Fluid flow model for energy-aware server performance evaluation

Eleonora Deiana; Guy Latouche; Marie Ange Remiche

doi:10.1145/3199524.3199560

Fluid flow model for energy-aware server performance evaluation

Eleonora Deiana, Guy Latouche, Marie Ange Remiche

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Résumé

We use a fluid flow model with reactive bounds to analyse 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. Every state consumes different amounts of energy. We use a regenerative approach to calculate the stationary distribution of the system and the expected energy consumption.

langue originale	Anglais
Pages (de - à)	204-209
Nombre de pages	6
journal	Performance Evaluation Review
Volume	45
Numéro de publication	3
Les DOIs	https://doi.org/10.1145/3199524.3199560
Etat de la publication	Publié - 20 mars 2018
Evénement	35th IFIP International Symposium on Computer Performance, Modeling, Measurements and Evaluation, IFIP WG 7.3 Performance 2017 - New York, États-Unis Durée: 13 nov. 2017 → 17 nov. 2017

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10.1145/3199524.3199560

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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 analyse 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. Every state consumes different amounts of energy. We use a regenerative approach to calculate the stationary distribution of the system and the expected energy consumption.",

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AB - We use a fluid flow model with reactive bounds to analyse 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. Every state consumes different amounts of energy. We use a regenerative approach to calculate the stationary distribution of the system and the expected energy consumption.

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Fluid flow model for energy-aware server performance evaluation

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