The highly dynamic nature of Low-Earth Orbit (LEO) satellite networks introduces challenges that existing transport protocols fail to address, including non-congestive latency variation and loss, transient congestion hotspots, and frequent handovers that cause temporary disconnections and route changes with unknown congestion and delay characteristics. Our contention is that with this increase in complexity, there is insufficient information being returned from the network for existing congestion control algorithms to minimise latency while maintaining high throughput and minimising retransmissions. Our approach, OrbCC, leverages in-network support to collect per-hop congestion information and uses it to (1) minimise buffer occupancy and end-user latency, (2) maximise application throughput and network utilisation, and (3) rapidly respond to congestion hotspots. We evaluate OrbCC against state-of-the-art transport protocols using OMNeT++/INET-based LEO satellite simulations and targeted micro-benchmarks. The simulations capture RTT dynamics in a LEO constellation, while the micro-benchmarks isolate key characteristics such as non-congestive latency variation and loss, path changes, and congestion hotspots. Results show that OrbCC significantly improves goodput while simultaneously reducing latency and retransmissions compared to existing approaches.

翻译：低地球轨道（LEO）卫星网络的高度动态性带来了现有传输协议难以应对的挑战，包括非拥塞性延迟波动与丢包、瞬态拥塞热点，以及因频繁切换导致的临时断连和路由变更（其拥塞与延迟特征未知）。我们认为，随着复杂性的增加，网络反馈给现有拥塞控制算法的信息不足以在保持高吞吐量并最小化重传的同时实现延迟最小化。本文提出的方法OrbCC利用网内支持收集逐跳拥塞信息，并据此实现：(1) 最小化缓冲区占用与终端用户延迟；(2) 最大化应用吞吐量与网络利用率；(3) 快速响应拥塞热点。我们通过基于OMNeT++/INET的LEO卫星仿真及针对性的微基准测试，将OrbCC与最先进的传输协议进行评估。仿真捕获了LEO星座中的RTT动态特性，而微基准测试则分离了非拥塞性延迟波动与丢包、路径变化及拥塞热点等关键特征。结果表明，与现有方法相比，OrbCC在显著降低延迟与重传次数的同时，大幅提升了有效吞吐量。