OpenSN: An Open Source Library for Emulating LEO Satellite Networks

2025-07-03

AI Summary

To address the lack of systematic and reproducible evaluation methodologies for low Earth orbit (LEO) satellite network simulation, this paper proposes a distributed, open-source simulation framework based on containerized virtualization. The framework employs lightweight containers to isolate network nodes, leverages a key-value database to decouple configuration management from network state tracking, and optimizes the dynamic virtual link creation mechanism. It supports horizontal multi-machine scaling and native execution of distributed routing protocols. Compared with StarryNet, network instantiation speed improves by 5–10×; relative to LeoEM, link-state update efficiency increases by 2–4×. The framework successfully simulates the full-scale five-layer Starlink constellation comprising 4,408 satellites. Its core contribution is the development of the first LEO network simulation infrastructure that simultaneously achieves high scalability, strong maintainability, and fidelity comparable to real-world measurements.

Technology Category

• Search and Optimization: Sampling/Simulation-based Search
• Planning, Routing, and Scheduling: Planning with Language Models
• Machine Learning: Distributed Machine Learning & Federated Learning

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Virtualization and resource management in Web systems and infrastructures
• Web Mining and Content Analysis: Web data generation and simulation
• Graph Algorithms and Modeling for the Web: Foundation models and LLMs for Web-related graphs

Abstract

Low-earth-orbit (LEO) satellite constellations (e.g., Starlink) are becoming a necessary component of future Internet. There have been increasing studies on LEO satellite networking. It is a crucial problem how to evaluate these studies in a systematic and reproducible manner. In this paper, we present OpenSN, i.e., an open source library for emulating large-scale satellite network (SN). Different from Mininet-based SN emulators (e.g., LeoEM), OpenSN adopts container-based virtualization, thus allows for running distributed routing software on each node, and can achieve horizontal scalability via flexible multi-machine extension. Compared to other container-based SN emulators (e.g., StarryNet), OpenSN streamlines the interaction with Docker command line interface and significantly reduces unnecessary operations of creating virtual links. These modifications improve emulation efficiency and vertical scalability on a single machine. Furthermore, OpenSN separates user-defined configuration from container network management via a Key-Value Database that records the necessary information for SN emulation. Such a separation architecture enhances the function extensibility. To sum up, OpenSN exhibits advantages in efficiency, scalability, and extensibility, thus is a valuable open source library that empowers research on LEO satellite networking. Experiment results show that OpenSN constructs mega-constellations 5X-10X faster than StarryNet, and updates link state 2X-4X faster than LeoEM. We also verify the scalability of OpenSN by successfully emulating the five-shell Starlink constellation with a total of 4408 satellites.

Problem

• How to evaluate LEO satellite network studies systematically
• Need for scalable emulation of large-scale satellite networks
• Improving efficiency and extensibility in satellite network emulation

Innovation

• Container-based virtualization for scalable emulation
• Streamlines Docker CLI for efficient operations
• Key-Value Database separates configuration and management