posted on 2020-05-18, 15:10authored byH Melgratti, CA Mezzina, I Ulidowski
Petri Nets are a well-known model of concurrency and provide an ideal setting for the study of fundamental aspects in concurrent systems. Despite their simplicity, they still lack a satisfactory causally reversible semantics. We develop such semantics for Place/Transitions Petri Nets (P/T nets) based on two observations. Firstly, a net that explicitly expresses causality and conflict among events, e.g., an occurrence net, can be straightforwardly reversed by adding reversal for each of its transitions. Secondly, the standard unfolding construction associates a P/T net with an occurrence net that preserves all of its computation. Consequently, the reversible semantics of a P/T net can be obtained as the reversible semantics of its unfolding. We show that such reversible behaviour can be expressed as a finite net whose tokens are coloured by causal histories. Colours in our encoding resemble the causal memories that are typical in reversible process calculi.
Funding
Research partly supported by the EU H2020 RISE programme under the Marie Skłodowska Curie grant agreement No 778233. Partly supported by UBACyT projects 20020170100544BA and 20020170100086BA, and CONICET project PIP 11220130100148CO. Also, we thank COST Action IC1405 on Reversible Computation for partial support. The second author acknowledges the support of the Marie Skłodowska Curie Action Individual Fellowship RCADE No 794405.
History
Citation
Melgratti H., Mezzina C.A., Ulidowski I. (2019) Reversing P/T Nets. In: Riis Nielson H., Tuosto E. (eds) Coordination Models and Languages. COORDINATION 2019. Lecture Notes in Computer Science, vol 11533. Springer, Cham
Author affiliation
/Organisation/COLLEGE OF SCIENCE AND ENGINEERING/Department of Informatics
Source
21st IFIP WG 6.1 International Conference, COORDINATION 2019, Held as Part of the 14th International Federated Conference on Distributed Computing Techniques, DisCoTec 2019, Kongens Lyngby, Denmark, June 17–21, 2019,
Version
AM (Accepted Manuscript)
Published in
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)