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A Prediction-Based Cache Replacement Policy for Flash Storage

  • Van Nguyen Pham
  • , Mwasinga Lusungu Josh
  • , Duc Tai Le
  • , Sang Won Lee
  • , Hyunseung Choo

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Replacement algorithms in most disk-based operating systems focus on optimizing memory hit counts. For flash storage, such algorithms would incur high replacement costs in terms of time and energy consumption because writing dirty pages to flash memory is costly. Thus, this work proposes an intelligent approach for efficiently balancing the trade-off between cache replacement costs and cache hit rate performance. Our logistic regression-based approach predicts future reference probabilities of pages in the cache to identify candidate pages for eviction. To ascertain our superiority of the proposed system, we conducted rigorous simulations based on online transaction processing workload traces. Simulation results shows that our approach outperforms state-of-the-art methods.

Original languageEnglish
Title of host publicationFuture Data and Security Engineering. Big Data, Security and Privacy, Smart City and Industry 4.0 Applications - 8th International Conference, FDSE 2021, Proceedings
EditorsTran Khanh Dang, Josef Küng, Tai M. Chung, Makoto Takizawa
PublisherSpringer Science and Business Media Deutschland GmbH
Pages161-169
Number of pages9
ISBN (Print)9789811680618
DOIs
StatePublished - 2021
Event8th International Conference on Future Data and Security Engineering, FDSE 2021 - Virtual, Online
Duration: 24 Nov 202126 Nov 2021

Publication series

NameCommunications in Computer and Information Science
Volume1500 CCIS
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937

Conference

Conference8th International Conference on Future Data and Security Engineering, FDSE 2021
CityVirtual, Online
Period24/11/2126/11/21

Keywords

  • Cache replacement policy
  • Flash memory
  • Logistic regression
  • Machine learning

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