Abstract: This paper uses two kinds of infection mechanisms including the same infection probability of all nodes and different infection probability according to different edge weight of nodes adopted to BBV weighted network for immunization simulation. Study finds the nodes betweenness-first immunization effect is better than the intensity-first immune which is widely used at present, the edge betweenness-first immunization strategy is better than the other edge-immunization strategy. It adopts the different immunization strategy under the different infection mechanism, and gets the different effect. It is more effective to control the increase speed of virus at the first stage when adopts different infection probability according to different edge weight of nodes.

Key words: complex network, weighted network, infection mechanism, immunization strategy, simulation

摘要： 基于所有节点采用相同感染概率和根据节点边权采用不同感染概率这2种感染机制对BBV加权网络进行免疫仿真。仿真结果表明，节点介数优先免疫的效果优于目前普遍采用的强度优先免疫，边介数优先免疫策略也优于其他边免疫策略。根据节点边权采用不同感染概率对边权大的边进行免疫，可有效控制病毒在感染初期的增长速度。

关键词: 复杂网络, 加权网络, 感染机制, 免疫策略, 仿真

CLC Number: 

• TP393