Paper 3, Section II, K

Applied Probability | Part II, 2012

We consider a system of two queues in tandem, as follows. Customers arrive in the first queue at rate λ\lambda. Each arriving customer is immediately served by one of infinitely many servers at rate μ1\mu_{1}. Immediately after service, customers join a single-server second queue which operates on a first-come, first-served basis, and has a service rate μ2\mu_{2}. After service in this second queue, each customer returns to the first queue with probability 0<1p<10<1-p<1, and otherwise leaves the system forever. A schematic representation is given below:

(a) Let MtM_{t} and NtN_{t} denote the number of customers at time tt in queues number 1 and 2 respectively, including those currently in service at time tt. Give the transition rates of the Markov chain (Mt,Nt)t0\left(M_{t}, N_{t}\right)_{t \geqslant 0}.

(b) Write down an equation satisfied by any invariant measure π\pi for this Markov chain. Let α>0\alpha>0 and β(0,1)\beta \in(0,1). Define a measure π\pi by

π(m,n):=eααmm!βn(1β),m,n{0,1,}\pi(m, n):=e^{-\alpha} \frac{\alpha^{m}}{m !} \beta^{n}(1-\beta), \quad m, n \in\{0,1, \ldots\}

Show that it is possible to find α>0,β(0,1)\alpha>0, \beta \in(0,1) so that π\pi is an invariant measure of (Mt,Nt)t0\left(M_{t}, N_{t}\right)_{t \geqslant 0}, if and only if λ<μ2p\lambda<\mu_{2} p. Give the values of α\alpha and β\beta in this case.

(c) Assume now that λp>μ2\lambda p>\mu_{2}. Show that the number of customers is not positive recurrent.

[Hint. One way to solve the problem is as follows. Assume it is positive recurrent. Observe that MtM_{t} is greater than a M/M/M / M / \infty queue with arrival rate λ\lambda. Deduce that NtN_{t} is greater than a M/M/1M / M / 1 queue with arrival rate λp\lambda p and service rate μ2\mu_{2}. You may use without proof the fact that the departure process from the first queue is then, at equilibrium, a Poisson process with rate λ\lambda, and you may use without proof properties of thinned Poisson processes.]

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