Improvement of lifetime duty cycle using genetic algorithm and network coding in wireless sensor networks

Abstract

The process of a sensor network is to control by a big number of parameters, such as the wireless duty cycle, the frequency of neighbor discovery inspirations, and the rate of sample sensors. In this paper we propose a reduced-complexity Genetic Algorithm (GA) for optimization of multi-hop sensor networks in two stages such as randomized and circular bottleneck network node scheduling. The goal of the system is to generate optimal number of sensor clusters with Cluster-Heads (CHs). The GA is used to adaptively create various components such as cluster-members; Performance improvement by using GA namely; packet delivery ratio and average latency have also been investigated. A full theoretical analysis and simulation results have been providing to display the efficacy of the proposed approach improved x-OR using GA showing efficiency better as compare to basic XOR method and producing maximum packet delivery ratio.