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Paper Abstract and Keywords
Presentation 2025-11-06 13:15
Design, Implementation, and Evaluation of Service Function Chaining for Multi-hop Split Inference and Training
Takanori Hara (NAIST), Masahiro Sasabe (Kansai Univ.) NS2025-136
Abstract (in Japanese) (See Japanese page) 
(in English) Service Function Chaining (SFC) enables the realization of diverse network services by steering traffic through a predefined sequence of service functions, referred to as a service path. This paper introduces an SFC architecture tailored for Multi-hop Split Inference (MSI), which facilitates the execution of a global model by treating split models (i.e., sub-models) as service functions and steering traffic through the corresponding service path. In the proposed architecture, Neural Service Functions (NSFs) that execute sub-models are implemented as transparent TCP proxies and seamlessly integrated with Segment Routing over IPv6 (SRv6) and extended Berkeley Packet Filter (eBPF)-based SFC proxy. This integration ensures compatibility with existing applications while enabling dynamic and efficient communication paths for inference. Furthermore, the architecture is extended to Multi-hop Split Learning (MSL) by applying SFC to the bidirectional communication required for learning tasks. Evaluation results demonstrate that the architecture is particularly effective for realizing real-time MSI.
Keyword (in Japanese) (See Japanese page) 
(in English) Service Function Chaining (SFC) / Multi-hop Split Inference/Learning (MSI/MSL) / Neural Service Function (NSF) / Segment Routing over IPv6 (SRv6) / Transparent Proxy / extended Berkeley Packet Filter (eBPF) / /  
Reference Info. IEICE Tech. Rep., vol. 125, no. 225, NS2025-136, pp. 31-36, Nov. 2025.
Paper # NS2025-136 
Date of Issue 2025-10-30 (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 NS2025-136

Conference Information
Committee ICM NS NV  
Conference Date 2025-11-06 - 2025-11-07 
Place (in Japanese) (See Japanese page) 
Place (in English) Daisan-Hakata-Kaisei Bldg. + Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Network quality, Network measurement/management, Network virtualization, Network service, Blockchain, Security, Network intelligence/AI, etc. 
Paper Information
Registration To NS 
Conference Code 2025-11-ICM-NS-NV 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Design, Implementation, and Evaluation of Service Function Chaining for Multi-hop Split Inference and Training 
Sub Title (in English)  
Keyword(1) Service Function Chaining (SFC)  
Keyword(2) Multi-hop Split Inference/Learning (MSI/MSL)  
Keyword(3) Neural Service Function (NSF)  
Keyword(4) Segment Routing over IPv6 (SRv6)  
Keyword(5) Transparent Proxy  
Keyword(6) extended Berkeley Packet Filter (eBPF)  
Keyword(7)  
Keyword(8)  
1st Author's Name Takanori Hara  
1st Author's Affiliation Nara Institute of Science and Technology (NAIST)
2nd Author's Name Masahiro Sasabe  
2nd Author's Affiliation Kansai University (Kansai Univ.)
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Speaker Author-1 
Date Time 2025-11-06 13:15:00 
Presentation Time 25 minutes 
Registration for NS 
Paper # NS2025-136 
Volume (vol) vol.125 
Number (no) no.225 
Page pp.31-36 
#Pages 6 
Date of Issue 2025-10-30 (NS) 

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