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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
LIX - Laboratoire d'informatique de l'École polytechnique [Palaiseau], Inria Saclay - Ile de France
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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Contributor : Cecile Germain Connect in order to contact the contributor
Submitted on : Monday, September 24, 2007 - 9:20:52 AM
Last modification on : Friday, February 4, 2022 - 3:23:38 AM


  • HAL Id : inria-00174286, version 1



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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