QoS-Aware Proportional Fairness scheduling for multi-flow 5G UEs: a smart factory perspective

Simple item page
dc.contributor.authorSeliem, Mohamed
dc.contributor.authorRoedig, Utz
dc.contributor.authorSreenan, Cormac
dc.contributor.authorPesch, Dirk
dc.contributor.funderResearch Ireland, 13/RC/2077 P2
dc.date.accessioned2026-03-13T15:50:10Z
dc.date.available2026-03-13T15:50:10Z
dc.date.issued2025-12-30
dc.description.abstractPrivate 5G networks are emerging as key enablers for smart factories, where a single device often handles multiple concurrent traffic flows with distinct Quality of Service (QoS) requirements. Existing simulation frameworks, however, lack the fidelity to model such multi-flow behavior at the QoS Flow Identifier (QFI) level. This paper addresses this gap by extending Simu5G to support per-QFI modeling and by introducing a novel QoS-aware Proportional Fairness (QoS-PF) scheduler. The scheduler dynamically balances delay, Guaranteed Bit Rate (GBR), and priority metrics to optimize resource allocation across heterogeneous flows. We evaluate the proposed approach in a realistic smart factory scenario featuring edge-hosted machine vision, real-time control loops, and bulk data transfer. Results show that QoS-PF improves deadline adherence and fairness without compromising throughput. All extensions are implemented in a modular and open-source manner to support future research. Our work provides both a methodological and architectural foundation for simulating and analyzing advanced QoS policies in industrial 5G deployments.en
dc.description.sponsorshipThis publication has emanated from research conducted with the financial support of Taighde Éireann - Research Ireland under Grant number 13/RC/2077 P2. For the purpose of Open Access, the author has applied a CC-BY public copyright license to any Author Accepted Manuscript version arising from this submission
dc.format.extent8
dc.format.mimetypeapplication/pdfen
dc.identifier.authororcidSeliem, Mohamed§0000-0002-2132-9249
dc.identifier.authororcidRoedig, Utz§0000-0002-4020-0889
dc.identifier.authororcidSreenan, Cormac§0000-0002-0767-7888
dc.identifier.authororcidPesch, Dirk§0000-0001-9706-5705
dc.identifier.citationSeliem, M, Roedig, U, Sreenan, C & Pesch, D 2025, QoS-Aware Proportional Fairness scheduling for multi-flow 5G UEs: a smart factory perspective. in MSWiM 2025 - 27th International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems. MSWiM 2025 - 27th International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems, pp. 20-27. https://doi.org/10.1109/MSWiM67937.2025.11309032
dc.identifier.doi10.1109/MSWiM67937.2025.11309032
dc.identifier.endpage27
dc.identifier.isbn9798331568733
dc.identifier.otherArXiv: http://arxiv.org/abs/2508.21783v1
dc.identifier.otherORCID: /0000-0002-2132-9249/work/208441655
dc.identifier.otherORCID: /0000-0001-9706-5705/work/208442891
dc.identifier.otherORCID: /0000-0002-4020-0889/work/208442954
dc.identifier.startpage20
dc.identifier.urihttps://hdl.handle.net/10468/18635
dc.language.isoen
dc.relation.ispartofseriesMSWiM 2025 - 27th International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems
dc.relation.urihttps://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=pureucc&SrcAuth=WosAPI&KeyUT=WOS:001679935400008&DestLinkType=FullRecord&DestApp=WOS_CPL
dc.relation.urihttps://www.scopus.com/pages/publications/105032536346
dc.rightsPublisher Copyright: © 2025 IEEE.
dc.rights.accessrightsopen access
dc.rights.licensenameAttribution 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.statusPeer reviewed
dc.subject5G
dc.subjectQFI
dc.subjectQoS
dc.subjectSimu5G
dc.subjectindustrial networks
dc.subjectproportional fairness
dc.subjectscheduling
dc.titleQoS-Aware Proportional Fairness scheduling for multi-flow 5G UEs: a smart factory perspectiveen
dc.typeConference item
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
2508.21783v1.pdf
Size:
3.17 MB
Format:
Adobe Portable Document Format
Description:
Accepted Version
Download
Collections
School of Computer Science and Information Technology