Recently, a parametric State Reward Markov Model SRMM p has been developed for the reliability and availability analysis of self-healing SONET mesh networks 2 . In this paper, we investigate the factors that a ect the run-time complexity of the model presented in 2 . In order to accelerate the reliability and availability analysis, we present an approach that aggregates a set of states in the model based on 2-phase hypoexponential distribution. A comparison of the original and the reduced model, with respect to runtime complexity and accuracy, is carried out by applying the models for the analysis of few complex networks.
Hakki C. Cankaya, V. S. S. Nair