Failure prediction in IBM BlueGene/L event logs

Yanyong Zhang, Anand Sivasubramaniam

Research output: Chapter in Book/Report/Conference proceedingConference contribution

29 Scopus citations

Abstract

In this paper, we present our effort in developing a failure prediction model based on event logs collected from IBM BlueGene/L. We first show how the event records can be converted into a data set that is appropriate for running classification techniques. Then we apply classifiers on the data, including RIPPER (a rule-based classifier), Support Vector Machines (SVMs), a traditional Nearest Neighbor method, and a customized Nearest Neighbor method. We show that the customized nearest neighbor approach can outperform RIPPER and SVMs in terms of both coverage and precision. The results suggest that the customized nearest neighbor approach can be used to alleviate the impact of failures.

Original languageEnglish (US)
Title of host publicationIPDPS Miami 2008 - Proceedings of the 22nd IEEE International Parallel and Distributed Processing Symposium, Program and CD-ROM
DOIs
StatePublished - 2008
EventIPDPS 2008 - 22nd IEEE International Parallel and Distributed Processing Symposium - Miami, FL, United States
Duration: Apr 14 2008Apr 18 2008

Publication series

NameIPDPS Miami 2008 - Proceedings of the 22nd IEEE International Parallel and Distributed Processing Symposium, Program and CD-ROM

Other

OtherIPDPS 2008 - 22nd IEEE International Parallel and Distributed Processing Symposium
Country/TerritoryUnited States
CityMiami, FL
Period4/14/084/18/08

All Science Journal Classification (ASJC) codes

  • Hardware and Architecture
  • Software
  • Electrical and Electronic Engineering

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