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A New Continuous Nearest Neighbor Technique for Query Processing on Mobile Environments

  • Conference paper
Computational Science and Its Applications – ICCSA 2005 (ICCSA 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3481))

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Abstract

Recently, as growing of interest for LBS(location-based services) techniques, researches for NN(nearest neighbor) query which has often been used in LBS, are progressed variously. However, the results of conventional NN query processing techniques may be invalidated as the query and data objects move. To solve these problems, in this paper we propose a new nearest neighbor query processing technique, called CTNN, which is possible to meet continuous query processing for mobile objects. In order to evaluate the proposed techniques, we experimented with various datasets and experimental results showed that the proposed techniques can find accurately NN objects. The proposed techniques can be applied to navigation system, traffic control system, distribution information system, etc., and specially are most suitable when both data and query are mobile objects.

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References

  1. Roussopoulos, N., Kelley, S., Vincent, F.: Nearest Neighbor Queries. In: SIGMOD Conference 1995, pp. 71–79 (1995)

    Google Scholar 

  2. Yu, C., Ooi, B.C., Tan, K.-L., Jagadish, H.V.: Indexing the Distance: An Efficient Method to KNN Processing. In: VLDB 2001, pp. 421–430 (2001)

    Google Scholar 

  3. King, I., Yang, C.: The ANN-tree: An Index for Efficient Approximate Nearest Neighbor Search, DASFAA, pp.174-181 (2001)

    Google Scholar 

  4. Volmer, S.: Fast Approximate Nearest Neighbor Queries in Metric Feature Spaces by Buoy-Indexing. in: VISUAL 2002, pp. 36–49 (2002)

    Google Scholar 

  5. Kollios, G., Gunopulos, D., Tsotras, V.J.: Nearest Neighbor Queries in a Mobile Environment. Spatio-Temporal Database Management, 119–134 (1999)

    Google Scholar 

  6. Benetis, R., Jensen, C.S., Karciauskas, G., Saltenis, S.: Nearest Neighbor and Reverse Nearest Neighbor Queries for Moving Objects. In: IDEAS 2002, pp. 44–53 (2002)

    Google Scholar 

  7. Saltenis, S., Jensen, C.S.: Indexing the Position of Continuously Moving Object. In: SIGMOD Conference 2000, pp. 331–342 (2000)

    Google Scholar 

  8. Tao, Y., Papadias, D.: Spatial Queries in Dynamic Environments. In: TODS (2003)

    Google Scholar 

  9. de Berg, M., van Kreveld, M., Overmars, M., Schwarzkopf, O.: Computational Geometry Algorithms and Applications. Springer, Heidelberg (1997)

    MATH  Google Scholar 

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Author information

Authors and Affiliations

  1. Database Laboratory, Chungbuk National University, Korea

    Jeong Hee Chi, Sang Ho Kim & Keun Ho Ryu

Authors
  1. Jeong Hee Chi
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  2. Sang Ho Kim
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  3. Keun Ho Ryu
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Editor information

Editors and Affiliations

  1. Department of Mathematics and Computer Science, University of Perugia, via Vanvitelli, 1, I-06123, Perugia, Italy

    Osvaldo Gervasi

  2. Department of Computer Science, University of Calgary, 2500 University Drive N.W., T2N 1N4, Calgary, AB, Canada

    Marina L. Gavrilova

  3. William Norris Professor, Head of the Computer Science and Engineering Department, University of Minnesota, USA

    Vipin Kumar

  4. Department of Chemistry, University of Perugia, Via Elce di Sotto, 8, P.O. Box, I-06123, Perugia, Italy

    Antonio Laganà

  5. Institute of High Performance Computing, IHCP, 1 Science Park Road, 01-01 The Capricorn, Singapore Science Park II, 117528, Singapore

    Heow Pueh Lee

  6. School of Computing, Soongsil University, Seoul, Korea

    Youngsong Mun

  7. Clayton School of IT, Monash University, 3800, Clayton, Australia

    David Taniar

  8. OptimaNumerics Ltd, P.O. Box, Belfast, United Kingdom

    Chih Jeng Kenneth Tan

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© 2005 Springer-Verlag Berlin Heidelberg

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Chi, J.H., Kim, S.H., Ryu, K.H. (2005). A New Continuous Nearest Neighbor Technique for Query Processing on Mobile Environments. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2005. ICCSA 2005. Lecture Notes in Computer Science, vol 3481. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11424826_105

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  • DOI: https://doi.org/10.1007/11424826_105

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-25861-2

  • Online ISBN: 978-3-540-32044-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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