Optimized algorithms for predictive range and KNN queries on moving objects
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 ar...
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sg-smu-ink.sis_research-43042016-11-29T05:53:23Z Optimized algorithms for predictive range and KNN queries on moving objects ZHANG, Rui JAGADISH, H.V. Bing Tian DAI, RAMAMOHANARAO, Kotagiri 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. 2010-12-01T08:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/3302 info:doi/10.1016/j.is.2010.05.004 https://ink.library.smu.edu.sg/context/sis_research/article/4304/viewcontent/OptimizedAlgorPredicRangeKNN_2010_InfoSys_pp.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Transformed Minkowski Sum Spatio-temporal databases Moving objects Range query Nearest neighbor query kNN Computer Sciences Theory and Algorithms |
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Transformed Minkowski Sum Spatio-temporal databases Moving objects Range query Nearest neighbor query kNN Computer Sciences Theory and Algorithms ZHANG, Rui JAGADISH, H.V. Bing Tian DAI, RAMAMOHANARAO, Kotagiri Optimized algorithms for predictive range and KNN queries on moving objects |
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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. |
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ZHANG, Rui JAGADISH, H.V. Bing Tian DAI, RAMAMOHANARAO, Kotagiri |
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ZHANG, Rui JAGADISH, H.V. Bing Tian DAI, RAMAMOHANARAO, Kotagiri |
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ZHANG, Rui |
title |
Optimized algorithms for predictive range and KNN queries on moving objects |
title_short |
Optimized algorithms for predictive range and KNN queries on moving objects |
title_full |
Optimized algorithms for predictive range and KNN queries on moving objects |
title_fullStr |
Optimized algorithms for predictive range and KNN queries on moving objects |
title_full_unstemmed |
Optimized algorithms for predictive range and KNN queries on moving objects |
title_sort |
optimized algorithms for predictive range and knn queries on moving objects |
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Institutional Knowledge at Singapore Management University |
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2010 |
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https://ink.library.smu.edu.sg/sis_research/3302 https://ink.library.smu.edu.sg/context/sis_research/article/4304/viewcontent/OptimizedAlgorPredicRangeKNN_2010_InfoSys_pp.pdf |
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