Limit Theorems for Queueing Systems with Various Service Disciplines in Heavy-Traffic Conditions
S. A. Grishunina ()
Additional contact information
S. A. Grishunina: Lomonosov Moscow State University
Methodology and Computing in Applied Probability, 2020, vol. 22, issue 4, 1529-1538
Abstract:
Abstract In this paper a multi-server queueing system with regenerative input flow and independent service times with finite means is studied. We consider queueing systems with various disciplines of the service performance: systems with a common queue and systems with individual queues in front of the servers. In the second case an arrived customer chooses one of the servers in accordance with a certain rule and stays in the chosen queue up to the moment of its departure from the system. We define some classes of disciplines and analyze the asymptotical behavior of a multi-server queueing system in a heavy-traffic situation (traffic rate ρ ≥ 1). The main result of this work is limit theorems concerning the weak convergence of scaled processes of waiting time and queue length to the process of the Brownian motion for the case ρ > 1 and its absolute value for the case ρ = 1.
Keywords: Queueing system; Heavy-traffic; Limit theorems; Service disciplines; 60K25 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
http://link.springer.com/10.1007/s11009-018-9660-1 Abstract (text/html)
Access to the full text of the articles in this series is restricted.
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:spr:metcap:v:22:y:2020:i:4:d:10.1007_s11009-018-9660-1
Ordering information: This journal article can be ordered from
https://www.springer.com/journal/11009
DOI: 10.1007/s11009-018-9660-1
Access Statistics for this article
Methodology and Computing in Applied Probability is currently edited by Joseph Glaz
More articles in Methodology and Computing in Applied Probability from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().