Querying Mobile Objects in Spatio-Temporal Databases

  • Kriengkrai Porkaew
  • Iosif Lazaridis
  • Sharad Mehrotra
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2121)


In dynamic spatio-temporal environments where objects may continuously move in space, maintaining consistent information about the location of objects and processing motion-specific queries is a challenging problem. In this paper, we focus on indexing and query processing techniques for mobile objects. Specifically, we develop a classification of different types of selection queries that arise in mobile environments and explore efficient algorithms to evaluate them. Query processing algorithms are developed for both native space and parametric space indexing techniques. A performance study compares the two indexing strategies for different types of queries.


Query Processing Range Query Query Point Native Space Mobile Object 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    B. Becker, S. Gschwind, T. Ohler, B. Seeger, and P. Widmayer. An asymptotically optimal multiversion b-tree. VLDB Journal, 5(4):264–275, 1996.CrossRefGoogle Scholar
  2. 2.
    N. Beckmann, H.-P. Kriegel, R. Schneider, and B. Seeger. The R*-tree: an efficient and robust access method for points and rectangles. In ACM SIGMOD Int’l Conf. on Management of Data, pages 322–331, May 1990.Google Scholar
  3. 3.
    A. Guttman. R-tree: a dynamic index structure for spatial searching. In ACM SIGMOD Int’l Conf. on Management of Data, pages 47–57, June 1984.Google Scholar
  4. 4.
    G. R. Hjaltason and H. Samet. Ranking in spatial databases. In Int’l Symposium on Large Spatial Databases, 1995.Google Scholar
  5. 5.
    G. Kollios, D. Gunopulos, and V. J. Tsotras. On indexing mobile objects. In Symposium on Principles of Database Systems, 1999.Google Scholar
  6. 6.
    D. Lomet and B. Salzberg. The hB-Tree: A multiattribute indexing method with good guaranteed performance. ACM Trans. on Database Systems, 15(4):625–658, 1990.CrossRefGoogle Scholar
  7. 7.
    D. Lomet and B. Salzberg. The performance of a multiversion access method. In ACM SIGMOD Int’l Conf. on Management of Data, 1990.Google Scholar
  8. 8.
    J. A. Orenstein. A comparison of spatial query processing techniques for native and parameter spaces. In ACM SIGMOD Int’l Conf. on Management of Data, pages 343–352, 1990.Google Scholar
  9. 9.
    K. Porkaew. Database support for similarity retrieval and querying mobile objects. Technical report, PhD thesis, University of Illinois at Urbana-Champaign, 2000.Google Scholar
  10. 10.
    J. T. Robinson. The k-d-b-tree: A search structure for large multidimensional dynamic indexes. In ACM SIGMOD Int’l Conf. on Management of Data, 1981.Google Scholar
  11. 11.
    N. Roussopoulos, S. Kelley, and F. Vincent. Nearest neighbor queries. In ACM SIGMOD Int’l Conf. on Management of Data, 1995.Google Scholar
  12. 12.
    S. Saltenis, C. Jensen, S. Leutenegger, and M. Lopez. Indexing the positions of continuously moving objects. In ACM SIGMOD Int’l Conf. on Management of Data, 2000.Google Scholar
  13. 13.
    B. Salzberg and V. Tsotras. Comparison of access methods for time-evolving data. ACM Computing Surveys, 31(2):158–221, 1999.CrossRefGoogle Scholar
  14. 14.
    H. Samet. The quadtree and related hierarchial data structures. ACM Computing Surveys, 16(2):187–260, 1984.CrossRefMathSciNetGoogle Scholar
  15. 15.
    T. Sellis, N. Roussopoulos, and C. Faloutsos. The R+ tree: A dynamic index for multi-dimensional objects. In Int’l Conf. on Very Large Data Bases, 1987.Google Scholar
  16. 16.
    J. Tayeb, O. Ulusoy, and O. Wolfson. A quadtree based dynamic attribute indexing method. Computer Journal, 41(3):185–200, 1998.zbMATHCrossRefGoogle Scholar
  17. 17.
    Y. Theodoridis, T. Sellis, A. N. Papadopoulos, and Y. Manolopoulos. Specifications for efficient indexing in spatiotemporal databases. In Int’l Conf. on Scientific and Statistical Database Management, pages 123–132, 1998.Google Scholar
  18. 18.
    O. Wolfson, B. Xu, S. Chamberlain, and L. Jiang. Moving objects databases: Issues and solutions. In Int’l Conf. on Scientific and Statistical Database Management, pages 111–122, 1998.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Kriengkrai Porkaew
    • 1
  • Iosif Lazaridis
    • 2
  • Sharad Mehrotra
    • 2
  1. 1.King Mongkut’s University of Technology at ThonburiThailand
  2. 2.University of CaliforniaIrvineUSA

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