IDEAS home Printed from https://ideas.repec.org/a/eee/tefoso/v166y2021ics0040162521000238.html
   My bibliography  Save this article

Management of cloud resources and social change in a multi-tier environment: A novel finite automata using ant colony optimization with spanning tree

Author

Listed:
  • Aliyu, Muhammad
  • Murali, M.
  • Zhang, Zuopeng Justin
  • Gital, Abdulsalam
  • Boukari, Souley
  • Huang, Yongbin
  • Yakubu, Ismail Zahraddeen

Abstract

The enormous demand for computational resources due to rapid Cloud growth has led to the creation of large-scale data centers (DC). Consequently, a tremendous amount of energy is consumed with high carbon dioxide emissions, which necessitates that cloud service providers (CSP) develop high quality of service (QoS) strategies to address such challenges. Proper management and utilization of resources ensure a well-balanced load distribution that makes energy consumption sufficient. Developing new algorithms and exploring efficient methods and techniques is highly desired for the management of virtualized DCs. This research proposes Finite Automata using Ant Colony Optimization with Spanning Tree (FAACOST), a machine-learning concept for managing cloud resources in a multi-tier environment. The overall objective is to minimize energy consumption through data placement leverage and virtual machines (VM) consolidation. The proposed technique's efficiency was benchmarked on four performance metrics (machine learning, dynamic nature, scalability, and QoS). Based on the extensive experiments conducted, FAACOST recorded an energy consumption of 132 w with 20 tasks compared to the benchmarked techniques that consumed 363 w. The experimental results show that FAACOST achieves the optimal number of physical machines (PMs) and is more energy-efficient.

Suggested Citation

  • Aliyu, Muhammad & Murali, M. & Zhang, Zuopeng Justin & Gital, Abdulsalam & Boukari, Souley & Huang, Yongbin & Yakubu, Ismail Zahraddeen, 2021. "Management of cloud resources and social change in a multi-tier environment: A novel finite automata using ant colony optimization with spanning tree," Technological Forecasting and Social Change, Elsevier, vol. 166(C).
    • Handle: RePEc:eee:tefoso:v:166:y:2021:i:c:s0040162521000238
    DOI: 10.1016/j.techfore.2021.120591
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0040162521000238
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.techfore.2021.120591?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. Jenia Afrin Jeba & Shanto Roy & Mahbub Or Rashid & Syeda Tanjila Atik & Md Whaiduzzaman, 2019. "Towards Green Cloud Computing an Algorithmic Approach for Energy Minimization in Cloud Data Centers," International Journal of Cloud Applications and Computing (IJCAC), IGI Global, vol. 9(1), pages 59-81, January.
    2. Abdellah Ouaguid & Noreddine Abghour & Mohammed Ouzzif, 2018. "A Novel Security Framework for Managing Android Permissions Using Blockchain Technology," International Journal of Cloud Applications and Computing (IJCAC), IGI Global, vol. 8(1), pages 55-79, January.
    Full references (including those not matched with items on IDEAS)

    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. Pan, Wen-Tsao & Zhuang, Mei-Er & Zhou, Ying-Ying & Yang, Jia-Jia, 2021. "Research on sustainable development and efficiency of China's E-Agriculture based on a data envelopment analysis-Malmquist model," Technological Forecasting and Social Change, Elsevier, vol. 162(C).

    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:tefoso:v:166:y:2021:i:c:s0040162521000238. 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.sciencedirect.com/science/journal/00401625 .

    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.