Starfield: Demand-Aware Satellite Topology Design for Low-Earth Orbit Mega Constellations
Shayan Hamidi Dehshali, Tzu-Hsuan Liao, Shaileshh Bojja Venkatakrishnan

TL;DR
Starfield is a demand-aware satellite topology design heuristic for LEO mega-constellations that improves network efficiency by optimizing inter-satellite links based on traffic patterns using a Riemannian metric approach.
Contribution
It introduces a novel demand-aware topology heuristic algorithm supported by mathematical analysis, outperforming existing patterns like +Grid and Random in simulations.
Findings
Up to 30% reduction in hop count with Starfield.
15% improvement in stretch factor over +Grid.
Robustness of Starfield under traffic demand perturbations.
Abstract
Low-Earth orbit (LEO) mega-constellations are emerging as high-capacity backbones for next-generation Internet. Deployment of laser terminals enables high-bandwidth, low-latency inter-satellite links (ISLs); however, their limited number, slow acquisition, and instability make forming a stable satellite topology difficult. Existing patterns like +Grid and Motif ignore regional traffic, ground station placement, and constellation geometry. Given sparse population distribution on Earth and the isolation of rural areas, traffic patterns are inherently non-uniform, providing an opportunity to orient inter-satellite links (ISLs) according to these traffic patterns. In this paper, we propose Starfield, a novel demand-aware satellite topology design heuristic algorithm supported by mathematical analysis. We first formulate a vector field on the constellation's shell according to traffic flows…
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