Energy conserving hybrid sensor network for target tracking in Wireless Sensor Networks

Abstract

Wireless Sensor Network is made up of tiny nodes with ability to sense, communicate and compute due to the presence of battery, sensors, transceivers, memory, and processor in them. This paper deals with a single target tracking scenario performed with static as well as mobility optimized mobile sensor nodes in an energy conserving manner, hence the name hybrid sensor network. Using the static nodes the current target location is estimated using waltz algorithm. Energy is conserved by activating only selected sensor nodes using Okumura Hata Model. Further the mobile nodes are selected in an energy aware manner and their position is optimized using particle swarm optimization for better target tracking. Simulation results analyze the target estimation results using static and mobile nodes. The computation time for sensor node relocation using particle swam optimization as against optimization using ant colony optimization is also compared.