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Service Function Chain Routing in LEO Networks Using Shortest-Path Delay Statistical Stability

Li Zeng, Zixin Wang, Yuanming Shi, Khaled B. Letaief

TL;DR

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, and introduces the Stability-Aware Multi-Stage Graph Routing algorithm, which incorporates pre-computed average delays into a multi-stage graph optimization framework.

Abstract

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.

Service Function Chain Routing in LEO Networks Using Shortest-Path Delay Statistical Stability

TL;DR

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, and introduces the Stability-Aware Multi-Stage Graph Routing algorithm, which incorporates pre-computed average delays into a multi-stage graph optimization framework.

Abstract

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.
Paper Structure (15 sections, 6 equations, 4 figures, 2 tables)

This paper contains 15 sections, 6 equations, 4 figures, 2 tables.

Table of Contents

  1. Introduction
  2. System Model
  3. Laser Inter-Satellite Link Model
  4. Service Function Chain Task Request
  5. SFC Routing Path and End-to-End Delay
  6. The Shortest-Path Delay Stability Property
  7. Pairwise Shortest-Path Delay Stability
  8. SFC Path Total Propagation Delay Stability
  9. Problem formulation and the Proposed SA-MSGR Algorithm
  10. Multi-Stage Graph Construction
  11. Optimal Path Calculation
  12. Performance Evaluation
  13. Simulation Setup
  14. Results and Analysis
  15. Conclusion

Figures (4)

  • Figure 1: Illustration of the system model. An SFC user request specifies an ordered sequence of VNFs (e.g., 1, 2, 3) between a source and destination. This logical chain is mapped onto the physical LEO network, where satellites host corresponding pre-installed VNF modules.
  • Figure 3: The proposed SA-MSGR method.
  • Figure 4: Average end-to-end SFC delay comparison
  • Figure 5: Distribution of end-to-end SFC delays for different algorithms. The box represents the interquartile range (IQR, 25th to 75th percentile). The line inside the box is the median. Whiskers extend to 1.5 × IQR from the box edges.