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Shares and utilities based power consolidation in virtualized server environments (2009)
| Venue: | in Proceedings of the 11th IFIP/IEEE Integrated Network Management (IM 2009 |
| Citations: | 39 - 1 self |
BibTeX
@INPROCEEDINGS{Cardosa09sharesand,
author = {Michael Cardosa and Madhukar R. Korupolu and Aameek Singh},
title = {Shares and utilities based power consolidation in virtualized server environments},
booktitle = {in Proceedings of the 11th IFIP/IEEE Integrated Network Management (IM 2009},
year = {2009}
}
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Abstract
Abstract—Virtualization technologies like VMware and Xen provide features to specify the minimum and maximum amount of resources that can be allocated to a virtual machine (VM) and a shares based mechanism for the hypervisor to distribute spare resources among contending VMs. However much of the existing work on VM placement and power consolidation in data centers fails to take advantage of these features. One of our experiments on a real testbed shows that leveraging such features can improve the overall utility of the data center by 47 % or even higher. Motivated by these, we present a novel suite of techniques for placement and power consolidation of VMs in data centers taking advantage of the min-max and shares features inherent in virtualization technologies. Our techniques provide a smooth mechanism for power-performance tradeoffs in modern data centers running heterogeneous applications, wherein the amount of resources allocated to a VM can be adjusted based on available resources, power costs, and application utilities. We evaluate our techniques on a range of large synthetic data center setups and a small real data center testbed comprising of VMware ESX servers. Our experiments confirm the end-to-end validity of our approach and demonstrate that our final candidate algorithm, PowerExpandMinMax, consistently yields the best overall utility across a broad spectrum of inputs – varying VM sizes and utilities, varying server capacities and varying power costs – thus providing a practical solution for administrators. I.
Keyphrases
power consolidation data center virtualized server environment overall utility power cost virtual machine heterogeneous application broad spectrum vm placement abstract virtualization technology practical solution vm size share feature smooth mechanism small real data center real testbed show vmware esx server modern data center virtualization technology novel suite final candidate algorithm end-to-end validity power-performance tradeoff available resource maximum amount spare resource server capacity application utility large synthetic data center setup
