A DISCRETE PARTICLE SWARM OPTIMIZATION APPROACH FOR GRID JOB SCHEDULING

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F10%3A86075395" target="_blank" >RIV/61989100:27240/10:86075395 - 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 DISCRETE PARTICLE SWARM OPTIMIZATION APPROACH FOR GRID JOB SCHEDULING

Popis výsledku v původním jazyce

Scheduling is one of the core steps to efficiently exploit the capabilities of emergent computational systems such as grid. Grid environment is a dynamic, heterogeneous and unpredictable one sharing different services among many different users. Becauseof heterogeneous and dynamic nature of grid, the methods used in traditional systems could not be applied to grid scheduling and therefore new methods should be looked for. This paper represents a discrete Particle Swarm Optimization (DPSO) approach forgrid job scheduling. PSO is a population-based search algorithm based on the simulation of the social behavior of bird flocking and fish schooling. Particles fly in problem search space to find optimal or near-optimal solutions. In this paper, the scheduler aims at minimizing makespan and flowtime simultaneously in grid environment. Experimental studies illustrate that the proposed method is more efficient and surpasses those of reported meta-heuristic algorithms for this problem.

Název v anglickém jazyce

A DISCRETE PARTICLE SWARM OPTIMIZATION APPROACH FOR GRID JOB SCHEDULING

Popis výsledku anglicky

Scheduling is one of the core steps to efficiently exploit the capabilities of emergent computational systems such as grid. Grid environment is a dynamic, heterogeneous and unpredictable one sharing different services among many different users. Becauseof heterogeneous and dynamic nature of grid, the methods used in traditional systems could not be applied to grid scheduling and therefore new methods should be looked for. This paper represents a discrete Particle Swarm Optimization (DPSO) approach forgrid job scheduling. PSO is a population-based search algorithm based on the simulation of the social behavior of bird flocking and fish schooling. Particles fly in problem search space to find optimal or near-optimal solutions. In this paper, the scheduler aims at minimizing makespan and flowtime simultaneously in grid environment. Experimental studies illustrate that the proposed method is more efficient and surpasses those of reported meta-heuristic algorithms for this problem.

Druh

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

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

<a href="/cs/project/GA102%2F09%2F1494" target="_blank" >GA102/09/1494: Nové metody přenosu dat založené na turbo kódech</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2010

Kód důvěrnosti údajů

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

Název periodika

Kyushu Tokai University

ISSN

1349-4198

e-ISSN

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Svazek periodika

6

Číslo periodika v rámci svazku

9

Stát vydavatele periodika

JP - Japonsko

Počet stran výsledku

15

Strana od-do

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Kód UT WoS článku

000281745700028

EID výsledku v databázi Scopus

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