by Christian Zöllner, Matthias Barkowsky, Maria Maximova, Melanie Schneider, Holger Giese
Abstract:
Future cyber-physical systems, like networks of autonomous vehicles, will result in a huge number of collaborating systems acting together on large-scale topologies. Modeling them requires capturing timed and probabilistic behavior as well as structure dynamics. In [9], we introduced Probabilistic Timed Graph Transformation Systems (PTGTSs) as a means of modeling a high-level view of these systems of systems and provided model checking support. However, given the scale of emerging systems of systems and their often complex topologies, analyzing only small or medium size models using model checking is insufficient. To close this gap, we developed a simulator for PTGTSs that can import real-world topologies, automatically detect violations of state properties, and handle the graph pattern matching as well as time and probabilities efficiently so that complex large-scale topologies can be considered.
Reference:
A Simulator for Probabilistic Timed Graph Transformation Systems with Complex Large-Scale Topologies (Christian Zöllner, Matthias Barkowsky, Maria Maximova, Melanie Schneider, Holger Giese), In Graph Transformation - 13th International Conference, ICGT 2020 Held as Part of STAF 2020, Bergen, Norway, June 25-26, 2020, Proceedings (Fabio Gadducci, Timo Kehrer, eds.), Springer, volume 12150, 2020.
Bibtex Entry:
@InProceedings{ZBMSG20Simulator,
AUTHOR = {Zöllner, Christian and Barkowsky, Matthias and Maximova, Maria and Schneider, Melanie and Giese, Holger},
TITLE = {{A Simulator for Probabilistic Timed Graph Transformation Systems with Complex Large-Scale Topologies}},
YEAR = {2020},
BOOKTITLE = {Graph Transformation - 13th International Conference, ICGT 2020 Held as Part of STAF 2020, Bergen, Norway, June 25-26, 2020, Proceedings},
VOLUME = {12150},
PAGES = {325--334},
EDITOR = {Gadducci, Fabio and Kehrer, Timo},
SERIES = {Lecture Notes in Computer Science},
PUBLISHER = {Springer},
URL = {https://doi.org/10.1007/978-3-030-51372-6_20},
DOI = {10.1007/978-3-030-51372-6_20},
ABSTRACT = {Future cyber-physical systems, like networks of autonomous vehicles, will result in a huge number of collaborating systems acting together on large-scale topologies. Modeling them requires capturing timed and probabilistic behavior as well as structure dynamics. In [9], we introduced Probabilistic Timed Graph Transformation Systems (PTGTSs) as a means of modeling a high-level view of these systems of systems and provided model checking support. However, given the scale of emerging systems of systems and their often complex topologies, analyzing only small or medium size models using model checking is insufficient. To close this gap, we developed a simulator for PTGTSs that can import real-world topologies, automatically detect violations of state properties, and handle the graph pattern matching as well as time and probabilities efficiently so that complex large-scale topologies can be considered.}
}