ACM Transactions on Computer Systems (TOCS)
Graph-Based Algorithms for Boolean Function Manipulation
IEEE Transactions on Computers
Efficient implementation of a BDD package
DAC '90 Proceedings of the 27th ACM/IEEE Design Automation Conference
Symbolic Boolean manipulation with ordered binary-decision diagrams
ACM Computing Surveys (CSUR)
Improving the Variable Ordering of OBDDs Is NP-Complete
IEEE Transactions on Computers
Algebraic decision diagrams and their applications
ICCAD '93 Proceedings of the 1993 IEEE/ACM international conference on Computer-aided design
A probabilistic dynamic technique for the distributed generation of very large state spaces
Performance Evaluation - Special issue on modelling techniques and tools for performance evaluation
Efficient encoding schemes for symbolic analysis of petri nets
Proceedings of the conference on Design, automation and test in Europe
Multi-Terminal Binary Decision Diagrams: An Efficient DataStructure for Matrix Representation
Formal Methods in System Design
Parallel State Space Exploration for GSPN Models
Proceedings of the 16th International Conference on Application and Theory of Petri Nets
Efficient Reachability Set Generation and Storage Using Decision Diagrams
Proceedings of the 20th International Conference on Application and Theory of Petri Nets
PNPM '99 Proceedings of the The 8th International Workshop on Petri Nets and Performance Models
Complexity of Kronecker Operations on Sparse Matrices with Applications to the Solution of Markov Models
Efficient symbolic state-space construction for asynchronous systems
Efficient symbolic state-space construction for asynchronous systems
A new petri net modeling technique for the performance analysis of discrete event dynamic systems
Journal of Systems and Software
Saturation for a General Class of Models
IEEE Transactions on Software Engineering
Improving static variable orders via invariants
ICATPN'07 Proceedings of the 28th international conference on Applications and theory of Petri nets and other models of concurrency
| Hi-index | 0.00 |
Generalised Stochastic Petri Nets (GSPNs) suffer from the same problem as any other state-transition modelling technique: it is difficult to represent sufficient states so that general, real life systems can be analysed. In this paper we use symbolic techniques to perform state space exploration for unstructured GSPNs. We present an algorithm for finding an encoding function which attempts to minimize the height of BDDs used to encode GSPN state spaces. This technique brings together and extends a spectrum of ad-hoc heuristics in a formal algorithm. We also develop a BDD state exploration algorithm which incorporates an adjustable memory threshold. Our results show the ability to encode over 108 states using just 13.7MB of memory.