HiMo: End-to-End Congestion Control for High Speed Rail Data Networking

Abstract

The highly variable nature of cellular networks challenges end-to-end network transmissions in achieving low-latency and high-throughput performance. In high-speed rail (HSR) networks, the intermittent connectivity and capacity dynamics imposed by high client mobility further add complexity and difficulty in providing seamless service. While congestion control algorithms (CCAs) play an essential role in ensuring optimal network performance, prior works on congestion control have predominantly concentrated on enhancing network performance within stationary or low-mobility mobile networks without considering frequent disconnections and highly dynamic network capacities imposed by HSR networks, resulting in severe RTT inflation and slow loss recovery. In this paper, we argue that a dedicated transport layer protocol is necessary for high-mobility scenarios. We propose an end-to-end low-latency congestion control algorithm HiMo for HSR networks that reacts to abrupt bandwidth changes quickly, handles frequent handovers, and is immediately deployable. Our trace-driven emulation on real-world datasets demonstrates that HiMo can reduce 51.3% 95th-percentile latency with comparable throughput on high-speed rail networks, compared to state-of-the-art CCAs.