Node Localization Method for Wireless Sensor Networks Based on HybridOptimization of Differential Evolution and Particle Swarm Algorithm

摘要

Regarding the node localization problems for wireless sensor network, a hybrid optimization method was proposedaccordingly on differential evolution(DE) algorithm and particle swarm optimization(PSO) algorithm. Firstly, theposition and velocity of the initial population were randomly generated by PSO, and the fitness function was constructedaccording to the mean square error of estimated and measured distance between the unknown nodes and their adjacent anchornode. Secondly, the mutation and selection operation of DE algorithm were executed to find out the optimum positionof the population. Lastly, the current velocities and positions of all particles of the population were updated, and thecrossover operation and selection operation of DE algorithm were executed to update the current global optimum positionof the whole population. Population global optimum solution of iterative search algorithm is the position coordinate of theunknown node. Simulation results indicate that the proposed localization method has smaller average localization errorand higher localization accuracy than that of DE algorithm and PSO algorithm in the same environment.