Energy Aware Metaheuristics Unequal Clustering Protocol for WSN

Wireless sensor networks have gained significant interest from every field owing to their high applicability. Maximization of network lifetime and resolving hot spot problems are considered as the major challenges involved in the design of WSN. This article develops an energy aware oppositional group search optimizer based unequal clustering protocol (EAOGSO-UCP) for WSN. The main aim of the EAOGSO-UCP approach is for organizing the network into a collection of unequal clusters by properly electing the CHs and unequal cluster sizes. The EAOGSO-UCP technique involves the design of oppositional group search optimizer(OGSO) technique that is stimulated from the searching characteristics of the animals in the real world environment. Besides, the OGSO algorithm is derived by the integration of the oppositional based learning (OBL) technique as to the GSO approach for effective population initialization. The design of OGSO algorithm for unequal clustering shows the novelty of the study. Moreover, a fitness function is derived involving three input variables as energy, distance to BS (DBS), and node degree (ND). For ensuring the energy efficient performance of the EAOGSO-UCP approach, a comprehensive simulation analysis is carried out and the comparative results reported the promising performance over the other existing techniques.