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Paper Abstract and Keywords
Presentation 2021-11-25 14:40
[Invited Talk] Application of learned index structures to IP FIB lookup
Yuki Koizumi, Shunsuke Higuchi, Junji Takemasa (Osaka Univ.), Atushi Tagami (KDDI Research), Toru Hasegawa (Osaka Univ.) NS2021-83 CQ2021-67 ICM2021-21
Abstract (in Japanese) (See Japanese page) 
(in English) An emerging data structure, a learned index structure, which uses machine learning to associate key-position pairs in a key-value store. We have applied learned index structures to a forwarding information base (FIB) of IP, referred to as a learned FIB. The learned FIB consists of the following two phases: First, it predicts the position of the FIB entry corresponding to an input IP address by leveraging a machine learning regression model. Second, it searches around the predicted position for the FIB entry to correct errors caused by the regression model. In this study, we optimize our implementation for lookup speed, exploiting that for fast FIB lookups it is enough to approximate the key-position pairs with a piece-wise linear function, instead of having to learn the key-position pairs. The experiments using real BGP routing information snapshots suggest that the size of the proposed FIB is compact and lookup speed is sufficiently fast regardless of the length of matched prefixes.
Keyword (in Japanese) (See Japanese page) 
(in English) Forwarding / Longest prefix matching / Learned index / Forwarding information base / / / /  
Reference Info. IEICE Tech. Rep., vol. 121, no. 263, CQ2021-67, pp. 18-21, Nov. 2021.
Paper # CQ2021-67 
Date of Issue 2021-11-18 (NS, CQ, ICM) 
ISSN Online edition: ISSN 2432-6380
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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 NS2021-83 CQ2021-67 ICM2021-21

Conference Information
Committee CQ ICM NS NV  
Conference Date 2021-11-25 - 2021-11-26 
Place (in Japanese) (See Japanese page) 
Place (in English) JR Hakata Stn. Hakata EkiHigashi Rental Room 
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 CQ 
Conference Code 2021-11-CQ-ICM-NS-NV 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Application of learned index structures to IP FIB lookup 
Sub Title (in English)  
Keyword(1) Forwarding  
Keyword(2) Longest prefix matching  
Keyword(3) Learned index  
Keyword(4) Forwarding information base  
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1st Author's Name Yuki Koizumi  
1st Author's Affiliation Osaka University (Osaka Univ.)
2nd Author's Name Shunsuke Higuchi  
2nd Author's Affiliation Osaka University (Osaka Univ.)
3rd Author's Name Junji Takemasa  
3rd Author's Affiliation Osaka University (Osaka Univ.)
4th Author's Name Atushi Tagami  
4th Author's Affiliation KDDI Research, Inc. (KDDI Research)
5th Author's Name Toru Hasegawa  
5th Author's Affiliation Osaka University (Osaka Univ.)
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Speaker Author-1 
Date Time 2021-11-25 14:40:00 
Presentation Time 45 minutes 
Registration for CQ 
Paper # NS2021-83, CQ2021-67, ICM2021-21 
Volume (vol) vol.121 
Number (no) no.262(NS), no.263(CQ), no.264(ICM) 
Page pp.2-5(NS), pp.18-21(CQ), pp.2-5(ICM) 
#Pages
Date of Issue 2021-11-18 (NS, CQ, ICM) 


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