A hybrid aggregation and compression technique for road network databases |
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Authors: | Ali Khoshgozaran Ali Khodaei Mehdi Sharifzadeh Cyrus Shahabi |
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Affiliation: | (1) Department of Computer Science, Information Laboratory (InfoLab), University of Southern California, Los Angeles, CA 90089-0781, USA |
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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.
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Keywords: | Multi-resolution compression Vector data Aggregation Road networks Spatial databases GIS |
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