Reducing energy footprint in cloud computing: a study on the impact of clustering techniques and scheduling algorithms for scientific workflows-Reference-Cited by-同舟云学术

Reducing energy footprint in cloud computing: a study on the impact of clustering techniques and scheduling algorithms for scientific workflows

Published:2023-05-13 Issue:10 Volume:105 Page:2231-2261
ISSN:0010-485X
Container-title:Computing
language:en
Short-container-title:Computing

Author:

Saadi Youssef^ORCID,Jounaidi Soufiane,El Kafhali Said^ORCID,Zougagh Hicham

Publisher

Springer Science and Business Media LLC

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Numerical Analysis,Theoretical Computer Science,Software

Link

https://link.springer.com/content/pdf/10.1007/s00607-023-01182-w.pdf

Reference56 articles.

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3. Asad Z, Chaudhry MAR (2016) A two-way street: green big data processing for a greener smart grid. IEEE Syst J 11(2):784–795

4. Rincon D, Agusti-Torra A, Botero JF, Raspall F, Remondo D, Hesselbach X, Giuliani G (2013) A novel collaboration paradigm for reducing energy consumption and carbon dioxide emissions in data centres. Comput J 56(12):1518–1536

5. Ma Y, Ma G, Zhang S, Zhou F (2016) Cooling performance of a pump-driven two phase cooling system for free cooling in data centers. Appl Therm Eng 95:143–149

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