基于范围查询的移动对象快照KNN查询算法

Moving Objects Snapshot KNN Query Algorithm Based on Range Query

提出一种基于范围查询的移动对象快照K最近邻(KNN)查询算法——SKNN。预估包含结果集的子空间,使用该子空间作为范围,计算查询点的KNN兴趣点,以降低I/O成本。引入移动数据库中的缓存技术,缩短查询的平均响应时间。实验结果表明,当移动对象的规模较大时,SKNN算法的性能较优。

This paper presents a moving objects snapshot K Nearest Neighbor（KNN） query algorithm based on range query,named SKNN.It estimates the subspace containing the result set and uses the subspace as range to efficiently compute the KNN Points of Interest（POIs） from the query points to reduce I/O cost.It introduces cache to shorten the average response time of query.Experimental results show that after introducing cache,SKNN has better performance while scaling to a very large number of moving objects.