Improved DV-Hop Algorithm Based on Ant Colony Algorithm and Particle Swarm Optimization for Wireless Sensor Network Location Problem

Abstract

Wireless sensor network location problem is one of hot focus in the academic community recently and DV-Hop algorithm is commonly used to solve the typical location algorithms in wireless sensor Network. In order to improve the efficiency of the DV-Hop algorithm, ant colony algorithm and particle swarm optimization have been brought into DV-Hop algorithm for optimizing globally. The AP-DV-Hop algorithm makes use of the advantages of ACA and PSO so as to guarantee the globality of optimal solutions which avoids trapping in local optimum with the help of the particle nature of ant agents and initialized random solutions. Finally, the simulation experiment results have shown that AP-DV-Hop algorithm has smaller average location error than DV-Hop algorithm and genetic algorithm.