Minimizing energy of scalable distributed least squares localization

Abstract

In recent years, Wireless Sensor Networks (WSN) have become a growing technology that has broad range of applications. One of the major areas of research in Sensor Networks is location estimation. Distributed Least Squares (DLS) algorithm is a good solution for fine grained localization. Here localization process is split into a complex precalculation and a simple postcalculation process. This paper presents a revised version of DLS, i.e. minimized energy Distributed Least Squares (meDLS) algorithm where each blind node collects position of neighbouring beacon nodes and directly sends it to the sink node for precalculation. The precaluated data is sent back to the blind node for postcalculation, where location of blind node is estimated. The proposed algorithm is simulated and compared with scalable DLS (sDLS) for computational and communicational cost. © 2012 Springer-Verlag.