A hybrid aggregation and compression technique for road network databases
Knowledge and Information Systems
Location privacy in geospatial decision-making
DNIS'07 Proceedings of the 5th international conference on Databases in networked information systems
Optimal algorithm for lossy vector data compression
ICIAR'07 Proceedings of the 4th international conference on Image Analysis and Recognition
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Vector data and in particular road networks are being queried, hosted, and processed by many application domains such as mobile computing. However, many hosting/ processing clients such as PDAs cannot afford this bulky data due to their storage and transmission limitations. In particular, the result of a typical spatial query such as window query is too huge for a transfer-and-store scenario. 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 empirical results verify that our approach exhibits both a high compression ratio and fast query processing.