Time-constrained persistent deletion for key-value store engine on ZNS SSD

被引:0
作者
Nie, Shiqiang [1 ]
Lei, Tong [1 ]
Niu, Jie [1 ]
Hu, Qihan [1 ]
Liu, Song [1 ]
Wu, Weiguo [1 ]
机构
[1] Xi An Jiao Tong Univ, Sch Comp Sci & Technol, Xian 710049, Shaanxi, Peoples R China
来源
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE | 2025年 / 164卷
基金
中国国家自然科学基金;
关键词
ZNS SSD; Data deletion; NAND flash; LSM-tree; Key-value store;
D O I
10.1016/j.future.2024.107598
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
The inherent out-of-place update characteristic of the Log-Structured Merge tree (LSM tree) cannot guarantee persistent deletion within a specific time window, leading to potential data privacy and security issues. Existing solutions like Lethe-Fade ensure time-constrained persistent deletion but introduce considerable write overhead, worsening the write amplification issue, particularly for key-value stores on ZNS SSD. To address this problem, we propose a zone-aware persistent deletion scheme for key-value store engines. Targeting mitigating the write amplification induced by level compaction, we design an adaptive SSTable selection strategy for each level in the LSM tree. Additionally, as the SSTable with deletion records would become invalid after the persistent deletion timer reaches its threshold, we design a tombstone-aware zone allocation strategy to reduce the data migration induced by garbage collection. In further, we optimize the victim zone selection in GC to reduce the invalid migration of tombstone files. Experimental results demonstrate that our scheme effectively ensures that most outdated physical versions are deleted before reaching the persistent deletion time threshold. When deleting 10% of keys in the key-value store engine, this scheme reduces write amplification by 74.7% and the garbage collection-induced write by 87.3% compared to the Lethe-Fade scheme.
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页数:10
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共 34 条
  • [11] Hwang JY, 2024, PROCEEDINGS OF THE 2024 USENIX ANNUAL TECHNICAL CONFERENCE, ATC 2024, P173
  • [12] Lakshman Avinash, 2010, Operating Systems Review, V44, P35, DOI 10.1145/1773912.1773922
  • [13] Lee Sangjin, 2022, SIGMOD/PODS '22: Proceedings of the 2022 International Conference on Management of Data, P988, DOI 10.1145/3514221.3526188
  • [14] LifetimeKV: Narrowing the Lifetime Gap of SSTs in LSMT-based KV Stores for ZNS SSDs
    Liu, Biyong
    Xia, Yuan
    Wei, Xueliang
    Tong, Wei
    [J]. 2023 IEEE 41ST INTERNATIONAL CONFERENCE ON COMPUTER DESIGN, ICCD, 2023, : 300 - 307
  • [15] Hi-ZNS: High Space Efficiency and Zero-Copy LSM-tree-based Stores on ZNS SSDs
    Liu, Renping
    Chen, Junhua
    Chen, Peng
    Long, Linbo
    Xiong, Anping
    Liu, Duo
    [J]. 53RD INTERNATIONAL CONFERENCE ON PARALLEL PROCESSING, ICPP 2024, 2024, : 1217 - 1226
  • [16] WA-Zone: Wear-Aware Zone Management Optimization for LSM-Tree on ZNS SSDs
    Long, Linbo
    He, Shuiyong
    Shen, Jingcheng
    Liu, Renping
    Tan, Zhenhua
    Gao, Congming
    Liu, Duo
    Zhong, Kan
    Jiang, Yi
    [J]. ACM TRANSACTIONS ON ARCHITECTURE AND CODE OPTIMIZATION, 2024, 21 (01)
  • [17] WiscKey: Separating Keys from Values in SSD-Conscious Storage
    Lu, Lanyue
    Pillai, Thanumalayan Sankaranarayana
    Gopalakrishnan, Hariharan
    Arpaci-Dusseau, Andrea C.
    Arpaci-Dusseau, Remzi H.
    [J]. ACM TRANSACTIONS ON STORAGE, 2017, 13 (01)
  • [18] ZoneKV: A Space-Efficient Key-Value Store for ZNS SSDs
    Lu, Mingchen
    Jin, Peiquan
    Wang, Xiaoliang
    Luo, Yongping
    Guo, Kuankuan
    [J]. 2023 60TH ACM/IEEE DESIGN AUTOMATION CONFERENCE, DAC, 2023,
  • [19] Min J, 2023, PROCEEDINGS OF THE 17TH USENIX SYMPOSIUM ON OPERATING SYSTEMS DESIGN AND IMPLEMENTATION, OSDI 2023, P461
  • [20] Nie S., 2024, 2024 IEEE NONV MEM S, P1