Analysis of a fork/join station with inputs from a finite population subnetwork with multi-server stations

Nico Goossens (), Ananth Krishnamurthy () and Nico Vandaele ()
Additional contact information
Nico Goossens: UZ Brussel
Ananth Krishnamurthy: University of Wisconsin-Madison
Nico Vandaele: Katholieke Universiteit Leuven

OR Spectrum: Quantitative Approaches in Management, 2019, vol. 41, issue 1, No 9, 315 pages

Abstract: Abstract Forks/join stations are commonly used to model synchronization constraints in queuing networks. This paper presents an exact analysis of a fork/join station with inputs from stations composed of multiple exponential servers. The queue length process at the input buffers is analyzed exactly using the underlying Markov process. The semi-Markov kernel characterizing the departure process is analyzed to derive expressions for the marginal and joint distributions of inter-departure times from the fork/join station. These analyses are used to study the effect of inputs from multiple servers on key performance measures at a fork/join station. Comparison studies show that inputs from multiple servers have a significant effect on performance measures such as throughput, synchronization delays and queue lengths at the individual buffers. These insights are important to obtain better representation of synchronization constraints in closed queuing network models of computer networks, fabrication/assembly systems and material control strategies for manufacturing systems.

Keywords: Fork/join; Synchronization; Assembly systems; Closed queuing networks (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://link.springer.com/10.1007/s00291-018-0528-0 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:orspec:v:41:y:2019:i:1:d:10.1007_s00291-018-0528-0

Ordering information: This journal article can be ordered from
http://www.springer. ... research/journal/291

DOI: 10.1007/s00291-018-0528-0

Access Statistics for this article

OR Spectrum: Quantitative Approaches in Management is currently edited by Rainer Kolisch

More articles in OR Spectrum: Quantitative Approaches in Management from Springer, Gesellschaft für Operations Research e.V.
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().