Skip to main content
SpringerLink
Log in

VTPR-Tree: An Efficient Indexing Method for Moving Objects with Frequent Updates

  • Conference paper
Advances in Conceptual Modeling - Theory and Practice (ER 2006)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 4231))

Included in the following conference series:

Abstract

Moving object databases are required to support queries on a large number of continuous moving objects. Indexes for moving objects must support both query and update operations efficiently. In previous work TPR-tree is the most popular indexing method for the future predicted position, but its frequent updates performance is very poor. In this paper we propose a novel indexing method, called VTPR-tree, for predicted trajectory of moving objects. VTPR-tree takes into account both the velocity and space distribution of moving objects. First the velocity domain is split, and moving objects are classified into different velocity buckets by their velocities, thus objects in one bucket have similar velocities. Then we use an improved TPR-tree structure to index objects in each bucket. VTPR-tree is supplemented by a hash index on IDs of moving objects to support frequent updates. Also an extended bottom-up update algorithm is developed for VTPR-tree, thus having a good dynamic update performance and concurrency. Experimental results show that the update and query performance of VTPR-tree outperforms the TPR*-tree.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Jensen, C.S., Lin, D., Ooi, B.C.: Query and Update Efficient B+-tree Based Indexing of Moving Objects. In: Proc. VLDB Conf. (2004)

    Google Scholar 

  2. Saltenis, S., Jensen, C.S., et al.: Indexing the Positions of Continuously Moving Objects. In: Proc. SIGMOD Conf., pp. 331–342 (2000)

    Google Scholar 

  3. Mokbel, M.F., Ghanem, T.M.: Spatio-temporal Access Methods. IEEE Data Engineering Bulletin (2003)

    Google Scholar 

  4. Tao, Y., Papadias, D., Sun, J.: The TPR*-Tree: An Optimized Spatio-Temporal Access Method for Predictive Queries. In: Proc. VLDB Conf., pp. 790–801 (2003)

    Google Scholar 

  5. Lee, M., Hsu, W., Jensen, C., Cui, B., Teo, K.: Supporting Frequent Updates in R-Trees: A Bottom-Up Approach. In: Proc. VLDB Conf. (2003)

    Google Scholar 

  6. Lin, B., Su, J.: On bulk loading TPR-tree. In: Proc. IEEE Conf. Mobile Data Management, pp. 114–124 (2004)

    Google Scholar 

  7. Brinkhoff, T.: A Framework for Generating Network-Based Moving Objects. GeoInformatica 6(2), 153–180 (2002)

    Article  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Electronic Science and Engineering, National University of Defense Technology, China

    Wei Liao, Guifen Tang, Ning Jing & Zhinong Zhong

Authors
  1. Wei Liao
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Guifen Tang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ning Jing
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Zhinong Zhong
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Flinders University, Adelaide, Australia

    John F. Roddick

  2. iSOCO, Spain

    V. Richard Benjamins

  3. CEDRIC-CNAM, France

    Samira Si-said Cherfi

  4. University of Cincinnati, USA

    Roger Chiang

  5. Naval Academy Research Institute, Brest Naval, France

    Christophe Claramunt

  6. Department of Computer Science and Engineering, The University of Texas at Arlington, USA

    Ramez A. Elmasri

  7. Dipartimento di Elettronica, Informatica e Sistemistica, Alma Mater Studiorum – Università di Bologna, Italy

    Fabio Grandi

  8. Drexel University, USA

    Hyoil Han

  9. E-Business and Web Science Research Group, Bundeswehr University Munich, Germany

    Martin Hepp

  10. University of Patras, Argolidos 40-42, 153-44, Gerakas Attikis, Greece

    Miltiadis D. Lytras

  11. University of Manitoba, Canada

    Vojislav B. Mišić

  12. Ghent University, Belgium

    Geert Poels

  13. College of Information Science and Technology, Drexel University, USA

    Il-Yeol Song

  14. Department of Software and Computing Systems, University of Alicante, Spain

    Juan Trujillo

  15. EPFL, Switzerland

    Christelle Vangenot

Rights and permissions

Reprints and permissions

Copyright information

© 2006 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Liao, W., Tang, G., Jing, N., Zhong, Z. (2006). VTPR-Tree: An Efficient Indexing Method for Moving Objects with Frequent Updates. In: Roddick, J.F., et al. Advances in Conceptual Modeling - Theory and Practice. ER 2006. Lecture Notes in Computer Science, vol 4231. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11908883_15

Download citation

  • DOI: https://doi.org/10.1007/11908883_15

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-47703-7

  • Online ISBN: 978-3-540-47704-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation