Xin Xie, Chentao Wu, Chao Li, Jie Li, M. Guo, Fang Xu
{"title":"A Comprehensive Rearranging Priority Based Method To Accelerate the Reconstruction of RAID Arrays","authors":"Xin Xie, Chentao Wu, Chao Li, Jie Li, M. Guo, Fang Xu","doi":"10.1109/SRDSW49218.2019.00010","DOIUrl":null,"url":null,"abstract":"With the development of cloud computing, the reliability of disk arrays are increasingly concerned. Data centers usually use erasure codes to provide high reliability. However, most of reconstruction methods on disk arrays focus on single/ multiple disk(s) recovery, which ignores how to efficiently reconstruct the lost data such as Latent Sector Errors (LSEs), etc. In real situations, local stripe errors are much more common than disk failures. It has become an urgent problem that how to improve reconstruction efficiently for stripes. This paper proposes a comprehensive rearranging priority reconstruction(CRPR), which combines temporal locality, spatial locality and coding characteristics together. CRPR divides different blocks into various priorities and recovers them sequentially. To demonstrate the effectiveness of CRPR, we conduct several simulations via disksim. The simulations results show that, the comprehensive rearranging priority reconstruction method keeps up with previous methods and can save up to 63.9% in terms of waiting time.","PeriodicalId":297328,"journal":{"name":"2019 38th International Symposium on Reliable Distributed Systems Workshops (SRDSW)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 38th International Symposium on Reliable Distributed Systems Workshops (SRDSW)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SRDSW49218.2019.00010","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
With the development of cloud computing, the reliability of disk arrays are increasingly concerned. Data centers usually use erasure codes to provide high reliability. However, most of reconstruction methods on disk arrays focus on single/ multiple disk(s) recovery, which ignores how to efficiently reconstruct the lost data such as Latent Sector Errors (LSEs), etc. In real situations, local stripe errors are much more common than disk failures. It has become an urgent problem that how to improve reconstruction efficiently for stripes. This paper proposes a comprehensive rearranging priority reconstruction(CRPR), which combines temporal locality, spatial locality and coding characteristics together. CRPR divides different blocks into various priorities and recovers them sequentially. To demonstrate the effectiveness of CRPR, we conduct several simulations via disksim. The simulations results show that, the comprehensive rearranging priority reconstruction method keeps up with previous methods and can save up to 63.9% in terms of waiting time.