Potential effects on server power metering and modeling View Full Text


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Article Info

DATE

2018-11-29

AUTHORS

Yewan Wang, David Nörtershäuser, Stéphane Le Masson, Jean-Marc Menaud

ABSTRACT

Cloud datacenters are compute facilities formed by hundreds or even thousands of servers. With the increasing demand of cloud services, energy efficiency of servers in data center has become a significant issue. The knowledge of the energy consumption corresponding to hardware and software configuration is important for operators to optimize energy efficiency of a data center. We are currently working on a predictive model for energy consumption of a server, with inputs as service provided, hardware material equipped (type and quantity of processor, memory and hard drive) and technical environment (energy conversion and cooling). In this article, we characterize some potential factors on the power variation of the servers, such as: original fabrication, position in the rack, voltage variation and temperature of components on motherboard. The results show that certain factors, such as original fabrication, ambient temperature and CPU temperature, have noticeable effects on the power consumption of servers. The experimental results emphasize the importance of adding these external factors into the metric, so as to build an energy predictive model adaptable in real situations. More... »

PAGES

1-8

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s11276-018-1882-1

DOI

http://dx.doi.org/10.1007/s11276-018-1882-1

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1110267854


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