Data Center Sustainability: Revisits and Outlooks

IF 3 3区 计算机科学 Q2 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE
Zhiwei Cao;Xin Zhou;Xiangyu Wu;Zhaomeng Zhu;Tracy Liu;Jeffery Neng;Yonggang Wen
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Abstract

As energy-intensive entities, data centers are associated with significant environmental impacts, making their sustainability a subject of growing interest in recent years. In this article, we revisit data center sustainability and propose a forward-looking vision for improving data center sustainability. We argue that data center sustainability encompasses more than just energy efficiency and must be evaluated and optimized through a multi-faceted approach. To this end, we first present an overview of the sustainability metrics from five aspects. After that, we demonstrate the sustainability status of the latest data centers utilizing publicly available data center sustainability ratings. Furthermore, we examine the evolution of data center sustainability standards in Singapore to highlight several trending features. Based on the analysis, we identify several key elements of sustainable data centers. We then propose the Cognitive Digital Twin (CDT) architecture, which incorporates a digital twin engine for system-wide simulation and a decision engine for optimal control to improve data center sustainability. A case study is performed to optimize the chiller plant efficiency of a production data center in Singapore. The results demonstrate that the CDT can improve chiller plant energy efficiency by 5%, indicating around 140 metric tons of annual carbon emission savings.
数据中心的可持续性:回顾与展望
作为能源密集型实体,数据中心对环境有重大影响,因此其可持续性近年来日益受到关注。在本文中,我们将重新审视数据中心的可持续发展,并提出改善数据中心可持续发展的前瞻性愿景。我们认为,数据中心的可持续发展不仅包括能源效率,还必须通过多方面的方法进行评估和优化。为此,我们首先从五个方面概述了可持续性指标。然后,我们利用公开的数据中心可持续发展评级来展示最新数据中心的可持续发展状况。此外,我们还研究了新加坡数据中心可持续发展标准的演变,以突出几个趋势特征。根据分析,我们确定了可持续数据中心的几个关键要素。然后,我们提出了认知数字孪生(CDT)架构,该架构集成了用于全系统仿真的数字孪生引擎和用于优化控制的决策引擎,以提高数据中心的可持续性。我们进行了一项案例研究,以优化新加坡一个生产数据中心的冷水机组效率。结果表明,CDT 可以将冷水机组的能效提高 5%,每年可减少碳排放约 140 公吨。
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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来源期刊
IEEE Transactions on Sustainable Computing
IEEE Transactions on Sustainable Computing Mathematics-Control and Optimization
CiteScore
7.70
自引率
2.60%
发文量
54
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