ABSTRACT
In WSN clustering algorithm, the reasonable selection of cluster heads directly influences the network performance of the clustering structure. The excessive concentration of the cluster nodes will result in unbalanced energy consumption. In this paper, we put forward an Energy-Balancing Adaptive Clustering Algorithm in WSN (EBACA). EBACA algorithm selects the cluster head with three parameters: node remaining energy, distance to the Sink node, node density in the cluster. The node density in the cluster is set to be no higher than the average node density in the whole WSN, and the node with abundant remaining energy and the shortest distance to the Sink node possesses the priority of being selected as cluster head, which can make whole network energy consumption more balancing, and the network topology more reasonable. By referring toAffinity Propagation (AP) clustering algorithm, EBACA algorithm optimizes the communication mode among the cluster heads, and selects the path with shortest sum of Euclidean distance between the cluster heads to transmit data, which can minimize the communication energy consumption. Compared with Low Energy Adaptive Clustering Hierarchy (LEACH) algorithm, the simulation results show that EBACA algorithm can effectively realize the network energy balancing and prolong the network life.
