Stochastic Reward Nets for Reliability Prediction
نویسندگان
چکیده
We describe the use of stochastic Petri nets (SPNs) and stochastic reward nets (SRNs) which are SPNs augmented with the ability to specify output measures as reward-based functions, for the evaluation of reliability for complex systems. The solution of SRNs involves generation and analysis of the corresponding Markov reward model. The use of SRNs in modeling complex systems is illustrated through several interesting examples. We mention the use of the Stochastic Petri Net Package (SPNP) for the description and solution of SRN models.
منابع مشابه
Analysis of Markov Reward Models with Stochastic Petri Nets
Analysis of Markov reward models with stochastic Petri nets is presented. Generation methods and analysis of continuous-time Markov chains and Markov reward models is provided for modeling of reliability of very large systems and working out measures for their performance. Examples and numerical results for M/D/1/2/2 system are shown.
متن کاملAnalyzing Concurrent and Fault-Tolerant Software Using Stochastic Reward Nets
We present two software applications and develop models for them. The first application considers a producer-consumer tasking system with an intermediate buffer task and studies how the performance is affected by different selection policies when multiple tasks are ready to synchronize. The second application studies the reliability of a fault-tolerant software system using the recovery block s...
متن کاملStochastic Petri nets for the reliability analysis of communication network applications with alternate-routing
In this paper, we present a comparative reliability analysis of an application on a corporate B-ISDN network under various alternate-routing protocols. For simple cases, the reliability problem can be cast into fault-tree models and solved rapidly by means of known methods. For more complex scenarios, state space (Markov) models are required. However, generation of large state space models can ...
متن کاملSymbolic Model Checking of Stochastic Reward Nets
This paper describes a symbolic model checking approach for the Continuous Stochastic Reward Logic (CSRL) and stochastic reward nets, stochastic Petri nets augmented with rate rewards. CSRL model checking requires the computation of the joint distribution of time and accumulated reward, which is done by Markovian approximation. An implementation is available in the model checker MARCIE. It appl...
متن کاملReliability Prediction and Sensitivity Analysis of Web Services Composition
Web services are emerging as a major technology for deploying automated interactions between distributed and heterogeneous applications. It aims at the transparent integration of Web applications, based on XML-related standards (F.Curbera et al., 2002). Until now, many research efforts have been made in the field of Web services composition. Moreover, many composition languages have recently em...
متن کامل