Probabilistic Fault Diagnosis in the MAGNETO Autonomic Control Loop

  • Pablo Arozarena
  • Raquel Toribio
  • Jesse Kielthy
  • Kevin Quinn
  • Martin Zach
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6155)


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.


Autonomic Home Area Networks (HAN) Probabilistic Management Bayesian Network Self-learning 


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Copyright information

© IFIP International Federation for Information Processing 2010

Authors and Affiliations

  • Pablo Arozarena
    • 1
  • Raquel Toribio
    • 1
  • Jesse Kielthy
    • 2
  • Kevin Quinn
    • 2
  • Martin Zach
    • 3
  1. 1.Telefónica Investigación y DesarrolloMadridSpain
  2. 2.Telecommunications Software and Systems Group (TSSG)WaterfordIreland
  3. 3.Siemens AG AustriaVienaAustria

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