Paper 4, Section II, 26K26 K

Applied Probability
Part II, 2017

(a) Give the definition of an M/M/1M / M / 1 queue. Prove that if λ\lambda is the arrival rate and μ\mu the service rate and λ<μ\lambda<\mu, then the length of the queue is a positive recurrent Markov chain. What is the equilibrium distribution?

If the queue is in equilibrium and a customer arrives at some time tt, what is the distribution of the waiting time (time spent waiting in the queue plus service time)?

(b) We now modify the above queue: on completion of service a customer leaves with probability δ\delta, or goes to the back of the queue with probability 1δ1-\delta. Find the distribution of the total time a customer spends being served.

Hence show that equilibrium is possible if λ<δμ\lambda<\delta \mu and find the stationary distribution.

Show that, in equilibrium, the departure process is Poisson.

[You may use relevant theorems provided you state them clearly.]