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Indexing Fast Moving Objects for kNN Queries Based on Nearest Landmarks

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Abstract

With the rapid advancements in positioning technologies such as the Global Positioning System (GPS) and wireless communications, the tracking of continuously moving objects has become more convenient. However, this development poses new challenges to database technology since maintaining up-to-date information regarding the location of moving objects incurs an enormous amount of updates. Existing indexes can no longer keep up with the high update rate while providing speedy retrieval at the same time. This study aims to improve k nearest neighbor (kNN) query performance while reducing update costs. Our approach is based on an important observation that queries usually occur around certain places or spatial landmarks of interest, called reference points. We propose the Reference-Point-based tree (RP-tree), which is a two-layer index structure that indexes moving objects according to reference points. Experimental results show that the RP-tree achieves significant improvement over the TPR-tree.

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Authors and Affiliations

  1. Department of Computer Science, The National University of Singapore, Singapore, Singapore

    Dan Lin & Rui Zhang

  2. Department of Computer Science and Engineering, Fudan University, Shanghai, China

    Aoying Zhou

Authors
  1. Dan Lin
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  2. Rui Zhang
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  3. Aoying Zhou
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Correspondence to Dan Lin.

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Lin, D., Zhang, R. & Zhou, A. Indexing Fast Moving Objects for kNN Queries Based on Nearest Landmarks. Geoinformatica 10, 423–445 (2006). https://doi.org/10.1007/s10707-006-0341-9

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  • DOI: https://doi.org/10.1007/s10707-006-0341-9

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