Performance models of multiprocessor systems
Performance models of multiprocessor systems
Time Scale Decomposition of a Class of Generalized Stochastic Petri Net Models
IEEE Transactions on Software Engineering
Improving the linearly based characterization of P/T nets
APN 90 Proceedings on Advances in Petri nets 1990
Data Structures and Algorithms
Data Structures and Algorithms
Iterative Decomposition and Aggregation of Stochastic Marked Graph Petri Nets
Papers from the 12th International Conference on Applications and Theory of Petri Nets: Advances in Petri Nets 1993
On the Product Form Solution for Stochastic Petri Nets
Proceedings of the 13th International Conference on Application and Theory of Petri Nets
SIGMETRICS '84 Proceedings of the 1984 ACM SIGMETRICS conference on Measurement and modeling of computer systems
Structured Solution of Asynchronously Communicating Stochastic Modules
IEEE Transactions on Software Engineering
Throughput Approximation of Decision Free Processes Using Decomposition
PNPM '97 Proceedings of the 6th International Workshop on Petri Nets and Performance Models
Structured Solution of Stochastic DSSP Systems
PNPM '97 Proceedings of the 6th International Workshop on Petri Nets and Performance Models
Product-form and stochastic Petri nets: a structural approach
Performance Evaluation
Approximation in non-product form finite capacity queue systems
Future Generation Computer Systems - Systems performance analysis and evaluation
Hybrid performance modeling approach for network intensive distributed software
WOSP '07 Proceedings of the 6th international workshop on Software and performance
Statistical Performance Analysis and Estimation for Parallel Multimedia Processing
Journal of Signal Processing Systems
Determinate STG decomposition of marked graphs
ICATPN'05 Proceedings of the 26th international conference on Applications and Theory of Petri Nets
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A general iterative technique for approximate throughput computation of stochastic strongly connected marked graphs is presented. It generalizes a previous technique based on net decomposition through a single input-single output cut, allowing the split of the model through any cut. The approach has two basic foundations. First, a deep understanding of the qualitative behavior of marked graphs leads to a general decomposition technique. Second, after the decomposition phase, an iterative response time approximation method is applied for the computation of the throughput. Experimental results on several examples generally have an error of less than 3%. The state space is usually reduced by more than one order of magnitude; therefore, the analysis of otherwise intractable systems is possible.