中文摘要：

在仅知道节点本地信息的情况下，基于加权网络的特点，提出一种边权优先的改进熟人免疫策略。借助经典的sI病毒传播模型，考虑节点之间病毒传播概率的差异性，在人工网络和真实网络中进行仿真分析，结果表明，在加权网络中，边权优先的改进熟人免疫策略获得的免疫临界值比经典的熟人免疫策略低，免疫效果好，并且计算复杂度比目标免疫策略低，所需的节点信息少。BBV网络的优先连接特性越明显，改进熟人免疫策略的效果越好。

英文摘要：

In the case of only knowing nodes local information, using the weighted networks＇ characteristics, this paper proposes an Improved Acquaintance Immunization strategy based on Weight-priority （IAI-WP）. Using the classic susceptible-infected model and considering the difference of the viral spreading probability between different nodes, simulation results in artificial networks and real networks show that, in weighted networks, the immunization strategy gets lower density of infected individuals and has better effect than the classic acquaintance immunization. And the strategy needs lower computational complexity and less nodes information than the targeted immunization. Moreover, it is shown that the more obvious the preferential attachment in BBV network is,the better effect of IAI-WP is.