Date de début:
17:00
Date de fin:
17:00
Lieu:
Institut de Physique du Globe de Paris
Ville:
Paris
Producteur:
-

Durée:
33:34
Type:
video/mp4
Poids:
215.5 Mo
Format:
mp4
Résolution:
704x560
Codec:
-

Efficient fault monitoring with Collaborative Prediction

Isolating users from the inevitable faults in large distributed systems is critical to Quality of Experience. We formulate the problem of probe selection for fault prediction based on end-to-end probing as a Collaborative Prediction (CP) problem. On an extensive experimental dataset from the EGI grid, the combination of the Maximum Margin Matrix Factorization approach to CP and Active Learning shows excellent performance, reducing the number of probes typically by 80% to 90%.

Cécile Germain, Laboratoire de Recherche en Informatique (LRI)

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