{"title":"Near-optimal multi-version codes","authors":"M. Khabbazian","doi":"10.1109/ALLERTON.2015.7447076","DOIUrl":null,"url":null,"abstract":"Motivated by applications to distributed storage and computing, the multi-version coding problem was formulated by Wang and Cadambe in [4]. In this problem, a client sequently over time stores v independent versions of a message in a storage system with n server nodes. It is assumed that, a message version may not reach some servers, and that each server is unaware of what has been stored in other servers. The problem requires that any c servers must be able to reconstruct their latest common version. An extended multi-version problem introduced in [5] relaxes the above requirement by requiring any c servers to be able to reconstruct their latest common version or any version later than that. The objective in both the original and extended multi-version problem is to minimize the worst case storage cost. In this work, we propose codes for both the multi-version problem and its extension. For the original multi-version coding problem, we show that the storage cost of our proposed codes are near-optimal. For the extended multi-version coding problem, we show that the storage cost of our first algorithm is optimal when v|c - 1. Our second proposed extended multi-version code shows that storage cost of strictly less than one is achievable even when v is 50% larger than c. This is interesting, as the storage cost of existing codes becomes one as soon as v becomes larger than c.","PeriodicalId":112948,"journal":{"name":"2015 53rd Annual Allerton Conference on Communication, Control, and Computing (Allerton)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 53rd Annual Allerton Conference on Communication, Control, and Computing (Allerton)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ALLERTON.2015.7447076","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

Motivated by applications to distributed storage and computing, the multi-version coding problem was formulated by Wang and Cadambe in [4]. In this problem, a client sequently over time stores v independent versions of a message in a storage system with n server nodes. It is assumed that, a message version may not reach some servers, and that each server is unaware of what has been stored in other servers. The problem requires that any c servers must be able to reconstruct their latest common version. An extended multi-version problem introduced in [5] relaxes the above requirement by requiring any c servers to be able to reconstruct their latest common version or any version later than that. The objective in both the original and extended multi-version problem is to minimize the worst case storage cost. In this work, we propose codes for both the multi-version problem and its extension. For the original multi-version coding problem, we show that the storage cost of our proposed codes are near-optimal. For the extended multi-version coding problem, we show that the storage cost of our first algorithm is optimal when v|c - 1. Our second proposed extended multi-version code shows that storage cost of strictly less than one is achievable even when v is 50% larger than c. This is interesting, as the storage cost of existing codes becomes one as soon as v becomes larger than c.
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近乎最佳的多版本代码
受分布式存储和计算应用的影响,Wang和Cadambe在[4]中提出了多版本编码问题。在这个问题中,客户端在具有n个服务器节点的存储系统中依次存储消息的v个独立版本。假设消息版本可能无法到达某些服务器,并且每个服务器都不知道其他服务器中存储的内容。该问题要求任何c服务器都必须能够重建其最新的公共版本。[5]中引入的扩展多版本问题放宽了上述要求,要求任何c服务器能够重构其最新的通用版本或任何更新的版本。原始多版本问题和扩展多版本问题的目标都是最小化最坏情况下的存储成本。在这项工作中,我们提出了多版本问题及其扩展的代码。对于原始的多版本编码问题,我们证明了我们所提出的编码的存储成本接近最优。对于扩展的多版本编码问题,我们证明了第一种算法的存储成本在v|c - 1时是最优的。我们提出的第二个扩展多版本代码表明,即使v比c大50%,也可以实现严格小于1的存储成本。这很有趣,因为一旦v大于c,现有代码的存储成本就会变为1。
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