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Constrained Shortest Path Computation

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Advances in Spatial and Temporal Databases (SSTD 2005)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 3633))

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Abstract

This paper proposes and solves a-autonomy and k-stops shortest path problems in large spatial databases. Given a source s and a destination d, an a-autonomy query retrieves a sequence of data points connecting s and d, such that the distance between any two consecutive points in the path is not greater than a. A k-stops query retrieves a sequence that contains exactly k intermediate data points. In both cases our aim is to compute the shortest path subject to these constraints. Assuming that the dataset is indexed by a data-partitioning method, the proposed techniques initially compute a sub-optimal path by utilizing the Euclidean distance information provided by the index. The length of the retrieved path is used to prune the search space, filtering out large parts of the input dataset. In a final step, the optimal (a-autonomy or k-stops) path is computed (using only the non-eliminated data points) by an exact algorithm. We discuss several processing methods for both problems, and evaluate their efficiency through extensive experiments.

Supported by grant HKUST 6180/03E from Hong Kong RGC.

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Author information

Authors and Affiliations

  1. Electrical and Computer Engineering Department, National Technical University of Athens, Greece

    Manolis Terrovitis

  2. Computer Science Department, Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong

    Spiridon Bakiras, Dimitris Papadias & Kyriakos Mouratidis

Authors
  1. Manolis Terrovitis
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  2. Spiridon Bakiras
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  3. Dimitris Papadias
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  4. Kyriakos Mouratidis
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Editor information

Editors and Affiliations

  1. Institute of Computing, CP 6176, University of Campinas, 13084-971, Campinas, Brazil

    Claudia Bauzer Medeiros

  2. National Center for Geographic Information and Analysis and Department of Spatial Information Science and Engineering, University of Maine, Boardman Hall, ME 04469-5711, Orono, USA

    Max J. Egenhofer

  3. Purdue University,  

    Elisa Bertino

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© 2005 Springer-Verlag Berlin Heidelberg

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Terrovitis, M., Bakiras, S., Papadias, D., Mouratidis, K. (2005). Constrained Shortest Path Computation. In: Bauzer Medeiros, C., Egenhofer, M.J., Bertino, E. (eds) Advances in Spatial and Temporal Databases. SSTD 2005. Lecture Notes in Computer Science, vol 3633. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11535331_11

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  • DOI: https://doi.org/10.1007/11535331_11

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28127-6

  • Online ISBN: 978-3-540-31904-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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