Scheduling jobs on computational grids using a fuzzy particle swarm optimization algorithm
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F10%3A86075417" target="_blank" >RIV/61989100:27240/10:86075417 - isvavai.cz</a>
Result on the web
—
DOI - Digital Object Identifier
—
Alternative languages
Result language
angličtina
Original language name
Scheduling jobs on computational grids using a fuzzy particle swarm optimization algorithm
Original language description
Grid computing is a computational framework used to meet growing computational demands. This paper introduces a novel approach based on Particle Swarm Optimization (PSO) for scheduling jobs on computational grids. The representations of the position andvelocity of the particles in conventional PSO is extended from the real vectors to fuzzy matrices. The proposed approach is to dynamically generate an optimal schedule so as to complete the tasks within a minimum period of time as well as utilizing the resources in an efficient way. We evaluate the performance of the proposed PSO algorithm with a Genetic Algorithm (GA) and Simulated Annealing (SA) approach. Empirical results illustrate that an important advantage of the PSO algorithm is its speed of convergence and the ability to obtain faster and feasible schedules. (C) 2009 Elsevier B.V. All rights reserved
Czech name
—
Czech description
—
Classification
Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
IN - Informatics
OECD FORD branch
—
Result continuities
Project
—
Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2010
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Future Generation Computer Systems 22
ISSN
0167-739X
e-ISSN
—
Volume of the periodical
26
Issue of the periodical within the volume
8
Country of publishing house
NL - THE KINGDOM OF THE NETHERLANDS
Number of pages
8
Pages from-to
—
UT code for WoS article
000281508700026
EID of the result in the Scopus database
—