Tail Asymptotics for a Retrial Queue with Bernoulli Schedule

Bin Liu and Yiqiang Q. Zhao ()
Additional contact information
Bin Liu: School of Mathematics & Physics, Anhui Jianzhu University, Hefei 230601, China
Yiqiang Q. Zhao: School of Mathematics and Statistics, Carleton University, Ottawa, ON K1S 5B6, Canada

Mathematics, 2022, vol. 10, issue 15, 1-13

Abstract: In this paper, we study the asymptotic behaviour of the tail probability of the number of customers in the steady-state M / G / 1 retrial queue with Bernoulli schedule, under the assumption that the service time distribution has a regularly varying tail. Detailed tail asymptotic properties are obtained for the conditional probability of the number of customers in the (priority) queue and orbit, respectively, in terms of the recently proposed exhaustive stochastic decomposition approach. Numerical examples are presented to show the impacts of system parameters on the tail asymptotic probabilities.

Keywords: M / G /1 retrial queue; Bernoulli schedule; number of customers; asymptotic tail probability; regularly varying distribution (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/2227-7390/10/15/2799/pdf (application/pdf)
https://www.mdpi.com/2227-7390/10/15/2799/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:10:y:2022:i:15:p:2799-:d:882267

Access Statistics for this article

Mathematics is currently edited by Ms. Emma He

More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().