• DocumentCode
    3027819
  • Title

    The Conditional Diagnosability of Twisted Cubes under the Comparison Model

  • Author

    Zhou, Shuming

  • Author_Institution
    Key Lab. of Network Security, Cryptology Fujian Normal Univ., Fuzhou, China
  • fYear
    2009
  • fDate
    10-12 Aug. 2009
  • Firstpage
    696
  • Lastpage
    701
  • Abstract
    In evaluating the fault tolerance of an network structure, it is essential to estimate the order of a maximal connected component of this network provided the faulty vertices may break its connectedness, and it is crucial to local and to replace the faulty processors to maintain systempsilas high reliability. The fault diagnosis is the process of identifying fault processors in a system through testing. The conditional diagnosis requires that for each processor v in a system, all the processors that are directly connected to v do not fail at the same time. In this paper, the conditional diagnosability of the twisted cubes TQn under the comparison diagnosis model is 3n-5 when n>6. Hence the conditional diagnosability of TQn is three times larger than its classical diagnosability.
  • Keywords
    fault diagnosis; fault tolerant computing; hypercube networks; microcomputers; performance evaluation; component order estimate; conditional diagnosis; fault diagnosis; faulty processors replacement; hypercube networks; maximal connected component; network processors; network structure fault tolerance; processors system testing; twisted cube network; Cryptography; Distributed processing; Fault diagnosis; Fault tolerant systems; Hypercubes; Laboratories; Maintenance; Multiprocessing systems; System testing; Tin; comparison diagnosis model; conditional diagnosability; twisted-cubes;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Parallel and Distributed Processing with Applications, 2009 IEEE International Symposium on
  • Conference_Location
    Chengdu
  • Print_ISBN
    978-0-7695-3747-4
  • Type

    conf

  • DOI
    10.1109/ISPA.2009.9
  • Filename
    5207858