• DocumentCode
    301076
  • Title

    A task-based dependability model for k-ary n-cubes

  • Author

    Vaidya, Aniruddha S. ; Yoo, Byung S. ; Das, Chita R. ; Kim, Jong

  • Author_Institution
    Dept. of Comput. Sci. & Eng., Pennsylvania State Univ., University Park, PA, USA
  • Volume
    1
  • fYear
    1996
  • fDate
    12-16 Aug 1996
  • Firstpage
    9
  • Abstract
    Dependability (reliability and availability) modeling of k-ary n-cube architectures is addressed in this paper. The dependability model considered here is known as task-based dependability because the system working condition is specified by the task requirement. For the k-ary n-cube, we therefore compute the probability of finding a working k-ary m-cube. Due to the complexity of the problem, a structural decomposition technique is used to develop the analytical model. Two probability terms care required for computing either reliability or availability. The first term finds the probability that there are x working nodes in the system. Computation of this term for the availability analysis needs the solution of a simple Markov chain. The second term finds the probability that the x working nodes form the required subcube, called the task connection probability. A recursive expression, is developed for this. Analytical results are provided for various system configurations and task requirements. It is shown through simulation that the analytical model is quite accurate
  • Keywords
    hypercube networks; multiprocessing systems; parallel architectures; Markov chain; complexity; dependability model; k-ary n-cubes; n-cube architectures; structural decomposition; Analytical models; Availability; Buildings; Computer architecture; Computer science; Concurrent computing; Employee welfare; Hypercubes; Multiprocessor interconnection networks; Topology;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Parallel Processing, 1996. Vol.3. Software., Proceedings of the 1996 International Conference on
  • Conference_Location
    Ithaca, NY
  • ISSN
    0190-3918
  • Print_ISBN
    0-8186-7623-X
  • Type

    conf

  • DOI
    10.1109/ICPP.1996.537137
  • Filename
    537137