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Author manuscript, published in "5th IEEE International Conference on Cloud Computing (CLOUD) (2012)" Energy Management in IaaS Clouds: A Holistic Approach (2012)
BibTeX
@MISC{Feller12authormanuscript,,
author = {Eugen Feller and Cyril Rohr and David Margery and Christine Morin and Inria Centre and Rennes Bretagne Atlantique},
title = {Author manuscript, published in "5th IEEE International Conference on Cloud Computing (CLOUD) (2012)" Energy Management in IaaS Clouds: A Holistic Approach},
year = {2012}
}
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Abstract
Abstract—Energy efficiency has now become one of the major design constraints for current and future cloud data center operators. One way to conserve energy is to transition idle servers into a lower power-state (e.g. suspend). Therefore, virtual machine (VM) placement and dynamic VM scheduling algorithms are proposed to facilitate the creation of idle times. However, these algorithms are rarely integrated in a holistic approach and experimentally evaluated in a realistic environment. In this paper we present the energy management algorithms and mechanisms of a novel holistic energy-aware VM management framework for private clouds called Snooze. We conduct an extensive evaluation of the energy and performance implications of our system on 34 power-metered machines of the Grid’5000 experimentation testbed under dynamic web workloads. The results show that the energy saving mechanisms allow Snooze to dynamically scale data center energy consumption proportionally to the load, thus achieving substantial energy savings with only limited impact on application performance.
Keyphrases
holistic approach iaa cloud ieee international conference author manuscript cloud computing energy management virtual machine future cloud data center operator abstract energy efficiency realistic environment scale data center energy consumption idle time dynamic vm scheduling algorithm application performance extensive evaluation major design constraint dynamic web workload energy management algorithm substantial energy saving performance implication private cloud idle server power-metered machine limited impact
