Removing Heavily Curved Path: Improved DV-hop Localization in Anisotropic Sensor Networks

Abstract

In Wireless Sensor Networks (WSNs) a multitude of location-dependent applications have been proposed recently, which is very intriguing for researchers to discover and design more accurate and cost-effective localization algorithms. In an isotropic networks, the Euclidean distance between a pair of nodes may not correlate closely with the hop count between them because the corresponding shortest path may have to curve around intermediate holes, resulting in poor distance estimation. And without the help of a large number of uniformly deployed seed nodes, those schemes fail in an isotropic WSNs. To address this issue and improve the accuracy of localization, we propose the Removing Heavily Curved Path (RHCP) scheme in this paper. RHCP takes advantage of selecting the paths which are not heavily affected by the holes to recalculate the location of each unknown node. Through simulation, the results reveal that RHCP performs better than original DV-Hop in an isotropic networks with different shape of holes. In addition, through iterations of RHCP, the results get improved for different anchor node densities.