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Related Experiment Video

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Experimental Investigation of the Hierarchical Control in DC Microgrids Using a Real-time Simulator

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Published on: February 14, 2025

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

Chengjian Wen¹, Yifen Mu²

¹Department of Computer Science and Engineering, Beihang University, Beijing, China.

|July 31, 2015

Summary

This summary is machine-generated.

This study introduces a new predictive controller for virtualized systems, balancing performance and power consumption. The model effectively manages energy use, achieving 33% savings while meeting 99.76% of performance requirements.

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Area of Science:

Computer Science
Electrical Engineering
Energy Systems

Background:

Virtualized computing systems are crucial for data centers, driving demand for advanced power and performance management.
Existing linear power models are inadequate for modern hardware due to significant nonlinearity and complex control dynamics.
Time delays and diverse control actions in virtual environments complicate system optimization.

Purpose of the Study:

To develop a sophisticated control strategy for virtualized systems that addresses nonlinearity and time delays.
To optimize the dynamic balance between system performance and power consumption.
To propose a discrete system state model capable of integrating control actions and time effects.

Main Methods:

A discrete system state model was constructed to represent control actions and time delays.
Performance and power consumption were defined for each state within the model.
A predictive controller was designed to dynamically optimize a quadratic cost function for performance and power.

Main Results:

The predictive controller demonstrated effectiveness in managing virtualized systems.
A balance between performance and power was achieved by adjusting controller weights.
The controller met 99.76% of performance requirements while reducing power consumption by 33% compared to open-loop control.

Conclusions:

The proposed discrete system state model and predictive controller effectively handle nonlinearity and time delays in virtualized systems.
The controller offers a significant improvement in energy efficiency without compromising performance.
This approach provides a viable solution for optimizing power and performance in modern data centers.