Dataset : Optimal sizing of a globally distributed low carbon cloud federation

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General metadata

Identifiers :
local : FR-13002091000019-2023-02-03 external : doi:10.25666/DATAUBFC-2023-02-03
Description :
The carbon footprint of IT technologies has been a significant concern in recent years. This concern mainly focuses on the electricity consumption of data centers; many cloud suppliers commit to using 100% of renewable energy sources. However, this approach neglects the impact of device manufacturing. We consider in this work the question of dimensioning the renewable energy sources of a geographically distributed cloud with considering the carbon impact of both the grid electricity consumption in the considered locations and the manufacturing of solar panels and batteries. We design a linear program to optimize cloud dimensioning over one year, considering worldwide locations for data centers, real-life workload traces, and solar irradiation values. Our results show a carbon footprint reduction of about 30% compared to a cloud fully supplied by solar energy and of 85% compared to the 100% grid electricity model.
Disciplines :
Keywords :

Dates :
Data acquisition : from Apr 2022 ongoing
Data provision : 1 Feb 2023
Metadata record : Creation : 3 Feb 2023 Update : 16 Mar 2023

Update periodicity : as needed
Language : English (eng)
Audience : Research, Policy maker
RightsAttribution, Non Commercial, Share Alike
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Quotation

Miguel Vasconcelos, Daniel Cordeiro, Georges Da Costa, Fanny Dufossé, Jean-Marc Nicod, Veronika Rehn-Sonigo (2023): Optimal sizing of a globally distributed low carbon cloud federation. GitLab. doi:10.25666/DATAUBFC-2023-02-03

Administrative metadata

Data creators : Miguel Vasconcelos [1] [2], Daniel Cordeiro [2], Georges Da Costa [3], Fanny Dufossé [1], Jean-Marc Nicod [4], Veronika Rehn-Sonigo [5]
[1] : Laboratoire d'Informatique de Grenoble
[2] : University of São Paulo
[3] : Institut de recherche en informatique de Toulouse
[4] : Franche-Comté Electronique Mécanique Thermique et Optique - Sciences et Technologies (UMR 6174) (École Nationale Supérieure de Mécanique et des Microtechniques)
[5] : Franche-Comté Electronique Mécanique Thermique et Optique - Sciences et Technologies (UMR 6174) (Université de Franche-Comté)
Publisher : GitLab
Science contact : Jean-Marc Nicod e-mail
Computing contact : Miguel Vasconcelos e-mail
Access : available

Technical metadata

Formats : application/json, application/x-sh, text/csv, text/plain, text/x-python
Data acquisition methods :
  • Simulation or computational data :
    Considering given inputs (datacenter federation, appropriate configuration files, weather conditions, etc.), the software is able to propose an optimal sizing for the globally distributed low carbon cloud federation: surface area of solar panels, battery capacity for each data center location. . Scripts are available to shape the optimal configuration.
Datatype : Dataset

Publications

  • Miguel Vasconcelos, Daniel Cordeiro, Georges Da Costa, Fanny Dufossé, Jean-Marc Nicod and Veronika Rehn-Sonigo. Optimal sizing of a globally distributed low carbon cloud federation. in Cluster, Cloud and Internet Computing'23, Bangalore, India, May 2023. (to appear)

dat@FEMTO-ST

dat@FEMTO-ST is a sub-portal of dat@UBFC, a metadata catalogue for research data produced at UBFC.

Université de Bourgogne, Université de Franche-Comté, UTBM, AgroSup Dijon, ENSMM, BSB, Arts des Metiers