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Moving Point Indexing for Future Location Query

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3289))

Abstract

Nowadays, with a great number of mobile (moving) objects using wireless communication or GPS technology, monitoring systems having the capability of handling anticipated future queries of the mobile objects are literally important. To cater for these applications, the TPR-tree indexing method, which is able to support the future queries, is substantially feasible for the real world. The crucial idea of them is to make the bounding rectangle as a motion function of time. In this paper, we propose an extended method of the TPR-tree, named Horizon TPR-tree or HTPR-tree. The general idea that we make a new motion function of time is to reduce speed of growing sizes of MBR (minimum bounding rectangles). Smaller MBR alleviates overlap problem and increases the effect of query in R-tree based methods. During creating and updating index, motion function influences organizing operations, such as splitting and adjusting. Our experiments show that the HTPR-tree outperforms the TPR-tree for anticipated future queries. In addition, the idea of the proposed method is able to apply to not only the TPR-tree but also variants of the TPR-tree. The proposed method is applicable to vehicle-traffic network systems.

This work was supported by the RRC of MOST and KOSEF as well as University IT Research Center Project in Korea.

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© 2004 Springer-Verlag Berlin Heidelberg

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Do Thanh Tung, H., Jung, Y.J., Lee, E.J., Ryu, K.H. (2004). Moving Point Indexing for Future Location Query. In: Wang, S., et al. Conceptual Modeling for Advanced Application Domains. ER 2004. Lecture Notes in Computer Science, vol 3289. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30466-1_8

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  • DOI: https://doi.org/10.1007/978-3-540-30466-1_8

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-23722-8

  • Online ISBN: 978-3-540-30466-1

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