Improved Cluster Heads Selection Method in Wireless Sensor Networks
GREENCOM-CPSCOM '10 Proceedings of the 2010 IEEE/ACM Int'l Conference on Green Computing and Communications & Int'l Conference on Cyber, Physical and Social Computing
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One important application of wireless sensor networks is data storage for the ubiquitous access of mobile collectors. Events are detected and their readings are disseminated in the sensor network, where sensors store the coded form of received data for the access of mobile collectors. Clustering is an effective method to reduce the data dissemination cost in this application. In clustered networks, data are only disseminated inside cluster, and sensors encode the data of its own cluster. However, the probability of recovering all the original data decreases in clustered networks. This paper first analyzes the optimal network structure to minimize the overall energy consumption of sensor network under the constraint of successful decoding probability. An optimization model is proposed and equal clustered networks are strictly proved to be optimal in our model. We also prove that clustering sharply decreases the successful data decoding probability, and show that increasing the mobile collector’s sample size will significantly improve the decoding efficiency.