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ABSTRACT

Existing methods for peediction spatio-temporal databases assume that objects move according to linear functions. This severely limits their applicability, since in practice movement is more complex, and individual objects may follow drastically diffferent motion patterns. In order to overcome these problems, we first introduce a general framework for monitoring and indexing moving objects, where (i) each boject computes individually the function that accurately captures its movement and (ii) a server indexes the object locations at a coarse level and processes queries using a filter-refinement mechanism. Our second contribution is a novel recursive motion function that supports a broad class of non-linear motion patterns. The function does not presume any a-priori movement but can postulate the particular motion of each object by examining its locations at recent timestamps. Finally. we propse an efficient indexing scheme that faciliates the processing of predicitive queries without false misses.

REFERENCES

• 1: Pankaj K. Agarwal , Lars Arge , Jeff Erickson, Indexing moving points (extended abstract), Proceedings of the nineteenth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems, p.175-186, May 15-18, 2000, Dallas, Texas, United States [doi>10.1145/335168.335220]
• 2: Charu C. Aggarwal , Dakshi Agrawal, On nearest neighbor indexing of nonlinear trajectories, Proceedings of the twenty-second ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems, p.252-259, June 09-11, 2003, San Diego, California [doi>10.1145/773153.773178]
• 3: Norbert Beckmann , Hans-Peter Kriegel , Ralf Schneider , Bernhard Seeger, The R*-tree: an efficient and robust access method for points and rectangles, Proceedings of the 1990 ACM SIGMOD international conference on Management of data, p.322-331, May 23-26, 1990, Atlantic City, New Jersey, United States [doi>10.1145/93597.98741]
• 4: Yong-Jin Choi , Chin-Wan Chung, Selectivity estimation for spatio-temporal queries to moving objects, Proceedings of the 2002 ACM SIGMOD international conference on Management of data, June 03-06, 2002, Madison, Wisconsin [doi>10.1145/564691.564742]
• 5: {HKT03} Hadjieleftheriou, M., Kollios, G., Tsotras, V. Performance Evaluation of Spatio-temporal Selectivity Estimation Techniques, SSDBM, 2003.
• 6: {HKTG02} Hadjieleftheriou, M., Kollios, G., Tsotras, V., Gunopulos, D. Efficient Indexing of Spatiotemporal Objects. EDBT, 2002.
• 7: {ISS03} Iwerks, G., Samet, H., Smith, K. Continuous K-Nearest Neighbor Queries for Continuously Moving Points with Updates. VLDB, 2003.
• 8: George Kollios , Dimitrios Gunopulos , Vassilis J. Tsotras, On indexing mobile objects, Proceedings of the eighteenth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems, p.261-272, May 31-June 03, 1999, Philadelphia, Pennsylvania, United States [doi>10.1145/303976.304002]
• 9: {PFTV02} Press, W., Flannery, B., Teukolsky, S., Vetterling, W. Numerical Recipes in C++ (second edition). Combridge University Press, ISBN 0-521-75034-2, 2002.
• 10: Bernd-Uwe Pagel , Hans-Werner Six , Heinrich Toben , Peter Widmayer, Towards an analysis of range query performance in spatial data structures, Proceedings of the twelfth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems, p.214-221, May 25-28, 1993, Washington, D.C., United States [doi>10.1145/153850.153878]
• 11: {SJ02} Saltenis, S., Jensen, C. Indexing of Moving Objects for Location-Based Services. ICDE, 2002.
• 12: Simonas Šaltenis , Christian S. Jensen , Scott T. Leutenegger , Mario A. Lopez, Indexing the positions of continuously moving objects, Proceedings of the 2000 ACM SIGMOD international conference on Management of data, p.331-342, May 15-18, 2000, Dallas, Texas, United States [doi>10.1145/342009.335427]
• 13: {Tiger} http://www.census.gov/geo/www/tiger/
• 14: Yufei Tao , Dimitris Papadias, Time-parameterized queries in spatio-temporal databases, Proceedings of the 2002 ACM SIGMOD international conference on Management of data, June 03-06, 2002, Madison, Wisconsin [doi>10.1145/564691.564730]
• 15: {TPS03} Tao, Y., Papadia, D., Sun, J. The TPR*-Tree: An Optimized Spatio-Temporal Access Method for Predictive Queries. VLDB, 2003.
• 16: {TSP03} Tao, Y., Sun, J., Papadias, D. Selectivity Estimation for Predictive Spatio-Temporal Queries. ICDE, 2003.
• 17: {TUW98} Tayeb, J., Ulusoy, O., Wolfson, O. A. Quadtree-Based Dynamic Attribute Indexing Method. The Computer Journal, 41(3):185--200, 1998.