Model-based Simulation of VoIP Network Reconfigurations using Graph Transformation Systems

We address the modelling and validation of P2P networks with special attention for problems related to VoIP services, focusing particularly on Skype. We use generalised stochastic graph transformation systems and associated stochastic simulation techniques based on generalised semi- Markov processes

Incremental Graph Pattern Matching: Data Structures and Initial Experiments

Despite the large variety of existing graph transformation tools, the implementation of their pattern matching engine typically follows the same principle. First a matching occurrence of the left-hand side of the graph transformation rule is searched by some graph pattern matching algorithm. Then potential negative application conditions are checked that might eliminate the previous occurrence. However, when a new transformation step is started, all the information on previous matchings is lost, and the complex graph pattern matching phase is restarted from scratch each time. In the paper, we present the foundational data structures and initial experiments for an incremental graph pattern matching engine which keeps track of existing matchings in an incremental way to reduce the execution time of graph pattern matching

Graph transformation with incremental updates

We propose an efficient implementation technique for graph transformation systems based on incremental updates. The essence of the technique is to keep track of all possible matchings of graph transformation rules in database tables, and update these tables incrementally to exploit the fact that rules typically perform only local modifications to models. Key words: graph transformation, graph pattern matching, relational databases.