无标度网络中基于最短路径免疫策略的病毒传播研究

Research of Virus Spreading Based on Shortest Path Immunization Strategy in Scale-free Network

传统病毒免疫策略大多基于网络的全局拓扑信息。然而现实生活中的大部分复杂网络仅仅只能了解其局部拓扑信息。鉴于许多实际复杂网络具有无标度特性,研究了在无标度复杂演化网络中基于网络局部拓扑信息最短路径免疫策略的病毒传播现象。利用平均场理论建立含个体抵抗力重要因素的无标度网络病毒传播模型,并引入基于最短路径的免疫策略。比较了随机免疫、目标免疫和最短路径免疫3种策略对无标度复杂网络病毒传播的影响,结果表明了基于最短路径免疫策略的有效性。

Most of the traditional virus immunization strategies are based on global network topology information,however,most real-life complex networks are known to us with only the local topology information.In view of that scale-free property exists in many real-life complex networks,the virus spreading with shortest path immunization strategy based on local topology information in scale-free complex evolving network was studied.This article used the mean-field theory to build a virus spreading model in scale-free network introducing a immunization strategy based on shortest path and a key factor：individual resistance.After comparing the efficiency of random immunization,target immunization and shortest path immunization for virus spreading in scale-free complex networks,the result indicates that the immunization strategy based on shortest path has important effectiveness.