BoaviztAPI: A Bottom-Up Model to Assess the Environmental Impacts of Cloud Services

Awareness surrounding the environmental impacts of the digital industry has led numerous professionals to incorporate these considerations into their work. However, the conceptualization of environmental impacts has often been narrowed to the scope of carbon footprint. This limitation can be attributed to various technical and data accessibility constraints, hindering a comprehensive evaluation, including a multi-criteria analysis over the entire life cycle of digital technologies. In response to these limitations, we introduce a comprehensive bottom-up evaluation method suitable for servers and cloud instances, employing a life cycle thinking approach. We start by modeling the life cycle impacts of a server based on its hardware configuration. Then, we aggregate these with the impacts of its technical and physical environment to define the impacts of a cloud platform. We finally model the impacts of a cloud instance as a portion of the cloud platform. The proposed approach has been implemented as an open-source toolkit and published as an API. This initiative aims to provide developers and researchers with a tool for conducting environmental evaluations of their infrastructure based on open data and open methodologies, enhancing their ability to explore the environmental materiality of ICT products, services, and infrastructures.

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Publication Details

Journal
ACM SIGEnergy Energy Informatics Review
Published
2024-12-01
DOI
https://doi.org/10.1145/3727200.3727213
Citations
10
Primary Topic
Green IT and Sustainability
Type
article
Field-Weighted Citation Impact
2.09

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article

BoaviztAPI: A Bottom-Up Model to Assess the Environmental Impacts of Cloud Services

Simon Thibault, Romain Rouvoy, David Ekchajzer, Adrien Berthelot et al.
10 citations
ACM SIGEnergy Energy Informatics Review
Green IT and Sustainability
2.09
article

BoaviztAPI: A Bottom-Up Model to Assess the Environmental Impacts of Cloud Services

Simon Thibault, Romain Rouvoy, David Ekchajzer, Adrien Berthelot, Eric Fourboul, Samuel Rincé
article en
10 citations

Abstract

Awareness surrounding the environmental impacts of the digital industry has led numerous professionals to incorporate these considerations into their work. However, the conceptualization of environmental impacts has often been narrowed to the scope of carbon footprint. This limitation can be attributed to various technical and data accessibility constraints, hindering a comprehensive evaluation, including a multi-criteria analysis over the entire life cycle of digital technologies. In response to these limitations, we introduce a comprehensive bottom-up evaluation method suitable for servers and cloud instances, employing a life cycle thinking approach. We start by modeling the life cycle impacts of a server based on its hardware configuration. Then, we aggregate these with the impacts of its technical and physical environment to define the impacts of a cloud platform. We finally model the impacts of a cloud instance as a portion of the cloud platform. The proposed approach has been implemented as an open-source toolkit and published as an API. This initiative aims to provide developers and researchers with a tool for conducting environmental evaluations of their infrastructure based on open data and open methodologies, enhancing their ability to explore the environmental materiality of ICT products, services, and infrastructures.

ACM SIGEnergy Energy Informatics ReviewVol. 4(5)
École Normale Supérieure de Lyon (FR), Centre National de la Recherche Scientifique (FR), Institut national de recherche en sciences et technologies du numérique (FR), Orange (France) (FR), Université de Lille (FR), Université Paris-Saclay (FR)
Agence Nationale de la Recherche
Climate action
Openalex Percentile: Top 13%
Green IT and Sustainability
2.09
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BoaviztAPI: A Bottom-Up Model to Assess the Environmental Impacts of Cloud Services — Simon Thibault, Romain Rouvoy, et al. · ACM SIGEnergy Energy Informatics Review (2024) | TGRS Research Map | TGRS