{"title":"A framework for efficient evaluation of the fault tolerance of deduplicated storage systems","authors":"Eric Rozier, W. Sanders","doi":"10.1109/DSN.2012.6263921","DOIUrl":null,"url":null,"abstract":"In this paper we present a framework for analyzing the fault tolerance of deduplicated storage systems. We discuss methods for building models of deduplicated storage systems by analyzing empirical data on a file category basis. We provide an algorithm for generating component-based models from this information and a specification of the storage system architecture. Given the complex nature of detailed models of deduplicated storage systems, finding a solution using traditional discrete event simulation or numerical solvers can be difficult. We introduce an algorithm which allows for a more efficient solution by exploiting the underlying structure of dependencies to decompose the model of the storage system. We present a case study of our framework for a real system.We analyze a production deduplicated storage system and propose extensions which improve fault tolerance while maintaining high storage efficiency.","PeriodicalId":236791,"journal":{"name":"IEEE/IFIP International Conference on Dependable Systems and Networks (DSN 2012)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE/IFIP International Conference on Dependable Systems and Networks (DSN 2012)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DSN.2012.6263921","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 13
Abstract
In this paper we present a framework for analyzing the fault tolerance of deduplicated storage systems. We discuss methods for building models of deduplicated storage systems by analyzing empirical data on a file category basis. We provide an algorithm for generating component-based models from this information and a specification of the storage system architecture. Given the complex nature of detailed models of deduplicated storage systems, finding a solution using traditional discrete event simulation or numerical solvers can be difficult. We introduce an algorithm which allows for a more efficient solution by exploiting the underlying structure of dependencies to decompose the model of the storage system. We present a case study of our framework for a real system.We analyze a production deduplicated storage system and propose extensions which improve fault tolerance while maintaining high storage efficiency.