Efficient Deterministic Anchor Deployment for Sensor Network Positioning

Sensor network positioning systems have been extensively studied in recent years. Most of the systems share a common assumption that some known-position anchor nodes have existed. However, a more fundamental question is always being overlooked, that is, how to acquire the anchor's position. In general, GPS-based measures and the artificial calibration are two dominant methods to acquire anchor positions. Due to the high energy cost and failures in occlusion regions of the GPS modules, the artificial calibration method is adopted extensively. Nevertheless, numerous disadvantages of the artificial calibration, such as the expensive labor cost and error-prone features, also make it hard to be an efficient solution for the anchor positioning. For this reason, we design an efficient mapping algorithm between anchors and their positions (MD-SKM) to avoid the complicated artificial calibration. Additionally, we propose a best feature matching (BFM) method to further relax the restriction of MDS-KM where three or more calibrated anchors are needed. We evaluate our MDS-KM algorithm under various topologies and connectivity settings. Experiment results show that at a slightly higher connectivity level, our algorithm can achieve the exactly correct matching between anchors and their positions without any calibrated anchors.