Citation
Abstract
Cloud computing environments facilitate applications by providing visualized resources that can be provisioned dynamically. The advent of cloud computing as a new model of service provisioning in distributed systems, encourages researchers to investigate its benefits and drawbacks in executing scientific applications such as workflows. One of the fundamental issues in this environment is related to task scheduling. Cloud task scheduling is an NP-hard optimization problem and many meta-heuristic algorithms have been proposed to solve it. A good task scheduler should adapt its scheduling strategy to the changing environment and the types of tasks with minimum scheduler execution time. A Genetic Algorithm (GA) for job scheduling has been proposed and produced good results. The main disadvantage of GA algorithm is time consuming problem. In this study, a novel Simulated Annealing (SA) algorithm is proposed for scheduling task in cloud environment. SA based approach produced comparative result in a minimal execution time.
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Official URL or Download Paper: http://thescipub.com/abstract/10.3844/ajassp.2014....
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Additional Metadata
Item Type: | Article |
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Divisions: | Institute for Mathematical Research Faculty of Computer Science and Information Technology |
DOI Number: | https://doi.org/10.3844/ajassp.2014.872.877 |
Publisher: | Science Publications |
Keywords: | Simulated annealing algorithm; Cloud computing; Quality of service |
Depositing User: | Nurul Ainie Mokhtar |
Date Deposited: | 05 Jan 2016 07:04 |
Last Modified: | 22 Nov 2017 09:33 |
Altmetrics: | http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.3844/ajassp.2014.872.877 |
URI: | http://psasir.upm.edu.my/id/eprint/35376 |
Statistic Details: | View Download Statistic |
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