Semantic caching for multiresolution spatial query processing in mobile environments

  • Authors:

  • Sai Sun;Xiaofang Zhou;Heng Tao Shen

  • Affiliations:

  • School of Information Technology and Electrical Engineering, The University of Queensland, Australia;School of Information Technology and Electrical Engineering, The University of Queensland, Australia;School of Information Technology and Electrical Engineering, The University of Queensland, Australia

  • Venue:
  • SSTD'05 Proceedings of the 9th international conference on Advances in Spatial and Temporal Databases
  • Year:
  • 2005

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Abstract

Spatial data are particularly useful in mobile environments. However, due to the low bandwidth of most wireless networks, developing large spatial database applications becomes a challenging process. In this paper, we provide the first attempt to combine two important techniques, multiresolution spatial data structure and semantic caching, towards efficient spatial query processing in mobile environments. Based on the study of the characteristics of multiresolution spatial data (MSD) and multiresolution spatial query, we propose a new semantic caching model called Multiresolution Semantic Caching (MSC) for caching MSD in mobile environments. MSC enriches the traditional three-category query processing in semantic cache to five categories, thus improving the performance in three ways: 1) a reduction in the amount and complexity of the remainder queries; 2) the redundant transmission of spatial data already residing in a cache is avoided; 3) a provision for satisfactory answers before 100% query results have been transmitted to the client side. Our extensive experiments on a very large and complex real spatial database show that MSC outperforms the traditional semantic caching models significantly.