Fluid Flow Model for Energy-Aware Server Performance Evaluation

Eleonora Deiana; Guy Latouche; Marie Ange Remiche

doi:10.1007/s11009-020-09784-z

Fluid Flow Model for Energy-Aware Server Performance Evaluation

Eleonora Deiana, Guy Latouche, Marie Ange Remiche

Research output: Contribution to journal › Article › peer-review

Abstract

We use a fluid flow model with reactive bounds to analyze a data processing center with energy-aware servers. The servers switch between four energy states depending on the level of the buffer content and on three reactive bounds. We use a regenerative approach to calculate the stationary distribution of the system and the expected energy consumption.

Original language	English
Pages (from-to)	801-821
Number of pages	21
Journal	Methodology and Computing in Applied Probability
Volume	23
Issue number	3
DOIs	https://doi.org/10.1007/s11009-020-09784-z
Publication status	Published - Sept 2021

Keywords

Fluid flow models
Markov processes
Queueing systems
Regenerative processes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1007/s11009-020-09784-z

Cite this

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title = "Fluid Flow Model for Energy-Aware Server Performance Evaluation",

abstract = "We use a fluid flow model with reactive bounds to analyze a data processing center with energy-aware servers. The servers switch between four energy states depending on the level of the buffer content and on three reactive bounds. We use a regenerative approach to calculate the stationary distribution of the system and the expected energy consumption.",

keywords = "Fluid flow models, Markov processes, Queueing systems, Regenerative processes",

author = "Eleonora Deiana and Guy Latouche and Remiche, {Marie Ange}",

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AU - Latouche, Guy

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AB - We use a fluid flow model with reactive bounds to analyze a data processing center with energy-aware servers. The servers switch between four energy states depending on the level of the buffer content and on three reactive bounds. We use a regenerative approach to calculate the stationary distribution of the system and the expected energy consumption.

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KW - Markov processes

KW - Queueing systems

KW - Regenerative processes

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Fluid Flow Model for Energy-Aware Server Performance Evaluation

Abstract

Keywords

UN SDGs

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