ACM Transactions on Computer Systems (TOCS)
Analysis of large stochastic petri net models
Analysis of large stochastic petri net models
Dependability modeling of a heterogeneous VAX-cluster system using stochastic reward nets
Hardware and software fault tolerance in parallel computing systems
A decomposition approach for stochastic reward net models
Performance Evaluation
On the modeling of parallel access to shared data
Communications of the ACM
Petri Net Theory and the Modeling of Systems
Petri Net Theory and the Modeling of Systems
SPNP: Stochastic Petri Net Package
PNPM '89 The Proceedings of the Third International Workshop on Petri Nets and Performance Models
Performance Analysis Using Stochastic Petri Nets
IEEE Transactions on Computers
Queueing Network Models for Parallel Processing with Asynchronous Tasks
IEEE Transactions on Computers
Using the exact state space of a Markov model to compute approximate stationary measures
Proceedings of the 2000 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
A simplified framework for stochastic workflow networks
Computers & Mathematics with Applications
Performance analysis of wireless opportunistic schedulers using stochastic Petri nets
IEEE Transactions on Wireless Communications
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Stochastic Petri net models of large systems that are solved by generating the underlying Markov chain pose the problem of largeness of the state-space. Hierarchical and iterative models of systems have been used extensively to solve this problem. A problem with models which use fixed point iteration is the theoretical proof of existence, uniqueness, and convergence of the fixed point equations, which still remains an "art". We establish conditions, in terms of the net structure and the characteristics of the iterated variables, under which existence of a solution is guaranteed when fixed point iteration is used in stochastic Petri nets.