Abstract
Wireless Sensor Networks (WSNs) are networks of spatially distributed autonomous nodes used to perform various monitoring tasks. Localization is one of the challenging issues in WSNs. Several approaches have been proposed to calculate positions of randomly deployed sensor nodes. In this paper, an attempt is made to optimize the location of the sensor nodes. A new hybrid Bio-inspired algorithm is used to improve the efficiency and accuracy and overcome the drawbacks like getting trapped at a local extreme in the optimization process of Bacterial Foraging Algorithm. In the proposed algorithm the idea of Particle swarm optimization is merged into the chemotaxis of bacterial foraging optimization algorithm which can effectively speed up the convergence rate and the elimination probability in elimination-dispersion is proposed according to the energy of bacteria which can improve the global searching ability.
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