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Performance Evaluation of Stochastic Bipartite Matching Models

Authors :
Comte, C.
Dorsman, J.-P.
Ballarini, P.
Castel, H.
Dimitriou, I.
Iacono, M.
Phung-Duc, T.
Walraevens, J.
Eindhoven University of Technology [Eindhoven] (TU/e)
University of Amsterdam [Amsterdam] (UvA)
Stochastics (KDV, FNWI)
KdV Other Research (FNWI)
Source :
Performance Engineering and Stochastic Modeling, Performance Engineering and Stochastic Modeling, 13104, Springer International Publishing, pp.425-440, 2021, Lecture Notes in Computer Science, ⟨10.1007/978-3-030-91825-5_26⟩, Performance Engineering and Stochastic Modeling: 17th European Workshop, EPEW 2021, and 26th International Conference, ASMTA 2021, virtual event, December 9–10 and December 13–14, 2021 : proceedings, 425-440, STARTPAGE=425;ENDPAGE=440;TITLE=Performance Engineering and Stochastic Modeling, Lecture Notes in Computer Science ISBN: 9783030918248, Lecture Notes in Computer Science
Publication Year :
2021
Publisher :
HAL CCSD, 2021.

Abstract

International audience; We consider a stochastic bipartite matching model consisting of multi-class customers and multiclass 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.

Details

Language :
English
ISBN :
978-3-030-91824-8
ISBNs :
9783030918248
Database :
OpenAIRE
Journal :
Performance Engineering and Stochastic Modeling, Performance Engineering and Stochastic Modeling, 13104, Springer International Publishing, pp.425-440, 2021, Lecture Notes in Computer Science, ⟨10.1007/978-3-030-91825-5_26⟩, Performance Engineering and Stochastic Modeling: 17th European Workshop, EPEW 2021, and 26th International Conference, ASMTA 2021, virtual event, December 9–10 and December 13–14, 2021 : proceedings, 425-440, STARTPAGE=425;ENDPAGE=440;TITLE=Performance Engineering and Stochastic Modeling, Lecture Notes in Computer Science ISBN: 9783030918248, Lecture Notes in Computer Science
Accession number :
edsair.doi.dedup.....ad87ac062a11a6a30669c218132441ad
Full Text :
https://doi.org/10.1007/978-3-030-91825-5_26⟩