VITA-Group/SymbolicPCC
📜 [NeurIPS 2022] "Symbolic Distillation for Learned TCP Congestion Control", S P Sharan, Wenqing Zheng, Kuo-Feng Hsu, Jiarong Xing, Ang Chen, Zhangyang Wang
This project helps network engineers optimize TCP congestion control. It takes complex, black-box AI policies for managing network traffic and converts them into simple, transparent rules. These rules can then be easily understood, verified, and implemented in network devices, making your network both efficient and predictable. Network operations engineers or performance specialists would find this particularly useful.
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Use this if you need to implement high-performing, AI-driven TCP congestion control but require the transparency and simplicity of traditional rule-based systems.
Not ideal if you are looking for an off-the-shelf congestion control solution without the need to understand or modify its underlying logic.
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Language
C++
License
MIT
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Last pushed
Oct 13, 2022
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