Article (Scientific journals)
Scheduling with uncertainties on new computing platforms
Mahjoub, Amine; Pecero, Johnatan; Trystram, Denis
2010In Computational Optimization and Applications, 48 (2), p. 369-398
Peer reviewed
 

Files


Full Text
COAP.pdf
Publisher postprint (1.03 MB)
Request a copy

All documents in ORBilu are protected by a user license.

Send to



Details



Keywords :
Optimization; Heuristics; Scheduling; Uncertainties; Stability; Grid Computing
Abstract :
[en] New distributed computing platforms (grids) are based on interconnections of a large number of processing elements. A most important issue for their effective utilization is the optimal use of resources through proper task scheduling. It consists of allocating the tasks of a parallel program to processors on the platform and to determine at what time the tasks will start their execution. As data may be subject to uncertainties or disturbances, it is practically impossible to precisely predict the input parameters of the task scheduling problem. We briefly survey existing approaches for dealing with data uncertainties and discuss their relevance in the context of grid computing. We describe the stabilization process and analyze a scheduling algorithm that is intrinsically stable (i.e., it mitigates the effects of disturbances in input data at runtime). This algorithm is based on a decomposition of the application graph into convex sets of vertices. Finally, it is compared experimentally to pure on-line and well-known off-line algorithms.
Disciplines :
Computer science
Identifiers :
UNILU:UL-ARTICLE-2011-024
Author, co-author :
Mahjoub, Amine;  UTIC, Higher School of Sciences and Techniques of Tunis, Tunisia
Pecero, Johnatan ;  LIG, Grenoble Institute of Technology
Trystram, Denis
Language :
English
Title :
Scheduling with uncertainties on new computing platforms
Publication date :
02 March 2010
Journal title :
Computational Optimization and Applications
ISSN :
0926-6003
Publisher :
Springer Netherlands
Volume :
48
Issue :
2
Pages :
369-398
Peer reviewed :
Peer reviewed
Available on ORBilu :
since 11 February 2014

Statistics


Number of views
19 (0 by Unilu)
Number of downloads
0 (0 by Unilu)

Scopus citations®
 
10
Scopus citations®
without self-citations
8
OpenCitations
 
11
WoS citations
 
7

Bibliography


Similar publications



Contact ORBilu