A Forced Transplant Algorithm for Dynamic R-tree Implementation

  • Mingbo Zhang
  • Feng Lu
  • Changxiu Cheng
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4080)


Spatial access methods play a crucial role in spatial database management and manipulation. The R-tree and its variations have been widely accepted as some of the most efficient spatial indexing structures in recent years. However, neither considers storage utilization and the global optimization of a R-tree structure. Presented in this paper is a new optimization technique named forced transplant algorithm, which can improve the node storage utilization and optimize the R-tree overall structures at the same time. Our experiments show that the R-tree with our new optimization technique achieves almost 100% storage utilization and excellent query performance for all types of data.


Range Query Spatial Database Node Splitting Query Size Sibling Node 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Ang, C.H., Tan, T.C.: New Linear Node Splitting Algorithm for R-trees. In: Scholl, M.O., Voisard, A. (eds.) SSD 1997. LNCS, vol. 1262, pp. 339–349. Springer, Heidelberg (1997)Google Scholar
  2. 2.
    Beckmann, N., Kriegel, H.P., Schneider, R., Seeger, B.: The R*-Tree: An Efficient and Robust Access Method for Points and Rectangles. In: Proceedings of SIGMOD, Atlantic City, New Jersey, pp. 322–331 (1990)Google Scholar
  3. 3.
    Gaede, V., Gunther, O.: Multidimensional Access Methods. ACM Computing Surveys 30(2), 170–231 (1998)CrossRefGoogle Scholar
  4. 4.
    Garcia, Y., Lopez, M., Leutenegger, S.: A Greedy Algorithm for Bulk Loading R-trees. In: Proceedings of 6th ACM-GIS, Washington, DC, pp. 163–164 (1998)Google Scholar
  5. 5.
    Garcia, Y., Lopez, M., Leutenegger, S.: On Optimal Node Splitting for R-trees. In: Proceedings of 24th VLDB, New York, pp. 334–344 (1998)Google Scholar
  6. 6.
    Garcia, Y., Lopez, M., Leutenegger, S.: Post-optimization and Incremental Refinement of R-trees. In: Proceedings of ACM GIS 1999, Kansas City, USA, pp. 91–96 (1999)Google Scholar
  7. 7.
    Guttman, A.: R-trees: A Dynamic Index Structure for Spatial Searching. In: Proceedings of ACM SIGMOD, Boston, MA, pp. 47–57 (1984)Google Scholar
  8. 8.
    Huang, P.W., Lin, P.L., Lin, H.Y.: Optimizing Storage Utilization in R-tree Dynamic Index Structure for Spatial Databases. Journal of Systems and Software 55, 291–299 (2001)CrossRefGoogle Scholar
  9. 9.
    Kamel, I., Faloutsos, C.: Hilbert R-tree: an Improved R-tree Using Fractals. In: Proceedings of 20th VLDB, Santiago, Chile, pp. 500–509 (1994)Google Scholar
  10. 10.
    Kamel, I., Faloutsos, C.: On Packing R-trees. In: Proceedings of CIKM, Washington, DC, USA, pp. 490–499 (1993)Google Scholar
  11. 11.
    Leutenegger, S., Edgington, J.M., Lopez, M.A.: STR: a Simple and Efficient Algorithm for R-tree Packing. In: Proceedings of 13th IEEE ICDE, Birmingham, England, pp. 497–506 (1997)Google Scholar
  12. 12.
    Schreck, T., Chen, Z.: Branch Grafting Method for R-tree Implementation. Journal of Systems and Software 53, 83–93 (2000)CrossRefGoogle Scholar
  13. 13.
    Sellis, T., Roussopoulos, N., Faloutsos, C.: The R+-Tree: A Dynamic Index for Multi-Dimensional Objects. In: Proceedings of 13th VLDB, Brighton, England, pp. 507–518 (1987)Google Scholar
  14. 14.
    Theodoridis, Y., Sellis, T.: Optimization Issues in R-tree Construction. In: Nievergelt, J., Widmayer, P., Roos, T., Schek, H.-J. (eds.) IGIS 1994. LNCS, vol. 884, pp. 270–273. Springer, Heidelberg (1994)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Mingbo Zhang
    • 1
    • 2
  • Feng Lu
    • 1
  • Changxiu Cheng
    • 1
  1. 1.State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijingP.R. China
  2. 2.Department of Architecture EngineeringShandong University of TechnologyZiboP.R. China

Personalised recommendations