xPUE：面向云基础设施扩展电能使用效率度量指标
xPUE: Extending Power Usage Effectiveness Metrics for Cloud Infrastructures
AI总结：
本文提出xPUE指标，将传统PUE扩展到从硬件到软件层的云基础设施全栈能效评估，为云生态提供实时、多视角的能耗优化依据。
摘要：
过去几年中，数据中心的能耗分析与优化已成为越来越受关注的话题。人们普遍认识到，已有若干有效指标可用于刻画这些基础设施中托管的硬件和/或软件的效率。然而，针对特定基础设施选择相应指标并随时间评估其效率，仍被视为一个开放问题。为此，诸如电能使用效率（Power Usage Effectiveness，PUE）等能效指标被用于评估基础设施计算设备的效率。但该指标止步于所托管服务器的供电环节，无法提供更细的粒度来深入洞察云基础设施中运行硬件和软件的电能使用效率。因此，我们提出利用互补的PUE指标，命名为xPUE，来计算从硬件组件到上层运行软件层的计算连续体的能源效率。我们的贡献旨在从不同视角为云基础设施提供实时能效指标，从而帮助云生态系统——从云提供商到其客户——进行实验并大规模优化云基础设施的能源使用。
英文摘要：
The energy consumption analysis and optimization of data centers have been an increasingly popular topic over the past few years. It is widely recognized that several effective metrics exist to capture the efficiency of hardware and/or software hosted in these infrastructures. Unfortunately, choosing the corresponding metrics for specific infrastructure and assessing its efficiency over time is still considered an open problem. For this purpose, energy efficiency metrics, such as the Power Usage Effectiveness (PUE), assess the efficiency of the computing equipment of the infrastructure. However, this metric stops at the power supply of hosted servers and fails to offer a finer granularity to bring a deeper insight into the Power Usage Effectiveness of hardware and software running in cloud infrastructure.Therefore, we propose to leverage complementary PUE metrics, coined xPUE, to compute the energy efficiency of the computing continuum from hardware components, up to the running software layers. Our contribution aims to deliver realtime energy efficiency metrics from different perspectives for cloud infrastructure, hence helping cloud ecosystems-from cloud providers to their customers-to experiment and optimize the energy usage of cloud infrastructures at large.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
