2024 NSDI NSDI 2024

TECC: Towards Efficient QUIC Tunneling via Collaborative Transmission Control

Abstract

In this paper, we present TECC, a system based on collaborative transmission control that mitigates the mismatch of sending behavior between the inner and outer connections to achieve efficient QUIC tunneling. In TECC, a feedback framework is implemented to enable end hosts to collect more precise network information that is sensed on the tunnel server, which assists the inner end-to-end connection to achieve better congestion control and loss recovery. Extensive experiments in emulated networks and real-world large-scale A/B tests demonstrate the efficiency of TECC. Specifically, compared with the state-of-the-art QUIC tunneling solution, TECC significantly reduces flow completion time. In emulated networks, TECC decreases flow completion time by 30% on average and 53% at the 99th percentile. TECC also gains a reduction in RPC (Remote Procedure Call) request completion time of 3.9% on average and 13.3% at the 99th percentile in large-scale A/B tests.

🧭 Keyword Pioneer — quic tunneling
🐝 Cross-Pollinator — Artificial Intelligence, Machine Learning, Mathematics & Optimization, Reinforcement Learning