A hybrid aggregation and compression technique for road network databases

  • Authors:

  • Ali Khoshgozaran;Ali Khodaei;Mehdi Sharifzadeh;Cyrus Shahabi

  • Affiliations:

  • University of Southern California, Department of Computer Science, Information Laboratory (InfoLab), 90089-0781, Los Angeles, CA, USA;University of Southern California, Department of Computer Science, Information Laboratory (InfoLab), 90089-0781, Los Angeles, CA, USA;University of Southern California, Department of Computer Science, Information Laboratory (InfoLab), 90089-0781, Los Angeles, CA, USA;University of Southern California, Department of Computer Science, Information Laboratory (InfoLab), 90089-0781, Los Angeles, CA, USA

  • Venue:
  • Knowledge and Information Systems
  • Year:
  • 2008

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Abstract

Vector data and in particular road networks are being queried, hosted and processed in many application domains such as in mobile computing. Many client systems such as PDAs would prefer to receive the query results in unrasterized format without introducing an overhead on overall system performance and result size. While several general vector data compression schemes have been studied by different communities, we propose a novel approach in vector data compression which is easily integrated within a geospatial query processing system. It uses line aggregation to reduce the number of relevant tuples and Huffman compression to achieve a multi-resolution compressed representation of a road network database. Our experiments performed on an end-to-end prototype verify that our approach exhibits fast query processing on both client and server sides as well as high compression ratio.