Swarm intelligence based localization in wireless sensor networks

Abstract

In wireless sensor networks, sensor node localization is an important problem because sensor nodes are randomly scattered in the region of interest and they get connected into network on their own. Finding location without the aid of Global Positioning System (GPS) in each node of a sensor network is important in cases where GPS is either not accessible, or not practical to use due to power, cost, or line of sight conditions. The objective of this paper is to find the locations of nodes by using Particle Swarm Optimization and Artificial Bee Colony algorithm and compare the performance of these two algorithms. The term swarm is used in a general manner to refer to a collection of interacting agents or individuals. We also propose multi stage localization and compared multi stage localization performance with single stage localization. © 2011 Springer-Verlag.