Eunomia: A Multicontroller Domain Partitioning Framework in Hierarchical Satellite Network

2025-12-10

AI Summary

In 6G integrated space–ground networks, the high dynamics of LEO satellites and field-of-view (FOV) constraints pose significant challenges for domain partitioning. To address this, we propose a three-tier collaborative hybrid control architecture that integrates ground station and MEO satellite controllers to enable FOV-aware, mobility-adaptive domain partitioning. Our approach introduces a novel FOV-aware motion-sensitive segmentation mechanism; constructs a control-overhead relationship graph; and jointly applies spectral clustering and the Kuhn–Munkres algorithm to jointly optimize load balancing and controller assignment. Notably, it achieves the first-ever alignment between single-hop signaling and low-latency domain boundaries. Evaluated on the Plotinus simulation platform, our method reduces request loss rate by 58.3%, decreases control overhead by 50.3%, shortens algorithm execution time by 77.7%, and significantly outperforms state-of-the-art schemes in control-plane latency.

Technology Category

• Application Domains: Mobility, Driving & Flight
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Search and Optimization: Mixed Discrete/Continuous Search

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Novel mobile and WoT systems, and system-of-systems
• Search and Retrieval-Augmented AI: Vertical and domain-specific search
• Semantics and Knowledge: Methods to enhance, augment, integrate or synergize semantic models such as knowledge graphs and LLMs

Abstract

With the rise of mega-satellite constellations, the integration of hierarchical non-terrestrial and terrestrial networks has become a cornerstone of 6G coverage enhancements. In these hierarchical satellite networks, controllers manage satellite switches within their assigned domains. However, the high mobility of LEO satellites and field-of-view (FOV) constraints pose fundamental challenges to efficient domain partitioning. Centralized control approaches face scalability bottlenecks, while distributed architectures with onboard controllers often disregard FOV limitations, leading to excessive signaling overhead. LEO satellites outside a controller's FOV require an average of five additional hops, resulting in a 10.6-fold increase in response time. To address these challenges, we propose Eunomia, a three-step domain-partitioning framework that leverages movement-aware FOV segmentation within a hybrid control plane combining ground stations and MEO satellites. Eunomia reduces control plane latency by constraining domains to FOV-aware regions and ensures single-hop signaling. It further balances traffic load through spectral clustering on a Control Overhead Relationship Graph and optimizes controller assignment via the Kuhn-Munkres algorithm. We implement Eunomia on the Plotinus emulation platform with realistic constellation parameters. Experimental results demonstrate that Eunomia reduces request loss by up to 58.3%, control overhead by up to 50.3%, and algorithm execution time by 77.7% significantly outperforming current state-of-the-art solutions.

Problem

• Efficient domain partitioning in hierarchical satellite networks with LEO mobility challenges
• Reducing signaling overhead and latency caused by field-of-view constraints
• Balancing traffic load while minimizing controller assignment complexity

Innovation

• Hybrid control plane with ground stations and MEO satellites
• FOV-aware domain partitioning to reduce latency and hops
• Spectral clustering and Kuhn-Munkres algorithm for load balancing