research-article

Neural Packet Routing

Authors:

Fenglin LiAuthors Info & Claims

NetAI '20: Proceedings of the Workshop on Network Meets AI & ML

Pages 28 - 34

https://doi.org/10.1145/3405671.3405813

Published: 10 August 2020 Publication History

Abstract

Deep learning has shown great potential in automatically generating routing protocols for different optimization objectives. Although it may bring superior performance gains, there exists a fundamental obstacle to prevent existing network operators from deploying it into a real-world network, i.e., the uncertainty of statistical nature in deep learning can not provide the certainty of basic connectivity guarantee required in real-world routing.

In this paper, we propose the first deep-learning-based distributed routing system (named NGR) that can achieve the connectivity guarantee while still attaining the routing optimality. NGR provides a novel packet routing framework based on the link reversal theory. Specially-designed neural network structures are further proposed to seamlessly incorporate into the framework. We apply NGR in the tasks of shortest-path routing and load balancing. The evaluation results validate that NGR can achieve 100% connectivity guarantee despite the uncertainty of deep learning and gain performance close to the optimal solution.

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Cited By

Zhang JGuan JLiu KHu YShen AMa Y(2025)ScaIRComputer Networks: The International Journal of Computer and Telecommunications Networking10.1016/j.comnet.2024.110915257:COnline publication date: 1-Feb-2025
https://dl.acm.org/doi/10.1016/j.comnet.2024.110915
Jiang WHan HZhang YWang JHe MGu WMu JCheng X(2024)Graph Neural Networks for Routing Optimization: Challenges and OpportunitiesSustainability10.3390/su1621923916:21(9239)Online publication date: 24-Oct-2024
https://doi.org/10.3390/su16219239
Zhang PZhang HPi YCao ZWang JLiao J(2024)AdapINT: A Flexible and Adaptive In-Band Network Telemetry System Based on Deep Reinforcement LearningIEEE Transactions on Network and Service Management10.1109/TNSM.2024.342740321:5(5505-5520)Online publication date: Oct-2024
https://doi.org/10.1109/TNSM.2024.3427403
Show More Cited By

Index Terms

Neural Packet Routing
1. Computing methodologies
  1. Artificial intelligence
2. Networks
  1. Network protocols

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cover image ACM Conferences

NetAI '20: Proceedings of the Workshop on Network Meets AI & ML

August 2020

66 pages

ISBN:9781450380430

DOI:10.1145/3405671

Copyright © 2020 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGCOMM: ACM Special Interest Group on Data Communication

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New York, NY, United States

Publication History

Published: 10 August 2020

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SIGCOMM '20

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SIGCOMM

SIGCOMM '20: Annual conference of the ACM Special Interest Group on Data Communication on the applications, technologies, architectures, and protocols for computer communication

August 10 - 14, 2020

Virtual Event, USA

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Overall Acceptance Rate 13 of 38 submissions, 34%

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Cited By

Zhang JGuan JLiu KHu YShen AMa Y(2025)ScaIRComputer Networks: The International Journal of Computer and Telecommunications Networking10.1016/j.comnet.2024.110915257:COnline publication date: 1-Feb-2025
https://dl.acm.org/doi/10.1016/j.comnet.2024.110915
Jiang WHan HZhang YWang JHe MGu WMu JCheng X(2024)Graph Neural Networks for Routing Optimization: Challenges and OpportunitiesSustainability10.3390/su1621923916:21(9239)Online publication date: 24-Oct-2024
https://doi.org/10.3390/su16219239
Zhang PZhang HPi YCao ZWang JLiao J(2024)AdapINT: A Flexible and Adaptive In-Band Network Telemetry System Based on Deep Reinforcement LearningIEEE Transactions on Network and Service Management10.1109/TNSM.2024.342740321:5(5505-5520)Online publication date: Oct-2024
https://doi.org/10.1109/TNSM.2024.3427403
Rao ZXu YYao YMeng W(2024)DAR-DRL: A Dynamic Adaptive Routing Method based on Deep Reinforcement LearningComputer Communications10.1016/j.comcom.2024.107983(107983)Online publication date: Oct-2024
https://doi.org/10.1016/j.comcom.2024.107983
Liu KQuan WCheng NWu WXu ZGuo LGao DZhang H(2023)Reliable PPO-Based Concurrent Multipath Transfer for Time-Sensitive ApplicationsIEEE Transactions on Vehicular Technology10.1109/TVT.2023.327771272:10(13575-13590)Online publication date: Oct-2023
https://doi.org/10.1109/TVT.2023.3277712
Krämer PZeidler ODiederich PZerwas JBlenk AKellerer W(2023)Mistill: Distilling Distributed Network Protocols From ExamplesIEEE Transactions on Network and Service Management10.1109/TNSM.2023.326352920:4(4110-4125)Online publication date: Dec-2023
https://doi.org/10.1109/TNSM.2023.3263529
Swamy TRucker AShahbaz MGaur IOlukotun KFalsafi BFerdman MLu SWenisch T(2022)Taurus: a data plane architecture for per-packet MLProceedings of the 27th ACM International Conference on Architectural Support for Programming Languages and Operating Systems10.1145/3503222.3507726(1099-1114)Online publication date: 28-Feb-2022
https://dl.acm.org/doi/10.1145/3503222.3507726
Liu KQuan WCheng NXu ZDeng JGao D(2022)PPO-based Reliable Concurrent Transmission Control for Telemedicine Real-time ServicesICC 2022 - IEEE International Conference on Communications10.1109/ICC45855.2022.9839084(4655-4660)Online publication date: 16-May-2022
https://doi.org/10.1109/ICC45855.2022.9839084
Salman MWang B(2022)Near-optimal responsive traffic engineering in software defined networks based on deep learningFuture Generation Computer Systems10.1016/j.future.2022.04.036135:C(172-180)Online publication date: 1-Oct-2022
https://dl.acm.org/doi/10.1016/j.future.2022.04.036
Jiang W(2022)Graph-based deep learning for communication networksComputer Communications10.1016/j.comcom.2021.12.015185:C(40-54)Online publication date: 1-Mar-2022
https://dl.acm.org/doi/10.1016/j.comcom.2021.12.015
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