Reliability Evaluation of Erasure-coded Storage Systems with Latent Errors

Author:

Iliadis Ilias1ORCID

Affiliation:

1. IBM Research Europe–Zurich, Rüschlikon, Switzerland

Abstract

Large-scale storage systems employ erasure-coding redundancy schemes to protect against device failures. The adverse effect of latent sector errors on the Mean Time to Data Loss (MTTDL) and the Expected Annual Fraction of Data Loss (EAFDL) reliability metrics is evaluated. A theoretical model capturing the effect of latent errors and device failures is developed, and closed-form expressions for the metrics of interest are derived. The MTTDL and EAFDL of erasure-coded systems are obtained analytically for (i) the entire range of bit error rates; (ii) the symmetric, clustered, and declustered data placement schemes; and (iii) arbitrary device failure and rebuild time distributions under network rebuild bandwidth constraints. The range of error rates that deteriorate system reliability is derived analytically. For realistic values of sector error rates, the results obtained demonstrate that MTTDL degrades, whereas, for moderate erasure codes, EAFDL remains practically unaffected. It is demonstrated that, in the range of typical sector error rates and for very powerful erasure codes, EAFDL degrades as well. It is also shown that the declustered data placement scheme offers superior reliability.

Publisher

Association for Computing Machinery (ACM)

Subject

Hardware and Architecture

Reference61 articles.

1. Amazon Web Services. 2021. Amazon Simple Storage Service (Amazon S3). Retrieved from http://aws.amazon.com/s3/.

2. 2022. Backblaze Drive Stats for 2021. Retrieved April 15, 2022 from https://www.backblaze.com/blog/backblaze-drive-stats-for-2021/.

3. 2022. Seagate, Exos X20, Data Sheet. Retrieved April 15, 2022 from https://www.seagate.com/products/enterprise-drives/exos-x/x20/.

4. 2022. Tape Roadmap, Information Storage Industry Consortium (INSIC) Report, 2019. Retrieved April 15, 2022 from https://www.insic.org/wp-content/uploads/2019/07/INSIC-Applications-and-Systems-Roadmap.pdf.

5. Dhruba Borthakur. 2021. HDFS and Erasure Codes (HDFS-RAID), Aug. 2009. Retrieved April 15, 2022 from https://hadoopblog.blogspot.com/2009/08.

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