基于改进差分进化蚁群算法的云计算资源调度

X. Xie, Ke Xu, Xiangwei Wang
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引用次数: 8

摘要

针对云计算资源分布不均匀、资源调度处理时间长等问题,提出了一种基于改进差分进化蚁群算法的云计算资源调度策略。通过改变微分进化算法中变异算子F的大小,控制微分进化算法不陷入局部搜索状态和收敛过早现象。然后将改进的差分进化算法与蚁群算法相结合,实现蚁群的保护。该算法具有局部搜索最优的特点,又具有改进差分进化算法全局进化的特点。两者的结合可以很好地优化云计算资源调度过程中负载不均衡、处理时间长等问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Cloud computing resource scheduling based on improved differential evolution ant colony algorithm
Due to the uneven distribution of cloud computing resources and the long processing time of resource scheduling, a cloud computing resource scheduling strategy based on improved differential evolution ant colony algorithm is proposed. By changing the size of the mutation operator F in the differential evolution algorithm, the differential evolution algorithm is controlled not to fall into the local search state and the convergence premature phenomenon. Then the improved differential evolution algorithm is combined with the ant colony algorithm to preserve the ant colony. The algorithm local search optimal characteristics, and has the characteristics of improved global evolution of differential evolution algorithm. The combination of the two can well optimize the problem of unbalanced load and long processing time in the cloud computing resource scheduling process.
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