• DocumentCode
    979177
  • Title

    Stochastic well-formed colored nets and symmetric modeling applications

  • Author

    Chiola, G. ; Dutheillet, C. ; Franceschinis, G. ; Haddad, Serge

  • Author_Institution
    Dipartimento di Inf., Torino Univ., Italy
  • Volume
    42
  • Issue
    11
  • fYear
    1993
  • fDate
    11/1/1993 12:00:00 AM
  • Firstpage
    1343
  • Lastpage
    1360
  • Abstract
    The class of stochastic well-formed colored nets (SWN´s) was defined as a syntactic restriction of stochastic high-level nets. The interest of the introduction of restrictions in the model definition is the possibility of exploiting the symbolic reachability graph (SRG) to reduce the complexity of Markovian performance evaluation with respect to classical Petri net techniques. It turns out that SWN´s allow the representation of any color function in a structured form, so that any unconstrained high-level net can be transformed into a well-formed net. Moreover, most constructs useful for the modeling of distributed computer systems and architectures directly match the “well-formed” restriction, without any need of transformation. A nontrivial example of the usefulness of the technique in the performance modeling and evaluation of multiprocessor architectures is included
  • Keywords
    Petri nets; computational complexity; multiprocessing systems; performance evaluation; Markovian performance evaluation; Petri net; SWN; complexity; computational complexity; lumpability condition; memory contention; model definition; performance modeling; stochastic high-level nets; stochastic well-formed colored nets; symbolic reachability graph; syntactic restriction; Computational complexity; Computer architecture; Distributed computing; Laboratories; Multiprocessing systems; Petri nets; Polynomials; Roentgenium; Steady-state; Stochastic processes;
  • fLanguage
    English
  • Journal_Title
    Computers, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9340
  • Type

    jour

  • DOI
    10.1109/12.247838
  • Filename
    247838