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OrbCC: High-Throughput and Low-Latency Data Transport for LEO Satellite Networks

Aiden Valentine, Ian Wakeman, George Parisis

Abstract

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.

OrbCC: High-Throughput and Low-Latency Data Transport for LEO Satellite Networks

Abstract

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.

Paper Structure

This paper contains 14 sections, 4 equations, 10 figures, 1 table.

Table of Contents

  1. Introduction
  2. OrbCC Design
  3. Experimental Evaluation
  4. Path Sharing - Same RTTs
  5. Intermittent Path Sharing - Different RTTs
  6. Responsiveness
  7. Multi-bottleneck fairness
  8. Inter-RTT Fairness
  9. Intra-RTT Fairness
  10. Soft Handovers
  11. Hard Handover Efficiency
  12. OrbCC Average RTT
  13. OrbCC Initial Phase
  14. Discussion and Conclusion

Figures (10)

  • Figure 1: CC Responsiveness: Cumulative Distributions
  • Figure 2: OrbCC Header
  • Figure 3: Experimentation with the LEO simulation model: (a) and (b) two flows on the same path; and (c) two flows on different RTT paths that intermittently converge at shared bottlenecks.
  • Figure 4: Goodput ratio between the flow experiencing multiple bottlenecks and the highest goodput achieved by any single-bottleneck flow, both experiencing the same RTT (x-axis).
  • Figure 5: Goodput ratio of two competing flows. Starting flow has 20ms RTT and joining flows' RTT is shown on the x-axis.
  • ...and 5 more figures