摘要
如何免疫网络中较少数量的节点是当前的热点,目标免疫被认为是当前最好的免疫策略,尤其对于无标度网络。考虑到目标免疫可能把网络分割成较小的单元,而多重图形剖分算法可以把图形分成特定大小的单元,并且单元之间具有很少的边相连。因而,采用多重图形剖分算法来免疫ER网络和BA网络。实验结果表明:该策略是可行的。
The question of how to immunize a network with a minimal number of immunization does is of current interest. Targeted immunization is widely regarded as the most effective strategy, especially for scale-free networks. Considering the strategy can partition the network into small size clusters, but multilevel graph partitioning algorithm can dividing the vertices of a graph into sets of specified sizes, so that few edges cross between sets. Multilevel graph partitioning algorithm is adopted to immunize a ER network and BA network. Experimental results show that this strategy is feasible.
出处
《传感器与微系统》
CSCD
北大核心
2010年第10期68-70,74,共4页
Transducer and Microsystem Technologies
关键词
目标免疫
多重图形剖分算法
SIS病毒传播模型
ER网络
无标度网络
targeted immunization
multilevel graph partitioning algorithm
SIS virus spreading model
ER network
scale-free network
