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Intelligent Data Prefetching for Hybrid Flash-Disk Storage Using Sequential Pattern Mining Technique

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3 Author(s)
Un-Keun Yoon ; Sch. of Electr. & Comput. Eng., Univ. of Seoul, Seoul, South Korea ; Han-joon Kim ; Jae-young Chang

This paper presents an intelligent prefetching technique that significantly improves hybrid flash-disk storage, a combination of hard disk and flash memory. As a prefetching strategy, we adopt the sequential pattern mining, a variant of association rule mining. Our goal is to minimize overall I/O processing time of hybrid storage systems with using the Fully Associated Sector Translation (FAST) technique that is known to be the best mapping method in managing flash memory. It is very significant to further enhance the system performance of the hybrid storage when applying FAST to it. In our work, the hybrid storage uses the flash memory as a cache space to improve system performance. With this memory architecture, the proposed method is to prefetch objects onto `prefetching' blocks in the level of both file and block in hybrid storage systems. Through extensive experiments using real UCC data and synthetic data, we show that the proposed prefetching method outperforms conventional ones.

Published in:

Computer and Information Science (ICIS), 2010 IEEE/ACIS 9th International Conference on

Date of Conference:

18-20 Aug. 2010

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