Reliability: probabilistic models and statistical methods
Reliability: probabilistic models and statistical methods
Probability and Computing: Randomized Algorithms and Probabilistic Analysis
Probability and Computing: Randomized Algorithms and Probabilistic Analysis
Applied Stochastic Models in Business and Industry - Reliability
IEEE Transactions on Dependable and Secure Computing
Sensitivity analysis of network reliability using monte carlo
WSC '05 Proceedings of the 37th conference on Winter simulation
Joint structural importance in consecutive-k systems
ACS'07 Proceedings of the 7th Conference on 7th WSEAS International Conference on Applied Computer Science - Volume 7
Model of optimal paths design for GMPLS network and evaluation of solution
WSEAS TRANSACTIONS on SYSTEMS
Speeding up computation of the reliability polynomial coefficients for a random graph
Automation and Remote Control
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In this paper we focus on computational aspects of network reliability importance measure evaluation. It is a well known fact that most network reliability problems are NP-hard and therefore there is a significant gap between theoretical analysis and the ability to compute different reliability parameters for large or even moderate networks. In this paper we present two very efficient combinatorial Monte Carlo models for evaluating network reliability importance measures.