Continual Neighborhood Tracking for Moving Objects Using Adaptive Distances

Based on the recent progress of digital cartography, global positioning systems (GPSs), and hand-held devices, there are growing needs of technology that provides neighborhood information to moving objects according to their locations and trajectories. In this paper, we propose spatial query generation models that take account of the current position and the past/future trajectories of a moving object to provide appropriate neighborhood information to it. For this purpose, we introduce an influence model of trajectory points and derive neighborhood query generation models using adaptive ellipsoid distances. We describe query processing strategies for these query generation models and show incremental query update procedures to support continual query facilities with low processing cost. Finally, we present experimental results to show the effectiveness of our approach.