改进的记忆认知启发机会网络社区检测方法

Community detection in opportunistic networks using improved memory-based cognitive heuristics

社区检测是研究网络结构的基础,在分析现有机会网络社区检测算法的基础上,提出一种改进的基于记忆的认知启发社区检测方法IMBC。节点通过记录与其它节点的历史接触信息,计算和其它节点的记忆激活量,通过约束处理,把记忆激活量在某一阈值范围的节点归入同一社区,完成网络社区的检测。进行随机生成网络仿真,与MBC算法性能进行比较,比较结果验证了该算法的有效性。

Community detection is the basis of research in network structure.After analyzing the existing algorithm of community detection in opportunistic networks,a community detection algorithm was presented,which was called improved memory-based cognitive heuristics.Node remembered the historical contact information with other nodes,and the memory activation with other nodes was calculated and processed,putting the nodes in same memory activation threshold range to the same community,then completing the community detection.A simulation was run on randomly generated network and a contraction with MBC was made.It is verified that this algorithm is effective.