Efficient Wear-Leveling-Aware Data Placement for LSM-Tree based key-value store on ZNS SSDs

被引:0
作者
Zhang, Runyu [1 ]
Zhou, Lening [1 ]
Li, Mingjie [1 ]
Tan, Yunlin [1 ]
Yang, Chaoshu [1 ]
机构
[1] Guizhou Univ, Coll Comp Sci & Technol, State Key Lab Publ Big Data, Guiyang 550025, Peoples R China
关键词
ZNS SSD; Key-value store; LSM-tree; Wear-leveling;
D O I
10.1016/j.jksuci.2024.102156
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Emerging Zoned Namespace (ZNS) is a new-style Solid State Drive (SSD) that manages data in a zoned manner, which can achieve higher performance by strictly obeying the sequential write mode in each zone and alleviating the redundant overhead of garbage collections. Unfortunately, flash memory usually has a serious problem with limited program/erase cycles. Meanwhile, inappropriate data placement strategy of storage systems can lead to imbalanced wear among zones, severely reducing the lifespan of ZNS SSDs. In this paper, we propose a Wear-Leveling-Aware Data Placement (WADP) to solve this problem with negligible performance cost. First, WADP employs a wear-aware empty zone allocation algorithm to quantify the resets of zones and choose the less-worn zone for each allocation. Second, to prevent long-term zone occupation of infrequently written data (namely cold data), we propose a wear-leveling cold zone monitoring mechanism to identify cold zones dynamically. Finally, WADP adopts a real-time I/O pressure-aware data migration mechanism to adaptively migrate cold data for achieving wear-leveling among zones. We implement the proposed WADP in ZenFS and evaluate it with widely used workloads. Compared with state-of-the-art solutions, i.e., LIZA and FAR, the experimental results show that WADP can significantly reduce the standard deviation of zone resets while maintaining decent performance.
引用
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页数:11
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