Prioritized failure recovery in communication networks and its transient analysis

Abstract

Prioritized recovery can provide differentiated recovery services to the users in communication networks. This paper studies the transient behavior of communication 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, i.e. failure-free phase, failure is detected, higher priority service is recovered, and 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 with round-robin fashion. With the help of Stochastic Petri Net Package (SPNP), the transient performances of the queueing system during each phase are numerically studied. The queue with the higher recovery priority significantly outperforms the queue with the lower recovery priority during the recovery process. A new concept about performance recovery is introduced. Performance recovery time, which is defined as the time required for a performance index to reach a desired and acceptable value, if it is deteriorated by the service disruption, is distinct from and more important than the failure recovery time. The models and analytical methods presented in this paper can be used to quantify the performance recovery time.