Fluid approximation for a Markovian queue under disaster and reboot

A fluid approximation for the performance analysis of a Markovian disaster queue with reboot and repair is presented. During normal operation, the system may suffer disaster failure, in which case all jobs in the system will be lost. If the fault is successfully covered, the system recovers from the failure by rebooting; otherwise, the system enters a repair state, where a specialised repairman removes the fault. Analytical methods of continued fractions (CFs) and probability generating function (PGF) are used to get the probability distribution of buffer content. To analyse the fluctuation in buffer content with regard to buffer content probabilities, the numerical data is computed and displayed in the form of graphs and tables. Furthermore, numerical results obtained using analytical formulae are compared with the results obtained by adaptive neuro-fuzzy inference system (ANFIS).