An experiment-driven energy consumption model for virtual machine management systems

•Host configuration greatly influences on energy consumption.•The cost of VM management operations is non-negligible.•Migration cost varies with the host configuration. As energy consumption is becoming critical in Cloud data centers, Cloud providers are adopting energy-efficient virtual machines ma...

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Bibliographic Details
Published in:Sustainable computing informatics and systems 2018-06, Vol.18, p.163-174
Main Authors: Callau-Zori, Mar, Samoila, Lavinia, Orgerie, Anne-Cécile, Pierre, Guillaume
Format: Article
Language:English
Subjects:
Cloud computing
Computer Science
Distributed, Parallel, and Cluster Computing
Energy model
Green computing
Networking and Internet Architecture
Virtual machine management
Virtual machine migration
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Summary:•Host configuration greatly influences on energy consumption.•The cost of VM management operations is non-negligible.•Migration cost varies with the host configuration. As energy consumption is becoming critical in Cloud data centers, Cloud providers are adopting energy-efficient virtual machines management systems. These systems essentially rely on “what-if” analysis to determine what the consequence of their actions would be and to choose the best one according to a number of metrics. However, modeling energy consumption of simple operations such as starting a new VM or live-migrating is complicated by the fact that multiple phenomena occur. It is therefore important to identify which factors influence energy consumption before proposing any new model. We claim in this paper that one critical parameter is the host configuration, characterized by the number of VMs it is currently executing. Based on this observation, we present an energy model that provides energy estimation associated with VM management operations, such as VMs placement, VM start up and VM migration. The average relative estimation error is lower than 10% using the transactional web benchmark TPC-W, making it a good candidate for driving the actions of future energy-aware cloud management systems.
ISSN:2210-5379
DOI:10.1016/j.suscom.2017.11.001