This paper focuses on the power management of state-of-the-art networked devices (like common PCs, servers, set-top boxes, etc.) to evaluate their behavior, model their internal dynamics and possible sources of inefficiency, and optimize their performance and energy efficiency. To this purpose, we started from an experimental characterization of the power management schemes in common device platforms based on commercial off-the-shelf hardware and open-source software (i.e., common PCs/servers devices running the Linux operating system). The characterization allowed us to formalize an analytical model able to accurately capture the power management dynamics at hardware (at ACPI level and beyond) and software levels (Linux Governors). Finally, the proposed model has been applied to analyze the efficiency of networked devices according to various configurations of internal parameters and incoming workload. Thanks to its intrinsic accuracy and the representation of different fine-grained details, the model is able to provide precious information on the possible sources of inefficiency, and on how to act on policy parameters to optimize the system behavior.

Modeling Power Management in Networked Devices

LOMBARDO, Alfio;SCHEMBRA, Giovanni
2014-01-01

Abstract

This paper focuses on the power management of state-of-the-art networked devices (like common PCs, servers, set-top boxes, etc.) to evaluate their behavior, model their internal dynamics and possible sources of inefficiency, and optimize their performance and energy efficiency. To this purpose, we started from an experimental characterization of the power management schemes in common device platforms based on commercial off-the-shelf hardware and open-source software (i.e., common PCs/servers devices running the Linux operating system). The characterization allowed us to formalize an analytical model able to accurately capture the power management dynamics at hardware (at ACPI level and beyond) and software levels (Linux Governors). Finally, the proposed model has been applied to analyze the efficiency of networked devices according to various configurations of internal parameters and incoming workload. Thanks to its intrinsic accuracy and the representation of different fine-grained details, the model is able to provide precious information on the possible sources of inefficiency, and on how to act on policy parameters to optimize the system behavior.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11769/30691
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