EVOLUTIONARY ALGORITHMS FOR CLUSTERING IN WIRELESS SENSOR NETWORKS

Recent studies have shown that hierarchical routing is one of the best approaches for routing in Wireless Sensor Networks (WSN). In typical hierarchical routing techniques, the network divided into regions (a.k.a. Clusters); each cluster is then managed as a standalone network with its Cluster Head serving as the node of communication coordination and data collection. Accordingly, nodes across the network can save their energy when attempting to communicate with the other nodes far across the network. Several hierarchical routing techniques have been proposed over the last few years, despite the fact that most of these algorithms are fundamentally similar.  Due to the nature and complexity of hierarchical routing, Evolutionary Optimization algorithms have been used recently to perform clustering and routing techniques.  In this paper, we present, to the best of our knowledge, one of the first surveys on the use of Evolutionary Algorithms (EA) for clustering in hierarchical routing in WSNs. Categorization and classification of the various clustering techniques are presented and used to understand the existing algorithms. A comparison among these techniques is also presented in this work.