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Assessing anthropogenic heat flux of public cloud data centers: current and future trends
Global average temperature had been significantly increasing during the past century, mainly due to the growing rates of greenhouse gas (GHG) emissions, leading to a global warming problem. Many research works indicated other causes of this problem, such as the anthropogenic heat flux (AHF). Cloud c...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8114818/ https://www.ncbi.nlm.nih.gov/pubmed/34013027 http://dx.doi.org/10.7717/peerj-cs.478 |
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author | Baniata, Hamza Mahmood, Sami Kertesz, Attila |
author_facet | Baniata, Hamza Mahmood, Sami Kertesz, Attila |
author_sort | Baniata, Hamza |
collection | PubMed |
description | Global average temperature had been significantly increasing during the past century, mainly due to the growing rates of greenhouse gas (GHG) emissions, leading to a global warming problem. Many research works indicated other causes of this problem, such as the anthropogenic heat flux (AHF). Cloud computing (CC) data centers (DCs), for example, perform massive computational tasks for end users, leading to emit huge amounts of waste heat towards the surrounding (local) atmosphere in the form of AHF. Out of the total power consumption of a public cloud DC, nearly 10% is wasted in the form of heat. In this paper, we quantitatively and qualitatively analyze the current state of AHF emissions of the top three cloud service providers (i.e., Google, Azure and Amazon) according to their average energy consumption and the global distribution of their DCs. In this study, we found that Microsoft Azure DCs emit the highest amounts of AHF, followed by Amazon and Google, respectively. We also found that Europe is the most negatively affected by AHF of public DCs, due to its small area relative to other continents and the large number of cloud DCs within. Accordingly, we present mean estimations of continental AHF density per square meter. Following our results, we found that the top three clouds (with waste heat at a rate of 1,720.512 MW) contribute an average of more than 2.8% out of averaged continental AHF emissions. Using this percentage, we provide future trends estimations of AHF densities in the period [2020–2100]. In one of the presented scenarios, our estimations predict that by 2100, AHF of public clouds DCs will reach 0.01 Wm(−2). |
format | Online Article Text |
id | pubmed-8114818 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-81148182021-05-18 Assessing anthropogenic heat flux of public cloud data centers: current and future trends Baniata, Hamza Mahmood, Sami Kertesz, Attila PeerJ Comput Sci Computer Networks and Communications Global average temperature had been significantly increasing during the past century, mainly due to the growing rates of greenhouse gas (GHG) emissions, leading to a global warming problem. Many research works indicated other causes of this problem, such as the anthropogenic heat flux (AHF). Cloud computing (CC) data centers (DCs), for example, perform massive computational tasks for end users, leading to emit huge amounts of waste heat towards the surrounding (local) atmosphere in the form of AHF. Out of the total power consumption of a public cloud DC, nearly 10% is wasted in the form of heat. In this paper, we quantitatively and qualitatively analyze the current state of AHF emissions of the top three cloud service providers (i.e., Google, Azure and Amazon) according to their average energy consumption and the global distribution of their DCs. In this study, we found that Microsoft Azure DCs emit the highest amounts of AHF, followed by Amazon and Google, respectively. We also found that Europe is the most negatively affected by AHF of public DCs, due to its small area relative to other continents and the large number of cloud DCs within. Accordingly, we present mean estimations of continental AHF density per square meter. Following our results, we found that the top three clouds (with waste heat at a rate of 1,720.512 MW) contribute an average of more than 2.8% out of averaged continental AHF emissions. Using this percentage, we provide future trends estimations of AHF densities in the period [2020–2100]. In one of the presented scenarios, our estimations predict that by 2100, AHF of public clouds DCs will reach 0.01 Wm(−2). PeerJ Inc. 2021-05-05 /pmc/articles/PMC8114818/ /pubmed/34013027 http://dx.doi.org/10.7717/peerj-cs.478 Text en ©2021 Baniata et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Computer Science) and either DOI or URL of the article must be cited. |
spellingShingle | Computer Networks and Communications Baniata, Hamza Mahmood, Sami Kertesz, Attila Assessing anthropogenic heat flux of public cloud data centers: current and future trends |
title | Assessing anthropogenic heat flux of public cloud data centers: current and future trends |
title_full | Assessing anthropogenic heat flux of public cloud data centers: current and future trends |
title_fullStr | Assessing anthropogenic heat flux of public cloud data centers: current and future trends |
title_full_unstemmed | Assessing anthropogenic heat flux of public cloud data centers: current and future trends |
title_short | Assessing anthropogenic heat flux of public cloud data centers: current and future trends |
title_sort | assessing anthropogenic heat flux of public cloud data centers: current and future trends |
topic | Computer Networks and Communications |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8114818/ https://www.ncbi.nlm.nih.gov/pubmed/34013027 http://dx.doi.org/10.7717/peerj-cs.478 |
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