为了有效控制自适应网络中病毒的传播,对自适应网络的重连策略进行了系统的研究。基于先前研究中网络断边后,随机地或根据欧几里德距离进行重连的策略,提出了基于最短路径和节点度的重连策略。首先根据元胞自动机理论建立自适应复杂网络的病毒传播模型。在此基础上,分别在WS小世界网络和BA无标度网络中对Random、Degree、SP、SP-Degree和Degree-SP策略进行比较分析。实验结果表明,SP-Degree策略能够有效破坏具有小世界特征网络的传输性和连通性,对其抑制病毒传播效果最好;而Degree-SP策略能够有效破坏无标度特征网络的传输性.和连通性,对其抑制病毒传播效果最好。
This paper was. devoted to systematically research of effective strategies of reconnecting edges to prevent the epi- demic propagation on adaptive networks. Differently from previous studies where established links randomly, or preferentially depending on spatial distance, it proposed effective strategies to reconnect edges depend on both shortest path length and node degree. It constructed the epidemic propagation model on adaptive networks based on cellular automaton, and also demonstra- ted the advantage of the newly proposed strategy comparing with the random strategy and spatial distance strategy by numerical simulations. It indicates that the SP-Degree strategy involving reconnecting network edges is the most effective to restrain epi- demic propagation in Watts-Strogatz networks at an equally given rate, while the Degree-SP strategy is the most effective in Barabasi-Albert networks.