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

Wen C, Mu Y - PLoS ONE (2015)

Bottom Line: 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.Experiment results show the effectiveness of the controller.

View Article: PubMed Central - PubMed

Affiliation: Department of Computer Science and Engineering, Beihang University, Beijing, China.

ABSTRACT
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.

No MeSH data available.


The architecture and control flow in the virtualized computing system.
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pone.0134017.g004: The architecture and control flow in the virtualized computing system.

Mentions: Then the flow chart with predictive controller in the virtualized computer system is drawn in Fig 4.


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

Wen C, Mu Y - PLoS ONE (2015)

The architecture and control flow in the virtualized computing system.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4520487&req=5

pone.0134017.g004: The architecture and control flow in the virtualized computing system.
Mentions: Then the flow chart with predictive controller in the virtualized computer system is drawn in Fig 4.

Bottom Line: 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.Experiment results show the effectiveness of the controller.

View Article: PubMed Central - PubMed

Affiliation: Department of Computer Science and Engineering, Beihang University, Beijing, China.

ABSTRACT
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.

No MeSH data available.