Probabilistic fault diagnosis in the MAGNETO autonomic control loop

Authors:
Pablo Arozarena;Raquel Toribio;Jesse Kielthy;Kevin Quinn;Martin Zach
Affiliations:
Telefónica Investigación y Desarrollo, Madrid, Spain;Telefónica Investigación y Desarrollo, Madrid, Spain;Telecommunications Software and Systems Group, Waterford, Ireland;Telecommunications Software and Systems Group, Waterford, Ireland;Siemens AG Austria, Viena, Austria
Venue:
AIMS'10 Proceedings of the Mechanisms for autonomous management of networks and services, and 4th international conference on Autonomous infrastructure, management and security
Year:
2010

Citing 3
Cited 2

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Abstract

Management of outer edge domains is a big challenge for service providers due to the diversity, heterogeneity and large amount of such networks, together with limited visibility on their status. This paper focuses on the probabilistic fault diagnosis functionality developed in the MAGNETO project, which enables finding the most probable cause of service problems and thus triggering appropriate repair actions. Moreover, its self-learning capabilities allow continuously enhancing the accuracy of the diagnostic process.