Research On Clustering Routing Protocol And Topology Control Algorithm For Large-Scale WSN

In recent years, there has been a growing interest in wireless sensor networks. They can be applied to monitoring, military, urban management, medical care, etc. One of the major issues in wireless sensor network is developing an energy-efficient routing protocol and its topology control. Since the sensor nodes have limited available power, energy conservation is a critical issue in wireless sensor network for nodes and network life. Especially, for the large area covered WSN monitoring network, its nodes wide distribution, communication radius considerably extended, the energy efficiency of routing protocol in WSN is more critical.In this paper, aimed at the application characteristics of large-scale WSN, we analyzed the principles and mechanisms of the classical routing protocol about LEACH, to further improve the energy efficiency of the protocol, a new clustering routing protocol LEACH_CHMST for large scale WSN application environment is proposed. In this new protocol, we introduced the multi-hop strategy for cluster-heads communication instead of the one-hop strategy in LEACH. A minimum spanning tree of cluster-head is established by the node of sink, in which the routes from all cluster-heads to sink are found. As well as, we proposed a three-layer topology architecture, furthermore, the algorithm to discovery and label the bottleneck-nodes of the top-layer network was brought up, the basic ways to eliminate the negative influence of the bottleneck node have been discussed.The simulation experiment indicated that, compared with the conventional LEACH protocol, the performance of this improved protocol has remarkable improvement; the life-cycle of the network is extended and the energy consumption of the cluster-heads is reduced. By the three-layer topology architecture and the algorithm for eliminate bottleneck-node can balance the overall communication load, control the key-level communication energy consumption, and improve the monitoring network robustness in large-scale WSN.