Independent And Dependent Job Scheduling Algorithms Based On Weighting Model For Grid Environment

Grid system has been used to solve complex problems that need years to be executed. One of the issues in improving the performance of a grid system is how to schedule the submitted jobs in an efficient, fast and reliable way. In addition, job scheduling is considered as a NP-hard problem. Therefore,...

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Main Author:	M. Al-Najjar, Hazem
Format:	Thesis
Language:	English
Published:	2018
Subjects:	T Technology
Online Access:	http://eprints.usm.my/56089/1/Independent%20And%20Dependent%20Job%20Scheduling%20Algorithms%20Based%20On%20Weighting%20Model%20For%20Grid%20Environment_Hazem%20M.%20Al-Najjar.pdf
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spelling	my-usm-ep.560892022-12-21T08:27:55Z Independent And Dependent Job Scheduling Algorithms Based On Weighting Model For Grid Environment 2018-06-01 M. Al-Najjar, Hazem T Technology TK Electrical Engineering. Electronics. Nuclear Engineering Grid system has been used to solve complex problems that need years to be executed. One of the issues in improving the performance of a grid system is how to schedule the submitted jobs in an efficient, fast and reliable way. In addition, job scheduling is considered as a NP-hard problem. Therefore, finding the optimal sequence to improve the total execution time and average waiting time will be very difficult and will consume a lot of computational resources. As a result, researchers have tried to improve job scheduling system using multiple algorithms. However, the previous algorithms are complicated and needed a lot of computational resources. Besides that, their works have not considered using job categorical variables in serving jobs as a dominant parameter. This thesis presents job weighting model using a Twostep clustering to assign the categorical and continuous variables of jobs into classes for both independent and dependent job scheduling. After that, ranking equation is used to arrange the generated classes from lightest to heaviest. Moreover, linear regression model with the generated ranking classes is employed into the proposed weighting model. The resulting model is then applied onto the independent and dependent job scheduling algorithms to verify the capability of proposed job scheduling model in a real environment. To validate the capability of the proposed weighting model which aims to improve independent job scheduling, a combination between job weight value and job ranking backfilling is considered. On the other hand, a job weight is combined with a graph of dependent jobs to improve dependent job scheduling. By simulation, independent job scheduling algorithm showed improvement in total execution time and average waiting time which is equal to 1.13 and 7.12 times, respectively. For the dependent algorithm, the results outperform the previous algorithms in total execution time and average waiting time, the improvement is 1.31 and 3.05 times, respectively. The results have demonstrated that the categorical and continuous variables of jobs can be used to improve the total execution time and average waiting time of job scheduling algorithms with less overhead in a real environment. 2018-06 Thesis http://eprints.usm.my/56089/ http://eprints.usm.my/56089/1/Independent%20And%20Dependent%20Job%20Scheduling%20Algorithms%20Based%20On%20Weighting%20Model%20For%20Grid%20Environment_Hazem%20M.%20Al-Najjar.pdf application/pdf en public phd doctoral Universiti Sains Malaysia Pusat Pengajian Kejuruteraan Elektrik dan Elektronik
institution	Universiti Sains Malaysia
collection	USM Institutional Repository
language	English
topic	T Technology T Technology
spellingShingle	T Technology T Technology M. Al-Najjar, Hazem Independent And Dependent Job Scheduling Algorithms Based On Weighting Model For Grid Environment
description	Grid system has been used to solve complex problems that need years to be executed. One of the issues in improving the performance of a grid system is how to schedule the submitted jobs in an efficient, fast and reliable way. In addition, job scheduling is considered as a NP-hard problem. Therefore, finding the optimal sequence to improve the total execution time and average waiting time will be very difficult and will consume a lot of computational resources. As a result, researchers have tried to improve job scheduling system using multiple algorithms. However, the previous algorithms are complicated and needed a lot of computational resources. Besides that, their works have not considered using job categorical variables in serving jobs as a dominant parameter. This thesis presents job weighting model using a Twostep clustering to assign the categorical and continuous variables of jobs into classes for both independent and dependent job scheduling. After that, ranking equation is used to arrange the generated classes from lightest to heaviest. Moreover, linear regression model with the generated ranking classes is employed into the proposed weighting model. The resulting model is then applied onto the independent and dependent job scheduling algorithms to verify the capability of proposed job scheduling model in a real environment. To validate the capability of the proposed weighting model which aims to improve independent job scheduling, a combination between job weight value and job ranking backfilling is considered. On the other hand, a job weight is combined with a graph of dependent jobs to improve dependent job scheduling. By simulation, independent job scheduling algorithm showed improvement in total execution time and average waiting time which is equal to 1.13 and 7.12 times, respectively. For the dependent algorithm, the results outperform the previous algorithms in total execution time and average waiting time, the improvement is 1.31 and 3.05 times, respectively. The results have demonstrated that the categorical and continuous variables of jobs can be used to improve the total execution time and average waiting time of job scheduling algorithms with less overhead in a real environment.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	M. Al-Najjar, Hazem
author_facet	M. Al-Najjar, Hazem
author_sort	M. Al-Najjar, Hazem
title	Independent And Dependent Job Scheduling Algorithms Based On Weighting Model For Grid Environment
title_short	Independent And Dependent Job Scheduling Algorithms Based On Weighting Model For Grid Environment
title_full	Independent And Dependent Job Scheduling Algorithms Based On Weighting Model For Grid Environment
title_fullStr	Independent And Dependent Job Scheduling Algorithms Based On Weighting Model For Grid Environment
title_full_unstemmed	Independent And Dependent Job Scheduling Algorithms Based On Weighting Model For Grid Environment
title_sort	independent and dependent job scheduling algorithms based on weighting model for grid environment
granting_institution	Universiti Sains Malaysia
granting_department	Pusat Pengajian Kejuruteraan Elektrik dan Elektronik
publishDate	2018
url	http://eprints.usm.my/56089/1/Independent%20And%20Dependent%20Job%20Scheduling%20Algorithms%20Based%20On%20Weighting%20Model%20For%20Grid%20Environment_Hazem%20M.%20Al-Najjar.pdf
_version_	1776101130807279616

Independent And Dependent Job Scheduling Algorithms Based On Weighting Model For Grid Environment

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