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http://dx.doi.org/10.3745/KIPSTD.2005.12D.4.507

Policies of Trajectory Clustering in Index based on R-trees for Moving Objects  

Ban ChaeHoon (경남정보대학 인터넷응용계열)
Kim JinGon (삼성전자 소프트웨어랩 무선 4그룹)
Jun BongGi (신라대학교 컴퓨터정보공학부)
Hong BongHee (주산대학교 공과대학 컴퓨터공학과)
Publication Information
The KIPS Transactions:PartD / v.12D, no.4, 2005 , pp. 507-520 More about this Journal
Abstract
The R-trees are usually used for an index of trajectories in moving-objects databases. However, they need to access a number of nodes to trace same trajectories because of considering only a spatial proximity. Overlaps and dead spaces should be minimized to enhance the performance of range queries in moving-objects indexes. Trajectories of moving-objects should be preserved to enhance the performance of the trajectory queries. In this paper, we propose the TP3DR-tree(Trajectory Preserved 3DR-tree) using clusters of trajectories for range and trajectory queries. The TP3DR-tree uses two split policies: one is a spatial splitting that splits the same trajectory by clustering and the other is a time splitting that increases space utilization. In addition, we use connecting information in non-leaf nodes to enhance the performance of combined-queries. Our experiments show that the new index outperforms the others in processing queries on various datasets.
Keywords
Moving Object Database; Spatiotemporal Database; Trajectory Query; Split Policy;
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