Queueing models with random resetting

We introduce and study some queueing models with random resetting, including Markovian and non--Markovian models. The Markovian models include M/M/1, M/M/r and M/M/$\infty$ queues with random resetting, in which a continuous-time Markov chain is formulated and the transition from each state includes a resetting to state zero in addition to the arrival and service transitions. Hence the chains are no longer a birth and death process as in the classical models. We explicitly characterize the stationary distributions of the queueing processes in these models. It is worth noting the distinction of the stability conditions from the standard models, that is, the positive recurrence of the Markov chains does not require the usual traffic intensity to be less than one. The non--Markovian models include GI/GI/1, GI/GI/$r$ and GI/GI/$\infty$ queues with random resetting to state zero. For GI/GI/1 and GI/GI/$r$ queues, we consider random resetting at arrival times, and introduce modified Lindley recursions and Kiefer--Wolfowitz recursions, respectively. Using an operator representation for these recursions, we characterize the stationary distributions via convergent series, as solutions to the modified Wiener--Hopf equations. For GI/GI/1 queues with random resetting, a particularly interesting case is when the difference of the service and interarrival times is positive, for which an explicit characterization of the stationary distribution of the delay/waiting time is provided via the associated characteristic functions. For GI/GI/$\infty$ queues, we also consider random resettings at arrival times, by utilizing a version of the Kiefer--Wolfowitz recursion motivated from that for GI/GI/$r$ queues, and also characterize the corresponding stationary distribution.