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Fault Detection and Diagnosis from the Logging and Bookkeping Data

Xiangliang Zhang 1 Michèle Sebag 1 Cecile Germain-Renaud 1
1 TANC - Algorithmic number theory for cryptology
Inria Saclay - Ile de France, LIX - Laboratoire d'informatique de l'École polytechnique [Palaiseau]
Abstract : Autonomic Computing (AC) is defined as ‘computing systems that manage themselves in accordance with high-level objectives from humans'. AC is now a well-established scientific domain, and a priority for industry. Automated detection, diagnosis, and ultimately management, of software/hardware problems define autonomic dependability. The paper reports on applying state of the art autonomic dependability methods to the Logging and Bookkeeping data, with promising results on detection.
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https://hal.inria.fr/inria-00174286
Contributor : Cecile Germain <>
Submitted on : Monday, September 24, 2007 - 9:20:52 AM
Last modification on : Wednesday, March 27, 2019 - 4:41:29 PM

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  • HAL Id : inria-00174286, version 1

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Xiangliang Zhang, Michèle Sebag, Cecile Germain-Renaud. Fault Detection and Diagnosis from the Logging and Bookkeping Data. 2nd EGEE User Forum, May 2007, Manchester, United Kingdom. ⟨inria-00174286⟩

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