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加权网络的级联故障建模及其抗毁性分析
引用本文:彭兴钊,姚宏,肖明清,杜军,丁超,李浩敏.加权网络的级联故障建模及其抗毁性分析[J].系统工程与电子技术,2014,36(6):1096-1102.
作者姓名:彭兴钊  姚宏  肖明清  杜军  丁超  李浩敏
作者单位:1. 空军工程大学航空航天工程学院, 陕西 西安 710038; 2. 空军工程大学理学院, 陕西 西安 710051
摘    要:考虑权重因素,建立了加权网络的级联故障模型,其中初始负荷定义为节点强度的函数且其分布通过控制参数α可调,当节点故障时其负荷通过一定的规则分配给邻居节点。研究表明,级联抗毁性的度量指标必须同时考虑权重和拓扑结构的因素,否则将可能高估故障的严重程度。在BBV(Barrat Barthélemy Vespignani)网络的框架内,得出如下结论:当α>1时,攻击负荷大的节点更容易引发大规模级联故障;而当α<1时,攻击负荷小的节点更容易导致网络的瘫痪;且BBV模型参数δ与网络级联抗毁性负相关。最后从不同角度对上述结论进行了理论分析和仿真说明。


Cascading failure model for weighted networks and invulnerability analyses
PENG Xing-zhao,YAO Hong,XIAO Ming-qing,DU Jun,DING Chao,LI Hao-min.Cascading failure model for weighted networks and invulnerability analyses[J].System Engineering and Electronics,2014,36(6):1096-1102.
Authors:PENG Xing-zhao  YAO Hong  XIAO Ming-qing  DU Jun  DING Chao  LI Hao-min
Institution:1. Aeronautics and Astronautics Engineering College, Air Force Engineering University, Xi’an 710038, China; ; 2. Science College, Air Force Engineering University, Xi’an 710051, China
Abstract:A cascading failure model for weighted networks is built by considering the influence of weight. In this model the networks’ initial loads are defined as the function of node strength and their distribution can be adjusted with the parameter α. When a node fails, the loads on it will be distributed to its neighbors through certain rules. The study shows that both factors of weight and topological structure should be considered in order to measure the cascading invulnerability, otherwise the cascading failure may be overrated. The following conclusions are validated under the framework of Barrat Barthélemy Vespignani (BBV) network: in the case of α>1, attacking the larger load nodes is more prone to large scale cascading failures; while for α<1, attacking the smaller load nodes is more easily leads to the whole network’s paralysis; and the modeling parameter δ negatively correlates with the networks’ invulnerability. Finally, theoretical analyses and simulations are made to explain these conclusions.
Keywords:
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