Application of Soft Computing on Localization in Wireless Sensor Networks

Abstract

Localization is identifying coordinates of nodes in Wireless Sensor Networks (WSNs). It is required for almost all kinds of applications. It is of two types-Ranges based and range free. Due to low cost, range free is most preferable solution. Distance-Vector Hop (DV-Hop) is most promising solution in range free algorithms because of its points of interest, however it has low precision. To enhance localization precision, this paper introduces a novel solution that merges soft computing approach such as Particle Swarm Optimization (PSO) and Grey-Wolf Algorithm (GWO) to optimize DV-Hop. The results demonstrate viability of the proposed solution over previous one.