Continuous Reverse Nearest Neighbor Queries on Moving Objects in Road Networks

Continuous reverse nearest neighbor (CRNN) query processing in road networks has received considerable attention of location-based services on moving objects. Most RNN queries in traffic networks only consider the moving objects as the static objects at each timestamp, which is difficult to adapt to different traffic situations such as traffic jams. Relying on the heuristic expansion strategy, we propose a new CRNN query algorithm that can be adapted to the dynamic traffic situation updating. PMR quad-tree and Dijkstra search strategy are adopted in RNN query algorithm. The experiments with real datasets show that the algorithm has a high efficiency and scalability.