A Power Monitoring System Based on a Multi-Component Power Model

A Power Monitoring System Based on a Multi-Component Power Model

Weiwei Lin (South China University of Technology, Guangzhou, China), Haoyu Wang (South China University of Technology, Guangzhou, China) and Wentai Wu (South China University of Technology, Guangzhou, China)
Copyright: © 2018 |Pages: 15
DOI: 10.4018/IJGHPC.2018010102
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As the increasing IT energy consumption emerged as a prominent issue, computer system energy consumption monitoring and optimization has gradually become a significant research forefront. However, most existing energy monitoring methods are limited to hardware-based measurement or coarse-grained energy consumption estimation. They cannot provide fine-grained energy consumption data (i.e., component energy consumption) and high-scalability for distributed cloud environments. In this article, the authors first study widely-used power models of CPUs, memory and hard disks. Then, following an investigation into disk power behaviors in sequential I/O and random I/O, they propose an improved I/O-mode aware disk power model with multiple variables and thresholds. They developed EnergyMeter, a monitoring software utility that can provide accurate power estimate by exploiting a multi-component power model. Experiments based on PCMark prove that the average error of EnergyMeter is merely 5% under a variety of workloads
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At present, most energy consumption monitoring software are still not popular. This section first analyzes the current mainstream energy consumption measurement methods. And then we introduce two energy consumption estimation software: Joulemeter and PowerTOP.

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