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计算机工程 ›› 2012, Vol. 38 ›› Issue (7): 49-52,56. doi: 10.3969/j.issn.1000-3428.2012.07.017

• 软件技术与数据库 • 上一篇    下一篇

基于范围查询的移动对象快照KNN查询算法

卢秉亮,刘 娜,张大伟   

  1. (沈阳航空航天大学计算机学院,沈阳 110136)
  • 收稿日期:2011-05-04 出版日期:2012-04-05 发布日期:2012-04-05
  • 作者简介:卢秉亮(1953-),男,副教授、硕士,主研方向:数据 库技术;刘 娜,硕士研究生;张大伟,讲师、硕士研究生

Moving Objects Snapshot KNN Query Algorithm Based on Range Query

LU Bing-liang, LIU Na, ZHANG Da-wei   

  1. (School of Computer, Shenyang Aerospace University, Shenyang 110136, China)
  • Received:2011-05-04 Online:2012-04-05 Published:2012-04-05

摘要: 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。

关键词: 移动数据库, 范围查询, 位置相关, K最近邻, 双索引, 缓存

Abstract: 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.

Key words: mobile database, range query, location-dependent, K Nearest Neighbor(KNN), dual index, cache

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