Abstract：The functionality of a framework that supported location-based services on moving objects in road networks was extended and Snapshot K Nearest Neighbor (SKNN) queries based on Mobile Network Distance Range (MNDR) queries was proposed using an on-disk R-tree to store the network connectivity and an in-memory grid structure to maintain the moving object position updates. The minimum and maximum number of grid cells of a given arbitrary edge in the space that were possibly affected were analyzed. The maximum bound that could be used in snapshot range query processing to prune the search space was shown. SKNN estimated the subspace containing the query results and used the subspace as range to efficiently compute the KNN POI from the query points to reduce I/O cost and time of query. Analysis shows that the maximum bound can be used in snapshot range query processing to prune the search space. The contrast experiments show that SKNN has better system throughput than S-GRID while scaling to hundreds of thousands of moving objects.
卢秉亮 刘娜. 路网中移动对象快照K近邻查询处理[J]. 计算机应用, 2011, 31(11): 3078-3083.
LU Bing-liang LIU Na. Snapshot K neighbor query processing on moving objects in road networks. Journal of Computer Applications, 2011, 31(11): 3078-3083.
2011, Vol. 31 
