Indexing of Moving Objects on Road Network Using Composite Structure

  • Jun Feng
  • Jiamin Lu
  • Yuelong Zhu
  • Naoto Mukai
  • Toyohide Watanabe
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4693)

Abstract

Composite structures are proposed to index moving objects in road network. However, there are many problems for indexing moving objects for current and forecasting queries on road network, efficiently. This paper proposes methods for improving such kinds of structure, and gives a new structure R-TPR± Tree. Evaluation shows the new structure outperforms that of R-TPR-tree in query validity and disk access.

Keywords

Road Network Composite Structure Leaf Node Road Segment Vehicle Speed 
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.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Chung, J.D., Peak, O.H., Lee, J.W., Ryu, K.H.: Temporal pattern mining of moving objects for location-based services. In: Proc. Int’l Conf. Database and Expert Systems Applications (2002)Google Scholar
  2. 2.
    Hadjieleftheriou, M., Kollios, G., Tsotras, V., Gunopulos, D.: Efficient indexing of spatiotemporal objects. In: Proc. of the 8th Int’l Conference on Extending Database Technology, pp. 251–268 (2002)Google Scholar
  3. 3.
    Kollios, G., Gunopulos, D., Tsotras, V., Delis, A., Hadjieleftheriou, M.: Indexing animated objects using spatiotemporal access methods. IEEE TKDE 13(5), 758–777 (2001)Google Scholar
  4. 4.
    Lazaridis, I., Porkaew, K., Mehrotra, S.: Dynamic queries over mobile objects. In: Proc. of ACM-SIGMOD Conference on the Management of Data, pp. 269–286. ACM Press, New York (2002)Google Scholar
  5. 5.
    Pfoser, D., Jensen, C.S.: Indexing of network constrained moving objects. In: Proc. of GIS 2003, pp. 25–32 (2003)Google Scholar
  6. 6.
    Agarwal, P.K., Arge, L., Erickson, J.: Indexing moving points. In: Proc. of the 19th ACM Symposium on Principals of Database Systems, pp. 175–186. ACM Press, New York (2000)Google Scholar
  7. 7.
    Pfoser, D.: Indexing the trajectories of moving objects. IEEE Data Engineering Bulletin (2), 3–9 (2002)Google Scholar
  8. 8.
    Saltenis, S., Jensen, C.S., Leutenegger, S., Lopez, M.: Indexing the positions of continuously moving objects. In: Proc. of ACM-SIGMOD Conference on Management of Data, pp. 331–342. ACM Press, New York (2000)Google Scholar
  9. 9.
    Saltenis, S., Jensen, C.S.: Indexing of moving objects for location-based services. In: Proc. of the 18th Int’l Conference on Data Engineering, pp. 463–472 (2002)Google Scholar
  10. 10.
    Sistla, A.P., Wolfson, O., Chamberlain, S., Dao, S.: Modeling and querying moving objects. In: IEEE Int’l Conf. on Data Engineering, pp. 422–432. IEEE Computer Society Press, Los Alamitos (1997)Google Scholar
  11. 11.
    Civilis, A., Jensen, C.S., Pakalnis, S.: Techniques for efficient road-network-based tracking of moving objects. IEEE Trans. on Knowledeg and Data Engineering 17(5), 698–712 (2005)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Jun Feng
    • 1
  • Jiamin Lu
    • 1
  • Yuelong Zhu
    • 1
  • Naoto Mukai
    • 2
  • Toyohide Watanabe
    • 2
  1. 1.Hohai University, Nanjing, Jiangsu 210098China
  2. 2.Nagoya University, Nagoya, Aichi 464-8603Japan

Personalised recommendations