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INFORMS
1998

Distributed State Space Generation of Discrete-State Stochastic Models

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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 for the generation of state space graphs. The distributed construction allows us to take advantage of the combined memory readily available on a network of workstations. The key technical problem is to find effective methods for on-the-fly partitioning, so that the state space is evenly distributed among processors. In this paper we report on the implementation of a distributed state space generator that may be linked to a number of existing system modeling tools. We discuss partitioning strategies in the context of Petri net models, and report on performance observed on a network of workstat...
Gianfranco Ciardo, Joshua Gluckman, David M. Nicol
Added 22 Dec 2010
Updated 22 Dec 2010
Type Journal
Year 1998
Where INFORMS
Authors Gianfranco Ciardo, Joshua Gluckman, David M. Nicol
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