Abstract
As the task load of cloud system grows bigger, it becomes very important to design an efficiency task scheduling algorithm. This paper proposes a task scheduling algorithm based on genetic algorithm and ant colony optimization algorithm. The hybrid task scheduling algorithm can help the cloud system to complete users’ tasks faster. Simulation experiment results in CloudSim show that, comparing with genetic algorithm and ant colony optimization algorithm alone, the hybrid algorithm has better performance in the aspects of load balancing and optimal time span.
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CITATION STYLE
Wu, Z., Xing, S., Cai, S., Xiao, Z., & Ming, Z. (2017). A genetic-ant-colony hybrid algorithm for task scheduling in cloud system. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10135 LNCS, pp. 183–193). Springer Verlag. https://doi.org/10.1007/978-3-319-52015-5_19
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