Data-loss models for proactive-tolerance Reed–Solomon storage systems

IF 6.2 2区计算机科学 Q1 COMPUTER SCIENCE, THEORY & METHODS

Future Generation Computer Systems-The International Journal of Escience Pub Date : 2025-04-02 DOI:10.1016/j.future.2025.107832

Jing Li, Zhenrui Zhou, Jianli Ding

{"title":"Data-loss models for proactive-tolerance Reed–Solomon storage systems","authors":"Jing Li, Zhenrui Zhou, Jianli Ding","doi":"10.1016/j.future.2025.107832","DOIUrl":null,"url":null,"abstract":"<div><div>Proactive fault tolerance increasingly serves as an added protection for data in Reed–Solomon (RS) systems. Compared with declustered placement, grouped placement reduces the failure units and also decreases the repair parallelism, which have the opposite effect on systems reliability. For a RS (<span><math><mi>k</mi></math></span>, <span><math><mi>m</mi></math></span>) system, the values of (<span><math><mi>k</mi></math></span>, <span><math><mi>m</mi></math></span>) impact storage overhead, fault tolerance and repair traffic. When designing proactive RS storage systems, it is challenging to choose the proper placement scheme and coding scheme.</div><div>This paper presents four general reliability equations for estimating the number of data-loss events and the amount of data loss in proactive RS systems using declustered and grouped placement schemes. These equations model the effect of disk/node failures, repair bandwidth, block errors, disk scrubbing, disk/node failure prediction, stripe placement, and coding scheme on the reliability of systems. Moreover, we design a Monte-Carlo based simulator to analyze the reliability of proactive Reed–Solomon systems. The equational results are in good accord with the simulation results, which demonstrates the effectiveness of our proposed equations. Using these mathematical models, we can easily estimate and compare fault tolerant schemes and placement schemes, learn the effect of system parameters on system reliability, facilitating to maintain and design cloud storage systems.</div></div>","PeriodicalId":55132,"journal":{"name":"Future Generation Computer Systems-The International Journal of Escience","volume":"170 ","pages":"Article 107832"},"PeriodicalIF":6.2000,"publicationDate":"2025-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Future Generation Computer Systems-The International Journal of Escience","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0167739X2500127X","RegionNum":2,"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

Proactive fault tolerance increasingly serves as an added protection for data in Reed–Solomon (RS) systems. Compared with declustered placement, grouped placement reduces the failure units and also decreases the repair parallelism, which have the opposite effect on systems reliability. For a RS (

k

m

) system, the values of (

k

m

) impact storage overhead, fault tolerance and repair traffic. When designing proactive RS storage systems, it is challenging to choose the proper placement scheme and coding scheme.

This paper presents four general reliability equations for estimating the number of data-loss events and the amount of data loss in proactive RS systems using declustered and grouped placement schemes. These equations model the effect of disk/node failures, repair bandwidth, block errors, disk scrubbing, disk/node failure prediction, stripe placement, and coding scheme on the reliability of systems. Moreover, we design a Monte-Carlo based simulator to analyze the reliability of proactive Reed–Solomon systems. The equational results are in good accord with the simulation results, which demonstrates the effectiveness of our proposed equations. Using these mathematical models, we can easily estimate and compare fault tolerant schemes and placement schemes, learn the effect of system parameters on system reliability, facilitating to maintain and design cloud storage systems.

查看原文本刊更多论文

主动容忍Reed-Solomon存储系统的数据丢失模型

主动容错越来越多地成为Reed-Solomon （RS）系统中数据的附加保护。与分散放置相比，分组放置减少了故障单元，同时降低了维修并行度，对系统可靠性产生相反的影响。对于RS （k, m）系统，（k, m）的值会影响存储开销、容错性和修复流量。在设计主动RS存储系统时，如何选择合适的布局方案和编码方案是一个难题。本文提出了四个通用的可靠性方程，用于估计数据丢失事件的数量和数据丢失量在主动RS系统中使用分散和分组的安置方案。这些方程模拟了磁盘/节点故障、修复带宽、块错误、磁盘清洗、磁盘/节点故障预测、条带放置和编码方案对系统可靠性的影响。此外，我们设计了一个基于蒙特卡罗的模拟器来分析主动Reed-Solomon系统的可靠性。计算结果与仿真结果吻合较好，验证了所提方程的有效性。利用这些数学模型，我们可以方便地估计和比较容错方案和布局方案，了解系统参数对系统可靠性的影响，便于云存储系统的维护和设计。

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分钟内获得全文求助全文

来源期刊

Future Generation Computer Systems-The International Journal of Escience 工程技术-计算机：理论方法

CiteScore

19.90

自引率

2.70%

发文量

376

审稿时长

10.6 months

期刊介绍： Computing infrastructures and systems are constantly evolving, resulting in increasingly complex and collaborative scientific applications. To cope with these advancements, there is a growing need for collaborative tools that can effectively map, control, and execute these applications. Furthermore, with the explosion of Big Data, there is a requirement for innovative methods and infrastructures to collect, analyze, and derive meaningful insights from the vast amount of data generated. This necessitates the integration of computational and storage capabilities, databases, sensors, and human collaboration. Future Generation Computer Systems aims to pioneer advancements in distributed systems, collaborative environments, high-performance computing, and Big Data analytics. It strives to stay at the forefront of developments in grids, clouds, and the Internet of Things (IoT) to effectively address the challenges posed by these wide-area, fully distributed sensing and computing systems.