在服务器功率建模中结合全局回归和局部逼近

IF 2.4 Q1 Computer Science
Xiaoming Du, Cong Li
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引用次数: 0

摘要

为了评估绿色集群的能源使用情况,功率模型将资源利用数据作为输入来预测服务器的功耗。提出了一种结合全局线性模型和局部近似模型的功率建模新方法。该模型通过局部逼近补偿全局线性模型,具有较高的精度,同时具有全局回归模型的泛化能力,具有较强的鲁棒性。实证评估表明,新方法优于现有的两种服务器功率建模方法,即线性模型和k近邻回归模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Combining global regression and local approximation in server power modeling
To evaluate energy use in green clusters, power models take the resource utilization data as the input to predict server power consumption. We propose a novel method in power modeling combining a global linear model and a local approximation model. The new model enjoys high accuracy by compensating the global linear model with local approximation and exhibits robustness with the generalization capability of the global regression model. Empirical evaluation demonstrates that the new approach outperforms the two existing approaches to server power modeling, the linear model and the k-nearest neighbor regression model.
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来源期刊
SICS Software-Intensive Cyber-Physical Systems
SICS Software-Intensive Cyber-Physical Systems COMPUTER SCIENCE, HARDWARE & ARCHITECTURE-
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