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EnglishHigh-level Petri nets (HLPNs) are an expressive formalism well supported by a number of tools that automate the editing and the interactive simulation of models and some kinds of analytical techniques, mainly based on state-space exploration. Structural analysis of HLPNs is, however, a challenging task not yet adequately supported and it is often accomplished via the unfolding of an HLPN into a corresponding low-level Petri Net. An approach to derive a system of Ordinary Differential Equations (ODEs) from a Stochastic Symmetric Net (SSN) has been proposed a few years ago, based on the net's unfolding and subsequent grouping of similar equations. This method has been recently improved by providing an algorithm that directly derives a compact ODE system (from a partially unfolded net) in a symbolic way, through algebraic manipulation of SSN annotations. In this paper, we present the automation of the calculus of Symbolic ODEs (SODEs) for SSN models as a new module of SNexpression, a tool for the symbolic structural analysis of Symmetric Nets. An application of the tool/technique to a variant of a SIRS epidemic model including antibiotic resistance is also described.
| Titolo: | A Tool for the Automatic Derivation of Symbolic ODE from Symmetric Net Models | |
| Autori Riconosciuti: | ||
| Autori: | Marco Beccuti, Lorenzo Capra, Massimiliano De Pierro, Giuliana Franceschinis, Laura Follia, Simone Pernice | |
| Data di pubblicazione: | 2019 | |
| Abstract: | High-level Petri nets (HLPNs) are an expressive formalism well supported by a number of tools that automate the editing and the interactive simulation of models and some kinds of analytical techniques, mainly based on state-space exploration. Structural analysis of HLPNs is, however, a challenging task not yet adequately supported and it is often accomplished via the unfolding of an HLPN into a corresponding low-level Petri Net. An approach to derive a system of Ordinary Differential Equations (ODEs) from a Stochastic Symmetric Net (SSN) has been proposed a few years ago, based on the net's unfolding and subsequent grouping of similar equations. This method has been recently improved by providing an algorithm that directly derives a compact ODE system (from a partially unfolded net) in a symbolic way, through algebraic manipulation of SSN annotations. In this paper, we present the automation of the calculus of Symbolic ODEs (SODEs) for SSN models as a new module of SNexpression, a tool for the symbolic structural analysis of Symmetric Nets. An application of the tool/technique to a variant of a SIRS epidemic model including antibiotic resistance is also described. | |
| Editore: | IEEE Computer Society | |
| Titolo del libro: | 2019 IEEE 27th International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS) | |
| Pagina iniziale: | 36 | |
| Pagina finale: | 48 | |
| Nome del convegno: | 2019 IEEE 27th International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS) | |
| Luogo del convegno: | Rennes, France | |
| Anno del convegno: | October 22-24, 2019 | |
| Digital Object Identifier (DOI): | 10.1109/MASCOTS.2019.00015 | |
| ISBN: | 978-1-7281-4950-9 | |
| Parole Chiave: | Color;Tools;Petri nets;Stochastic processes;Mathematical model;Computational modeling;Analytical models;High-Level Petri Nets, Symmetric Nets, Symbolic structural relations, Ordinary Differential Equations | |
| Appare nelle tipologie: | 04A-Conference paper in volume |
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http://hdl.handle.net/2318/1725811
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