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Liao Wei, Jing Ning, Zhong Zhinong, and Chen Hongsheng. An Efficient Prediction Technique for Range Aggregation of Moving Objects[J]. Journal of Computer Research and Development, 2007, 44(6): 1015-1021.
Citation: Liao Wei, Jing Ning, Zhong Zhinong, and Chen Hongsheng. An Efficient Prediction Technique for Range Aggregation of Moving Objects[J]. Journal of Computer Research and Development, 2007, 44(6): 1015-1021.

An Efficient Prediction Technique for Range Aggregation of Moving Objects

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  • Published Date: June 14, 2007
  • Predictive range aggregate (PRA) queries are one of the important researching areas in the moving object database. In this paper an efficient prediction technique, PRA-tree, is presented for range aggregation of moving objects. PRA-tree splits the velocity domain regularly, and classifies moving objects into different velocity buckets by their velocities. Then a TPR-tree, which is based on the TPR-tree structure and added with aggregate information in intermediate nodes, is used to index the moving objects in each buckets, thus reducing the disk accesses of PRA queries. A PRA-tree is supplemented by a hash index on leaf nodes, and uses bottom-up delete algorithm, thus having a good update performance and concurrency. Also developed for the PRA tree is an enhanced predictive range aggregate (EPRA) query algorithm which uses a more precise branch and bound searching strategy, reducing the disk I/O greatly. Experimental results and analysis show that the EPRA algorithm for PRA-tree has a good query performance and outperforms the popular TPR\+*tree index.
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