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2nd EGEE User Forum, Manchester : Royaume-Uni (2007)
Predicting Bounds on Queuing Delay in the EGEE grid
Julien Perez1, Cecile Germain-Renaud1, Balázs Kégl2

Predicting the performance of schedulers is a notoriously difficult task. As a consequence, grid users might be tempted to work around the standard grid middleware by designing specific strategies, which would be counterproductive if generally adopted. On the other hand, Machine Learning has been successfully applied to performance prediction in distributed and shared environments. This paper reports on experiments on predicting the basic parameters of scheduling in the EGEE framework.
1 :  INRIA Futurs - TAO
2 :  LAL - Laboratoire de l'Accélérateur Linéaire
Informatique/Intelligence artificielle

Informatique/Calcul parallèle, distribué et partagé
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