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一种基于元胞自动机的自适应网络病毒传播模型
An epidemic spreading model in adaptive networks based on cellular automata
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摘要: 自适应网络是节点动力学和网络动力学相互作用和反馈的演化网络.基于元胞自动机建立自适应网络中易感-感染-易感（susceptible-infected-susceptible）的病毒传播模型,研究节点为了规避病毒传播所采取的多种网络重连规则对病毒传播及网络统计特征的影响.结果表明：自适应网络中的重连规则可以有效减缓病毒传播速度,降低病毒传播规模;随机重连规则使得网络统计特征趋于随机网络;基于元胞自动机建立的传播模型清晰地表达了病毒在传播过程中的双稳态现象.Abstract: An adaptive network is a kind of co-evolutionary network in which the behaviors of nodes and the dynamics of the network affect each other.A susceptible-infected-susceptible epidemics spreading model in the adaptive network is proposed using cellular automata.Under different rewriting rules for avoiding the epidemic spreading,the changes in epidemic dynamics and the properties of the network statistic are investigated.The simulation results show that the introduction of rewiring can slow down the spreading speed of epidemic and suppress the infected scale of epidemic.The random rewiring rules make the properties of an original network with any topology tend to those of a random network.Furthermore,the proposed cellular automata model can clearly exhibit the phenomenon of bi-stability in epidemic dynamics.
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