An Evaluation Framework for Comparative Analysis of Generalized Stochastic Petri Net Simulation Techniques

Rodriguez, R.J. ; Bernardi, S. (Universidad de Zaragoza) ; Zimmermann, A.

Resumen: Availability of a common, shared benchmark to provide repeatable, quantifiable, and comparable results is an added value for any scientific community. International consortia provide benchmarks in a wide range of domains, being normally used by industry, vendors, and researchers for evaluating their software products. In this regard, a benchmark of untimed Petri net models was developed to be used in a yearly software competition driven by the Petri net community. However, to the best of our knowledge there is not a similar benchmark to evaluate solution techniques for Petri nets with timing extensions. In this paper, we propose an evaluation framework for the comparative analysis of generalized stochastic Petri nets (GSPNs) simulation techniques. Although we focus on simulation techniques, our framework provides a baseline for a comparative analysis of different GSPN solvers (e.g., simulators, numerical solvers, or other techniques). The evaluation framework encompasses a set of 50 GSPN models including test cases and case studies from the literature, and a set of evaluation guidelines for the comparative analysis. In order to show the applicability of the proposed framework, we carry out a comparative analysis of steady-state simulators implemented in three academic software tools, namely, GreatSPN, PeabraiN, and TimeNET. The results allow us to validate the trustfulness of these academic software tools, as well as to point out potential problems and algorithmic optimization opportunities.

Idioma: Inglés

DOI: 10.1109/TSMC.2018.2837643

Año: 2018

Publicado en: IEEE transactions on systems, man, and cybernetics. Systems 50, 873612 (2018), 2834 - 2844
ISSN: 2168-2216

Factor impacto SCIMAGO: 2.147 - Computer Science Applications (Q1) - Control and Systems Engineering (Q1) - Software (Q1) - Human-Computer Interaction (Q1) - Information Systems (Q1) - Electrical and Electronic Engineering (Q1)

Financiación: info:eu-repo/grantAgreement/ES/DGA/T27
Financiación: info:eu-repo/grantAgreement/EC/H2020/644869/EU/Developing Data-Intensive Cloud Applications with Iterative Quality Enhancements/DICE
Financiación: info:eu-repo/grantAgreement/ES/MINECO/TIN2014-58457-R

Tipo y forma: Article (PostPrint)

Área (Departamento): Área Lenguajes y Sistemas Inf. (Dpto. Informát.Ingenie.Sistms.)