FRM: Foundation-policy Recommendation Model to Improve the Performance of NAND Flash Memory (FRM: NAND 플래시 메모리의 성능 향상을 위한 기본 관리 정책 제안 모델)

Won Ho Lee (이원호); Jun-Hyeong Choi (최준형); Jong Wook Kwak (곽종욱)

doi:10.9708/jksci.2023.28.08.001

FRM: Foundation-policy Recommendation Model to Improve the Performance of NAND Flash Memory

Journal of The Korea Society of Computer and Information
Abbr : JKSCI
2023, 28(8), pp.1-10
DOI : 10.9708/jksci.2023.28.08.001
Publisher : The Korean Society Of Computer And Information
Research Area : Engineering > Computer Science
Received : June 28, 2023
Accepted : July 24, 2023
Published : August 31, 2023

Won Ho Lee ¹, Jun-Hyeong Choi ², Jong Wook Kwak ³

¹(주)엔피니티7
²(재)경북IT융합산업기술원
³영남대학교

Accredited

ABSTRACT

Recently, NAND flash memories have replaced magnetic disks due to non-volatility, high capacity and high resistance, in various computer systems but it has disadvantages which are the limited lifespan and imbalanced operation latency. Therefore, many page replacement policies have been studied to overcome the disadvantages of NAND flash memories. Although it is clear that these policies reflect execution characteristics of various environments and applications, researches on the foundation-policy decision for disk buffer management are insufficient. Thus, in this paper, we propose a foundation-policy recommendation model, called FRM for effectively utilizing NAND flash memories. FRM proposes a suitable page replacement policy by classifying and analyzing characteristics of workloads through machine learning. As an implementation case, we introduce FRM with a disk buffer management policy and in experiment results, prediction accuracy and weighted average of FRM shows 92.85% and 88.97%, by training dataset and validation dataset for foundation disk buffer management policy, respectively.

KEYWORDS

page replacement policy, disk buffer, NAND flash memory, workload analysis, machine learning

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* References for papers published after 2023 are currently being built.

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KJCKorea
Journal Central

Journal of The Korea Society of Computer and Information 2023 KCI Impact Factor : 0.65

FRM: Foundation-policy Recommendation Model to Improve the Performance of NAND Flash Memory

ABSTRACT

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Citation status

* References for papers published after 2023 are currently being built.

Journal of The Korea Society of Computer and Information 2023 KCI Impact Factor : 0.65

FRM: Foundation-policy Recommendation Model to Improve the Performance of NAND Flash Memory

ABSTRACT

KEYWORDS

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* References for papers published after 2023 are currently being built.