Distributed network structure detection mechanism based on node importance in DTN
节点重要程度感知的分布式DTN结构检测机制

As nodes show strong social attributes in the intermittent connection wireless network, network structure detection can effectively improve the network performance. This paper presented a distributed network structure detection mechanism based on node importance in intermittent connection wireless network. First, nodes estimated their own importance degree based on the number of neighbors and forwarded messages, and selected the community center node in a distributed way. Then, according to the number of common neighbors nodes determined their own community center node. Eventually learned the entire network structure. The simulation results show that the proposed detection algorithm has higher accuracy than HCDA about 45%. Furthermore, this method with strong adaptability is suitable for a variety of mixed network scenarios.