Regenerative stochastic Petri nets
Performance Evaluation
Graph grammars with negative application conditions
Fundamenta Informaticae - Special issue on graph transformations
Handbook of graph grammars and computing by graph transformation: volume I. foundations
Handbook of graph grammars and computing by graph transformation: volume I. foundations
Modeling and analysis of stochastic systems
Modeling and analysis of stochastic systems
Process algebra and Markov chains
Lectures on formal methods and performance analysis
PRISM: Probabilistic Symbolic Model Checker
TOOLS '02 Proceedings of the 12th International Conference on Computer Performance Evaluation, Modelling Techniques and Tools
SSJ: SSJ: a framework for stochastic simulation in Java
Proceedings of the 34th conference on Winter simulation: exploring new frontiers
Fault-Tolerant Routing for P2P Systems with Unstructured Topology
SAINT '05 Proceedings of the The 2005 Symposium on Applications and the Internet
A theory of stochastic systems: part I: Stochastic automata
Information and Computation
Fundamentals of Algebraic Graph Transformation (Monographs in Theoretical Computer Science. An EATCS Series)
Introduction to Discrete Event Systems
Introduction to Discrete Event Systems
Stochastic analysis of graph transformation systems: a case study in P2P networks
ICTAC'05 Proceedings of the Second international conference on Theoretical Aspects of Computing
Stochastic modelling and simulation of mobile systems
Graph transformations and model-driven engineering
Incremental pattern matching for the efficient computation of transitive closure
ICGT'12 Proceedings of the 6th international conference on Graph Transformations
| Hi-index | 0.00 |
Stochastic Graph Transformation combines graphical modelling of various software artefacts with stochastic analysis techniques. Existing approaches are restricted to processes with exponential time distribution. Such processes are sufficient for modelling a significant class of stochastic systems, however there are interesting systems which cannot be specified appropriately in such a framework. In several cases one needs to consider non-exponential time distributions. This paper proposes a stochastic model based on graph transformation with general probability distributions. This model is well suited to represent concurrency and performance aspects of architecture reconfiguration. It is also possible to apply Monte Carlo simulation techniques in order to analyse behaviour of complex stochastic systems. The new model is implemented and used to simulate simple networks.