GSA-CHSR: Gravitational Search Algorithm for Cluster Head Selection and Routing in Wireless Sensor Networks

Abstract

Gravitational search algorithm (GSA) is a new paradigm for optimization that needs to be explored further to show its full potential. The focus of the current work is to address the most promising problems in wireless sensor networks (WSNs) such as cluster head selection and routing using GSA. In a two-tired architecture of WSN, cluster heads (CHs) are overloaded for receiving and aggregating the data packets from member nodes, thereafter, transmitting them to the base station (BS). Therefore, while selecting CHs proper care should be taken to enhance the life of WSNs. After formation of clusters, the data to be transmitted to the BS via intercluster route so that the life of the network is prolonged. In the current study, a new CH selection strategy is developed with an efficient encoding scheme by formulating a novel fitness function based on the residual energy, intra-cluster distance, and CH balancing factor. In addition, a GSA-based routing algorithm is also devised by considering residual energy and distance as parameters to be optimized. The proposed algorithm (GSA-CHSR) is extensively tested with existing techniques on various scenarios of the network to study the performance. The experimental results confirms the superiority and/or competitiveness of GSA-CHSR as compared with some of the well-known existing methods available the literature, such as DHCR, EADC, Hybrid Routing, GA, and PSO.