Balanced neighborhood aware clustering technique in Wireless Sensor Networks

Abstract

Clustering forms the basis of a well structured Wireless Sensor Networks. Formation of efficient clusters leads to longer lifetime of the sensor networks. So we tend to optimize the initial clustering process. In this paper we have proposed Mean neighbor clustering algorithm that evenly distributes the nodes around the clusters and form well balanced clusters in the system. The proposed Mean neighbor clustering protocol uses the local neighborhood information to form balanced clusters in sensor networks. The proposed method is also compared with various existing clustering protocols in sensor networks. Comparison is done based on parameters like cluster number, average cluster, cluster range, circularity and hop distance. Simulations show that our proposed algorithm performs better than other neighborhood aware clustering techniques.