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.

翻译：由数千颗通过光链路互连的卫星构成的大规模低地球轨道网络，其性能取决于其网络拓扑结构。现有的拓扑设计通常假设理想化条件，未考虑实际部署中的动态因素，例如部分星座部署、每日节点更替以及链路可用性变化，这使得它们难以应用于真实的低地球轨道网络。本文提出了两种在实际部署约束下明确运行的拓扑设计方法：长短链路方法，该方法系统性地结合长距离捷径链路与短距离本地链路；以及模拟退火方法，该方法通过随机优化构建拓扑。使用为期三个月的星链数据在完全部署与部分部署场景下进行评估，我们的方法相较于+Grid拓扑，实现了平均端到端延迟降低高达45%、跳数减少65%、网络容量提升高达$2.3\times$。两种方法均设计为通过增量更新拓扑来处理每日节点更替，在避免昂贵的拓扑完全重建的同时保持良好的网络性能。