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首页> 外文期刊>International Journal of Computational Science and Engineering >Executing time and cost-aware task scheduling in hybrid cloud using a modified DE algorithm
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Executing time and cost-aware task scheduling in hybrid cloud using a modified DE algorithm

机译:使用修改后的 DE 算法在混合云中执行时间和成本感知型任务调度

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Task scheduling is one of the basic problems in cloud computing. In hybrid cloud, tasks scheduling faces new challenges. In this paper, we propose a GaDE algorithm, based on differential evolution algorithm, to improve single objective scheduling performance of a hybrid cloud. In order to better deal with the multi-objective task scheduling optimisation 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 experiments 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 optimisation 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.
机译:任务调度是云计算的基本问题之一。在混合云中,任务调度面临着新的挑战。本文提出一种基于差分进化算法的GaDE算法,以提高混合云的单目标调度性能。为了更好地应对混合云中的多目标任务调度优化问题,在GaDE和Pareto最优快速排序方法的基础上,提出了一种多目标算法NSjDE。该算法还考虑了降低评估频率的因素。与Min-Min算法、GaDE算法和NSjDE算法的实验相比,结果表明,对于单目标任务调度,GaDE和NsjDE算法在获得近似最优解方面表现更好。多目标NSjDE算法的优化速度比单目标jDE算法快,NSjDE可以产生多个满足需求的非支配解,为用户提供更多选择。

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