dc.citation.conferencePlace |
KO |
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dc.citation.endPage |
777 |
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dc.citation.startPage |
775 |
- |
dc.citation.title |
8th International Conference on Information and Communication Technology Convergence, ICTC 2017 |
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dc.contributor.author |
Park, Jung Kyu |
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dc.contributor.author |
Kim, Jaeho |
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dc.date.accessioned |
2023-12-19T18:08:34Z |
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dc.date.available |
2023-12-19T18:08:34Z |
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dc.date.created |
2018-08-10 |
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dc.date.issued |
2017-10-18 |
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dc.description.abstract |
In this paper, we attempt to manage GC overhead at the operating system level. In our approach, first, we use a machine learning technique to devise a GC detecting mechanism at the operating system level, and second, we show that by making use of this mechanism performance variance normally observed on SSDs can be reduced. We develop a GC-detector that detects garbage collection of SSDs and request TRIM operations to the SSD when GC is detected. Experimental results running the GC-detector show increase average bandwidth and low performance variance compared to when not using GC-detector. |
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dc.identifier.bibliographicCitation |
8th International Conference on Information and Communication Technology Convergence, ICTC 2017, pp.775 - 777 |
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dc.identifier.doi |
10.1109/ICTC.2017.8190778 |
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dc.identifier.scopusid |
2-s2.0-85046885779 |
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dc.identifier.uri |
https://scholarworks.unist.ac.kr/handle/201301/37686 |
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dc.identifier.url |
https://ieeexplore.ieee.org/document/8190778/ |
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dc.language |
영어 |
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dc.publisher |
ICTC |
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dc.title |
A method for reducing garbage collection overhead of SSD using machine learning algorithms |
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dc.type |
Conference Paper |
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dc.date.conferenceDate |
2017-10-18 |
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