Meet Challenges of RTT Jitter, A Hybrid Internet Congestion Control Algorithm
Lianchen Jia, Chao Zhou, Tianchi Huang, Chaoyang Li, Lifeng Sun
Abstract
Congestion control has been a fundamental research focus in web transmission for over 30 years. However, with diverse network scenarios like cellular networks and WiFi, traditional models might no longer accurately describe current network conditions -- we empirically observe that the minimum round-trip time (RTTmin) still varies under different network conditions, challenging the assumption of its constancy in traditional models. In this paper, we model it as a normal distribution based on our measurements and propose a novel congestion control algorithm LingBo. LingBo consists of two phases: an offline trained decision model to achieve goals under different RTTmin distributions, and an online perception scheme to detect the current RTTmin distribution. We evaluate LingBo in various network environments and find it consistently performs well in terms of power metric and throughput compared to recent state-of-the-art baselines. Our code is available at https://github.com/thumedia/LingBo.
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