Transient analysis for prioritized failure recovery in communication networks

Prioritized recovery can provide differentiated recovery services to the users in communication networks. This paper studies the transient behavior of networks under prioritized recovery. Stochastic Petri net models are constructed to capture the behaviors of a queueing system at four different phases during the recovery process: failure free phase; failure is detected; higher priority service is recovered; lower priority service is recovered. The final state of the stochastic Petri net model in one phase is used as the initial state of the model in the next phase. Both the traffics for the higher and lower priority queue are modeled as Markov modulated Poisson processes. Two queues are served in round-robin fashion. With the help of the stochastic Petri net package, the transient performance of the queueing system during each phase is studied numerically. The queue with the higher recovery priority significantly outperforms the queue with the lower recovery priority during the recovery process. A new concept, performance recovery time, is introduced. It is defined as the time required for a performance index, if deteriorated by service disruption, to reach a desired and acceptable value and is distinct from, and more important than, the failure recovery time. The models and analytical methods presented can be used to quantify the performance recovery time.