Markovian analysis of unreliable multi-components redundant fault tolerant system with working vacation and F-policy

This investigation presents admission control policy for the fault tolerant system comprising of multi-components operating machines and multiple types of warm standbys under the maintenance of single unreliable server. The concepts of F-policy which deals with the controlling of inflow of failed machines and imperfect coverage are incorporated to make Markov model formulation more realistic. The unreliable repairman takes some time before allowing the failed machines to wait in the system for the repair job. The successive over relaxation (SOR) method is used to obtain the system state probabilities at the steady state which are further used to evaluate other system indices including the mean queue length of failed machines, mean number of standby machines, throughput, etc. By constructing the cost function in terms of various performance indices and associated cost elements, the optimal repair rate is determined so that the maintenance of the concerned failure prone FTS can be done in an economic manner. The hybrid soft computing approach based on a neuro-fuzzy inference system is implemented to compare the results obtained by SOR method and neuro-fuzzy approach