计算机应用 ›› 2011, Vol. 31 ›› Issue (07): 1952-1955.

• 网络与通信 • 上一篇    下一篇

基于耦合映像格子的有向网络相继故障

马秀娟,马福祥,赵海兴   

  1. 青海师范大学 计算机学院,西宁 810008
  • 收稿日期:2010-12-08 修回日期:2011-01-27 发布日期:2011-07-01 出版日期:2011-07-01
  • 通讯作者: 马秀娟
  • 作者简介:马秀娟(1977-),女,青海西宁人,讲师,硕士,主要研究方向:复杂网络、网络的相继故障;马福祥(1975-),男,青海大通人,副教授,硕士,主要研究方向:嵌入式操作系统、计算机网络;赵海兴(1969-),男,青海湟中人,教授,博士生导师,主要研究方向:随机网络的可靠性、图和超图多项式、化学分子图。
  • 基金资助:

    国家自然科学基金资助项目;科技部973前期研究专项;新世纪优秀人才支持计划项目

Cascading failure in coupled map lattices with directed network

Xiu-juan MA,Xiang-fu MA,Hai-xing ZHAO   

  1. School of Computer Science,Qinghai Normal University, Xining Qinghai 810008, China
  • Received:2010-12-08 Revised:2011-01-27 Online:2011-07-01 Published:2011-07-01
  • Contact: Xiu-juan MA

摘要: 针对现实世界中存在大量的有向网络,根据有向网络中边的有向性,提出适合描述有向网络耦合映像格子(CML)的相继故障模型,利用仿真分析的方法研究了BA无标度有向网络和ER随机图有向网络在该模型作用下的相继故障行为。仿真中,对节点数固定的网络采用蓄意攻击和随机攻击两种策略进行攻击,并记录相关数据。通过对所得数据的分析发现:1)这两类有向网络的相继故障进程比同规模的无向网络要剧烈;2)当网络遭受攻击时,有向网络比无向网络更加脆弱;3)ER随机图网络相继故障发生过程中引起网络相继故障规模增长的4个临界值之间存在线性关系。

关键词: 有向网络, 耦合映像格子, 相继故障, 复杂网络

Abstract: There are a large number of directed networks in the real world. According to a directional edge in the network, a cascading failure model was proposed which is suitable to describe the coupled map lattices with directed network. In this paper, using simulation methods, the cascading failures with BA (Barabási-Albert) scale free and ER (Erds-Rényi) random graph directed networks in this model was researched. Two attack strategies: deliberate attack and random attack were adopted in this fixed node number network, and relevant data were recorded. By analyzing the data, following conclusions can be made: 1) the cascading failures are much easier to occur in directed network than in undirected network; 2) when the networks are attacked, directed networks are more vulnerable than undirected networks; 3) in ER random graph networks, there is linear relationship among four thresholds with fault size increasing when network faults occur.

Key words: directed network, couple map lattices, cascading failure, complex network