NDLI: A practical failure prediction with location and lead time for Blue Gene/P

Content Provider	IEEE Xplore Digital Library
Author	Ziming Zheng Zhiling Lan Gupta, R. Coghlan, S. Beckman, P.
Copyright Year	2010
Description	Author affiliation: Mathematics and Computer Science Division, Argonne National Laboratory (Gupta, R.; Beckman, P.) \|\| Department of Computer Science, Illinois Institute of Technology (Ziming Zheng; Zhiling Lan) \|\| Argonne Leadership Computing Facility, Argonne National Laboratory (Coghlan, S.)
Abstract	Analyzing, understanding and predicting failure is of paramount importance to achieve effective fault management. While various fault prediction methods have been studied in the past, many of them are not practical for use in real systems. In particular, they fail to address two crucial issues: one is to provide location information (i.e., the components where the failure is expected to occur on) and the other is to provide sufficient lead time (i.e., the time interval preceding the time of failure occurrence). In this paper, we first refine the widely-used metrics for evaluating prediction accuracy by including location as well as lead time. We, then, present a practical failure prediction mechanism for IBM Blue Gene systems. A Genetic Algorithm based method is exploited, which takes into consideration the location and the lead time for failure prediction. We demonstrate the effectiveness of this mechanism by means of real failure logs and job logs collected from the IBM Blue Gene/P system at Argonne National Laboratory. Our experiments show that the presented method can significantly improve fault management (e.g., to reduce service unit loss by up to 52.4%) by incorporating location and lead time information in the prediction.
Starting Page	15
Ending Page	22
File Size	177315
Page Count	8
File Format	PDF
ISBN	9781424477296
e-ISBN	9781424477302
e-ISBN	9781424477289
DOI	10.1109/DSNW.2010.5542627
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-06-28
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Checkpointing Computer science Accuracy Lead time reduction Laboratories Failure analysis Prediction methods Mathematics Computer networks Genetic algorithms
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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