A hybrid metaheuristic algorithm for job scheduling on computational grids

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F13%3A86092928" target="_blank" >RIV/61989100:27240/13:86092928 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

A hybrid metaheuristic algorithm for job scheduling on computational grids

Popis výsledku v původním jazyce

The dynamic nature of grid resources and the demands of users produce complexity in the grid scheduling problem that cannot be addressed by deterministic algorithms with polynomial complexity. One of the best methods for grid scheduling is the genetic algorithm (GA); the simple and parallel features of this algorithm make it applicable to several optimization problems. A GA searches the problem space globally and is unable to search locally. Therefore, scholars have investigated combining GAs with othermeta-heuristic methods to resolve the local search problem. This is the focus of the present contribution, where we have developed a new hybrid scheduling algorithm GCA that combines GA and the gravitational emulation local search (GELS) algorithm. Thenoteworthy feature of the proposed optimal scheduler is that it decreases runtime and the number of submitted tasks whose deadlines are missed. A comparison of the performance of our proposed joint optimal scheduler to similar methods sho

Název v anglickém jazyce

A hybrid metaheuristic algorithm for job scheduling on computational grids

Popis výsledku anglicky

The dynamic nature of grid resources and the demands of users produce complexity in the grid scheduling problem that cannot be addressed by deterministic algorithms with polynomial complexity. One of the best methods for grid scheduling is the genetic algorithm (GA); the simple and parallel features of this algorithm make it applicable to several optimization problems. A GA searches the problem space globally and is unable to search locally. Therefore, scholars have investigated combining GAs with othermeta-heuristic methods to resolve the local search problem. This is the focus of the present contribution, where we have developed a new hybrid scheduling algorithm GCA that combines GA and the gravitational emulation local search (GELS) algorithm. Thenoteworthy feature of the proposed optimal scheduler is that it decreases runtime and the number of submitted tasks whose deadlines are missed. A comparison of the performance of our proposed joint optimal scheduler to similar methods sho

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

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Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2013

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Informatica

ISSN

0350-5596

e-ISSN

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Svazek periodika

37

Číslo periodika v rámci svazku

2

Stát vydavatele periodika

SI - Slovinská republika

Počet stran výsledku

8

Strana od-do

157-164

Kód UT WoS článku

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EID výsledku v databázi Scopus

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