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Simulated annealing approach to cost-based multi- quality of service job scheduling in cloud computing enviroment


Citation

Abdullah, Monir and Othman, Mohamed (2014) Simulated annealing approach to cost-based multi- quality of service job scheduling in cloud computing enviroment. American Journal of Applied Sciences, 11 (6). pp. 872-877. ISSN 1546-9239; ESSN: 1554-3641

Abstract / Synopsis

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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Additional Metadata

Item Type: Article
Divisions: Institute for Mathematical Research
Faculty of Computer Science and Information Technology
DOI Number: 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 15:04
Last Modified: 22 Nov 2017 17:33
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
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