach is applied to analyze the spatial network structure and reflect the difference degree between nodes. Two metrics, namely dynamic network size and dynamic network entropy, are proposed to evaluate the spatial network robustness and stability. During the cascading failure process, the spatial network evolution is analyzed, and the numbers of failure nodes caused by different reasons are also counted, respectively. Besides, we discuss the factors affecting network robustness. Simulations demonstrate that the larger the values of average degree <k>, the stronger the network robustness. As the length r decreases, the network performs better. When the probability p is small, as ζ decreases, the network robustness becomes more reliable. When p is large, the network robustness manifests better performance as ζ increases. These results provide insight into enhancing the robustness, maintaining the stability, and adjusting the difference degree between nodes of the embedded spatiality systems.

关键词: cascading failure, multilayer network, load distribution, spatial network, entropy

Abstract: Many complex networks in real life are embedded in space and most infrastructure networks are interdependent, such as the power system and the transport network. In this paper, we construct two cascading failure models on the multilayer spatial network. In our research, the distance l between nodes within the layer obeys the exponential distribution P(l)～exp(-l/ζ), and the length r of dependency link between layers is defined according to node position. An entropy approach is applied to analyze the spatial network structure and reflect the difference degree between nodes. Two metrics, namely dynamic network size and dynamic network entropy, are proposed to evaluate the spatial network robustness and stability. During the cascading failure process, the spatial network evolution is analyzed, and the numbers of failure nodes caused by different reasons are also counted, respectively. Besides, we discuss the factors affecting network robustness. Simulations demonstrate that the larger the values of average degree <k>, the stronger the network robustness. As the length r decreases, the network performs better. When the probability p is small, as ζ decreases, the network robustness becomes more reliable. When p is large, the network robustness manifests better performance as ζ increases. These results provide insight into enhancing the robustness, maintaining the stability, and adjusting the difference degree between nodes of the embedded spatiality systems.

Key words: cascading failure, multilayer network, load distribution, spatial network, entropy

中图分类号: (Networks)

64.60.aq

64.60.ah (Percolation) 89.75.Fb (Structures and organization in complex systems)

张敏, 王小娟, 金磊, 宋梅, 廖中华. Analysis of overload-based cascading failure in multilayer spatial networks[J]. 中国物理B, 2020, 29(9): 96401-096401.

Min Zhang(张敏), Xiao-Juan Wang(王小娟), Lei Jin(金磊), Mei Song(宋梅), Zhong-Hua Liao(廖中华). Analysis of overload-based cascading failure in multilayer spatial networks[J]. Chin. Phys. B, 2020, 29(9): 96401-096401.

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Analysis of overload-based cascading failure in multilayer spatial networks

Analysis of overload-based cascading failure in multilayer spatial networks

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