Cluster Merging Algorithm with Link Optimization for Wireless Sensor Networks

Clustering sensor nodes is an effective approach for large-scale wireless sensor networks to enhance their performance. In this paper, we proposed CMA (cluster merging algorithm with link optimization), a new clustering algorithm for wireless sensor networks with low density and short communication range of sensor nodes. CMA is a multipoint initiated topology discovery algorithm, which merges small clusters to larger clusters with multi-hop intra-cluster communication by means of neighborhood discovery. During this course, it also optimizes wireless links in clusters to form a well distributed network topology. Residual energy is an important factor for regrouping clusters during network lifetime in order to balance the energy consumption of nodes. With the application of the algorithm, networks can form clustered topology fast and cluster heads can be well elected again after growing energy consumption. The simulation results show that CMA can shorten the topology establish time and reduce network overhead during the course