基于节点相似度与影响力的CCN社区划分方案

CCN Community Partition Method Based on Node Similarity and Influence

内容中心网络(CCN)的内容检索过程存在低效冗余问题,为提升其性能,提出一种基于节点相似度和影响力的CCN社区划分方案(SI-LPA)。首先提出基于特征向量中心性和改进标签传播算法的社区划分方案,以帮助内容检索;随后利用节点与邻居节点间相似性和影响力提出一种更新标签值的方法;最后在每一个划分好的社区上选择竞争力最大的节点部署SDN控制器,以帮助实现更好的管理社区功能以及进行社区间路由。实验表明,引入SDN控制器和社区划分可以加快内容检索和路由分发的速度,从而提高CCN路由的性能。

The content retrieval process of content center network(CCN) is inefficient and redundant, In order to improve the performance of CCN, proposes a CCN community partition scheme(SI-LPA) based on node similarity and influence. Firstly, a community partition scheme based on feature vector centrality and improved label propagation algorithm is proposed to help content retrieval. Then, using the similarity and influence between nodes and neighbor nodes, a method to update the tag value is proposed;Finally, select the most competitive node on each divided community to deploy SDN controller to help better manage community functions and route between communities. Experiments show that the introduction of SDN controller and community partition can accelerate the speed of content retrieval and routing distribution, so as to improve the performance of CCN routing.