Article (Scientific journals)
Min_c: Heterogeneous concentration policy for energy-aware scheduling of jobs with resource contention
Armenta-Cano, F.A.; Tchernykh, A.; Cortes-Mendoza, J.M. et al.
2017In Programming and Computer Software, 43 (3), p. 204-215
Peer Reviewed verified by ORBi
 

Files


Full Text
minc.pdf
Publisher postprint (2.9 MB)
Request a copy

All documents in ORBilu are protected by a user license.

Send to



Details



Abstract :
[en] In this paper, we address energy-aware online scheduling of jobs with resource contention. We propose an optimization model and present new approach to resource allocation with job concentration taking into account types of applications and heterogeneous workloads that could include CPU-intensive, diskintensive, I/O-intensive, memory-intensive, network-intensive, and other applications. When jobs of one type are allocated to the same resource, they may create a bottleneck and resource contention either in CPU, memory, disk or network. It may result in degradation of the system performance and increasing energy consumption. We focus on energy characteristics of applications, and show that an intelligent allocation strategy can further improve energy consumption compared with traditional approaches. We propose heterogeneous job consolidation algorithms and validate them by conducting a performance evaluation study using the Cloud Sim toolkit under different scenarios and real data. We analyze several scheduling algorithms depending on the type and amount of information they require.
Disciplines :
Computer science
Author, co-author :
Armenta-Cano, F.A.
Tchernykh, A.
Cortes-Mendoza, J.M.
Yahyapour, R.
Drozdov, A. Yu.
Bouvry, Pascal ;  University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC)
Kliazovich, D.
Avetisyan, A.
Nesmachnow, S.
External co-authors :
yes
Language :
English
Title :
Min_c: Heterogeneous concentration policy for energy-aware scheduling of jobs with resource contention
Publication date :
2017
Journal title :
Programming and Computer Software
ISSN :
1608-3261
Publisher :
Springer Science & Business Media B.V.
Volume :
43
Issue :
3
Pages :
204-215
Peer reviewed :
Peer Reviewed verified by ORBi
Available on ORBilu :
since 15 January 2018

Statistics


Number of views
102 (9 by Unilu)
Number of downloads
0 (0 by Unilu)

Scopus citations®
 
11
Scopus citations®
without self-citations
6
WoS citations
 
9

Bibliography


Similar publications



Contact ORBilu