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Paper Abstract and Keywords
Presentation 2026-01-23 09:45
[Encouragement Talk] 5G Network Slicing Using Priority-Weighted Reinforcement Learning for SLA Isolation
Yutaro Hoashi, Shota Ono, Akihiro Nakao (The Univ. of Tokyo) NS2025-207
Abstract (in Japanese) (See Japanese page) 
(in English) In recent years, highly reliable communication services such as remote surgery are being actively deployed on 5G networks. To stably provide these services, communication environments that are isolated and independent from other services are required. Network Slicing is a key technology addressing this requirement, enabling diverse applications with strict SLAs to coexist on the same network through virtualized resource partitioning. However, in environments where numerous slices with heterogeneous requirements unpredictably compete and resources are heavily contended, satisfying all slice demands simultaneously is difficult, which may result in SLA failure within a critical slice. Conventional Reinforcement Learning methods struggle with simultaneously guaranteeing the SLA of a specific slice while maintaining high resource efficiency. Therefore, this paper proposes a model-based Reinforcement Learning approach that guarantees the SLA of high-priority slices by design through a deterministic, priority-based resource reallocation rule, while maximizing overall resource efficiency. The proposed method, compared to static reservation schemes, enables resource allocation that achieves both resource efficiency and SLA assurance, even during resource contention. In a scenario where the slice handling highly reliable communication services was guaranteed at a level of 99.8%, the proposed method achieved a 58.5% improvement in resource utilization for non-priority slices.
Keyword (in Japanese) (See Japanese page) 
(in English) network slicing / isolation / reinforcement learning / SLA / / / /  
Reference Info. IEICE Tech. Rep., vol. 125, no. 320, NS2025-207, pp. 86-91, Jan. 2026.
Paper # NS2025-207 
Date of Issue 2026-01-15 (NS) 
ISSN Online edition: ISSN 2432-6380
Copyright
and
reproduction		 All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
Download PDF NS2025-207

Conference Information
Committee NS NWS  
Conference Date 2026-01-22 - 2026-01-23 
Place (in Japanese) (See Japanese page) 
Place (in English) Kochi City Culture-Plaza CUL-PORT + Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Network software (Software architecture, Middleware), Network application, SOA/SDP, NGN/IMS/API, Distributed control/Dynamic routing, Grid, NFV, IoT, Network/System reliability, Network/System evaluation, etc. 
Paper Information
Registration To NS 
Conference Code 2026-01-NS-NWS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) 5G Network Slicing Using Priority-Weighted Reinforcement Learning for SLA Isolation 
Sub Title (in English)  
Keyword(1) network slicing  
Keyword(2) isolation  
Keyword(3) reinforcement learning  
Keyword(4) SLA  
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1st Author's Name Yutaro Hoashi  
1st Author's Affiliation The University of Tokyo (The Univ. of Tokyo)
2nd Author's Name Shota Ono  
2nd Author's Affiliation The University of Tokyo (The Univ. of Tokyo)
3rd Author's Name Akihiro Nakao  
3rd Author's Affiliation The University of Tokyo (The Univ. of Tokyo)
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Speaker Author-1 
Date Time 2026-01-23 09:45:00 
Presentation Time 25 minutes 
Registration for NS 
Paper # NS2025-207 
Volume (vol) vol.125 
Number (no) no.320 
Page pp.86-91 
#Pages 6 
Date of Issue 2026-01-15 (NS) 

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