Issue No. 10 - October (1998 vol. 24)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/32.729691
<p><b>Abstract</b>—High-level modeling representations, such as stochastic Petri nets, frequently generate very large state spaces and corresponding state-transition-rate matrices. In this paper, we propose a new steady-state solution approach that avoids explicit storing of the matrix in memory. This method does not impose any structural restrictions on the model, uses Gauss-Seidel and variants as the numerical solver, and uses less memory than current state-of-the-art solvers. An implementation of these ideas shows that one can realistically solve very large, general models in relatively little memory.</p>
Markov models, stochastic Petri nets, matrix-free methods.
D. D. Deavours and W. H. Sanders, ""On-the-Fly" Solution Techniques for Stochastic Petri Nets and Extensions," in IEEE Transactions on Software Engineering, vol. 24, no. , pp. 889-902, 1998.