IDEAS home Printed from https://ideas.repec.org/a/spr/ijsaem/v14y2023i1d10.1007_s13198-023-01878-4.html
   My bibliography  Save this article

Multi-channel data flow software fault detection for social internet of things with system assurance concerns

Author

Listed:
  • Ling You

    (Information Engineering College of Yango University)

Abstract

During application development, various unknown factors can affect the application and cause failures. According to the traditional software engineering techniques, software testing is usually performed later in software development, and it is difficult to find and correct these failures at this time. More and more distributed software systems are deployed on public cloud computing platforms and use the Internet to provide services outward. The complexity, dynamics, and openness of cloud computing environments make distributed software systems more prone to failure, which can result in service failures that can affect the normal use of large numbers of users. Therefore, in this paper, we study the fault detection algorithm of multi-channel parallel data flow software based on cloud computing. The data fusion and clustering models are integrated to detect the data features with the numerical verification, and the theoretical framework is also assigned to a better robustness for the theoretical framework implementation. The final results are also validated through the systematic overview. Future research directions are also included in the conclusion.

Suggested Citation

  • Ling You, 2023. "Multi-channel data flow software fault detection for social internet of things with system assurance concerns," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 14(1), pages 472-482, March.
  • Handle: RePEc:spr:ijsaem:v:14:y:2023:i:1:d:10.1007_s13198-023-01878-4
    DOI: 10.1007/s13198-023-01878-4
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s13198-023-01878-4
    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/s13198-023-01878-4?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:ijsaem:v:14:y:2023:i:1:d:10.1007_s13198-023-01878-4. 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.