Performance Evaluation of Stochastic Bipartite Matching Models

  • Céline Comte
  • , Jan-Pieter L. Dorsman

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

2 Citations (Scopus)

Abstract

We consider a stochastic bipartite matching model consisting of multi-class customers and multi-class servers. Compatibility constraints between the customer and server classes are described by a bipartite graph. Each time slot, exactly one customer and one server arrive. The incoming customer (resp. server) is matched with the earliest arrived server (resp. customer) with a class that is compatible with its own class, if there is any, in which case the matched customer-server couple immediately leaves the system; otherwise, the incoming customer (resp. server) waits in the system until it is matched. Contrary to classical queueing models, both customers and servers may have to wait, so that their roles are interchangeable. While (the process underlying) this model was already known to have a product-form stationary distribution, this paper derives a new compact and manageable expression for the normalization constant of this distribution, as well as for the waiting probability and mean waiting time of customers and servers. We also provide a numerical example and make some important observations.
Original languageEnglish
Title of host publicationPerformance Engineering and Stochastic Modeling - 17th European Workshop, EPEW 2021, and 26th International Conference, ASMTA 2021, Proceedings
EditorsPaolo Ballarini, Hind Castel, Ioannis Dimitriou, Mauro Iacono, Tuan Phung-Duc, Joris Walraevens
Pages425-440
Number of pages16
ISBN (Electronic)978-3-030-91825-5
DOIs
Publication statusPublished - 2021

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13104 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Keywords

  • Bipartite matching models
  • Order-independent queues
  • Performance analysis
  • Product-form stationary distribution

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