SIMULATED ANNEALING APPROACH TO COST-BASED MULTI- QUALITY OF SERVICE JOB SCHEDULING IN CLOUD COMPUTING ENVIROMENT
- 1 Department of Information Technology, Thamar University, Thamar, Yemen
- 2 Department of Communication Technology and Network, Institute of Mathematical Science, Universiti Putra Malaysia, 43400 UPM Serdang, Selangor D.E., Malaysia
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.
Copyright: © 2014 Monir Abdullah and Mohamed Othman. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
- 2,296 Views
- 2,504 Downloads
- 12 Citations
- Simulated Annealing Algorithm
- Cloud Computing
- Quality of Service