Abstract
Task scheduling is one of the basic problem on cloud computing. In hybrid cloud, tasks scheduling faces new challenges. In order to better deal the multi-objective task scheduling optimization in hybrid clouds, on the basis of the GaDE and Pareto optimum of quick sorting method, we present a multi-objective algorithm, named NSjDE. This algorithm also makes considerations to reduce the frequency of evaluation Comparing with experiment of Min-Min algorithm, GaDE algorithm and NSjDE algorithm, results show that for the single object task scheduling, GaDE and NsjDE algorithms perform better in getting the approximate optimal solution. The optimization speed of multi-objective NSjDE algorithm is faster than the single-objective jDE algorithm, and NSjDE can produce more than one non-dominated solution meeting the requirements, in order to provide more options to the user.
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Acknowledgment
The work was partially supported by Project 61501412 supported by National Natural Science Foundation of China.
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Fan, Y. et al. (2016). Executing Time and Cost-Aware Task Scheduling in Hybrid Cloud Using a Modified DE Algorithm. In: Li, K., Li, J., Liu, Y., Castiglione, A. (eds) Computational Intelligence and Intelligent Systems. ISICA 2015. Communications in Computer and Information Science, vol 575. Springer, Singapore. https://doi.org/10.1007/978-981-10-0356-1_8
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DOI: https://doi.org/10.1007/978-981-10-0356-1_8
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