Heuristic Approach for Optimizing the localization of wireless sensor Networks

Wireless Sensor Networks (WSNs) are networks of spatially distributed autonomous nodes used to perform various monitoring tasks. Localization is a challenging issue in WSNs. Many approaches have been proposed to determine the positions of randomly deployed sensor nodes. In this paper, an attempt is made for optimizing the localization of the sensor nodes. A hybrid approach is proposed to improve the efficiency and accuracy and overcome the drawbacks like getting trapped at a local extreme in the optimization process. In the proposed heuristic algorithm the idea of Particle swarm optimization is merged into the chemotaxis of bacterial foraging optimization algorithm to speed up the convergence rate and the elimination probability is selected according to the energy of bacteria to improve the global searching ability. Also the crossover technique of genetic algorithm is introduced in the reproduction stage to improve the evaluation of optimal objective function values.