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dc.contributor.author Kim, Taejin -
dc.contributor.author Kim, Jihong -
dc.contributor.author Lee, Sungjin -
dc.date.accessioned 2018-02-05T04:12:29Z -
dc.date.available 2018-02-05T04:12:29Z -
dc.date.created 2018-01-18 -
dc.date.issued 2017-10 -
dc.identifier.issn 1598-1657 -
dc.identifier.uri http://hdl.handle.net/20.500.11750/5643 -
dc.description.abstract Data deduplication is an effective solution in improving the lifetime of flash-based solid-state drives (SSDs) by preventing redundant data from being written to flash memory. Existing deduplication techniques for SSDs, however, fail to fully eliminate potential redundant data because of their coarse-grained granularity. In this paper, a fine-grained deduplication technique for SSDs, called FineDedup, is proposed to improve the likelihood of eliminating redundant data. FineDedup also resolves technical difficulties caused by its finer granularity, i.e., increased memory requirement and read response time. The results show that FineDedup reduces the amount of written data by up to 24% over existing techniques with negligible. © 2017, Institute of Electronics Engineers of Korea. All rights reserved. -
dc.language English -
dc.publisher Institute of Electronics Engineers of Korea -
dc.title FineDedup: A fine-grained deduplication technique for extending lifetime of flash-based SSDs -
dc.type Article -
dc.identifier.doi 10.5573/JSTS.2017.17.4.648 -
dc.identifier.scopusid 2-s2.0-85032784709 -
dc.identifier.bibliographicCitation Journal of Semiconductor Technology and Science, v.17, no.5, pp.648 - 659 -
dc.identifier.kciid ART002276380 -
dc.description.isOpenAccess FALSE -
dc.subject.keywordAuthor NAND flash memory -
dc.subject.keywordAuthor solid state disks -
dc.subject.keywordAuthor data deduplication -
dc.subject.keywordAuthor lifespan -
dc.subject.keywordAuthor reliability -
dc.citation.endPage 659 -
dc.citation.number 5 -
dc.citation.startPage 648 -
dc.citation.title Journal of Semiconductor Technology and Science -
dc.citation.volume 17 -
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Department of Electrical Engineering and Computer Science Data-Intensive Computing Systems Laboratory 1. Journal Articles

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