Hidden Markov model for hard-drive failure detection

Teik Toe Teoh, Siu Yeung Cho, Yok Yen Nguwi

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

5 Citations (Scopus)

Abstract

This paper illustrates the use of Hidden Markov Model (HMM) to model hard disk failure. The reason we use HMM is because HMM is a formal foundation for making probabilistic models of linear sequence 'labeling' problem. We use the database provided by University of California, San Diego for detection of hard-drive failure. We have selected 24 attributes and obtain accuracy of about 90%. We compare machine-learning methods applied to a difficult real-world problem: predicting computer hard-drive failure using attributes monitored internally by individual drives. The problem is one of detecting rare events in a time series of noisy and non-parametrically distributed data. We develop a new algorithm HMM which is specifically designed for the low false-alarm case, and is shown to have promising performance. Other methods compared are support vector machines (SVMs), unsupervised clustering, and non-parametric statistical tests (rank-sum and reverse arrangements). The failure-prediction performance of the SVM, rank-sum and mi-NB algorithm is considerably better than the threshold method currently implemented in drives, while maintaining low false alarm rates [13]. Our results suggest that non-parametric statistical tests should be considered for learning problems involving detecting rare events.

Original languageEnglish
Title of host publicationICCSE 2012 - Proceedings of 2012 7th International Conference on Computer Science and Education
Pages3-8
Number of pages6
DOIs
Publication statusPublished - 2012
Event2012 7th International Conference on Computer Science and Education, ICCSE 2012 - Melbourne, VIC, Australia
Duration: 14 Jul 201217 Jul 2012

Publication series

NameICCSE 2012 - Proceedings of 2012 7th International Conference on Computer Science and Education

Conference

Conference2012 7th International Conference on Computer Science and Education, ICCSE 2012
Country/TerritoryAustralia
CityMelbourne, VIC
Period14/07/1217/07/12

Keywords

  • detection
  • hard disk
  • hidden markov

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Theoretical Computer Science

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