Distributed State Space Generation of Discrete-State Stochastic Models

Distributed State Space Generation of Discrete-State Stochastic Models

High-level formalisms such as stochastic Petri nets can be used to model complex systems. Analysis of logical and numerical properties of these models often requires the generation and storage of the entire underlying state space. This imposes practical limitations on the types of systems which can be modeled. Because of the vast amount of memory consumed, we investigate distributed algorithms ...

Distributed State-Space Generation of Discrete-State Stochastic Models

Derivation of a termination detection algorithm for a distributed computation. A simple and fast algorithm to obtain all invariants of a generalised Petri net. A graphical tool for reliability and failure-mode-eeects analysis. 21 adopted for the speciication of the model. To improve the applicability and usefulness of our approach, two aspects need to explored further. First, a centralized nume...

Automated Parallelization of Discrete State-Space Generation

We consider the problem of generating a large state-space in a distributed fashion. Unlike previously proposed solutions that partition the set of reachable states according to a hashing function provided by the user, we explore heuristic methods that completely automate the process. The rst step is an initial random walk through the state space to initialize a search tree, duplicated in each p...

Automated Parallelization of Discrete State-space Generation

Distributed Graph-Based State Space Generation

LTSMIN provides a framework in which state space generation can be distributed easily over many cores on a single compute node, as well as over multiple compute nodes. The tool works on the basis of a vector representation of the states; the individual cores are assigned the task of computing all successors of states that are sent to them. In this paper we show how this framework can be applied...