International Transactions on Evolutionary and Metaheuristic Algorithms
Vol. 1, No. 1, Nov. 2015
A Novel Job Scheduler for Computational Grid Using Simulated Annealing Heuristic | Original Paper
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a Masjed-Soleiman Branch, Islamic Azad University (I.A.U), Masjed-Soleiman, Iran b Masjed-Soleiman Branch, Islamic Azad University (I.A.U), Masjed-Soleiman, Iran c Masjed-Soleiman Branch, Islamic Azad University (I.A.U), Masjed-Soleiman, Iran d Refer to the Manuscript for Other Authors, Addresses, and Affiliations
Eng. Hamid Saadi
Corresponding Author
Affiliation: Masjed-Soleiman Branch, Islamic Azad University (I.A.U), Masjed-Soleiman, Iran
Tel: +980916
E-mail: hamid.saadi@gmail.com
Biography: HAMID SAADI received his B.S. degree in Computer Engineering from Sharif University of Technology, Tehran, Iran, in 2004 and the M.S. degree in Software Engineering from Iran University of Science and Technology, Tehran, Iran, in 2006. His interests include advanced heuristic search algorithms, information retrieval, grid computing, and scheduling. Eng. Hamid Saadi's publications in ICSES
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This article has been retracted by International Computer Science and Engineering Society (ICSES) because of ethical misconduct, scientific distortion, or administrative error, and cannot be downloaded and used for any purpose based on the violation in ICSES Ethics in Publicationcall_made |
Retraction Note by the Editor-in-Chief
Highlights and Novelties
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Manuscript Abstract
Computational Grids enable the coordinated and aggregated use of geographically distributed resources for solving large-scale problems in science, engineering, and commerce. Achieving high performance in a grid system requires effective resource scheduling. The heterogeneous and dynamic nature of the grid, as well as the differing demands of applications running on the grid makes grid scheduling complicated. Also, the execution cost, besides the completion time, has become the great concern to the grid users. Many of grid scheduling systems optimize completion time and execution cost separately. In this paper, a novel scheduling algorithm based on simulated annealing heuristic which considers both the completion time and execution cost is introduced. The proposed model applies a weighted objective function that takes into account both the completion time and execution cost of the tasks. The results obtained from our algorithm have been compared with several algorithms such as random, best of N random and climb search algorithm according to the criteria of completion time and execution cost. We show that the proposed SA scheduler produces a comparatively better result in the case of both time and cost optimization.
Keywords
Computational grid scheduling Optimization simulated annealing.
Copyright and Licence
© Copyright was transferred to International Computer Science and Engineering Society (ICSES) by all the Authors. This manuscript is published in Open-Access manner based on the copyright licence of Creative Commons Attribution Non Commercial 4.0 International (CC BY-NC 4.0).
Cite this manuscript as
Hamid Saadi, AbdolHamid MomenZadeh, Ehsan PourAliAkbar, et al., "A Novel Job Scheduler for Computational Grid Using Simulated Annealing Heuristic," International Transactions on Evolutionary and Metaheuristic Algorithms, vol. 1, no. 1, pp. 6-13, Nov. 2015.
For External Scientific Databeses
--BibTex--
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@article{al._8 title="A Novel Job Scheduler for Computational Grid Using Simulated Annealing Heuristic", author="Hamid Saadi", author="AbdolHamid MomenZadeh", author="Ehsan PourAliAkbar", author="et al.", journal="International Transactions on Evolutionary and Metaheuristic Algorithms (ITEMA)", volume="1", number="1", pages="6-13", year="2015", month="11", day="01", publisher= "International Computer Science and Engineering Society (ICSES)", doi="", url="http://www.i-cses.com/files/download.php?pID=8"}
--EndNote--
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%0 Journal Article %T A Novel Job Scheduler for Computational Grid Using Simulated Annealing Heuristic %A Hamid Saadi %A AbdolHamid MomenZadeh %A Ehsan PourAliAkbar %A et al. %J International Transactions on Evolutionary and Metaheuristic Algorithms (ITEMA) %V 1 %N 1 %P 6-13 %D 2015 %I International Computer Science and Engineering Society (ICSES) %U http://www.i-cses.com/files/download.php?pID=8 %8 2015-11-30 %R %@ 2467-291X
--Dublin--
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