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Power and Performance Management in Nonlinear Virtualized Computing Systems via Predictive Control

The problem of power and performance management captures growing research interest in both academic and industrial field. Virtulization, as an advanced technology to conserve energy, has become basic architecture for most data centers. Accordingly, more sophisticated and finer control are desired in...

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Detalles Bibliográficos
Autores principales: Wen, Chengjian, Mu, Yifen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4520487/
https://www.ncbi.nlm.nih.gov/pubmed/26225769
http://dx.doi.org/10.1371/journal.pone.0134017
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author Wen, Chengjian
Mu, Yifen
author_facet Wen, Chengjian
Mu, Yifen
author_sort Wen, Chengjian
collection PubMed
description The problem of power and performance management captures growing research interest in both academic and industrial field. Virtulization, as an advanced technology to conserve energy, has become basic architecture for most data centers. Accordingly, more sophisticated and finer control are desired in virtualized computing systems, where multiple types of control actions exist as well as time delay effect, which make it complicated to formulate and solve the problem. Furthermore, because of improvement on chips and reduction of idle power, power consumption in modern machines shows significant nonlinearity, making linear power models(which is commonly adopted in previous work) no longer suitable. To deal with this, we build a discrete system state model, in which all control actions and time delay effect are included by state transition and performance and power can be defined on each state. Then, we design the predictive controller, via which the quadratic cost function integrating performance and power can be dynamically optimized. Experiment results show the effectiveness of the controller. By choosing a moderate weight, a good balance can be achieved between performance and power: 99.76% requirements can be dealt with and power consumption can be saved by 33% comparing to the case with open loop controller.
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spelling pubmed-45204872015-08-06 Power and Performance Management in Nonlinear Virtualized Computing Systems via Predictive Control Wen, Chengjian Mu, Yifen PLoS One Research Article The problem of power and performance management captures growing research interest in both academic and industrial field. Virtulization, as an advanced technology to conserve energy, has become basic architecture for most data centers. Accordingly, more sophisticated and finer control are desired in virtualized computing systems, where multiple types of control actions exist as well as time delay effect, which make it complicated to formulate and solve the problem. Furthermore, because of improvement on chips and reduction of idle power, power consumption in modern machines shows significant nonlinearity, making linear power models(which is commonly adopted in previous work) no longer suitable. To deal with this, we build a discrete system state model, in which all control actions and time delay effect are included by state transition and performance and power can be defined on each state. Then, we design the predictive controller, via which the quadratic cost function integrating performance and power can be dynamically optimized. Experiment results show the effectiveness of the controller. By choosing a moderate weight, a good balance can be achieved between performance and power: 99.76% requirements can be dealt with and power consumption can be saved by 33% comparing to the case with open loop controller. Public Library of Science 2015-07-30 /pmc/articles/PMC4520487/ /pubmed/26225769 http://dx.doi.org/10.1371/journal.pone.0134017 Text en © 2015 Wen, Mu http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Wen, Chengjian
Mu, Yifen
Power and Performance Management in Nonlinear Virtualized Computing Systems via Predictive Control
title Power and Performance Management in Nonlinear Virtualized Computing Systems via Predictive Control
title_full Power and Performance Management in Nonlinear Virtualized Computing Systems via Predictive Control
title_fullStr Power and Performance Management in Nonlinear Virtualized Computing Systems via Predictive Control
title_full_unstemmed Power and Performance Management in Nonlinear Virtualized Computing Systems via Predictive Control
title_short Power and Performance Management in Nonlinear Virtualized Computing Systems via Predictive Control
title_sort power and performance management in nonlinear virtualized computing systems via predictive control
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4520487/
https://www.ncbi.nlm.nih.gov/pubmed/26225769
http://dx.doi.org/10.1371/journal.pone.0134017
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