Energy-Conserving Air Indexes for Nearest Neighbor Search

  • Baihua Zheng
  • Jianliang Xu
  • Wang-Chien Lee
  • Dik Lun Lee
Conference paper

DOI: 10.1007/978-3-540-24741-8_5

Part of the Lecture Notes in Computer Science book series (LNCS, volume 2992)
Cite this paper as:
Zheng B., Xu J., Lee WC., Lee D.L. (2004) Energy-Conserving Air Indexes for Nearest Neighbor Search. In: Bertino E. et al. (eds) Advances in Database Technology - EDBT 2004. EDBT 2004. Lecture Notes in Computer Science, vol 2992. Springer, Berlin, Heidelberg

Abstract

A location-based service (LBS) provides information based on the location information specified in a query. Nearest-neighbor (NN) search is an important class of queries supported in LBSs. This paper studies energy-conserving air indexes for NN search in a wireless broadcast environment. Linear access requirement of wireless broadcast weakens the performance of existing search algorithms designed for traditional spatial database. In this paper, we propose a new energy-conserving index, called grid-partition index, which enables a single linear scan of the index for any NN queries. The idea is to partition the search space for NN queries into grid cells and index all the objects that are potential nearest neighbors of a query point in each grid cell. Three grid partition schemes are proposed for the grid-partition index. Performance of the proposed grid-partition indexes and two representative traditional indexes (enhanced for wireless broadcast) is evaluated using both synthetic and real data. The result shows that the grid-partition index substantially outperforms the traditional indexes.

Keywords

mobile computing location-based services energy-conserving index nearest-neighbor search wireless broadcast 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Baihua Zheng
    • 1
  • Jianliang Xu
    • 2
  • Wang-Chien Lee
    • 3
  • Dik Lun Lee
    • 4
  1. 1.Singapore Management UniversitySingapore
  2. 2.Hong Kong Baptist UniversityHong Kong
  3. 3.Penn State UniversityUniversity ParkUSA
  4. 4.Hong Kong University of Science and TechnologyHong Kong

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