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Dynamic Splitting Policies of the Adaptive 3DR-Tree for Indexing Continuously Moving Objects

  • Bonggi Jun
  • Bonghee Hong
  • Byunggu Yu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2736)

Abstract

Moving-objects databases need a spatio-temporal indexing scheme for moving objects to efficiently process queries over continuously changing locations of the objects. A simple extension of the R-tree that employs time as the third dimension of the data universe shows low space utilization and poor search performance because of overlapping index regions. In this paper, we propose a variant of the 3-dimensional R-tree called the Adaptive 3DR-tree. The dynamic splitting policies of the Adaptive 3DR-tree significantly reduce the overlap rate, and this, in turn, results in improved query performance. The results of our extensive experiments show that the Adaptive 3DR-tree outperforms the original 3D R-tree and the TB-tree typically by a big margin.

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References

  1. 1.
    Guttman, A.: R-trees: A dynamic index structure for spatial searching. In: Proceedings of ACM SIGMOD Conference, pp. 47–54 (1984)Google Scholar
  2. 2.
    Theodoridis, Y., Vazirgiannis, M., Sellis, T.K.: Spatio-Temporal Indexing for Large Multimedia Applications. In: IEEE International Conference on Multimedia Computing and Systems, pp. 441–448 (1996)Google Scholar
  3. 3.
    Nascimento, M.A., Silva, J.R.O.: Towards historical R-trees. In: ACM symposium on Applied Computing, pp. 235–240 (1998)Google Scholar
  4. 4.
    Tao, Y., Papadias, D.: MV3R-Tree: A Spatio-Temporal Access Method for Timestamp and Interval Queries. In: Proceedings of the VLDB Conference, pp. 431–440 (2001)Google Scholar
  5. 5.
    Pfoser, D., Jensen, C.S., Theodoridis, Y.: Novel Approaches in Query Processing for Moving Objects. In: Proceedings of the VLDB Conference, pp. 395–406 (2000)Google Scholar
  6. 6.
    Beckmann, N., Kriegel, H.P.: The R*-tree: An Efficient and Robust Access Method for Points and Rectangles. In: Proceedings of ACM SIGMOD Conference, pp. 332–331 (1990)Google Scholar
  7. 7.
    Pfoser, D., Theodoridis, Y., Jensen, C.S.: Indexing Trajectories in Query Processing for Moving Objects, Chorochronos Technical Report, CH-99-3 (1999)Google Scholar
  8. 8.
    Theodoridis, Y., Silva, J.R.O., Nascimento, M.A.: On the Generation of Spatiotemporal Datasets. In: Güting, R.H., Papadias, D., Lochovsky, F.H. (eds.) SSD 1999. LNCS, vol. 1651, pp. 147–164. Springer, Heidelberg (1999)CrossRefGoogle Scholar
  9. 9.
    Sellis, T.K., Roussopoulos, N., Faloutsos, C.: The R+-Tree: A Dynamic Index for Multi-Dimensional Objects. In: Proceedings of the VLDB Conference, pp. 507–518 (1987)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Bonggi Jun
    • 1
  • Bonghee Hong
    • 1
  • Byunggu Yu
    • 2
  1. 1.Department of Computer EngineeringPusan National UniversityBusanRepublic of Korea
  2. 2.Department of Computer ScienceUniversity of WyomingLaramieU.S.A

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