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中文摘要：
考虑网络交通流量对病毒传播行为的影响,基于平均场理论研究无标度网络上的病毒免疫策略,提出一种改进的熟人免疫机理.理论分析表明,在考虑网络交通流量影响的情况下,当免疫节点密度较小时,随机免疫几乎不能降低病毒的传播速率,而对网络实施目标免疫则能够有效抑制病毒的传播,并且选择度最大的节点进行免疫与选择介数最大的节点进行免疫的效果基本相同.研究还发现,对于网络全局信息未知的情况,与经典熟人免疫策略相比,所提出的免疫策略能够获得更好的免疫效果.通过数值仿真对理论分析进行了验证.
英文摘要：
In this paper,considering the influence of network traffic flow on the spreading behaviors of epidemics and according to the mean-field theory,we investigate the epidemic immunization strategies in scale-free networks,and propose an improved acquaintance immunization mechanism.Theoretical analysis shows that considering the influence of traffic flow,the random immunization can hardly reduce the spreading velocity of epidemics if the density of vaccinated nodes is small.However,the targeted immunization can sharply depress the epidemic spreading even only a tiny fraction of nodes are vaccinated,and the effects of immunizing the most highly connected nodes and vaccinating the nodes with the largest betweenness are almost the same.We also find that if the network global information is unknown,compared with the classical acquaintance immunization strategy,the strategy proposed in this paper can be used to obtain good immune effect.Numerical simulations confirm the theoretical results.
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