Version 1
: Received: 27 August 2024 / Approved: 28 August 2024 / Online: 28 August 2024 (05:21:58 CEST)
How to cite:
Barbato, D.; Cesaro, A.; D’Auria, B. Equilibrium Strategies for Overtaking-Free Queueing Networks under Partial Information. Preprints2024, 2024082017. https://doi.org/10.20944/preprints202408.2017.v1
Barbato, D.; Cesaro, A.; D’Auria, B. Equilibrium Strategies for Overtaking-Free Queueing Networks under Partial Information. Preprints 2024, 2024082017. https://doi.org/10.20944/preprints202408.2017.v1
Barbato, D.; Cesaro, A.; D’Auria, B. Equilibrium Strategies for Overtaking-Free Queueing Networks under Partial Information. Preprints2024, 2024082017. https://doi.org/10.20944/preprints202408.2017.v1
APA Style
Barbato, D., Cesaro, A., & D’Auria, B. (2024). Equilibrium Strategies for Overtaking-Free Queueing Networks under Partial Information. Preprints. https://doi.org/10.20944/preprints202408.2017.v1
Chicago/Turabian Style
Barbato, D., Alberto Cesaro and Bernardo D’Auria. 2024 "Equilibrium Strategies for Overtaking-Free Queueing Networks under Partial Information" Preprints. https://doi.org/10.20944/preprints202408.2017.v1
Abstract
In this paper, we investigate the equilibrium strategies for customers arriving at overtaking-free queueing networks and receiving partial information about the system’s state. In an overtaking-free network, customers cannot be overtaken by others arriving after them. We assume that customer arrivals follow a Poisson process and that service times at any queue are independent and exponentially distributed. Upon arrival, the received partial information consists in the total number of customers already in the network, however the distribution of these among the queues is left unknown. We prove the existence of equilibrium threshold strategies for such systems and provide methods to compute them.
Keywords
overtaking-free networks; equilibrium strategies; Jackson networks; tree networks
Subject
Computer Science and Mathematics, Probability and Statistics
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.