Identifying key node in multi-region opportunistic sensor network based on improved TOPSIS

The topology of multi-region opportunistic sensor networks is evolving, and it difficult to identify the key nodes in by traditional node identification methods. In this paper, a novel method based on improved TOPSIS proposed from ferry node. dynamic information represented graph model which modeled temporal reachable graph. Based graph, three attributes are constructed node, average degree, betweenness centrality message forwarding rate. game theory with combination weighting employed combine subjective weight objective weight, so as obtain combined each attribute. weight. identified TOPSIS. experiments simulation situations show that, compared MADM_TOPSIS method, has better accuracy for network.