Multilayer DS-MAC with game theory optimization

Abstract

Purpose Energy is the major concern in wireless sensor networks (WSNs) for most of the applications. There exist many factors for higher energy consumption in WSNs. The purpose of this work is to increase the coverage area maintaining the minimum possible nodes or sensors. Design/methodology/approach This paper has proposed multilayer (ML) nodes deployment with distributed MAC (DS-MAC) in which nodes listen time is controlled based on communication of neighbors. Game theory optimization helps in addressing path loss constraints while selecting path toward base stations (BS). Findings The simulation is carried out using NS-2.35, and it shows better performance in ML DS-MAC compared to random topology in DS-MAC with same number of BS. The proposed method improves performance of network in terms of energy consumption, network lifetime and better throughput. Research limitations/implications Energy consumption is the major problem in WSNs and for which there exist many reasons, and many approaches are being proposed by researchers based on application in which WSN is used. Node mobility, topology, multitier and ML deployment and path loss constraints are some of the concerns in WSNs. Practical implications Game theory is used in different situations like countries whose army race, business firms that are competing, animals generally fighting for prey, political parties competing for vote, penalty kicks for the players in football and so on. Social implications WSNs find applications in surveillance, monitoring, inspections for wild life, sea life, underground pipes and so on. Originality/value Game theory optimization helps in addressing path loss constraints while selecting path toward BS.