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Unifying buffer replacement and prefetching with data migration for heterogeneous storage devices
- Title
- Unifying buffer replacement and prefetching with data migration for heterogeneous storage devices
- Authors
- Lee S.; Koh K.; Bahn H.
- Ewha Authors
- 반효경
- SCOPUS Author ID
- 반효경
- Issue Date
- 2010
- Journal Title
- Proceedings of the International Conference on Parallel and Distributed Systems - ICPADS
- ISSN
- 1521-9097
- Citation
- Proceedings of the International Conference on Parallel and Distributed Systems - ICPADS, pp. 330 - 337
- Indexed
- SCOPUS
- Document Type
- Conference Paper
- Abstract
- With the good properties of NAND flash memory such as small size, shock resistance, and low-power consumption, large capacity SSD (Solid State Disk) is anticipated to replace hard disk in high-end systems. However, the cost of NAND flash memory is still high to substitute for hard disk entirely. Using hard disk and NAND flash memory together as secondary storage is an alternative solution to provide relatively low response time, large capacity, and reasonable cost. In this paper, we present a new buffer cache management scheme with data migration that is optimized to use both NAND flash memory and hard disk together as secondary storage. The proposed scheme has three salient features. First, it detects I/O access patterns from each storage, and allocates the buffer cache space for each pattern by computing marginal gain adaptively considering the I/O cost of storage. Second, it prefetches data selectively according to their access pattern and storage devices. Third, it moves the evicted data from the buffer cache to hard disk or NAND flash memory considering the access patterns of block references on the reclamation. Trace-driven simulations show that the proposed scheme improves the I/O performance significantly. It enhances the buffer cache hit ratio by up to 29.9% and reduces the total I/O elapsed time by up to 49.5% compared to the well-acknowledged UBM scheme. © 2010 IEEE.
- DOI
- 10.1109/ICPADS.2010.103
- ISBN
- 9780769543079
- Appears in Collections:
- 인공지능대학 > 컴퓨터공학과 > Journal papers
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