Issue |
MATEC Web of Conferences
Volume 40, 2016
2015 International Conference on Mechanical Engineering and Electrical Systems (ICMES 2015)
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Article Number | 09008 | |
Number of page(s) | 5 | |
Section | Computer information technology and application | |
DOI | https://doi.org/10.1051/matecconf/20164009008 | |
Published online | 29 January 2016 |
Cloud Computing Task Scheduling Based on Cultural Genetic Algorithm
1 College of Information and Statistics,Guangxi University of Finance and Economics, Nanning, China
2 School of Information Engineering ,Baise University, Baise, China
The task scheduling strategy based on cultural genetic algorithm(CGA) is proposed in order to improve the efficiency of task scheduling in the cloud computing platform, which targets at minimizing the total time and cost of task scheduling. The improved genetic algorithm is used to construct the main population space and knowledge space under cultural framework which get independent parallel evolution, forming a mechanism of mutual promotion to dispatch the cloud task. Simultaneously, in order to prevent the defects of the genetic algorithm which is easy to fall into local optimum, the non-uniform mutation operator is introduced to improve the search performance of the algorithm. The experimental results show that CGA reduces the total time and lowers the cost of the scheduling, which is an effective algorithm for the cloud task scheduling.
© Owned by the authors, published by EDP Sciences, 2016
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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