IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v349y2025i1d10.1007_s10479-023-05467-3.html
   My bibliography  Save this article

Reliability evaluation for multi-state network with cloud and fog computing by considering all transmission mechanisms

Author

Listed:
  • Ding-Hsiang Huang

    (Tunghai University)

Abstract

A cloud and fog distributed network is a necessary computing platform for hardware devices that an application, program or process executes upon. In order to manage such the network, a multi-state cloud and fog distributed network (MCFDN) is constructed. MCFDN reliability is proposed for evaluating performance of the MCFDN in the study. It is defined as the probability that demands can be transmitted through the MCFDN. Several phases of the data transmission exist in the MCFDN. The demands generated from data senders (such as IoT devices) can transmit to fog servers and cloud servers. When focused on the demands on the fog servers (resp. cloud servers), the demands would be compressed and transmitted back to the data senders and to the cloud servers (fog servers). Based on the transmission mechanisms, an algorithm is developed to calculate MCFDN reliability by elucidating flow relationships among the data senders, fog servers, and cloud servers. A benchmark is provided to demonstrate and validate the applicability of the proposed methodology. Finally, managers can manage and make suitable decisions for the cloud and fog distributed network by MCFDN reliability.

Suggested Citation

  • Ding-Hsiang Huang, 2025. "Reliability evaluation for multi-state network with cloud and fog computing by considering all transmission mechanisms," Annals of Operations Research, Springer, vol. 349(1), pages 67-86, June.
  • Handle: RePEc:spr:annopr:v:349:y:2025:i:1:d:10.1007_s10479-023-05467-3
    DOI: 10.1007/s10479-023-05467-3
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10479-023-05467-3
    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/s10479-023-05467-3?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.

    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:annopr:v:349:y:2025:i:1:d:10.1007_s10479-023-05467-3. 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: 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.