A novel centroid localization for wireless sensor networks

Abstract

Self-localization of sensor nodes is one of the key issues in wireless sensor networks. Based on the analysis of traditional range-free algorithms such as centroid and APIT (approximate perfect point in triangulation test) schemes, the effect of random deployment of all nodes on node localization is researched. And then, an improved centroid localization algorithm (ICLA) based on APIT and the quality of perpendicular bisector is proposed. In ICLA, nodes are categorized into several kinds and localized, respectively. Extensive simulation results indicate that ICLA obtains a better localization result in random topology networks without any additional hardware. Therefore, ICLA can be an alternate solution for the node self-localization problem in large-scale wireless sensor networks. Copyright © 2012 Yu Liu et al.