Izvestiya of Saratov University.

Mathematics. Mechanics. Informatics

ISSN 1816-9791 (Print)
ISSN 2541-9005 (Online)


For citation:

Sergeeva N. V., Pagano M., Tananko I. E., Stankevich E. P. A novel method for generating the optimal routing matrix of queuing networks with batch service. Izvestiya of Saratov University. Mathematics. Mechanics. Informatics, 2025, vol. 25, iss. 1, pp. 128-139. DOI: 10.18500/1816-9791-2025-25-1-128-139, EDN: ULANGK

This is an open access article distributed under the terms of Creative Commons Attribution 4.0 International License (CC-BY 4.0).
Published online: 
28.02.2025
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Russian
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517.98
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ULANGK

A novel method for generating the optimal routing matrix of queuing networks with batch service

Autors: 
Sergeeva Nadezhda Viktorovna, Saratov State University
Pagano Michele, University of Pisa
Tananko Igor Evstaf'evich, Saratov State University
Stankevich Elena Petrovna, Saratov State University
Abstract: 

In this paper, we consider a large-scale open queuing network. The arrival process in the queueing network is Poissonian. Сustomer transitions between nodes are described by the routing matrix. Each node consists of a single server and an infinite waiting queue. Customers are served as a unique batch of a given size with exponentially distributed service time. After the completion of service, customers are routed between nodes one at a time, independently of each other. We assume that, at any node, the number of destinations is much larger than the batch size. We also assume that the transition probabilities of customers between nodes are comparable. In this paper, we propose a method for generating the optimal routing matrix that provides the minimum average sojourn times in each node. We also provide a condition for relative arrival rates, under which the queuing network topology is radial (star-shaped), and expressions for optimal input rates to nodes. Finally, examples of the optimal routing matrix for different values of the overall input rate and in case of link failures are presented.

Acknowledgments: 
This research was partially funded by the Italian Ministry of Education and Research (MIUR) in the framework of the FoReLab project (Departments of Excellence) and by the University of Pisa in the framework of the PRA_2022_64 “hOlistic Sustainable Management of distributed softWARE systems (OSMWARE)” project.
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Received: 
18.01.2024
Accepted: 
07.02.2024
Published: 
28.02.2025