文章基本信息

标题：Optimization of power consumption in data centers using machine learning based approaches: a review
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作者：Rajendra Kumar ; Sunil Kumar Khatri ; Mario José Diván 等
期刊名称：International Journal of Electrical and Computer Engineering
电子版ISSN：2088-8708
出版年度：2022
卷号：12
期号：3
页码：3192-3203
DOI：10.11591/ijece.v12i3.pp3192-3203
语种：English
出版社：Institute of Advanced Engineering and Science (IAES)
摘要：Data center hosting is in higher demand to fulfill the computing and storage requirements of information technology (IT) and cloud services platforms which need more electricity to power on the IT devices and for data center cooling requirements. Because of the increased demand for data center facilities, optimizing power usage and ensuring that data center energy quality is not compromised has become a difficult task. As a result, various machine learning-based optimization approaches for enhancing overall power effectiveness have been outlined. This paper aims to identify and analyze the key ongoing research made between 2015 and 2021 to evaluate the types of approaches being used by researchers in data center energy consumption optimization using Machine Learning algorithms. It is discussed how machine learning can be used to optimize data center power. A potential future scope is proposed based on the findings of this review by combining a mixture of bioinspired optimization and neural network.
关键词：data center;decision-making;machine learning;optimization;power usage