云数据中心服务器能耗建模及量化计算

Energy Consumption Modeling and Quantitative Calculation of Servers in Cloud Data Center

构建精确的服务器能耗模型有助于资源提供者预测和优化数据中心的能耗.针对以往数据中心服务器因未考虑“负载的特征”而导致能耗模型精度低的问题,本文提出一种新的能耗建模及量化计算方法,其主要思路如下:根据数据中心服务器所处理任务特征的不同将其分成三类,分别为计算密集型任务、Web事务型任务和I/O密集型任务;针对每一种类型任务,分析其对服务器各部件能耗的影响;利用“主成分分析法”分析各部件参数对能耗的贡献并选择最具代表性的参数,进而结合多元线性回归和非线性回归方法建立能耗模型.实验结果表明,本文建立的能耗模型预测精度能达到95%以上;与其它模型相比,精度可提高3%左右.

Building an accurate energy-consumption model of servers can assist resource providers in predicting and optimizing energy consumption of data center.To address the problem of low accuracy of energy consumption model caused by the failure to consider"load characteristics"of servers in data center,a new energy consumption model and quantitative calculation method are proposed in this paper.The main ideas are summarized as follows:Firstly,we divide the tasks into three classes:CPU intensive task,transactional web task,and I/O intensive task.Then,energy consumption contributions of all components in a server are analyzed.After that,the dominant component parameters of server energy consumption are chosen by using the Principal Component Analysis(PCA),to build a power model through the multiple linear regression method and non-linear regression method.Experimental results show that the prediction accuracy of the proposed energy consumption model can achieve more than 95%.Compared with other energy consumption models,the accuracy can be improved by around 3%.