IDEAS home Printed from https://ideas.repec.org/a/spr/telsys/v71y2019i2d10.1007_s11235-019-00549-9.html
   My bibliography  Save this article

Energy-efficient Nature-Inspired techniques in Cloud computing datacenters

Author

Listed:
  • Mohammed Joda Usman

    (Universiti Teknology Malaysia
    Bauchi State University Gadau)

  • Abdul Samad Ismail

    (Universiti Teknology Malaysia)

  • Gaddafi Abdul-Salaam

    (Kwame Nkrumah University of Science and Technology)

  • Hassan Chizari

    (University of Gloucestershire)

  • Omprakash Kaiwartya

    (Nottingham Trent University)

  • Abdulsalam Yau Gital

    (Abubakar Tafawa Balewa Bauchi)

  • Muhammed Abdullahi

    (Ahmadu Bello University Zaria)

  • Ahmed Aliyu

    (Universiti Teknology Malaysia
    Bauchi State University Gadau)

  • Salihu Idi Dishing

    (Ahmadu Bello University Zaria)

Abstract

Cloud computing is a systematic delivery of computing resources as services to the consumers via the Internet. Infrastructure as a Service (IaaS) is the capability provided to the consumer by enabling smarter access to the processing, storage, networks, and other fundamental computing resources, where the consumer can deploy and run arbitrary software including operating systems and applications. The resources are sometimes available in the form of Virtual Machines (VMs). Cloud services are provided to the consumers based on the demand, and are billed accordingly. Usually, the VMs run on various datacenters, which comprise of several computing resources consuming lots of energy resulting in hazardous level of carbon emissions into the atmosphere. Several researchers have proposed various energy-efficient methods for reducing the energy consumption in datacenters. One such solutions are the Nature-Inspired algorithms. Towards this end, this paper presents a comprehensive review of the state-of-the-art Nature-Inspired algorithms suggested for solving the energy issues in the Cloud datacenters. A taxonomy is followed focusing on three key dimension in the literature including virtualization, consolidation, and energy-awareness. A qualitative review of each techniques is carried out considering key goal, method, advantages, and limitations. The Nature-Inspired algorithms are compared based on their features to indicate their utilization of resources and their level of energy-efficiency. Finally, potential research directions are identified in energy optimization in data centers. This review enable the researchers and professionals in Cloud computing datacenters in understanding literature evolution towards to exploring better energy-efficient methods for Cloud computing datacenters.

Suggested Citation

  • Mohammed Joda Usman & Abdul Samad Ismail & Gaddafi Abdul-Salaam & Hassan Chizari & Omprakash Kaiwartya & Abdulsalam Yau Gital & Muhammed Abdullahi & Ahmed Aliyu & Salihu Idi Dishing, 2019. "Energy-efficient Nature-Inspired techniques in Cloud computing datacenters," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 71(2), pages 275-302, June.
  • Handle: RePEc:spr:telsys:v:71:y:2019:i:2:d:10.1007_s11235-019-00549-9
    DOI: 10.1007/s11235-019-00549-9
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11235-019-00549-9
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s11235-019-00549-9?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. Saurabh Singh & Pradip Kumar Sharma & Seo Yeon Moon & Jong Hyuk Park, 2017. "EH-GC: An Efficient and Secure Architecture of Energy Harvesting Green Cloud Infrastructure," Sustainability, MDPI, vol. 9(4), pages 1-18, April.
    2. Dingde Jiang & Zhengzheng Xu & Jindi Liu & Wenhui Zhao, 2016. "An optimization-based robust routing algorithm to energy-efficient networks for cloud computing," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 63(1), pages 89-98, September.
    3. Dingde Jiang & Zhengzheng Xu & Zhihan Lv, 2016. "A multicast delivery approach with minimum energy consumption for wireless multi-hop networks," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 62(4), pages 771-782, August.
    4. n/a, 2015. "Book Reviews," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4).
    5. Faruk, Nasir & Ruttik, Kalle & Mutafungwa, Edward & Jäntti, Riku, 2016. "Energy savings through self-backhauling for future heterogeneous networks," Energy, Elsevier, vol. 115(P1), pages 711-721.
    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. Adeel Abro & Zhongliang Deng & Kamran Ali Memon & Asif Ali Laghari & Khalid Hussain Mohammadani & Noor ul Ain, 2019. "A Dynamic Application-Partitioning Algorithm with Improved Offloading Mechanism for Fog Cloud Networks," Future Internet, MDPI, vol. 11(7), pages 1-16, June.
    2. Teresa Murino & Roberto Monaco & Per Sieverts Nielsen & Xiufeng Liu & Gianluigi Esposito & Carlo Scognamiglio, 2023. "Sustainable Energy Data Centres: A Holistic Conceptual Framework for Design and Operations," Energies, MDPI, vol. 16(15), pages 1-14, August.
    3. S. M. Reza Dibaj & Ali Miri & SeyedAkbar Mostafavi, 2020. "A cloud dynamic online double auction mechanism (DODAM) for sustainable pricing," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 75(4), pages 461-480, December.
    4. Andrzej Lis & Agata Sudolska & Ilona Pietryka & Adam Kozakiewicz, 2020. "Cloud Computing and Energy Efficiency: Mapping the Thematic Structure of Research," Energies, MDPI, vol. 13(16), pages 1-21, August.

