research-article

KickTree: A Recursive Algorithmic Scheme for Packet Classification with Bounded Worst-Case Performance

Authors:

Yi WangAuthors Info & Claims

ANCS '21: Proceedings of the Symposium on Architectures for Networking and Communications Systems

Pages 23 - 30

https://doi.org/10.1145/3493425.3502752

Published: 18 January 2022 Publication History

Abstract

As a promising alternative to TCAM-based solutions for packet classification, FPGA has received increasing attention. Although extensive research has been conducted in this area, existing FPGA-based packet classifiers cannot satisfy the burgeoning needs from OpenFlow, which demands large-scale rule sets and frequent rule updates. As a recently proposed hardware-specific approach, TabTree avoids rule replication and supports dynamic rule update. However, it still faces problems of unbalanced rule subset partition, unevenly distributed subtrees and excessive TSS leaf nodes when implemented on FPGA. In this paper, we propose a hardware-friendly packet classification approach called KickTree, which is elaborated by considering hardware properties. To take advantage of intrinsic parallelism of FPGA, KickTree adopts multiple balanced decision trees which can run simultaneously. The bit selection is more flexible which breaks the restriction of rule subset. Moreover, each subset size is strictly limited, leading to bounded and evenly-distributed

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Cited By

Wang JXin YLu CJia CDing Y(2024)Evaluating Partitions in Packet Classification with the Asymmetric Metric of Disassortative ModularitySymmetry10.3390/sym1701003717:1(37)Online publication date: 28-Dec-2024
https://doi.org/10.3390/sym17010037
Lin HWang P(2024)Scalable packet classification based on rule categorization and cross-productingComputer Networks: The International Journal of Computer and Telecommunications Networking10.1016/j.comnet.2023.110116238:COnline publication date: 14-Mar-2024
https://dl.acm.org/doi/10.1016/j.comnet.2023.110116
Liu YXin YLi WSong HRottenstreich OXie GLi WWang Y(2023)HybridTSS: A Recursive Scheme Combining Coarse- and Fine- Grained Tuples for Packet ClassificationProceedings of the 6th Asia-Pacific Workshop on Networking10.1145/3542637.3542644(43-49)Online publication date: 7-Nov-2023
https://doi.org/10.1145/3542637.3542644
Show More Cited By

Index Terms

KickTree: A Recursive Algorithmic Scheme for Packet Classification with Bounded Worst-Case Performance
1. Networks
  1. Network algorithms
    1. Data path algorithms
      1. Packet classification

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cover image ACM Conferences

ANCS '21: Proceedings of the Symposium on Architectures for Networking and Communications Systems

December 2021

174 pages

ISBN:9781450391689

DOI:10.1145/3493425

Copyright © 2021 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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Publication History

Published: 18 January 2022

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Research-article
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Refereed limited

Funding Sources

Guangdong Basic and Applied Basic Research Foundation
National Key R&D Program of China
Key-Area Research and Development Program of Guangdong Province
Shanghai Pujiang Program
China Postdoctoral Science Foundation
the Major Key Project of PCL
NSFC
Science and Technology Commission of Shanghai Municipality

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ANCS '21

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ANCS '21: Symposium on Architectures for Networking and Communications Systems

December 13 - 16, 2021

IN, Layfette, USA

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Overall Acceptance Rate 88 of 314 submissions, 28%

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Cited By

Wang JXin YLu CJia CDing Y(2024)Evaluating Partitions in Packet Classification with the Asymmetric Metric of Disassortative ModularitySymmetry10.3390/sym1701003717:1(37)Online publication date: 28-Dec-2024
https://doi.org/10.3390/sym17010037
Lin HWang P(2024)Scalable packet classification based on rule categorization and cross-productingComputer Networks: The International Journal of Computer and Telecommunications Networking10.1016/j.comnet.2023.110116238:COnline publication date: 14-Mar-2024
https://dl.acm.org/doi/10.1016/j.comnet.2023.110116
Liu YXin YLi WSong HRottenstreich OXie GLi WWang Y(2023)HybridTSS: A Recursive Scheme Combining Coarse- and Fine- Grained Tuples for Packet ClassificationProceedings of the 6th Asia-Pacific Workshop on Networking10.1145/3542637.3542644(43-49)Online publication date: 7-Nov-2023
https://doi.org/10.1145/3542637.3542644
Xin YLi WJia CLi XXu YLiu BTian ZZhang W(2023)Recursive Multi-Tree Construction With Efficient Rule Sifting for Packet Classification on FPGAIEEE/ACM Transactions on Networking10.1109/TNET.2023.333038132:2(1707-1722)Online publication date: 10-Nov-2023
https://dl.acm.org/doi/10.1109/TNET.2023.3330381
Xin YLi WXie GXu YWang Y(2023)A Parallel and Updatable Architecture for FPGA-Based Packet Classification With Large-Scale Rule SetsIEEE Micro10.1109/MM.2023.323801243:2(110-119)Online publication date: 1-Mar-2023
https://dl.acm.org/doi/10.1109/MM.2023.3238012
Zhu LYu JHuang LZheng LPan JZhou ZChen HZhang DChen XWu C(2023)MiCuts: Combing Bit-Based Cutting and Splitting for Efficient Packet ClassificationICC 2023 - IEEE International Conference on Communications10.1109/ICC45041.2023.10278977(2345-2350)Online publication date: 28-May-2023
https://doi.org/10.1109/ICC45041.2023.10278977
Xin YLi WXie GXu YWang Y(2022)Updatable Packet Classification on FPGA with Bounded Worst-Case Performance2022 IEEE Symposium on High-Performance Interconnects (HOTI)10.1109/HOTI55740.2022.00019(21-28)Online publication date: Aug-2022
https://doi.org/10.1109/HOTI55740.2022.00019

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