Cluster Head Selection Using Genetic Algorithm in Hierarchical Clustered Sensor Network

Abstract

Wireless sensor networks contains various sensor nodes. Every node has little assets as far as power, and bandwidth. In hierarchal clustering of sensors in wireless sensor networks, type-2 fuzzy logic with three parameters (remaining energy, distance, concentration) is used for cluster head selection. Various hierarchical based routing protocols are there to route the traffic from source to the goal. This sort of protocol divides the network into small clusters and builds a hierarchy of nodes. Therefore, a genetic algorithm is proposed by taking same parameters to improve lifetime of the network. A comparison between type-2 fuzzy logic and genetic algorithm, respectively, is made. Various performance parameters such as alive node count, dead node count and residual energy has been evaluated based on these parameters. There is an improvement in case of genetic based approach as compared to type-2 fuzzy based selection approach and comparison has been done on different network topologies. One with random topology and second by taking fixed topology.