ABSTRACT
Wireless sensor network comprises sensor nodes equipped with the ability to sense and measure the surroundings and to communicate the data to the base station either directly or using multi-hop for the access to the end user. The scheme starts with initializing a population of random solutions from the available search space. Every solution vector is then evaluated for its strength, indicating the suitability as the final solution through a well-defined fitness function. The clustering environment refers to how the nodes are grouped together to shape the clusters. Cluster communication describes the message exchange among the network nodes. Treating clustering of the nodes as the most significant tool in achieving energy-efficiency and scalability in the wireless sensor networks, the present review emphasizes the clustering process and some metaheuristic clustering approaches especially based on the differential evolution and particle swarm optimization.
