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Evaluating power efficient algorithms for efficiency and carbon emissions in cloud data centers: A review

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  • Uddin, Mueen
  • Darabidarabkhani, Yasaman
  • Shah, Asadullah
  • Memon, Jamshed

Abstract

A Data center comprises of servers, storage devices, cooling and power delivery equipment to support other components, exchange data and information to provide general services such as software-as-a-service (SaaS), platform-as-a-service (PaaS), and Internet-as-a-service (IaaS). Data centers require massive amount of computational power to drive complex systems. In return these massive systems bring many challenges and concerns including power dissipation and environmental sustainability. Higher power demand in data centers and changes in computing technology together to maximize data center performance has led to deploying multitude methods to estimate power intensity. Energy cost increment, global economic downturn, and global warming and other concerns have resulted in new research in achieving power efficient data centers.

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  • Uddin, Mueen & Darabidarabkhani, Yasaman & Shah, Asadullah & Memon, Jamshed, 2015. "Evaluating power efficient algorithms for efficiency and carbon emissions in cloud data centers: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 51(C), pages 1553-1563.
  • Handle: RePEc:eee:rensus:v:51:y:2015:i:c:p:1553-1563
    DOI: 10.1016/j.rser.2015.07.061
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    References listed on IDEAS

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    6. Mueen Uddin & Azizah Abdul Rahman & Asadullah Shah, 2012. "Criteria to select energy efficiency metrics to measure performance of data centre," International Journal of Energy Technology and Policy, Inderscience Enterprises Ltd, vol. 8(3/4/5/6), pages 224-237.
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    Cited by:

    1. Liu, Wenyu & Yan, Yuejun & Sun, Yimeng & Mao, Hongju & Cheng, Ming & Wang, Peng & Ding, Zhaohao, 2023. "Online job scheduling scheme for low-carbon data center operation: An information and energy nexus perspective," Applied Energy, Elsevier, vol. 338(C).
    2. Di Salvo, André L.A. & Agostinho, Feni & Almeida, Cecília M.V.B. & Giannetti, Biagio F., 2017. "Can cloud computing be labeled as “green”? Insights under an environmental accounting perspective," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 514-526.
    3. Jing Ni & Bowen Jin & Bo Zhang & Xiaowei Wang, 2017. "Simulation of Thermal Distribution and Airflow for Efficient Energy Consumption in a Small Data Centers," Sustainability, MDPI, vol. 9(4), pages 1-16, April.
    4. Shiping Xu & Lili Wang, 2023. "Do Green Information and Communication Technologies (ICT) and Smart Urbanization Reduce Environmental Pollution in China?," Sustainability, MDPI, vol. 15(19), pages 1-18, October.
    5. Jerez Monsalves, Juan & Bergaentzlé, Claire & Keles, Dogan, 2023. "Impacts of flexible-cooling and waste-heat recovery from data centres on energy systems: A Danish case study," Energy, Elsevier, vol. 281(C).
    6. Li, Chao & Mao, Ruiyong & Wang, Yong & Zhang, Jun & Lan, Jiang & Zhang, Zujing, 2024. "Experimental study on direct evaporative cooling for free cooling of data centers," Energy, Elsevier, vol. 288(C).

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