The pervasive use of virtualization techniques in today's datacenters poses challenges in power monitoring since it is not possible to directly measure the power consumption of a virtual entity such as a virtual machine (VM) and a container. In this paper, we present cWatts++, a lightweight virtual power meter that enables accurate power usage measurement in virtualized computing environments such as VMs and containers of Cloud data centers. At the core of cWatts++ is its application-agnostic power model. To this end, we devise two power models (eventModel and raplModel) that are driven by CPU event counters and the Running Average Power Limit (RAPL) feature of modern Intel CPUs, respectively. While eventModel is more generic and, thus, applicable to a wide range of workloads, raplModel is particularly good for CPU-bound workloads. We have evaluated cWatts++ with its two power models in a real system using the PARSEC benchmark suite and our in-house benchmarks. Our evaluation study demonstrates that these power models have an average error of 4.55 and 1.25 percent, respectively, compared with actual power usage measurements of a real power meter, Cabac Power-Mate.

中文翻译：

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用于虚拟化计算环境的轻量级电源监控框架

由于无法直接测量虚拟机 (VM) 和容器等虚拟实体的功耗，因此当今数据中心广泛使用虚拟化技术对电源监控提出了挑战。在本文中，我们介绍了 cWatts++，这是一种轻量级虚拟功率计，可在虚拟化计算环境（如云数据中心的 VM 和容器）中实现准确的电力使用测量。cWatts++ 的核心是其与应用程序无关的电源模型。为此，我们设计了两个分别由 CPU 事件计数器和现代 Intel CPU 的运行平均功率限制 (RAPL) 功能驱动的功率模型（eventModel 和 raplModel）。虽然 eventModel 更通用，因此适用于范围广泛的工作负载，但 raplModel 特别适合 CPU 密集型工作负载。我们已经使用 PARSEC 基准套件和我们的内部基准在真实系统中评估了 cWatts++ 及其两个功率模型。我们的评估研究表明，与实际功率计 Cabac Power-Mate 的实际功率使用测量值相比，这些功率模型的平均误差分别为 4.55% 和 1.25%。