Brain-on-Switch

The repository of paper Brain-on-Switch: Towards Advanced Intelligent Network Data Plane via NN-Driven Traffic Analysis at Line-Speed, published in USENIX NSDI 2024. (The PDF is available at Link)

Repository Overview

Our artifact includes the following directories:

• dataset/ contains our datasets and the source code for data pre-processing.
• model/ contains the source code for training our binary RNN model, and converting the trained model into feed forward tables for switch-side implementation.
• PerPacket/ contains the source code for training the tree-based model for handling the flows without dedicated per-flow storage on switch.
• p4/ contains the source code for configuring a Barefoot Tofino 1 (Wedge 100BF-32X) switch and running our RNN-based traffic analysis on it.
• IMIS/ contains the source code for training the Transformer-based model for escalated traffic analysis, and the implementation of our server-side Integrated Model Inference System.

Follow the detailed instructions in each directory to implement the switch-side traffic analysis logic and server-side IMIS.

To forward the escalated traffic between the switch and the server, you need build a network topology to connect them.

Contact

Please post a Github issue or send an email to yanjz22@mails.tsinghua.edu.cn if you have any questions.

Credit

Cite this paper as follows if you find this code repo is useful to you.

@inproceedings{yan2024brain,

title={{Brain-on-Switch: Towards Advanced Intelligent Network Data Plane via NN-Driven Traffic Analysis at Line-Speed}},

author={Yan, Jinzhu and Xu, Haotian and Liu, Zhuotao and Li, Qi and Xu, Ke and Xu, Mingwei and Wu, Jianping},

booktitle={21st USENIX Symposium on Networked Systems Design and Implementation (NSDI 24)},

pages={419--440},

year={2024}

}