An Improved Estimation Model of Server Power Consumptionfor Saving Energy in a Server Cluster Environment 


Vol. 19,  No. 3, pp. 139-146, Jun.  2012
10.3745/KIPSTA.2012.19.3.139


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  Abstract

In the server cluster environment, one of the ways saving energy is to control server`s power according to traffic conditions. This is to determine the ON/OFF state of servers according to energy usage of data center and each server. To do this, we need a way to estimate each server`s energy. In this paper, we use a software-based power consumption estimation model because it is more efficient than the hardware model using power meter in terms of energy and cost. The traditional software-based power consumption estimation model has a drawback in that it doesn`t know well the computing status of servers because it uses only the idle status field of CPU. Therefore it doesn`t estimate consumption power effectively, In this paper, we present a CPU field based power consumption estimation model to estimate more accurate than the two traditional models (CPU/Disk/Memory utilization based power consumption estimation model and CPU idle utilization based power consumption estimation model) by using the various status fields of CPU to get the CPU status of servers and the overall status of system. We performed experiments using 2 PCs and compared the power consumption estimated by the power consumption model (software) with that measured by the power meter (hardware). The experimental results show that the traditional model has about 8-15% average error rate but our proposed model has about 2% average error rate.

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[IEEE Style]

D. J. Kim, H. K. Kwak, H. U. Kwon, Y. J. Kim, K. S. Chung, "An Improved Estimation Model of Server Power Consumptionfor Saving Energy in a Server Cluster Environment," The KIPS Transactions:PartA, vol. 19, no. 3, pp. 139-146, 2012. DOI: 10.3745/KIPSTA.2012.19.3.139.

[ACM Style]

Dong Jun Kim, Hu Keun Kwak, Hui Ung Kwon, Young Jong Kim, and Kyu Sik Chung. 2012. An Improved Estimation Model of Server Power Consumptionfor Saving Energy in a Server Cluster Environment. The KIPS Transactions:PartA, 19, 3, (2012), 139-146. DOI: 10.3745/KIPSTA.2012.19.3.139.

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