IDEAS home Printed from https://ideas.repec.org/a/eee/rensus/v51y2015icp1553-1563.html
   My bibliography  Save this article

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

Author

Listed:
  • 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.

Suggested Citation

  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S136403211500708X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.rser.2015.07.061?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Habibi Khalaj, Ali & Scherer, Thomas & Siriwardana, Jayantha & Halgamuge, Saman K., 2015. "Multi-objective efficiency enhancement using workload spreading in an operational data center," Applied Energy, Elsevier, vol. 138(C), pages 432-444.
    2. Oró, Eduard & Depoorter, Victor & Garcia, Albert & Salom, Jaume, 2015. "Energy efficiency and renewable energy integration in data centres. Strategies and modelling review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 42(C), pages 429-445.
    3. Uddin, Mueen & Rahman, Azizah Abdul, 2012. "Energy efficiency and low carbon enabler green IT framework for data centers considering green metrics," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(6), pages 4078-4094.
    4. Zhang, Hainan & Shao, Shuangquan & Xu, Hongbo & Zou, Huiming & Tian, Changqing, 2014. "Free cooling of data centers: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 35(C), pages 171-182.
    5. Depoorter, Victor & Oró, Eduard & Salom, Jaume, 2015. "The location as an energy efficiency and renewable energy supply measure for data centres in Europe," Applied Energy, Elsevier, vol. 140(C), pages 338-349.
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. 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).
    3. Habibi Khalaj, Ali & Abdulla, Khalid & Halgamuge, Saman K., 2018. "Towards the stand-alone operation of data centers with free cooling and optimally sized hybrid renewable power generation and energy storage," Renewable and Sustainable Energy Reviews, Elsevier, vol. 93(C), pages 451-472.
    4. Chu, Wen-Xiao & Wang, Chi-Chuan, 2019. "A review on airflow management in data centers," Applied Energy, Elsevier, vol. 240(C), pages 84-119.
    5. Habibi Khalaj, Ali & Halgamuge, Saman K., 2017. "A Review on efficient thermal management of air- and liquid-cooled data centers: From chip to the cooling system," Applied Energy, Elsevier, vol. 205(C), pages 1165-1188.
    6. Oró, Eduard & Depoorter, Victor & Garcia, Albert & Salom, Jaume, 2015. "Energy efficiency and renewable energy integration in data centres. Strategies and modelling review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 42(C), pages 429-445.
    7. 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.
    8. Wang, Fengjuan & Lv, Chengwei & Xu, Jiuping, 2023. "Carbon awareness oriented data center location and configuration: An integrated optimization method," Energy, Elsevier, vol. 278(C).
    9. Silva-Llanca, Luis & Ortega, Alfonso & Fouladi, Kamran & del Valle, Marcelo & Sundaralingam, Vikneshan, 2018. "Determining wasted energy in the airside of a perimeter-cooled data center via direct computation of the Exergy Destruction," Applied Energy, Elsevier, vol. 213(C), pages 235-246.
    10. Petrović, Stefan & Colangelo, Alessandro & Balyk, Olexandr & Delmastro, Chiara & Gargiulo, Maurizio & Simonsen, Mikkel Bosack & Karlsson, Kenneth, 2020. "The role of data centres in the future Danish energy system," Energy, Elsevier, vol. 194(C).
    11. Huang, Pei & Copertaro, Benedetta & Zhang, Xingxing & Shen, Jingchun & Löfgren, Isabelle & Rönnelid, Mats & Fahlen, Jan & Andersson, Dan & Svanfeldt, Mikael, 2020. "A review of data centers as prosumers in district energy systems: Renewable energy integration and waste heat reuse for district heating," Applied Energy, Elsevier, vol. 258(C).
    12. Maria Avgerinou & Paolo Bertoldi & Luca Castellazzi, 2017. "Trends in Data Centre Energy Consumption under the European Code of Conduct for Data Centre Energy Efficiency," Energies, MDPI, vol. 10(10), pages 1-18, September.
    13. Zhiyuan Liu & Hang Yu & Rui Liu & Meng Wang & Chaoen Li, 2020. "Configuration Optimization Model for Data-Center-Park-Integrated Energy Systems under Economic, Reliability, and Environmental Considerations," Energies, MDPI, vol. 13(2), pages 1-22, January.
    14. Ni, Jiacheng & Bai, Xuelian, 2017. "A review of air conditioning energy performance in data centers," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 625-640.
    15. Habibi Khalaj, Ali & Scherer, Thomas & K. Halgamuge, Saman, 2016. "Energy, environmental and economical saving potential of data centers with various economizers across Australia," Applied Energy, Elsevier, vol. 183(C), pages 1528-1549.
    16. Cheung, Howard & Wang, Shengwei & Zhuang, Chaoqun & Gu, Jiefan, 2018. "A simplified power consumption model of information technology (IT) equipment in data centers for energy system real-time dynamic simulation," Applied Energy, Elsevier, vol. 222(C), pages 329-342.
    17. Matteo Manganelli & Alessandro Soldati & Luigi Martirano & Seeram Ramakrishna, 2021. "Strategies for Improving the Sustainability of Data Centers via Energy Mix, Energy Conservation, and Circular Energy," Sustainability, MDPI, vol. 13(11), pages 1-25, May.
    18. Maroua Haddad & Jean-Marc Nicod & Marie-Cécile Péra & Christophe Varnier, 2021. "Stand-alone renewable power system scheduling for a green data center using integer linear programming," Journal of Scheduling, Springer, vol. 24(5), pages 523-541, October.
    19. Zhang, Hainan & Shao, Shuangquan & Tian, Changqing & Zhang, Kunzhu, 2018. "A review on thermosyphon and its integrated system with vapor compression for free cooling of data centers," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 789-798.
    20. Rong, Huigui & Zhang, Haomin & Xiao, Sheng & Li, Canbing & Hu, Chunhua, 2016. "Optimizing energy consumption for data centers," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 674-691.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:rensus:v:51:y:2015:i:c:p:1553-1563. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/600126/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.