2022
DOI: 10.1016/j.simpat.2021.102467
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Analyzing stochastic reward nets by model checking and parallel simulation

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Cited by 6 publications
(2 citation statements)
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“…Fourth, due to the uncertainty that unavoidably accompanies the correct prediction of the execution time of task actions (e.g., [5]), an important goal of the final real-time software is to possibly admit state degradation modes and abort decisions [33] with recovery means, so as to minimize the risks corresponding to a deadline miss. Fifth, to port C-TPN on top of the Theater actor system [34] for the schedulability analysis of large models of embedded systems and, e.g., for studying workflow scheduling schemes in cloud computing [35], by parallel simulations [28] on a multi-core machine.…”
Section: Discussionmentioning
confidence: 99%
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“…Fourth, due to the uncertainty that unavoidably accompanies the correct prediction of the execution time of task actions (e.g., [5]), an important goal of the final real-time software is to possibly admit state degradation modes and abort decisions [33] with recovery means, so as to minimize the risks corresponding to a deadline miss. Fifth, to port C-TPN on top of the Theater actor system [34] for the schedulability analysis of large models of embedded systems and, e.g., for studying workflow scheduling schemes in cloud computing [35], by parallel simulations [28] on a multi-core machine.…”
Section: Discussionmentioning
confidence: 99%
“…A C-TPN model can directly be mapped onto the Uppaal toolbox [17,18,27]. Uppaal, in fact, exposes powerful modeling abstractions that can be exploited to reproduce the operational semantics of an extended timed Petri Net formalism [20,28].…”
Section: Reducing C-tpn Onto Uppaalmentioning
confidence: 99%