基于产品矩阵构造的MSR再生代码并发故障恢复

Jingyao Zhang
{"title":"基于产品矩阵构造的MSR再生代码并发故障恢复","authors":"Jingyao Zhang","doi":"10.1145/3368235.3368871","DOIUrl":null,"url":null,"abstract":"Node failures are very common in distributed storage systems. Regenerating codes can minimize the network bandwidth required to recover the data lost on the failed nodes. Minimum Storage Regenerating (MSR) code is a class of regenerating codes that can maximize the storage efficiency, meanwhile minimizing the repair bandwidth. The original MSR code via Product Matrix (PM) provides a means for single failed node recovery. In this work, an algorithm of recovering multiple failed nodes concurrently with the minimum feasible bandwidth will be proposed, extending the framework of the original PM MSR code. Based on the proposed strategy, the needed bandwidth for centralized and distributed recovery policies, which are the two major categories of repairing policies, will be explicitly expressed against the coding parameters and the number of failed nodes, hence numerical comparison can be made between them. Moreover, the impact of Repairing Degree (the number of surviving nodes from which the assistant data are downloaded ) on the bandwidth cost will be studied to help make optimal decision in practical storage systems.","PeriodicalId":166357,"journal":{"name":"Proceedings of the 12th IEEE/ACM International Conference on Utility and Cloud Computing Companion","volume":"59 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Concurrent Failure Recovery for MSR Regenerating Code via Product Matrix Construction\",\"authors\":\"Jingyao Zhang\",\"doi\":\"10.1145/3368235.3368871\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Node failures are very common in distributed storage systems. Regenerating codes can minimize the network bandwidth required to recover the data lost on the failed nodes. Minimum Storage Regenerating (MSR) code is a class of regenerating codes that can maximize the storage efficiency, meanwhile minimizing the repair bandwidth. The original MSR code via Product Matrix (PM) provides a means for single failed node recovery. In this work, an algorithm of recovering multiple failed nodes concurrently with the minimum feasible bandwidth will be proposed, extending the framework of the original PM MSR code. Based on the proposed strategy, the needed bandwidth for centralized and distributed recovery policies, which are the two major categories of repairing policies, will be explicitly expressed against the coding parameters and the number of failed nodes, hence numerical comparison can be made between them. Moreover, the impact of Repairing Degree (the number of surviving nodes from which the assistant data are downloaded ) on the bandwidth cost will be studied to help make optimal decision in practical storage systems.\",\"PeriodicalId\":166357,\"journal\":{\"name\":\"Proceedings of the 12th IEEE/ACM International Conference on Utility and Cloud Computing Companion\",\"volume\":\"59 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-12-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 12th IEEE/ACM International Conference on Utility and Cloud Computing Companion\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3368235.3368871\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 12th IEEE/ACM International Conference on Utility and Cloud Computing Companion","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3368235.3368871","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

节点故障在分布式存储系统中非常常见。重新生成代码可以最大限度地减少恢复故障节点上丢失的数据所需的网络带宽。最小存储再生码(MSR)是一类能够使存储效率最大化,同时使修复带宽最小化的再生码。原始MSR代码通过产品矩阵(PM)提供了单个故障节点恢复的方法。本文提出了一种以最小可行带宽同时恢复多个故障节点的算法,扩展了原PM MSR代码的框架。基于该策略,集中式恢复策略和分布式恢复策略(两大类修复策略)所需的带宽将根据编码参数和故障节点数量明确表示,从而可以对两者进行数值比较。此外,还将研究修复度(下载辅助数据的幸存节点数量)对带宽成本的影响,以帮助在实际存储系统中做出最优决策。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Concurrent Failure Recovery for MSR Regenerating Code via Product Matrix Construction
Node failures are very common in distributed storage systems. Regenerating codes can minimize the network bandwidth required to recover the data lost on the failed nodes. Minimum Storage Regenerating (MSR) code is a class of regenerating codes that can maximize the storage efficiency, meanwhile minimizing the repair bandwidth. The original MSR code via Product Matrix (PM) provides a means for single failed node recovery. In this work, an algorithm of recovering multiple failed nodes concurrently with the minimum feasible bandwidth will be proposed, extending the framework of the original PM MSR code. Based on the proposed strategy, the needed bandwidth for centralized and distributed recovery policies, which are the two major categories of repairing policies, will be explicitly expressed against the coding parameters and the number of failed nodes, hence numerical comparison can be made between them. Moreover, the impact of Repairing Degree (the number of surviving nodes from which the assistant data are downloaded ) on the bandwidth cost will be studied to help make optimal decision in practical storage systems.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信