A Routing Optimization Strategy for Wireless Sensor Networks Based on Improved Genetic Algorithm

Abstract

In order to resolve the problem of generating invalid new individual when using genetic algorithm for routing optimization in wireless sensor networks (WSNs), an improved genetic algorithm (ROS_IGA) is put forward. By considering the position and neighbors of nodes in WSNs, ROS_IGA takes reasonable crossover and mutation operation to ensure compliance with the topological of actual WSNs and the demand of communication among nodes. Furthermore, ROS_IGA takes many factors, such as the residual energy of sensor nodes, distance and energy consumption between adjacent nodes, communication delay and relay hops, into consideration to select suitable routing. So ROS_IGA increases the speed of convergence and optimizes the performance of WSNs. Finally, a simulation experiment is carried out and the experimental results show that the improved algorithm in this study can effectively finds the best routing and decreases energy consuming and also increases the network life cycle.