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LLSM: A Lifetime-Aware Wear-Leveling for LSM-Tree on NAND Flash Memory

计算机科学 与非门 闪存 随机存取 合并(版本控制) 非易失性存储器 树(集合论) 闪存文件系统 计算机硬件 嵌入式系统 并行计算 操作系统 计算机存储器 频道(广播) 计算机网络 半导体存储器 数学分析 数学
作者
Dharamjeet,Yi-Shen Chen,Tseng‐Yi Chen,Yuan-Hung Kuan,Yuan-Hao Chang
出处
期刊:IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems [Institute of Electrical and Electronics Engineers]
卷期号:41 (11): 3946-3956 被引量:13
标识
DOI:10.1109/tcad.2022.3197542
摘要

The advancement of nonvolatile memory (NVM) technology reduces the cost-per-unit of solid-state drives (SSDs). Flash memory-based SSDs have become ubiquitous because they provide better performance and energy efficiency than hard disk drives. However, it suffers from wear-out problems caused by the out-of-place updates that limit its lifetime. Log-structured merge tree (LSM-tree) is a level-based data structure that is widely used in many database systems because it eliminates the random write operations to the storage devices. By transferring the random write operations into sequential write operations, the write performance of hard disk drives can be improved. However, LSM-tree is not efficient for SSDs because it is not aware of the access characteristics of flash memory. Moreover, the level-based indexing strategy of the LSM-tree significantly shortens the lifetime of SSDs because the data must be frequently updated due to the compaction operations between different levels. In contrast to many previous works that focus on alleviating the write amplification on SSDs for the database systems implemented by LSM-tree, we propose LLSM, a lifetime-aware wear-leveling for LSM-tree on NAND flash memory with open-channel SSD. By considering the data access frequency of the LSM-tree between different levels, LLSM rethinks the block allocation strategy during the compaction to evenly erase all the blocks of SSD storage devices, prolonging the SSD lifetime. Moreover, a proactive swapping strategy is designed to reorganize the data blocks for resolving the potential wear-leveling issues caused by the behaviors of the LSM-tree. The extensive experiments show that the results of lifetime improvement are encouraging.
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