IDEAS home Printed from https://ideas.repec.org/a/igg/jfsa00/v11y2022i4p1-24.html
   My bibliography  Save this article

Cloud Service Provider Selection Using Fuzzy Data Envelopment Analysis Based on SMI Attributes

Author

Listed:
  • Thasni Thaha

    (Presidency University, India)

  • Kalaiarasan C.

    (Presidency University, India)

  • Venkatesh K. A.

    (Myanmar Institute of Information Technology, Myanmar)

Abstract

A variety of business firms are moving towards the cloud after realizing the benefits and success of using cloud technology. With multiple cloud service providers having different features, selecting the best or ranking them becomes a tedious task. There are several multi-criteria decision-making models (MCDM) trying to handle the selection of the best cloud service provider problem. A significant amount of research focused on MCDM models using quality of service (QoS) characteristics, but not much research has been conducted to address the fuzziness inherent in data. Therefore, a suitable model for choosing suitable cloud service providers is proposed in this work to address this data fuzziness. The SMI attributes recommended by CSMIC, approved by ISO, are considered as the evaluation criteria for the evaluation of cloud service providers. In this research work, fuzzy DEA is used to compute the efficiency values of cloud service providers and modified Chen and Klein method is used to arrive at the final ranking of cloud service providers(CSPs).

Suggested Citation

  • Thasni Thaha & Kalaiarasan C. & Venkatesh K. A., 2022. "Cloud Service Provider Selection Using Fuzzy Data Envelopment Analysis Based on SMI Attributes," International Journal of Fuzzy System Applications (IJFSA), IGI Global, vol. 11(4), pages 1-24, October.
  • Handle: RePEc:igg:jfsa00:v:11:y:2022:i:4:p:1-24
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJFSA.312239
    Download Restriction: no
    ---><---

    More about this item

    Statistics

    Access and download statistics

    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:igg:jfsa00:v:11:y:2022:i:4:p:1-24. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Journal Editor (email available below). General contact details of provider: https://www.igi-global.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.