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Energy, performance and cost efficient datacenters: A survey

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  • Zakarya, Muhammad

Abstract

Computing systems have been focused on performance improvements, driven by the demand of user applications in past few decades, particularly from 1990 to 2010. However, due to their ever-increasing energy demand which causes large energy bills and CO2 emissions, over the past six years the focus has shifted towards energy-performance aware. The average energy consumption of servers is increasing continuously; and several researchers suggest, if this trend continues further, the cost of energy consumed by a server during its lifetime will exceed the hardware costs. The energy consumption problem is even greater for large-scale infrastructures, such as clusters, grids and clouds, which consist of several thousand heterogeneous servers. Efforts are continuously made to minimize the energy consumption of these systems, but the interest of people in computational services and popularity of smart devices make it a difficult task. In this paper, we discuss the energy consumption of ICT equipment, and present a taxonomy of energy and performance efficient techniques for large computing systems covering clusters, grids and clouds (datacenters). We discuss both energy and performance efficiency, which makes this survey different from those already published in the literature. Key research papers are surveyed and mapped onto taxonomies to characterise and identify outstanding and key issues for further research. We discuss several state-of-the-art resource management techniques, reported in the literature, that claim significant improvement in the energy efficiency and performance of ICT equipment and large-scale computing systems such as datacenters, and identify a few open challenges.

Suggested Citation

  • Zakarya, Muhammad, 2018. "Energy, performance and cost efficient datacenters: A survey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 363-385.
  • Handle: RePEc:eee:rensus:v:94:y:2018:i:c:p:363-385
    DOI: 10.1016/j.rser.2018.06.005
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    References listed on IDEAS

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    1. Shuja, Junaid & Gani, Abdullah & Shamshirband, Shahaboddin & Ahmad, Raja Wasim & Bilal, Kashif, 2016. "Sustainable Cloud Data Centers: A survey of enabling techniques and technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 62(C), pages 195-214.
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    1. Idun Osnes & Anis Yazidi & Hans-Arno Jacobsen & Frank Eliassen & Sabrina Sartori, 2022. "Harnessing Task Usage Prediction and Latency Sensitivity for Scheduling Workloads in Wind-Powered Data Centers," Energies, MDPI, vol. 15(12), pages 1-16, June.
    2. Cai, Wei & Wang, Lianguo & Li, Li & Xie, Jun & Jia, Shun & Zhang, Xugang & Jiang, Zhigang & Lai, Kee-hung, 2022. "A review on methods of energy performance improvement towards sustainable manufacturing from perspectives of energy monitoring, evaluation, optimization and benchmarking," Renewable and Sustainable Energy Reviews, Elsevier, vol. 159(C).
    3. Ma, Xiaoli & Zeng, Cheng & Zhu, Zishang & Zhao, Xudong & Xiao, Xin & Akhlaghi, Yousef Golizadeh & Shittu, Samson, 2023. "Real life test of a novel super performance dew point cooling system in operational live data centre," Applied Energy, Elsevier, vol. 348(C).
    4. Zhou, Haojie & Tian, Tong & Wang, Xinyue & Li, Ji, 2023. "Combining looped heat pipe and thermoelectric generator module to pursue data center servers with possible power usage effectiveness less than 1," Applied Energy, Elsevier, vol. 332(C).
    5. Rostirolla, G. & Grange, L. & Minh-Thuyen, T. & Stolf, P. & Pierson, J.M. & Da Costa, G. & Baudic, G. & Haddad, M. & Kassab, A. & Nicod, J.M. & Philippe, L. & Rehn-Sonigo, V. & Roche, R. & Celik, B. &, 2022. "A survey of challenges and solutions for the integration of renewable energy in datacenters," Renewable and Sustainable Energy Reviews, Elsevier, vol. 155(C).

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