Maximizing Energy Efficiency of Wireless Sensor Networks by Using Genetic Algorithm and Graph Theory

There are a large number of sensor nodes deployed in wireless sensor networks (WSN) Each sensor node in the network is equipped with a battery power. It is crucial task to change or recharge batteries. Now the question arises how to maximize the lifetime of wireless sensor networks by minimizing the energy consumption of the network. Various techniques and protocols have been used to optimize the energy of sensor nodes of WSN. Genetic algorithm is one of the best method to form cluster of sensor nodes and graph theory is also very efficient technique for finding the shortest distance between sensor nodes in the cluster. This paper describes the combination of both the techniques to propose a new and effective method that considerably improves the energy efficiency of wireless sensor networks.This technique is divided into three stages. In first stage, clusters are made and from that cluster head is selected using genetic algorithm. In second stage distance between various sensor nodes is calculated and shortest path is selected for sending data packets. In third step, data transmission between sensor nodes takes place. The experimental results show that the proposed method considerably improves the energy efficiency of WSNs and ultimately enhancing the lifetime of network.