Zone-Aware Persistent Deletion for Key-Value Store Engine

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 designed a tombstone aware zone allocation strategy to reduce the data migration induced by garbage collection. Experimental results demonstrate that our scheme effectively ensures that most outdated physical versions are deleted before reaching the persistent deletion time threshold.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 69.6% and the garbage collection-induced write by 82.4% compared to the Lethe-Fade scheme.

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Publication Details

Published
2024-08-21
DOI
https://doi.org/10.1109/nvmsa63038.2024.10693671
Primary Topic
Advanced Steganography and Watermarking Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

Zone-Aware Persistent Deletion for Key-Value Store Engine

Shiqiang Nie, Weiguo Wu, Jie Niu, Song Liu et al.
Advanced Steganography and Watermarking Techniques
article

Zone-Aware Persistent Deletion for Key-Value Store Engine

Shiqiang Nie, Weiguo Wu, Jie Niu, Song Liu, Menghan Li, Lei Tong
article en

Abstract

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 designed a tombstone aware zone allocation strategy to reduce the data migration induced by garbage collection. 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 69.6% and the garbage collection-induced write by 82.4% compared to the Lethe-Fade scheme.

Xi'an Jiaotong University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 84%
Advanced Steganography and Watermarking Techniques
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