    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. Wenyi Tang & Ke Zhang & Dingde Jiang, 2018. "Physarum-inspired routing protocol for energy harvesting wireless sensor networks," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 67(4), pages 745-762, April.
    2. Book, Laura A. & Tanford, Sarah & Chang, Wen, 2018. "Customer reviews are not always informative: The impact of effortful versus heuristic processing," Journal of Retailing and Consumer Services, Elsevier, vol. 41(C), pages 272-280.
    3. Posekany, Alexandra, 2015. "Bayesian Essentials with R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 67(b03).
    4. Josep M. Lozano, 2017. "Leadership: The Being Component. Can the Spiritual Exercises of Saint Ignatius Contribute to the Debate on Business Education?," Journal of Business Ethics, Springer, vol. 145(4), pages 795-809, November.
    5. Breffni M Noone, 2016. "Pricing for hotel revenue management: Evolution in an era of price transparency," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 15(3), pages 264-269, July.
    6. Siluo Yang & Xin Xing & Fan Qi & Maria Cláudia Cabrini Grácio, 2021. "Comparison of academic book impact from a disciplinary perspective: an analysis of citations and altmetric indicators," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(2), pages 1101-1123, February.
    7. Blackmore, Louise & Capon, Tim, 2015. "Book reviews," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 59(2), April.
    8. S. M. Reza Dibaj & Ali Miri & SeyedAkbar Mostafavi, 2020. "A cloud dynamic online double auction mechanism (DODAM) for sustainable pricing," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 75(4), pages 461-480, December.
    9. Dhakouani, Asma & Znouda, Essia & Bouden, Chiheb, 2019. "Impacts of energy efficiency policies on the integration of renewable energy," Energy Policy, Elsevier, vol. 133(C).
    10. Susan Athey & Guido W. Imbens, 2017. "The State of Applied Econometrics: Causality and Policy Evaluation," Journal of Economic Perspectives, American Economic Association, vol. 31(2), pages 3-32, Spring.
    11. Bijing Mao & Yafei Li & Zhimin Zhang & Chuan Chen & Yuanyuan Chen & Chenchen Ding & Lin Lei & Jian Li & Mei Jiang & Dong Wang & Ge Wang, 2015. "One-Carbon Metabolic Factors and Risk of Renal Cell Cancer: A Meta-Analysis," PLOS ONE, Public Library of Science, vol. 10(10), pages 1-10, October.
    12. Muhammad K. Shahzad & S. M. Riazul Islam & Mahmud Hossain & Mohammad Abdullah-Al-Wadud & Atif Alamri & Mehdi Hussain, 2020. "GAFOR: Genetic Algorithm Based Fuzzy Optimized Re-Clustering in Wireless Sensor Networks," Mathematics, MDPI, vol. 9(1), pages 1-18, December.
    13. Cristina López-Duarte & Marta M. Vidal-Suárez & Belén González-Díaz, 2019. "Cross-national distance and international business: an analysis of the most influential recent models," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(1), pages 173-208, October.
    14. Weishu Liu & Yishan Ding & Mengdi Gu, 2017. "Book reviews in academic journals: patterns and dynamics," Scientometrics, Springer;Akadémiai Kiadó, vol. 110(1), pages 355-364, January.
    15. Wen-Yu Tsao, 2019. "Understanding Users’ Preference to Engage in YouTubers," International Journal of Human Resource Studies, Macrothink Institute, vol. 9(1), pages 277-298, December.
    16. Derya Emir, 2014. "DISCRIMINATION, ASSIMILATION, and CULTURAL IDENTITY in TAHAR BEN JELLOUN'S LEAVING TANGIER," European Journal of Social Sciences Education and Research Articles, Revistia Research and Publishing, vol. 1, ejser_v1_.
    17. Hilbe, Joseph M., 2015. "The New Statistics with R: An Introduction for Biologists," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 68(b01).
    18. Katherine Mintz, 2017. "Arguments and actors in recent debates over US genetically modified organisms (GMOs)," Journal of Environmental Studies and Sciences, Springer;Association of Environmental Studies and Sciences, vol. 7(1), pages 1-9, March.
    19. Fetterman, David & Wandersman, Abraham, 2017. "Celebrating the 21st anniversary of empowerment evaluation with our critical friends," Evaluation and Program Planning, Elsevier, vol. 63(C), pages 132-135.
    20. Maja Jokić & Andrea Mervar & Stjepan Mateljan, 2019. "Comparative analysis of book citations in social science journals by Central and Eastern European authors," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(3), pages 1005-1029, September.

    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:spr:telsys:v:71:y:2019:i:2:d:10.1007_s11235-019-00549-9. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.