Optimized algorithms for predictive range and KNN queries on moving objects

被引:40
作者
Zhang, Rui [1 ]
Jagadish, H. V. [2 ]
Dai, Bing Tian [3 ]
Ramamohanarao, Kotagiri [1 ]
机构
[1] Univ Melbourne, Dept Comp Sci & Software Engn, Melbourne, Vic 3010, Australia
[2] Univ Michigan, Dept Elect Engn & Comp Sci, Ann Arbor, MI 48109 USA
[3] Natl Univ Singapore, Dept Comp Sci, Singapore 117548, Singapore
基金
澳大利亚研究理事会;
关键词
Transformed Minkowski Sum; Spatio-temporal databases; Moving objects; Range query; Nearest neighbor query; kNN; NEAREST-NEIGHBOR QUERIES; COST MODEL; TREE;
D O I
10.1016/j.is.2010.05.004
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
There have been many studies on management of moving objects recently. Most of them try to optimize the performance of predictive window queries. However, not much attention is paid to two other important query types: the predictive range query and the predictive k nearest neighbor query. In this article, we focus on these two types of queries. The novelty of our work mainly lies in the introduction of the Transformed Minkowski Sum, which can be used to determine whether a moving bounding rectangle intersects a moving circular query region. This enables us to use the traditional tree traversal algorithms to perform range and kNN searches. We theoretically show that our algorithms based on the Transformed Minkowski Sum are optimal in terms of the number of tree node accesses. We also experimentally verify the effectiveness of our technique and show that our algorithms outperform alternative approaches. (C) 2010 Elsevier B.V. All rights reserved.
引用
收藏
页码:911 / 932
页数:22
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