Optimal job scheduling in grid computing using efficient binary artificial bee colony optimization

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F13%3A86089347" target="_blank" >RIV/61989100:27240/13:86089347 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1007/s00500-012-0957-7" target="_blank" >http://dx.doi.org/10.1007/s00500-012-0957-7</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/s00500-012-0957-7" target="_blank" >10.1007/s00500-012-0957-7</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Optimal job scheduling in grid computing using efficient binary artificial bee colony optimization

Popis výsledku v původním jazyce

The artificial bee colony has the advantage of employing fewer control parameters compared with other population-based optimization algorithms. In this paper a binary artificial bee colony (BABC) algorithm is developed for binary integer job scheduling problems in grid computing. We further propose an efficient binary artificial bee colony extension of BABC that incorporates a flexible ranking strategy (FRS) to improve the balance between exploration and exploitation. The FRS is introduced to generate and use new solutions for diversified search in early generations and to speed up convergence in latter generations. Two variants are introduced to minimize the makepsan. In the first a fixed number of best solutions is employed with the FRS while in thesecond the number of the best solutions is reduced with each new generation. Simulation results for benchmark job scheduling problems show that the performance of our proposed methods is better than those alternatives such as genetic algo

Název v anglickém jazyce

Optimal job scheduling in grid computing using efficient binary artificial bee colony optimization

Popis výsledku anglicky

The artificial bee colony has the advantage of employing fewer control parameters compared with other population-based optimization algorithms. In this paper a binary artificial bee colony (BABC) algorithm is developed for binary integer job scheduling problems in grid computing. We further propose an efficient binary artificial bee colony extension of BABC that incorporates a flexible ranking strategy (FRS) to improve the balance between exploration and exploitation. The FRS is introduced to generate and use new solutions for diversified search in early generations and to speed up convergence in latter generations. Two variants are introduced to minimize the makepsan. In the first a fixed number of best solutions is employed with the FRS while in thesecond the number of the best solutions is reduced with each new generation. Simulation results for benchmark job scheduling problems show that the performance of our proposed methods is better than those alternatives such as genetic algo

Druh

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

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

—

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

Soft computing

ISSN

1432-7643

e-ISSN

—

Svazek periodika

17

Číslo periodika v rámci svazku

5

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

16

Strana od-do

867-882

Kód UT WoS článku

000317786400011

EID výsledku v databázi Scopus

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