DHISC : Disk Health Indexing System for Centers of Data Management
Name
1017566745-MIT.pdf
Size
15.68 MB
Format
Adobe PDF
Checksum (MD5)
a955ec6e3fe34f8c5cd9d9e20874fe9e
Author(s)
Kekelishvili, Rebecca.
Advisor(s)
Katrina LaCurtis and Wayne Booth.
Alternative Title
Disk Health Indexing System for Centers of data management
Date Issued
2017
Publisher
Massachusetts Institute of Technology
Abstract
If we want to have reliable data centers, we must improve reliability at the lowest level of data storage at the disk level. To improve reliability, we need to convert storage systems from reactive mechanisms that handle disk failures to a proactive mechanism that predict and address failures. Because the definition of disk failure is specific to a customer rather than defined by a standard, we developed a relative disk health metric and proposed a customer-oriented disk-maintenance pipeline. We designed a program that processes data collected from data center disks into a format that is easy to analyze using machine learning. Then, we used a neural network to recognize disks that show signs of oncoming failure with 95.4-98.7% accuracy, and used the result of the network to produce a rank of most and least reliable disks at the data center, enabling customers to perform bulk disk maintenance, decreasing system downtime.
Description
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2017
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 85-88).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
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