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An Efficient Compression Method for Multi-dimensional Index Structures  

조형주 (한국과학기술원 전자전산학과)
정진완 (한국과학기술원 전자전산학과)
Publication Information
Journal of KIISE:Databases / v.30, no.5, 2003 , pp. 429-437 More about this Journal
Abstract
Over the last decades, improvements in CPU speed have greatly exceeded those in memory and disk speeds by orders of magnitude and this enabled the use of compression techniques to reduce the database size as well as the query cost. Although compression techniques are employed in various database researches, there is little work on compressing multi-dimensional index structures. In this paper, we propose an efficient compression method called the hybrid encoding method (HEM) that is tailored to multi-dimensional indexing structures. The HEM compression significantly reduces the query cost and the size of multi-dimensional index structures. Through mathematical analyses and extensive experiments, we show that the HEM compression outperforms an existing method in terms of the index size and the query cost.
Keywords
Multi-dimensional index structure; Compression method; R'-tree;
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