IDEAS home Printed from https://ideas.repec.org/a/spr/jcomop/v32y2016i3d10.1007_s10878-015-9923-5.html
   My bibliography  Save this article

A diagnosis algorithm by using graph-coloring under the PMC model

Author

Listed:
  • Qiang Zhu

    (Xidian University
    West Virginia University)

  • Guodong Guo

    (West Virginia University)

  • Wenliang Tang

    (West Virginia University)

  • Cun-Quan Zhang

    (West Virginia University)

Abstract

Fault diagnosis is important to the design and maintenance of large multiprocessor systems. PMC model is the most well known and widely studied model in the system level diagnosis of multiprocessor systems. Under the PMC model, a diagnosis algorithm based on some graph-coloring techniques has been proposed in this paper. Given a syndrome $$\sigma $$ σ , the first part of the algorithm can locate all the definitely faulty vertices. Then in the second part of the algorithm a diagnosis graph corresponding to the syndrome can be constructed and the suspicious faulty sets can be determined by finding the maximal independent sets of the diagnosis graph. A weight is assigned to each suspicious faulty vertex set which can measure its occurring probability. The algorithm is shown to be correct, not based on any conjecture and can be applied to the fault identification for any multiprocessor system.

Suggested Citation

  • Qiang Zhu & Guodong Guo & Wenliang Tang & Cun-Quan Zhang, 2016. "A diagnosis algorithm by using graph-coloring under the PMC model," Journal of Combinatorial Optimization, Springer, vol. 32(3), pages 960-969, October.
    • Handle: RePEc:spr:jcomop:v:32:y:2016:i:3:d:10.1007_s10878-015-9923-5
    DOI: 10.1007/s10878-015-9923-5
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10878-015-9923-5
    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/s10878-015-9923-5?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. Wei Xiong & Zhao Zhang & Hong-Jian Lai, 2014. "Spanning 3-connected index of graphs," Journal of Combinatorial Optimization, Springer, vol. 27(1), pages 199-208, January.
    2. Tongliang Shi & Mei Lu, 2012. "Fault-tolerant diameter for three family interconnection networks," Journal of Combinatorial Optimization, Springer, vol. 23(4), pages 471-482, May.
    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. Guo, Jia & Lu, Mei, 2018. "Conditional diagnosability of the SPn graphs under the comparison diagnosis model," Applied Mathematics and Computation, Elsevier, vol. 336(C), pages 249-256.

    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:jcomop:v:32:y:2016:i:3:d:10.1007_s10878-015-9923-5. 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.