文献类型：期刊文献

英文题名：Cascades Tolerance of Scale-Free Networks with Attack Cost

作者：Hong, Chen[1];Yin, Nai-Yu[2];He, Ning[1];Lordan, Oriol[3];Maria Sallan, Jose[3]

通讯作者：Lordan, O[1]

机构：[1]Beijing Union Univ, Coll Informat Technol, Beijing 100101, Peoples R China;[2]Beihang Univ, Sch Engn & Informat Engn, Beijing 100191, Peoples R China;[3]Univ Politecn Cataluna, BarcelonaTech, Colom 11, Terrassa 08222, Spain

第一机构：北京联合大学智慧城市学院

通讯机构：[1]corresponding author), Univ Politecn Cataluna, BarcelonaTech, Colom 11, Terrassa 08222, Spain.

年份：2017

卷号：10

期号：1

起止页码：1330-1336

外文期刊名：INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS

收录：;EI(收录号：20240615505656);Scopus(收录号：2-s2.0-85112338268);WOS:【SCI-EXPANDED(收录号:WOS:000415593600039)】；

基金：The work is supported by the National Natural Science Foundation of China (Grant Nos. 61370138, 61572077), Beijing Municipal Natural Science Foundation (Nos. 4152017, 4162027), Characteristic Subject Research Projects of Beijing Union University (KYDE40201701) and New Starting Point Projects of Beijing Union University (Zk10201602).

语种：英文

外文关键词：Network robustness; Cascading failures; Genetic algorithm; Attack cost

摘要：Network robustness against cascades is a major topic in the fields of complex networks. In this paper, we propose an attack-cost-based cascading failure model, where the attack cost of nodes is positively related to its degree. We compare four attacking strategies: the random removal strategy (RRS), the low-degree removal strategy (LDRS), the high-degree removal strategy (HDRS) and the genetic algorithm removal strategy (GARS). It is shown that the network robustness against cascades is heavily affected by attack costs and the network exhibits the weakest robustness under GARS. We also explore the relationship between the network robustness and tolerance parameter under these attacking strategies. The simulation results indicate that the critical value of tolerance parameter under GARS is greatly larger than that of other attacking strategies. Our work can supply insight into the robustness and vulnerability of complex networks corresponding to cascading failures.