东北大学学报（自然科学版）

东北大学学报(自然科学版) ›› 2010, Vol. 31 ›› Issue (5): 644-646.DOI: -

• 论著 • 上一篇    下一篇

无标度网络中基于反馈机制的病毒传播模型

赵海;郑燕琴;党群;付瑶;   

  1. 东北大学信息科学与工程学院;
  • 收稿日期:2013-06-20 修回日期:2013-06-20 出版日期:2010-05-15 发布日期:2013-06-20
  • 通讯作者: -
  • 作者简介:-
  • 基金资助:
    高等学校科技创新工程重大项目培育基金资助项目(708026)

Feedback-mechanism-based virus spreading model in scale-free networks

Zhao, Hai (1); Zheng, Yan-Qin (1); Dang, Qun (1); Fu, Yao (1)   

  1. (1) School of Information Science and Engineering, Northeastern University, Shenyang 110004, China
  • Received:2013-06-20 Revised:2013-06-20 Online:2010-05-15 Published:2013-06-20
  • Contact: Zheng, Y.-Q.
  • About author:-
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摘要： 在网络中存在超强传染者的前提下,传统的病毒传播模型在无限规模的无标度网络上不存在病毒传播阈值,许多真实的无标度网络中并不存在这种超强传染者.针对这一问题提出了无标度网络中基于反馈机制的最大传染能力限定的病毒传播模型.通过数学方法证明了该模型中病毒传播阈值是存在的,最后通过数据仿真分析了反馈机制、最大传染能力值对网络感染率、控制病毒扩散以及传播阈值的影响.这为控制真实网络中的病毒传播提供了重要的参考依据

关键词: 无标度网络, 反馈机制, 最大传染能力, 感染率, 传播阈值

Abstract: Under the precondition that there is a highly virulent infector in network, no virus spreading threshold is found in conventional virus spreading models in infinitive scale-free networks. However, there is no highly virulent infector in many real scale-free networks. For this reason, a virus spreading/controlling model with finite maximum infectivity was developed in scale-free network, based on the feedback mechanism. In the model there is a virus spreading threshold that has been proved mathematically. The feedback mechanism and the effects of the maximum value of infectivity on the infection rate of network, control of virus diffusion and spreading threshold are all analyzed through numerical simulation. The results provide an important reference for controlling the virus spreading in real networks.

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