Reference : Energy Efficiency of Knowledge-Free Scheduling in Peer-to-Peer Desktop Grids

	Document type :	Scientific congresses, symposiums and conference proceedings : Paper published in a book
	Discipline(s) :	Engineering, computing & technology : Computer science
	To cite this reference:	http://hdl.handle.net/10993/15395

Title :	Energy Efficiency of Knowledge-Free Scheduling in Peer-to-Peer Desktop Grids
Language :	English
Author, co-author :	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) >]
Publication date :	2-Jul-2012
Main document title :	2012 International Conference on High Performance Computing and Simulation (HPCS)
Publisher :	IEEE
Pages :	105-111
Peer reviewed :	Yes
Audience :	International
ISBN :	978-1-4673-2361-1
Event name :	High Performance Computing & Simulations (HPCS 2012)
Event date :	July 2 - July 6
Event place (city) :	Madrid
Event country :	Spain
Keywords :	[en] energy conservation ; peer-to-peer computing ; scheduling ; quality of service ; application characteristics ; performance of systems
Abstract :	[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.
Permalink :	http://hdl.handle.net/10993/15395
DOI :	10.1109/HPCSim.2012.6266898
Commentary :	Proceedings of the 2012 International Conference on High Performance Computing & Simulation (HPCS 2012)

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