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Erschienen in: The Journal of Supercomputing 3/2021

25.06.2020

A model-based strategy for quantifying the impact of availability on the energy flow of data centers

verfasst von: Thiago Valentim, Gustavo Callou

Erschienen in: The Journal of Supercomputing | Ausgabe 3/2021

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Abstract

The demand for higher computing power increases and, as a result, also leads to an increased demand for services hosted in cloud computing environments. It is known, for example, that in 2018 more than 4 billion people made daily access to these services through the Internet, corresponding to more than half of the world’s population. To support such services, these clouds are made available by large data centers. These systems are responsible for the increasing consumption of electricity, given the increasing number of accesses, increasing the demand for greater communication capacity, processing and high availability. Since electricity is not always obtained from renewable resources, the relentless pursuit of cloud services can have a significant environmental impact. In this context, this paper proposes an integrated and dynamic strategy that demonstrates the impact of the availability of data center architecture equipment on energy consumption. For this, we used the technique of modeling colored Petri nets (CPN), responsible for quantifying the cost, environmental impact and availability of the electricity infrastructure of the data centers under analysis. Such proposed models are supported by the developed tool, where data center designers do not need to know CPN to compute the metrics of interest. A case study was proposed to show the applicability of the proposed strategy. Significant results were obtained, showing an increase in system availability of 100%, with equivalents operating cost and environmental impact.

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Metadaten
Titel
A model-based strategy for quantifying the impact of availability on the energy flow of data centers
verfasst von
Thiago Valentim
Gustavo Callou
Publikationsdatum
25.06.2020
Verlag
Springer US
Erschienen in
The Journal of Supercomputing / Ausgabe 3/2021
Print ISSN: 0920-8542
Elektronische ISSN: 1573-0484
DOI
https://doi.org/10.1007/s11227-020-03353-4

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