面向云计算数据中心的能耗建模方法

云计算对计算能力的需求，促进了大规模数据中心的飞速发展.与此同时，云计算数据中心产生了巨大的能耗.由于云计算的弹性服务和可扩展性等特性，云计算数据中心的硬件规模近年来极度膨胀，这使得过去分散的能耗问题变成了集中的能耗问题.因此，深入研究云计算数据中心的节能问题具有重要意义.为此，针对云计算数据中心的能耗问题，提出了一种精确度高的能耗模型来预测云计算数据中心单台服务器的能耗状况.精确的能量模型是很多能耗感知资源调度方法的研究基础，在大多数现有的云计算能耗研究中，多采用线性模型来描述能耗和资源利用率之间的关系.然而随着云计算数据中心服务器体系结构的变化，能耗和资源使用率的关系已经难以用简单的线性函数来描述.因此，从处理器性能计数器和系统使用情况入手，结合多元线性回归和非线性回归的数学方法，分析总结了不同参数和方法对服务器能耗建模的影响，提出了适合云计算数据中心基础架构的服务器能耗模型.实验结果表明，该能耗模型在只监控系统使用率的情况下，在系统稳定后，能耗预测精度可达到95%以上.

Energy Modeling Based on Cloud Data Center

Energy efficiency of cloud data centers has received significant attention recently as data centers often consume significant resources in operation. Most of the existing energy-saving algorithms focus on resource consolidation for energy efficiency. Accurate energy consumption model is the basis for these algorithms. This paper proposes an accurate energy model to predict energy consumption of single machine. In most of the existing cloud computing energy studies, linear models are used to describe the relationship between energy consumption and resource utilizations. However, with the changes in computer architecture, the relationship between energy and resource utilizations may not be linear. In fact, this paper explored a variety of regression analysis methods to estimate the energy consumption accurately while using low computational overhead. Initially, multiple linear regression models are used, but they often do not produce good enough results. Afterwards, this paper chooses three non-linear models and finally settled with the polynomial regression with Lasso as it produces the best estimation. Experimental results show that in adoption of energy model presented in this paper, the prediction accuracy can reach more than 95%.