1 School of Communication Engineering, Hangzhou Dianzi University, Hangzhou 310018, China; 2 China Intelligent Transportation Systems Association, Beijing 100160, China
Abstract Many networks in the real world have spatial attributes, such as location of nodes and length of edges, called spatial networks. When these networks are subject to some random or deliberate attacks, some nodes in the network fail, which causes a decline in the network performance. In order to make the network run normally, some of the failed nodes must be recovered. In the case of limited recovery resources, an effective key node identification method can find the key recovering node in the failed nodes, by which the network performance can be recovered most of the failed nodes. We propose two key recovering node identification methods for spatial networks, which are the Euclidean-distance recovery method and the route-length recovery method. Simulations on homogeneous and heterogeneous spatial networks show that the proposed methods can significantly recover the network performance.
Fund: Project supported by Zhejiang Provincial Natural Science Foundation of China (Grant No. LQ23F030012), and the Fundamental Research Funds for the Provincial Universities of Zhejiang (Grant No. GK229909299001-018).
Zijian Yan(严子健), Yongxiang Xia(夏永祥), Lijun Guo(郭丽君), Lingzhe Zhu(祝令哲), Yuanyuan Liang(梁圆圆), and Haicheng Tu(涂海程) Identification of key recovering node for spatial networks 2023 Chin. Phys. B 32 068901
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Characteristics of vapor based on complex networks in China Ai-Xia Feng(冯爱霞), Qi-Guang Wang(王启光), Shi-Xuan Zhang(张世轩), Takeshi Enomoto(榎本刚), Zhi-Qiang Gong(龚志强), Ying-Ying Hu(胡莹莹), and Guo-Lin Feng(封国林). Chin. Phys. B, 2022, 31(4): 049201.
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