CCFTL: A novel continuity compressed page-level flash address mapping method for SSDs

IF 3.4 3区 计算机科学 Q1 COMPUTER SCIENCE, THEORY & METHODS Journal of Parallel and Distributed Computing Pub Date : 2024-05-15 DOI:10.1016/j.jpdc.2024.104917
Liangkuan Su , Mingwei Lin , Jianpeng Zhang , Yubiao Pan
{"title":"CCFTL: A novel continuity compressed page-level flash address mapping method for SSDs","authors":"Liangkuan Su ,&nbsp;Mingwei Lin ,&nbsp;Jianpeng Zhang ,&nbsp;Yubiao Pan","doi":"10.1016/j.jpdc.2024.104917","DOIUrl":null,"url":null,"abstract":"<div><p>Given the distinctive characteristics of flash-based solid-state drives (SSDs), such as out-of-place update scheme, as compared to traditional block storage devices, a flash translation layer (FTL) has been introduced to hide these features. In the FTL, there is an address translation module that implements the conversion from logical addresses to physical addresses. However, existing address mapping algorithms currently fail to fully exploit the mapping information generated by large I/O requests. First, based on this observation, we propose a novel continuity compressed page-level flash address mapping method (CCFTL). This method effectively compresses the mapping relationship between consecutive logical addresses and physical addresses, enabling the storage of more mapping information within the same mapping cache size. Next, we introduce two-level LRU linked list to mitigate the issue of compressed mapping entry splitting that arises from handling write requests. Finally, our experiments show that CCFTL reduced average response times by 52.67%, 16.81%, and 12.71% compared to DFTL, TPFTL, and MFTL, respectively. As the mapping cache size decreases from 2 MB to 1 MB, then further decreases to 256 KB, 128 KB, and eventually down to 64 KB, CCFTL experiences an average decline ratio of less than 3% in average response time, while the other three algorithms show an average decline ratio of 9.51%.</p></div>","PeriodicalId":54775,"journal":{"name":"Journal of Parallel and Distributed Computing","volume":"191 ","pages":"Article 104917"},"PeriodicalIF":3.4000,"publicationDate":"2024-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Parallel and Distributed Computing","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0743731524000819","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, THEORY & METHODS","Score":null,"Total":0}
引用次数: 0

Abstract

Given the distinctive characteristics of flash-based solid-state drives (SSDs), such as out-of-place update scheme, as compared to traditional block storage devices, a flash translation layer (FTL) has been introduced to hide these features. In the FTL, there is an address translation module that implements the conversion from logical addresses to physical addresses. However, existing address mapping algorithms currently fail to fully exploit the mapping information generated by large I/O requests. First, based on this observation, we propose a novel continuity compressed page-level flash address mapping method (CCFTL). This method effectively compresses the mapping relationship between consecutive logical addresses and physical addresses, enabling the storage of more mapping information within the same mapping cache size. Next, we introduce two-level LRU linked list to mitigate the issue of compressed mapping entry splitting that arises from handling write requests. Finally, our experiments show that CCFTL reduced average response times by 52.67%, 16.81%, and 12.71% compared to DFTL, TPFTL, and MFTL, respectively. As the mapping cache size decreases from 2 MB to 1 MB, then further decreases to 256 KB, 128 KB, and eventually down to 64 KB, CCFTL experiences an average decline ratio of less than 3% in average response time, while the other three algorithms show an average decline ratio of 9.51%.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
CCFTL:适用于固态硬盘的新型连续性压缩页面级闪存地址映射方法
与传统的块存储设备相比,基于闪存的固态硬盘(SSD)具有不同的特性,如非就地更新方案,因此引入了闪存转换层(FTL)来隐藏这些特性。在 FTL 中,有一个地址转换模块可以实现从逻辑地址到物理地址的转换。然而,现有的地址映射算法目前无法充分利用大型 I/O 请求产生的映射信息。首先,基于这一观点,我们提出了一种新颖的连续性压缩页面级闪存地址映射方法(CCFTL)。这种方法能有效压缩连续逻辑地址和物理地址之间的映射关系,从而在相同的映射缓存大小内存储更多的映射信息。接下来,我们引入了两级 LRU 链接列表,以缓解处理写入请求时出现的压缩映射条目分割问题。最后,我们的实验表明,与 DFTL、TPFTL 和 MFTL 相比,CCFTL 的平均响应时间分别缩短了 52.67%、16.81% 和 12.71%。随着映射缓存大小从 2 MB 减小到 1 MB,然后进一步减小到 256 KB、128 KB,最终减小到 64 KB,CCFTL 的平均响应时间平均下降率不到 3%,而其他三种算法的平均下降率为 9.51%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Journal of Parallel and Distributed Computing
Journal of Parallel and Distributed Computing 工程技术-计算机:理论方法
CiteScore
10.30
自引率
2.60%
发文量
172
审稿时长
12 months
期刊介绍: This international journal is directed to researchers, engineers, educators, managers, programmers, and users of computers who have particular interests in parallel processing and/or distributed computing. The Journal of Parallel and Distributed Computing publishes original research papers and timely review articles on the theory, design, evaluation, and use of parallel and/or distributed computing systems. The journal also features special issues on these topics; again covering the full range from the design to the use of our targeted systems.
期刊最新文献
Enabling semi-supervised learning in intrusion detection systems Fault-tolerance in biswapped multiprocessor interconnection networks Editorial Board Front Matter 1 - Full Title Page (regular issues)/Special Issue Title page (special issues) Design and experimental evaluation of algorithms for optimizing the throughput of dispersed computing
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1