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Hauptverfasser: Huang, Dongzhou, Pang, Guodong, Stuhl, Izabella, Suhov, Yuri
Format: Preprint
Veröffentlicht: 2025
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Online-Zugang:https://arxiv.org/abs/2505.00198
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author Huang, Dongzhou
Pang, Guodong
Stuhl, Izabella
Suhov, Yuri
author_facet Huang, Dongzhou
Pang, Guodong
Stuhl, Izabella
Suhov, Yuri
contents We introduce and study some queueing models with random resetting, including Markovian and non--Markovian models. The Markovian models include M/M/$\infty$, M/M/r and M/M/1+M queues with random resetting, in which a continuous-time Markov chain is formulated, with transitions including a resetting to state zero in addition to arrivals and services. We explicitly characterize the stationary distributions of the queueing processes in these models by using parting balance equations. Although the stationary distribution for M/M/$\infty$ queue with resetting has been previously derived in the literature, we obtain an alternative and more interpretable expression by a different approach. That provides useful insights for the analysis of M/M/r and M/M/1+M queues with resetting under the first-come first-served (FCFS) discipline. The non--Markovian models include GI/GI/1, GI/GI/$r$ and GI/GI/$\infty$ queues with random resetting to state zero at arrival times. For GI/GI/1 and GI/GI/$r$ queues under the FCFS discipline, we introduce modified Lindley 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/$\infty$ queues with resettings, we utilize a version of the Kiefer--Wolfowitz recursion, and also characterize the corresponding stationary distribution.
format Preprint
id arxiv_https___arxiv_org_abs_2505_00198
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Queueing models with random resetting
Huang, Dongzhou
Pang, Guodong
Stuhl, Izabella
Suhov, Yuri
Probability
We introduce and study some queueing models with random resetting, including Markovian and non--Markovian models. The Markovian models include M/M/$\infty$, M/M/r and M/M/1+M queues with random resetting, in which a continuous-time Markov chain is formulated, with transitions including a resetting to state zero in addition to arrivals and services. We explicitly characterize the stationary distributions of the queueing processes in these models by using parting balance equations. Although the stationary distribution for M/M/$\infty$ queue with resetting has been previously derived in the literature, we obtain an alternative and more interpretable expression by a different approach. That provides useful insights for the analysis of M/M/r and M/M/1+M queues with resetting under the first-come first-served (FCFS) discipline. The non--Markovian models include GI/GI/1, GI/GI/$r$ and GI/GI/$\infty$ queues with random resetting to state zero at arrival times. For GI/GI/1 and GI/GI/$r$ queues under the FCFS discipline, we introduce modified Lindley 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/$\infty$ queues with resettings, we utilize a version of the Kiefer--Wolfowitz recursion, and also characterize the corresponding stationary distribution.
title Queueing models with random resetting
topic Probability
url https://arxiv.org/abs/2505.00198