The Self-relocating Index Scheme for Telematics GIS

  • Duksung Lim
  • Bonghee Hong
  • Daesoo Cho
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3833)


The history management of vehicles is important in telematics applications. To process queries for history data, trajectories, we generally use trajectory-preserving index schemes based on the trajectory preservation property. This property means that a leaf node only contains segments belonging to a particular trajectory, regardless of the spatiotemporal locality of segments. The sacrifice of spatiotemporal locality, however, causes the index to increase the dead space of MBBs of non-leaf nodes and the overlap between the MBBs of nodes. Therefore, an index scheme for trajectories shows good performance with trajectory-based queries, but not with coordinate-based queries, such as range queries. We propose a new index scheme that improves the performance of range queries without reducing performance with trajectory-based queries. In the new index scheme using the entry relocation strategy, two entries in different nodes are exchanged to minimize the dead spaces of the MBBs of the corresponding nodes.


Leaf Node Dead Space Range Query Target Node Index Scheme 
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.
    Zhu, H., Su, J., Ibarra, O.H.: Trajectory queries and octagons in moving object databases. In: Proc. of CIKM, pp. 413–421 (2002)Google Scholar
  2. 2.
    Tao, Y., Papadias, D.: MV3R-Tree: A Spatio-Temporal Access Method for Timestamp and Interval Queries. In: Proc. of VLDB, pp. 431–440 (2001)Google Scholar
  3. 3.
    Kumar, A., Tsotras, V.J., Faloutsos, C.: Designing Access Methods for Bitemporal Databases. TKDE 10(1), 1–20 (1998)Google Scholar
  4. 4.
    Guttman, A.: R-Trees: A Dynamic Index Structure for Spatial Searching. In: Proc. of SIGMOD, pp. 47–57 (1984)Google Scholar
  5. 5.
    Pfoser, D., Jensen, C.S., Theodoridis, Y.: Novel Approaches in Query Processing for Moving Object Trajectories. In: Proc. of VLDB, 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: Proc. of ACM SIGMOD, pp. 332–331 (1990)Google Scholar
  7. 7.
    Theodoridis, Y., Silva, R., Nascimento, M.: On the Generation of Spatiotemporal Datasets. In: Proc. of the 6th Int’l Symposium on Spatial Databases, pp. 147–164 (1999)Google Scholar
  8. 8.
    Worboys, M.F.: GIS: A Computing Perspective. Taylor & Francis, Abington (1995)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Duksung Lim
    • 1
  • Bonghee Hong
    • 2
  • Daesoo Cho
    • 3
  1. 1.Division of Computer Information TechnologyYeungjin CollegeTaeguKorea
  2. 2.Department of Computer EngineeringPusan National UniversityBusanKorea
  3. 3.School of Internet EngineeringDongseo UniversityBusanKorea

Personalised recommendations