Abstract
In a sink mobility based Wireless Sensor Network, the sink node moves on a trajectory in the network region and collects the data of the sensor nodes in the vicinity. Sink mobility reduces the distance from average source node to sink and saves network transmission energy. This paper proposes a Genetic Algorithm (GA) based sink mobility technique for WSN. Network region is divided into the optimal number of clusters and a sink movement trajectory is built over there. The GA process determines the optimal sink locations on the trajectory for each cluster. The moving sink stops at the optimal sink locations and gathers data from the nodes of the related clusters. An optimal sink location consumes minimum node energy in data transmission. For determining the optimal sink location for a cluster, the GA initializes a population of chromosomes. Further, a network energy consumption model is proposed that implements the fitness evaluation operator of the GA process. The developed GA model converges into a set of optimal sink locations on the trajectory for each cluster. The results depict that the GA based sink mobility provides increase in network lifetime than other protocols.
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