The design and analysis of spatial data structures
The design and analysis of spatial data structures
PODS '99 Proceedings of the eighteenth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Selectivity estimation in spatial databases
SIGMOD '99 Proceedings of the 1999 ACM SIGMOD international conference on Management of data
Selectivity estimation for spatio-temporal queries to moving objects
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
Selectivity Estimation for Spatial Joins
Proceedings of the 17th International Conference on Data Engineering
Analyzing Range Queries on Spatial Data
ICDE '00 Proceedings of the 16th International Conference on Data Engineering
Exploring Spatial Datasets with Histograms
ICDE '02 Proceedings of the 18th International Conference on Data Engineering
Performance evaluation of spatio-temporal selectivity estimation techniques
SSDBM '03 Proceedings of the 15th International Conference on Scientific and Statistical Database Management
Spatial selectivity estimation using compressed histogram information
APWeb'05 Proceedings of the 7th Asia-Pacific web conference on Web Technologies Research and Development
SSTD'05 Proceedings of the 9th international conference on Advances in Spatial and Temporal Databases
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Selectivity estimation is one of the query optimization techniques. It is difficult for the previous selectivity estimation techniques for moving objects to apply the location change of moving objects to synopsis. Therefore, they result in much error when estimating selectivity for queries, because they are based on the extended spatial synopsis which does not consider the property of the moving objects. In order to reduce the estimation error, the existing techniques should often rebuild the synopsis. Consequently problem occurs, that is, the whole database should be read frequently. In this paper, we proposed a moving object histogram method based on quadtree to develop a selectivity estimation technique for moving object queries. We then analyzed the performance of the proposed method through the implementation and evaluation of the proposed method. Our method can be used in various location management systems such as vehicle location tracking systems, location based services, telematics services, emergency rescue service, etc in which the location information of moving objects changes over time.