Distributed Localization for Anisotropic Sensor Networks Using Spatial Clustering

摘要

Anisotropic networks are characterized by the properties that vary with the direction of measurement. These characteristics are the result of geographic shape of the region, different node densities, irregular radio patterns and anisotropic terrain conditions. We propose a modification to distributed localization of anisotropic sensor networks which uses linear mapping method projecting an embedded space based on proximities into geographic distance space. This paper focuses on extracting regular structures through the distributed clustering scheme and later on carrying out the localization procedure.