Skip to main content
SpringerLink
Log in

New Query Processing Algorithms for Range and k-NN Search in Spatial Network Databases

  • 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:

  • 1398 Accesses

Abstract

In this paper, we design the architecture of disk-based data structures for spatial network databases (SNDB). Based on this architecture, we propose new query processing algorithms for range search and k nearest neighbors (k-NN) search, depending on the density of point of interests (POIs) in the spatial network. For this, we effectively combine Euclidean restriction and the network expansion techniques according to the density of POIs. In addition, our two query processing algorithms can reduce the computation time of network distance between a pair of nodes and the number of disk I/Os required for accessing nodes by using maintaining the shortest network distances of all the nodes in the spatial network. It is shown that our range query processing algorithm achieves about up to one order of magnitude better performance than the existing range query processing algorithm, such as RER and RNE [1]. In addition, our k-NN query processing algorithm achieves about up to 170~400% performance improvements over the existing network expansion k-NN algorithm, called INE, while it shows about up to one order of magnitude better performance than the existing Euclidean restriction k-NN algorithm, called IER [1].

This work is financially supported by the Ministry of Education and Human Resources Development(MOE), the Ministry of Commerce, Industry and Energy(MOCIE) and the Ministry of Labor(MOLAB) though the fostering project of the Lab of Excellency.

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. Papadias, D., Zhang, J., Mamoulis, N., Tao, Y.: Query Processing in Spatial Network Databases. In: Proc. of VLDB, pp. 802–813 (2003)

    Google Scholar 

  2. Shekhar, S., et al.: Spatial Databases – Accomplishments and Research Needs. IEEE Tran. on Knowledge and Data Engineering 11(1), 45–55 (1999)

    Article  MathSciNet  Google Scholar 

  3. Speicys, L., Jensen, C.S., Kligys, A.: Computational Data Modeling for Network-Constrained Moving Objects. In: Proc. of ACM GIS, pp. 118–125 (2003)

    Google Scholar 

  4. Pfoser, D., Jensen, C.S.: Indexing of Network Constrained Moving Objects. In: Proc. of ACM GIS, pp. 25–32 (2003)

    Google Scholar 

  5. Jensen, C.S., Kolář, J., Pedersen, T.B., Timko, I.: Nearest Neighbor Queries in Road Networks. In: Proc. of ACM GIS, pp. 1–8 (2003)

    Google Scholar 

  6. Kolahdouzan, M., Shahabi, C.: Voronoi-Based K Nearest Neighbor Querying in Spatial Networks. In: Proc. of VLDB, pp. 840–851 (2004)

    Google Scholar 

  7. Huang, X., Jensen, C.S., Saltenis, S.: The islands Approach to Nearest Neighbors Search for Spatial Network Databases. In: Bauzer Medeiros, C., Egenhofer, M.J., Bertino, E. (eds.) SSTD 2005. LNCS, vol. 3633, pp. 73–90. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  8. Seidl, T., Roussopoulos, N., Faloutsos, C.: The R+-tree: a Dynamic Index for Multi-Dimensional Objects. In: Proc. of VLDB (1987)

    Google Scholar 

  9. Jing, N., Huang, Y.-W., Rundensteiner, E.A.: Hierarchical Encoded Path Views for Path Query Processing: An Optimal Model and Its Performance Evaluation. IEEE Tran. on Knowledge and data Engineering 10(3), 409–432 (1998)

    Article  Google Scholar 

  10. Seidl, T., Kriegel, H.: Optimal Multi-step k-Nearest Neighbor Search. In: Proc. of ACM SIGMOD (1998)

    Google Scholar 

  11. San Francisco Bay map, http://www.fh-oow.de/institute/iapg/personen/brinkhoff/generator/

  12. 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. Dept. of Computer Engineering, Chonbuk National Univ., Chonju, Chonbuk, 561-756, South Korea

    Jae-Woo Chang, Yong-Ki Kim, Sang-Mi Kim & Young-Chang Kim

Authors
  1. Jae-Woo Chang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yong-Ki Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Sang-Mi Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Young-Chang Kim
    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

Chang, JW., Kim, YK., Kim, SM., Kim, YC. (2006). New Query Processing Algorithms for Range and k-NN Search in Spatial Network Databases. 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_16

Download citation

  • DOI: https://doi.org/10.1007/11908883_16

  • 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