Low Earth orbit (LEO) satellite constellations have become a critical enabler for global coverage, utilizing numerous satellites orbiting Earth at high speeds. By decomposing complex network services into lightweight service functions, network function virtualization (NFV) transforms global network services into diverse service function chains (SFCs), coordinated by resource-constrained LEOs. However, the dynamic topology of satellite networks, marked by highly variable inter-satellite link delays, poses significant challenges for designing efficient routing strategies that ensure reliable and low-latency communication. Many existing routing methods suffer from poor scalability and degraded performance, limiting their practical implementation. To address these challenges, this paper proposes a novel SFC routing approach that leverages the statistical properties of network link states to mitigate instability caused by instantaneous modeling in dynamic satellite networks. Through comprehensive simulations on end-to-end shortest-path propagation delays in LEO networks, we identify and validate the statistical stability of multi-hop routes. Building on this insight, we introduce the Stability-Aware Multi-Stage Graph Routing (SA-MSGR) algorithm, which incorporates pre-computed average delays into a multi-stage graph optimization framework. Extensive simulations demonstrate the superior performance of SA-MSGR, achieving significantly lower and more predictable end-to-end SFC delays compared to representative baseline strategies.

翻译：低地球轨道（LEO）卫星星座已成为实现全球覆盖的关键赋能技术，其利用大量卫星高速绕地球运行。通过将复杂网络服务分解为轻量级服务功能，网络功能虚拟化（NFV）将全球网络服务转化为多样化的服务功能链（SFC），并由资源受限的LEO卫星协调完成。然而，卫星网络动态拓扑结构（其特点是星间链路时延高度可变）对设计确保可靠、低时延通信的高效路由策略构成了重大挑战。许多现有路由方法存在可扩展性差、性能下降的问题，限制了其实际部署。为应对这些挑战，本文提出了一种新颖的SFC路由方法，该方法利用网络链路状态的统计特性来缓解动态卫星网络中瞬时建模所导致的不稳定性。通过对LEO网络中端到端最短路径传播时延的全面仿真，我们识别并验证了多跳路由的统计稳定性。基于这一发现，我们引入了稳定性感知多阶段图路由（SA-MSGR）算法，该算法将预计算的平均时延纳入多阶段图优化框架。大量仿真结果表明，SA-MSGR算法性能优越，与代表性基线策略相比，能够实现显著更低且更可预测的端到端SFC时延。