Abstract
The Wireless Sensor Networks (WSN) is a self-organizing networkwith random deployment of wireless nodes that connects each other for effectivemonitoring and data transmission. The clustering technique employed to groupthe collection of nodes for data transmission and each node is assigned with acluster head. The major concern with the identification of the cluster head isthe consideration of energy consumption and hence this paper proposes an hybridmodel which forms an energy efficient cluster head in the Wireless Sensor Net-work. The proposed model is a hybridization of Glowworm Swarm Optimization(GSO) and Artificial Bee Colony (ABC) algorithm for the better identification ofcluster head. The performance of the proposed model is compared with the exist-ing techniques and an energy analysis is performed and is proved to be more effi-cient than the existing model with normalized energy of 5.35% better value andreduction of time complexity upto 1.46%. Above all, the proposed model is 16%ahead of alive node count when compared with the existing methodologies.