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Grid-HPA: Predicting Resource Requirements of a Job in the Grid Computing Environment
| Citations: | 4 - 0 self |
BibTeX
@MISC{Bohlouli_grid-hpa:predicting,
author = {M. Bohlouli and M. Analoui},
title = {Grid-HPA: Predicting Resource Requirements of a Job in the Grid Computing Environment},
year = {}
}
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Abstract
that environment itself predicts resource requirements of a job by using special methods in the Grid computing. The exact and correct prediction causes exact matching of required resources with available resources. After the execution of each job, the used resources will be saved in the active database named "History". At first some of the attributes will be exploit from the main job and according to a defined similarity algorithm the most similar executed job will be exploited from "History " using statistic terms such as linear regression or average, resource requirements will be predicted. The new idea in this research is based on active database and centralized history maintenance. Implementation and testing of the proposed architecture results in accuracy percentage of 96.68 % to predict CPU usage of jobs and 91.29 % of memory usage and 89.80 % of the band width usage.
Keyphrases
predicting resource requirement grid computing environment resource requirement active database main job architecture result linear regression memory usage accuracy percentage correct prediction grid computing special method used resource band width usage available resource cpu usage new idea required resource statistic term centralized history maintenance
