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Workload-Aware Page-Level Flash Translation Layer for NAND Flash-Based Storage Systems

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Cloud Computing and Security (ICCCS 2017)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10603))

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Abstract

Demand-based flash translation layer is an efficient page-level flash translation layer, which can effectively reduce the RAM (Random Access Memory) footprint of NAND flash-based storage systems. However, this demand-based flash translation layer does not consider the spatial locality of workloads. In this paper, a new workload-aware page-level flash translation layer is proposed for NAND flash-based storage systems. The proposed flash translation layer maintains three caches in RAM to cache mapping entries, which are the on-demand mapping entry cache, frequent mapping entry cache, and dirty mapping entry cache. Considering both temporal locality and spatial locality of workloads, the on-demand mapping entry cache is designed to store the on-demand mapping entries and sequential mapping entries. Considering the access frequency of workloads, the frequent mapping entry cache is designed to cache the most frequently accessed mapping entries. To decrease the number of updates to translation pages, the dirty mapping entry cache is designed to cache the dirty mapping entries and flush the dirty mapping entries belonging to the same translation page to NAND flash memory in a batch mode. The experimental results show that the proposed flash translation layer performs better than existing page-level flash translation layers.

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Acknowledgments

This work was supported by the National Natural Science Foundation of China under Grant Nos. 61502102, 61402109, and 61502103; Natural Science Foundation of Fujian Province, China under Grant Nos. 2016J05149, 2015J05120, and 2017J01737; Fujian Provincial Key Laboratory of Network Security and Cryptology Research Fund (Fujian Normal University) (No. 15008); and Distinguished Young Scientific Research Talents Plan in Universities of Fujian Province (2017).

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Authors and Affiliations

  1. College of Mathematics and Informatics, Fujian Normal University, Fuzhou, 350108, China

    Huibing Wang, Li Lin & Ruliang Xiao

  2. Fujian Engineering Research Center of Public Service Big Data Mining and Application, Fuzhou, 350108, China

    Mingwei Lin & Jinbo Xiong

Authors
  1. Huibing Wang
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  2. Mingwei Lin
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  3. Jinbo Xiong
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  4. Li Lin
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  5. Ruliang Xiao
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Corresponding author

Correspondence to Ruliang Xiao .

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Editors and Affiliations

  1. Nanjing University of Information Science and Technology, Nanjing, China

    Xingming Sun

  2. National Dong Hwa University, Shoufeng, Taiwan

    Han-Chieh Chao

  3. China Information Technology Security Evaluation Center, Nanjing, China

    Xingang You

  4. Department of Computer Science, Purdue University, West Lafayette, Indiana, USA

    Elisa Bertino

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Wang, H., Lin, M., Xiong, J., Lin, L., Xiao, R. (2017). Workload-Aware Page-Level Flash Translation Layer for NAND Flash-Based Storage Systems. In: Sun, X., Chao, HC., You, X., Bertino, E. (eds) Cloud Computing and Security. ICCCS 2017. Lecture Notes in Computer Science(), vol 10603. Springer, Cham. https://doi.org/10.1007/978-3-319-68542-7_49

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  • DOI: https://doi.org/10.1007/978-3-319-68542-7_49

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-68541-0

  • Online ISBN: 978-3-319-68542-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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