A new range-free localisation in wireless sensor networks using support vector machine

Abstract

ABSTRACTLocation information of sensor nodes is of vital importance for most applications in wireless sensor networks (WSNs). This paper proposes a new range-free localisation algorithm using support vector machine (SVM) and polar coordinate system (PCS), LSVM-PCS. In LSVM-PCS, two sets of classes are first constructed based on sensor nodes’ polar coordinates. Using the boundaries of the defined classes, the operation region of WSN field is partitioned into a finite number of polar grids. Each sensor node can be localised into one of the polar grids by executing two localisation algorithms that are developed on the basis of SVM classification. The centre of the resident polar grid is then estimated as the location of the sensor node. In addition, a two-hop mass-spring optimisation (THMSO) is also proposed to further improve the localisation accuracy of LSVM-PCS. In THMSO, both neighbourhood information and non-neighbourhood information are used to refine the sensor node location. The results obtained verify that the proposed algorithm provides a significant improvement over existing localisation methods.