Parallel Simulation of Stochastic Reward Nets using Theatre

The work described in this paper develops a methodology for modelling and analysis of complex timed systems. The methodology is based on the Stochastic Reward Nets (SRN) [1]–[4] formalism, which has gained its popularity by its ability to enable the studying of the performability, reliability and availability of, e.g., computer and communication systems. SRN is an extension of Generalized Stochastic Petri Nets (GSPN) and it is supported by such tools as the Stochastic Petri Net Package (SPNP) [5]–[6]. Power and accuracy in the application of SRN derive from mapping a model into a corresponding Markov Reward Model (MRM) from which quantitative measures are extracted in terms of reward functions associated to tangible markings of the source model. To cope with large models which cause state explosions in the underlying MRM, simulations are used [2].

[1]  Kishor S. Trivedi,et al.  Performability Evaluation of Grid Environments Using Stochastic Reward Nets , 2015, IEEE Transactions on Dependable and Secure Computing.

[2]  Marco Ajmone Marsan,et al.  A class of generalized stochastic Petri nets for the performance evaluation of multiprocessor systems , 1984, TOCS.

[3]  Model Checking Actor-based Cyber-Physical Systems , 2020, 2020 IEEE/ACM 24th International Symposium on Distributed Simulation and Real Time Applications (DS-RT).

[4]  Andrea Bobbio,et al.  Reliability and Availability Engineering - Modeling, Analysis, and Applications , 2017 .

[5]  Kishor S. Trivedi,et al.  SPNP: stochastic Petri net package , 1989, Proceedings of the Third International Workshop on Petri Nets and Performance Models, PNPM89.

[6]  Kim G. Larsen,et al.  A Tutorial on Uppaal , 2004, SFM.

[7]  Franco Cicirelli,et al.  Home Energy Management Using Theatre With Hybrid Actors , 2019, 2019 IEEE/ACM 23rd International Symposium on Distributed Simulation and Real Time Applications (DS-RT).

[8]  Libero Nigro,et al.  Qualitative and quantitative model checking of distributed probabilistic timed actors , 2018, Simul. Model. Pract. Theory.

[9]  Mohammed Gharib,et al.  Modeling and Evaluation of Multi-Hop Wireless Networks Using SRNs , 2021, IEEE Transactions on Network Science and Engineering.

[10]  L. Nigro,et al.  Analyzing stochastic reward nets by model checking and parallel simulation , 2021, Simul. Model. Pract. Theory.

[11]  Franco Cicirelli,et al.  Performance Comparison of Two Java-Based Actor Systems , 2021, ICICT.

[12]  Kim G. Larsen,et al.  Uppaal SMC tutorial , 2015, International Journal on Software Tools for Technology Transfer.

[13]  Libero Nigro.  Parallel Theatre: An actor framework in Java for high performance computing , 2021, Simul. Model. Pract. Theory.

[14]  Franco Cicirelli,et al.  Admission Control in Home Energy Management Systems Using Theatre and Hybrid Actors , 2021 .

[15]  Libero Nigro,et al.  Statistical model checking of distributed real-time actor systems , 2017, 2017 IEEE/ACM 21st International Symposium on Distributed Simulation and Real Time Applications (DS-RT).

[16]  Kishor S. Trivedi,et al.  Simulation versus analytic-numeric methods: illustrative examples , 2007, ValueTools '07.

[17]  Libero Nigro,et al.  Time Synchronization in Wireless Sensor Networks: A Modeling and Analysis Experience Using Theatre , 2018, 2018 IEEE/ACM 22nd International Symposium on Distributed Simulation and Real Time Applications (DS-RT).

[18]  Kishor S. Trivedi.  SPNP User's Manual Version 6.0 , 1999 .

[19]  Alois Ferscha,et al.  Parallel and Distributed Simulation , 1996, Proceedings of HICSS-29: 29th Hawaii International Conference on System Sciences.

[20]  Tadao Murata,et al.  Petri nets: Properties, analysis and applications , 1989, Proc. IEEE.

[21]  L. Nigro,et al.  Performance Prediction of Scalable Multi-agent Systems Using Parallel Theatre , 2021, Intelligent Sustainable Systems.