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
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