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Design of an Efficient Parallel High-Dimensional Index Structure  

Park, Chun-Seo (Electronics and Telecommunications Research Institute)
Song, Seok-Il (Dept. of Information Communication Engineering, Chungbuk National University)
Sin, Jae-Ryong (Dept. of Information Communication Engineering, Chungbuk National University)
Yu, Jae-Su (Dept. of Information Communication Engineering, Chungbuk National University)
Publication Information
Journal of KIISE:Databases / v.29, no.1, 2002 , pp. 58-71 More about this Journal
Abstract
Generally, multi-dimensional data such as image and spatial data require large amount of storage space. There is a limit to store and manage those large amount of data in single workstation. If we manage the data on parallel computing environment which is being actively researched these days, we can get highly improved performance. In this paper, we propose a parallel high-dimensional index structure that exploits the parallelism of the parallel computing environment. The proposed index structure is nP(processor)-n$\times$mD(disk) architecture which is the hybrid type of nP-nD and lP-nD. Its node structure increases fan-out and reduces the height of a index tree. Also, A range search algorithm that maximizes I/O parallelism is devised, and it is applied to K-nearest neighbor queries. Through various experiments, it is shown that the proposed method outperforms other parallel index structures.
Keywords
parallel environment; high-dimensional index structure; range quer; K-nearest neighbor query;
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Times Cited By KSCI : 2  (Citation Analysis)
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