IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v12y2020i16p6383-d396093.html
   My bibliography  Save this article

Optimized Energy Cost and Carbon Emission-Aware Virtual Machine Allocation in Sustainable Data Centers

Author

Listed:
  • T. Renugadevi

    (School of Computing, SASTRA Deemed University, Thanjavur 613401, India)

  • K. Geetha

    (School of Computing, SASTRA Deemed University, Thanjavur 613401, India)

  • K. Muthukumar

    (School of Electrical and Electronics Engineering, SASTRA Deemed University, Thanjavur 613401, India)

  • Zong Woo Geem

    (Department of Energy IT, Gachon University, Seongnam 13120, Korea)

Abstract

Cloud data center’s total operating cost is conquered by electricity cost and carbon tax incurred due to energy consumption from the grid and its associated carbon emission. In this work, we consider geo-distributed sustainable datacenter’s with varying on-site green energy generation, electricity prices, carbon intensity and carbon tax. The objective function is devised to reduce the operating cost including electricity cost and carbon cost incurred on the power consumption of servers and cooling devices. We propose renewable-aware algorithms to schedule the workload to the data centers with an aim to maximize the green energy usage. Due to the uncertainty and time variant nature of renewable energy availability, an investigation is performed to identify the impact of carbon footprint, carbon tax and electricity cost in data center selection on total operating cost reduction. In addition, on-demand dynamic optimal frequency-based load distribution within the cluster nodes is performed to eliminate hot spots due to high processor utilization. The work suggests optimal virtual machine placement decision to maximize green energy usage with reduced operating cost and carbon emission.

Suggested Citation

  • T. Renugadevi & K. Geetha & K. Muthukumar & Zong Woo Geem, 2020. "Optimized Energy Cost and Carbon Emission-Aware Virtual Machine Allocation in Sustainable Data Centers," Sustainability, MDPI, vol. 12(16), pages 1-27, August.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:16:p:6383-:d:396093
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/12/16/6383/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/12/16/6383/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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.
    2. Iván Tomás Cotes-Ruiz & Rocío P Prado & Sebastián García-Galán & José Enrique Muñoz-Expósito & Nicolás Ruiz-Reyes, 2017. "Dynamic Voltage Frequency Scaling Simulator for Real Workflows Energy-Aware Management in Green Cloud Computing," PLOS ONE, Public Library of Science, vol. 12(1), pages 1-30, January.
    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. Wang, Jing & Munankarmi, Prateek & Maguire, Jeff & Shi, Chengnan & Zuo, Wangda & Roberts, David & Jin, Xin, 2022. "Carbon emission responsive building control: A case study with an all-electric residential community in a cold climate," Applied Energy, Elsevier, vol. 314(C).
    2. Alan A. Ahi & Noemi Sinkovics & Rudolf R. Sinkovics, 2023. "E-commerce Policy and the Global Economy: A Path to More Inclusive Development?," Management International Review, Springer, vol. 63(1), pages 27-56, February.
    3. Xihao Wang & Xiaojun Wang & Yuqing Liu & Chun Xiao & Rongsheng Zhao & Ye Yang & Zhao Liu, 2022. "A Sustainability Improvement Strategy of Interconnected Data Centers Based on Dispatching Potential of Electric Vehicle Charging Stations," Sustainability, MDPI, vol. 14(11), pages 1-19, June.

    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. Chen, Min & Gao, Ciwei & Song, Meng & Chen, Songsong & Li, Dezhi & Liu, Qiang, 2020. "Internet data centers participating in demand response: A comprehensive review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 117(C).
    3. Abbas Mardani & Dalia Streimikiene & Edmundas Kazimieras Zavadskas & Fausto Cavallaro & Mehrbakhsh Nilashi & Ahmad Jusoh & Habib Zare, 2017. "Application of Structural Equation Modeling (SEM) to Solve Environmental Sustainability Problems: A Comprehensive Review and Meta-Analysis," Sustainability, MDPI, vol. 9(10), pages 1-65, October.
    4. Mohamed Sameer Hoosain & Babu Sena Paul & Susanna Kass & Seeram Ramakrishna, 2023. "Tools Towards the Sustainability and Circularity of Data Centers," Circular Economy and Sustainability,, Springer.
    5. 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).
    6. Dawn Nafus & Eve M. Schooler & Karly Ann Burch, 2021. "Carbon-Responsive Computing: Changing the Nexus between Energy and Computing," Energies, MDPI, vol. 14(21), pages 1-26, October.
    7. Zakarya, Muhammad, 2018. "Energy, performance and cost efficient datacenters: A survey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 363-385.
    8. Abbas Akbari & Ahmad Khonsari & Seyed Mohammad Ghoreyshi, 2020. "Thermal-Aware Virtual Machine Allocation for Heterogeneous Cloud Data Centers," Energies, MDPI, vol. 13(11), pages 1-15, June.
    9. 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).
    10. 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.

    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:gam:jsusta:v:12:y:2020:i:16:p:6383-:d:396093. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.