Abstract
Although several sophisticated index structures for moving objects have been proposed, the hashing method based on a simple grid has been widely employed due to its simplicity. Since the performance of the hashing is largely affected by the size of a grid cell, it should be carefully decided with regard to the workload. In many real applications, however, the workload varies dynamically as time, for example the traffic in the commuting time vs. that in the night. The basic hashing cannot handle this dynamic workload because the cell size cannot be changed during the execution. In this paper, we propose the adaptive multi-level hashing to support the dynamic workload efficiently. The proposed technique maintains two levels of the hashes, one for fast moving objects and the other one for quasi-static objects. A moving object changes its level adaptively according to the degree of its movement.
This work was supported in part by the Brain Korea 21 Project and in part by the Ministry of Information & Communications, Korea, under the Information Technology Research Center (ITRC) Support Program in 2004.
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References
Song, Z., Roussopoulos, N.: Hashing moving objects. In: Proceedings of the 2nd Int’l. Conf. on Mobile Data Management, pp. 161–172 (2001)
Chon, H.D., Agrawal, D., Abbadi, A.E.: Using space-time grid for efficient management of moving objects. In: Proceedings of the 2nd ACM international workshop on Data engineering for wireless and mobile access, pp. 59–65. ACM Press, New York (2001)
Saltenis, S., Jensen, C.S., Leutenegger, S.T., Lopez, M.A.: Indexing the positions of continuously moving objects. In: Proceedings of the 2000 ACM SIGMOD Int’l. Conf. on Management of Data, pp. 331–342 (2000)
Tao, Y., Papadias, D., Sun, J.: The TPR*-Tree: An optimized spatio-temporal access method for predictive queries. In: Proceedings of 29nd Int’l. Conf. on Very Large Data Bases, pp. 790–801 (2003)
Kwon, D., Lee, S., Lee, S.: Indexing the current positions of moving objects using the Lazy Update R-tree. In: Proceedings of the 3rd Int’l. Conf. on Mobile Data Management, pp. 113–120 (2002)
Chon, H.D., Agrawal, D., Abbadi, A.E.: Storage and retrieval of moving objects. In: Proceedings of the 2nd Int’l. Conf. on Mobile Data Management, pp. 173–184 (2001)
Mokbel, M.F., Xiong, X., Aref, W.G.: SINA: scalable incremental processing of continuous queries in spatio-temporal databases. In: Proceedings of the 2004 ACM SIGMOD international conference on Management of data, pp. 623–634. ACM Press, New York (2004)
Xia, Y., Prabhakar, S.: Q+Rtree: Efficient indexing for moving object databases. In: Proceedings of the Eighth International Conference on Database Systems for Advanced Applications, p. 175. IEEE Computer Society, Los Alamitos (2003)
Mokbel, M.F., Ghanem, T.M., Aref, W.G.: Spatio-temporal access methods. IEEE Data Engineering Bulletin 26, 40–49 (2003)
Lee, M.L., Hsu, W., Jensen, C.S., Cui, B., Teo, K.L.: Supporting frequent updates in R-Trees: A bottom-up approach. In: Proceedings of 29th Int’l. Conf. on Very Large Data Bases, pp. 608–619 (2003)
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Kwon, D., Lee, S., Choi, W., Lee, S. (2005). Adaptive Multi-level Hashing for Moving Objects. In: Zhou, L., Ooi, B.C., Meng, X. (eds) Database Systems for Advanced Applications. DASFAA 2005. Lecture Notes in Computer Science, vol 3453. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11408079_85
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DOI: https://doi.org/10.1007/11408079_85
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