Eunomia: A Multicontroller Domain Partitioning Framework in Hierarchical Satellite Network

TL;DR

The paper addresses the core challenge of scalable, low-latency control in hierarchical mega-constellations under field-of-view constraints. It proposes Eunomia, a movement-aware, three-step domain-partitioning framework that combines a CORG-based overhead model, spectral clustering, and KM-based controller matching within a hybrid GS-MEO control plane. Through emulation on Plotinus with realistic constellations, Eunomia delivers substantial reductions in request loss, control overhead, and algorithm runtime across varied traffic loads and constellation sizes, outperforming state-of-the-art approaches. This work advances practical, mobility-aware SDN-style control for large-scale satellite networks and points to future extensions in fault tolerance and energy-aware optimization.

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.

Figures (12)

• Figure 1: Unified hybrid control plane architecture combining ground stations and MEO satellites to manage LEO satellite domains with field-of-view constraints.
• Figure 2: Geometric relationship between MEO controller and LEO satellite showing the elevation angle $\beta$ derived from geocentric angle $\alpha$, illustrating field-of-view coverage constraints in satellite networks.
• Figure 3: The overview workflow of Eunomia. Firstly, traffic preprocessing and CORG generation using satellite network information from current time slot. Then spectral clustering-based domain partitioning with controller assignment. Each subsequent time slot inherits and optimizes strategies from previous time slots to maintain domain stability while adapting to satellite movement.
• Figure 4: Flowchart of the domain partitioning algorithm. Firstly, FOV domain determination. Secondly, spectral clustering for overlapping regions. At last, controller-cluster matching with mobility-aware boundary fine-tuning.
• Figure 5: Containment relationship between FOV domains (determined by antenna elevation angle constraints) and control domains (actual satellites managed by controllers) in hierarchical satellite networks.