Localization of sensor nodes using modified particle swarm optimization in wireless sensor networks

An indigenous and efficient techniques for global optimization methodology based on particle intelligent swarm to be utilized for locating the nodes in a Wireless Network of sensors has been proposed in this work. The objective function used is the estimation error of neighboring anchor nodes in the environment. Particle Swarm Optimization is a globally used optimization tool that works on swarm intelligence technique. This algorithm ensures high rates of convergence and prevents the problem of trapping in local minima. The proposed work, uses a modified particle swarm optimization technique which is computationally efficient and subsequent simulation results have proven the better convergence results derived from the algorithm over traditional methods of particle swarm optimization technique.