Reference : Scalable and Energy-Efficient Scheduling Techniques for Large-Scale Systems

	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/10993/7009

Title :	Scalable and Energy-Efficient Scheduling Techniques for Large-Scale Systems
Language :	English
Author, co-author :	Diaz, Cesar [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC) >]
	Guzek, Mateusz [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
	Pecero, Johnatan [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC) >]
	Bouvry, Pascal [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC) >]
	Khan, Samee U. [North Dakota State University Fargo, ND, USA]
Publication date :	2011
Main document title :	Computer and Information Technology (CIT), 2011 IEEE 11th International Conference on
Pages :	641-647
Peer reviewed :	Yes
On invitation :	No
Audience :	International
ISBN :	978-0-7695-4388-8
Event name :	IEEE International Conference On Scalable Computing SCALCOM 2011
Event date :	from 31-08-2011 to 02-09-2011
Event place (city) :	Paphos
Event country :	Cyprus
Keywords :	[en] heterogenous computing systems ; energy conservation ; scheduling ; performance of systems
Abstract :	[en] The scalability of a computing system can be identified by at least three components: (a) size, (b) geograph- ical distribution, and (c) administrative constraints. Newer paradigms, such as clouds, grids, and clusters bring in more parameters to the aforementioned list, namely heterogeneity, energy consumption, and transparency. To optimize the per- formance of a computing system, it is manner that exploits heterogeneity and is scalable. Moreover, newer systems also demand energy efficiency as an integral part of schedulers. In this paper, we evaluate the behavior of low complexity energy- efficient algorithms for scheduling. The set of experimental results showed that the evaluated heuristics perform as effi- ciently as related approaches; demonstrating their applicability and scalability for the considered problem.
Research centres :	University of Luxembourg: High Performance Computing - ULHPC
Permalink :	http://hdl.handle.net/10993/7009
Commentary :	Proceedings of the 11th IEEE International Conference on Computer and Information Technology

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