LEO Topology Design Under Real-World Deployment Constraints

2026-02-08

AI Summary

This work addresses the gap between theoretical low Earth orbit (LEO) satellite network topology design and real-world deployment constraints—such as partial constellation deployment, daily node turnover, and dynamic inter-satellite links—which are often overlooked yet critical for practical applicability. To bridge this gap, the paper proposes two topology design approaches tailored to realistic constraints: a hybrid Long-Short Link (LSL) method integrating long-range shortcuts with short-range local links, and a simulated annealing–based stochastic optimization technique. Notably, this study is the first to explicitly model deployment dynamics in topology design, enabling efficient incremental updates without requiring full network reconstruction. Empirical evaluation using real Starlink data demonstrates that, compared to the +Grid baseline, the proposed methods reduce average end-to-end latency by 45%, decrease hop count by 65%, and improve network capacity by up to 2.3× under both fully and partially deployed scenarios.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Search and Optimization: Distributed Search
• Constraint Satisfaction and Optimization: Satisfiability

Application Category

• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• Graph Algorithms and Modeling for the Web: Foundation models and LLMs for Web-related graphs
• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments

Abstract

The performance of large-scale Low-Earth-Orbit (LEO) networks, which consist of thousands of satellites interconnected by optical links, is dependent on its network topology. Existing topology designs often assume idealized conditions and do not account for real-world deployment dynamics, such as partial constellation deployment, daily node turnovers, and varying link availability, making them inapplicable to real LEO networks. In this paper, we develop two topology design methods that explicitly operate under real-world deployment constraints: the Long--Short Links (LSL) method, which systematically combines long-distance shortcut links with short-distance local links, and the Simulated Annealing (SA) method, which constructs topologies via stochastic optimization. Evaluated under both full deployment and partial deployment scenarios using 3-months of Starlink data, our methods achieve up to 45% lower average end-to-end delay, 65% fewer hops, and up to $2.3\times$ higher network capacity compared to +Grid. Both methods are designed to handle daily node turnovers by incrementally updating the topology, maintaining good network performance while avoiding costly full reconstruction of the topology.

Problem

• LEO networks
• topology design
• deployment constraints
• node turnover
• link availability

Innovation

• LEO topology design
• real-world deployment constraints
• Long-Short Links (LSL)
• Simulated Annealing (SA)
• incremental topology update