energy conservation; peer-to-peer computing; scheduling; quality of service; application characteristics; performance of systems
Résumé :
[en] We address knowledge-free Bag-of-Tasks non-preemptive scheduling problem on heterogeneous grids, where scheduling decisions are free from information of resources and application characteristics. We consider a scheduling with task replications to overcome possible random bad resource allocation and ensure good performance. We analyze energy consumption of job allocation strategies based on variations of the replication threshold. In order to provide QoS and minimize energy consumption, we perform a joint analysis of two metrics. A case study is given and corresponding results indicate that proposed strategies reduce energy consumption without significant degradation in performance.
Disciplines :
Sciences informatiques
Identifiants :
UNILU:UL-CONFERENCE-2012-292
Auteur, co-auteur :
Barrondo, Aritz; CICESE Research Center, Ensenada, Baja California, Mexico
Tchernykh, Andrei; Universidad Autónoma de Nuevo Leon, Nuevo Leon, Mexico
SHAEFFER, Elisa ; University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC)
PECERO, Johnatan ; University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC)
Langue du document :
Anglais
Titre :
Energy Efficiency of Knowledge-Free Scheduling in Peer-to-Peer Desktop Grids
Date de publication/diffusion :
02 juillet 2012
Nom de la manifestation :
High Performance Computing & Simulations (HPCS 2012)
Lieu de la manifestation :
Madrid, Espagne
Date de la manifestation :
July 2 - July 6
Manifestation à portée :
International
Titre de l'ouvrage principal :
2012 International Conference on High Performance Computing and Simulation (HPCS)
Maison d'édition :
IEEE
ISBN/EAN :
978-1-4673-2361-1
Pagination :
105-111
Peer reviewed :
Peer reviewed
Commentaire :
Proceedings of the 2012 International Conference on High Performance Computing & Simulation (HPCS 2012)