DocumentCode :
3275884
Title :
System Power Model and Virtual Machine Power Metering for Cloud Computing Pricing
Author :
Wen Chengjian ; Long Xiang ; Yang Yang ; Fan Ni ; Yifen Mu
Author_Institution :
Dept. of Comput. Sci. & Eng., Beihang Univ., Beijing, China
fYear :
2013
fDate :
16-18 Jan. 2013
Firstpage :
1379
Lastpage :
1382
Abstract :
Multi-core virtualization platforms has been the basic infrastructure for data center for which Green computing and cloud computing are the most significant trends. Most servers don´t have build-in power measurement sensors in modern data center. Besides, even if the total server power can be measured in real time VM(virtual machine) power cannot be measured purely by any power sensor. A suitable VM power model can help data center operator save power and price the VM energy consumption in cloud computing platforms. We present a solution for system power estimation and VM power metering by using performance events counter. We build power models to infer power consumption from the system resource usage such as cpu and memory which can be indicated by certain performance events counter value. The result shows that this method can get the accuracy of 97% on average.
Keywords :
cloud computing; computer centres; multiprocessing systems; power aware computing; resource allocation; virtual machines; virtualisation; VM energy consumption; VM power model; cloud computing pricing; data center; green computing; multicore virtualization platform; performance events counter; performance events counter value; power measurement sensor; system power estimation; system resource usage; virtual machine power metering; Computational modeling; Energy consumption; Estimation; Load modeling; Power measurement; Virtualization; Yttrium; cloud computing pricing; performance counter; power metering; power model; virtual machine;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent System Design and Engineering Applications (ISDEA), 2013 Third International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4673-4893-5
Type :
conf
DOI :
10.1109/ISDEA.2012.327
Filename :
6456020
Link To Document :
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