中国邮电高校学报(英文) ›› 2010, Vol. 17 ›› Issue (1): 73-76.doi: 10.1016/S1005-8885(09)60427-1

• Artificial Intelligence • 上一篇    下一篇

Epidemic spreading on scale-free networks with diversity
of node anti-attack abilities

宋玉蓉 , 蒋国平   

  1. 1. Center for Control and Intelligence Technology, Nanjing University of Posts and Telecommunications, Nanjing 210003, China
    2. College of Automation, Nanjing University of Posts and Telecommunications, Nanjing 210003, China
  • 收稿日期:2009-04-23 修回日期:1900-01-01 出版日期:2010-02-28
  • 通讯作者: 蒋国平

Epidemic spreading on scale-free networks with diversity
of node anti-attack abilities

SONG Yu-rong, JIANG Guo-ping   

  1. 1. Center for Control and Intelligence Technology, Nanjing University of Posts and Telecommunications, Nanjing 210003, China
    2. College of Automation, Nanjing University of Posts and Telecommunications, Nanjing 210003, China
  • Received:2009-04-23 Revised:1900-01-01 Online:2010-02-28
  • Contact: JIANG Guo-ping

摘要:

In this article, a modified susceptible-infected-removed (SIR) model is proposed to study the influence of diversity of node anti-attack abilities on the threshold of propagation in scale-free networks. In particular, a vulnerability function related to node degree is introduced into the model to describe the diversity of a node anti-attack ability. Analytical results are derived using the mean-field theory and it is observed that the diversity of anti-attack of nodes in scale-free networks can increase effectively the threshold of epidemic propagation. The simulation results agree with the analytical results. The results show that the vulnerability functions can help adopt appropriate immunization strategies.

关键词:

epidemic;spreading,;scale-free;network,;SIR;model,;anti-attack,;vulnerability;function

Abstract:

In this article, a modified susceptible-infected-removed (SIR) model is proposed to study the influence of diversity of node anti-attack abilities on the threshold of propagation in scale-free networks. In particular, a vulnerability function related to node degree is introduced into the model to describe the diversity of a node anti-attack ability. Analytical results are derived using the mean-field theory and it is observed that the diversity of anti-attack of nodes in scale-free networks can increase effectively the threshold of epidemic propagation. The simulation results agree with the analytical results. The results show that the vulnerability functions can help adopt appropriate immunization strategies.

Key words:

epidemic spreading;scale-free network;SIR model;anti-attack;vulnerability function