Anticipatory troubleshooting

Netanel Hasidi, Roni Stern, Meir Kalech, Shulamit Reches

Research output: Contribution to journalConference articlepeer-review

1 Scopus citations

Abstract

Troubleshooting is the process of diagnosing and repairing a system that is behaving abnormally. Diagnostic and repair actions may incur costs, and traditional troubleshooting algorithms aim to minimize the costs incurred until the system is fixed. We propose an anticipatory troubleshooting algorithm, which is able to reason about both current and future failures. To reason about failures over time, we incorporate statistical tools from survival analysis that enable predicting when a failure is likely to occur. Incorporating this prognostic information in a troubleshooting algorithm enables (1) better fault isolation and (2) more intelligent decision making in which repair actions to employ to minimize troubleshooting costs over time.

Original languageEnglish
Pages (from-to)3133-3139
Number of pages7
JournalIJCAI International Joint Conference on Artificial Intelligence
Volume2016-January
StatePublished - 1 Jan 2016
Event25th International Joint Conference on Artificial Intelligence, IJCAI 2016 - New York, United States
Duration: 9 Jul 201615 Jul 2016

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