Resource Scheduling and Load Balancing Fusion Algorithm with Deep Learning Based on Cloud Computing

Xiaojing Hou, Guozeng Zhao
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引用次数: 11

Abstract

With the wide application of the cloud computing, the contradiction between high energy cost and low efficiency becomes increasingly prominent. In this article, to solve the problem of energy consumption, a resource scheduling and load balancing fusion algorithm with deep learning strategy is presented. Compared with the corresponding evolutionary algorithms, the proposed algorithm can enhance the diversity of the population, avoid the prematurity to some extent, and have a faster convergence speed. The experimental results show that the proposed algorithm has the most optimal ability of reducing energy consumption of data centers.
基于云计算的深度学习资源调度与负载均衡融合算法
随着云计算的广泛应用,高能源成本与低效率的矛盾日益突出。为了解决能源消耗问题,提出了一种基于深度学习策略的资源调度与负载均衡融合算法。与相应的进化算法相比,该算法可以增强种群的多样性,在一定程度上避免早熟,收敛速度更快。实验结果表明,该算法具有降低数据中心能耗的最优能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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