Poster Abstract: Multidimensional Scaling Based Sensor Positioning Algorithms in Wireless Sensor Networks

Recently, a family of methods have been proposed for large scale ad hoc sensor networks that estimate the approximate positions of sensor nodes in the network. In the paper, we first investigate some situations that most existing sensor positioning methods fail to perform well. An example of such situations is that the topology of a sensor network is anisotropic. Then, we study the multidimensional scaling (MDS) technique, and a centralized sensor positioning algorithm is proposed based on MDS. We also propose a distributed sensor positioning algorithm, which is in iteration paradigm, to address these situations. The MDS technique is applied to recover a series of local maps for adjacent sensors, and these maps are then stitched together to form a portion of globe map. At last, the estimated anchor positions are compared with the anchors’ physical position for accurate positioning.