Energy and carbon-aware distributed machine learning tasks scheduling scheme for the multi-renewable energy-based edge-cloud continuum

Energy and carbon-aware distributed machine learning tasks scheduling scheme for the multi-renewable energy-based edge-cloud continuum

As an increasing number of Distributed Machine Learning (DML) tasks are hosted on cloud platforms in the edge-cloud continuum, Data Centers (DCs) with massive data and computational requirements have become one of the world’s largest energy consumers, leading to significant carbon emissions. Reducin...

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Bibliographic Details
Main Authors: Miao Zicong, Liu Lei, Nan Haijing, Li Weize, Pan Xiaodong, Yang Xin, Yu Mi, Chen Hui, Zhao Yiming
Format: Article
Language:English
Published: EDP Sciences 2024-01-01
Series:Science and Technology for Energy Transition
Subjects:
edge-cloud continuum
dml task schedulilng
distributed data centers
multi-renewable energy
energy consumption
carbon emission
energy complementarity
Online Access:https://www.stet-review.org/articles/stet/full_html/2024/01/stet20240197/stet20240197.html
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