Alexander Kedrowitsch (Virginia Tech), Jonathan Black (Virginia Tech) Daphne Yao (Virginia Tech)

Inter-satellite links will unlock true global access to high-speed internet delivered by Low Earth Orbit (LEO) mega-constellations. Functional packet routing within the constraints of the space environment, spacecraft design, and continual satellite mobility is uniquely challenging and requires novel routing algorithm approaches. Additionally, recent real-world events have highlighted adversarial attempts to deny and disrupt mega-constellation networking capabilities. In this paper, we advance highly resilient LEO mega-constellation dynamic routing algorithms by presenting our novel, ISL architecture-derived, network coordinate system. This coordinate system simplifies the network topology and permits increasingly impactful routing decisions with minimal computational overhead. From our topology, we demonstrate a proof-of-concept, lightweight routing algorithm that is highly resilient and scalable. To promote standardized resilience comparisons for LEO mega-constellation routing algorithms, we also propose a routing resilience testing framework that defines key performance metrics, adversarial capabilities, and testing scenarios. Using our proposed framework, we demonstrate our routing algorithm’s increased resilience over several state-of-the-art dynamic routing algorithms, with 12% packet delivery rate improvement during high adversarial disruption intensities.

View More Papers

Transforming Raw Authentication Logs into Interpretable Events

Seth Hastings, Tyler Moore, Corey Bolger, Philip Schumway (University of Tulsa)

Read More

Threats Against Satellite Ground Infrastructure: A retrospective analysis of...

Jessie Hamill-Stewart (University of Bristol and University of Bath), Awais Rashid (University of Bristol)

Read More

Understanding the Internet-Wide Vulnerability Landscape for ROS-based Robotic Vehicles...

Wentao Chen, Sam Der, Yunpeng Luo, Fayzah Alshammari, Qi Alfred Chen (University of California, Irvine)

Read More

Timing Channels in Adaptive Neural Networks

Ayomide Akinsanya (Stevens Institute of Technology), Tegan Brennan (Stevens Institute of Technology)

Read More