Name
Abstract | ||
|---|---|---|
In the recent years, extensions of graph transformation systems with quantitative properties, such as real-time and stochastic behavior received considerable attention. In this paper, we describe the new quantitative modeling approach of probabilistic graph transformation systems (PGTSs) which incorporate probabilistic behavior into graph transformation systems. Among other applications, PGTSs permit to model randomized protocols in distributed and mobile systems, and systems with on-demand probabilistic failures, such as message losses in unreliable communication media. We define the semantics of PGTSs in terms of Markov decision processes and employ probabilistic model checking for the quantitative analysis of finite-state PGTS models. We present tool support using Henshin and Prism for the modeling and analysis and discuss a probabilistic broadcast case study for wireless sensor networks. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1007/978-3-642-33654-6_21 | ICGT |
Keywords | Field | DocType |
new quantitative modeling approach,probabilistic model checking,probabilistic behavior,probabilistic broadcast case study,graph transformation system,finite-state pgts model,on-demand probabilistic failure,quantitative analysis,quantitative property,probabilistic graph transformation system | Divergence-from-randomness model,Discrete mathematics,Computer science,Probabilistic CTL,Markov decision process,Probabilistic analysis of algorithms,Theoretical computer science,Graph rewriting,Probabilistic logic,Graphical model,Probabilistic relevance model | Conference |
Citations | PageRank | References |
1 | 0.35 | 14 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Christian Krause | 1 | 254 | 12.93 |
| Holger Giese | 2 | 2345 | 164.90 |