Time-Dependent Network Topology Optimization for LEO Satellite Constellations

Fuente: arXiv
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Main Authors: Ron, Dara, Yusufzai, Faisal Ahmed, Kwakye, Sebastian, Roy, Satyaki, Sastry, Nishanth, Shah, Vijay K.
Format: Preprint
Published: 2025
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author Ron, Dara
Yusufzai, Faisal Ahmed
Kwakye, Sebastian
Roy, Satyaki
Sastry, Nishanth
Shah, Vijay K.
author_facet Ron, Dara
Yusufzai, Faisal Ahmed
Kwakye, Sebastian
Roy, Satyaki
Sastry, Nishanth
Shah, Vijay K.
contents Today's Low Earth Orbit (LEO) satellite networks, exemplified by SpaceX's Starlink, play a crucial role in delivering global internet access to millions of users. However, managing the dynamic and expansive nature of these networks poses significant challenges in designing optimal satellite topologies over time. In this paper, we introduce the \underline{D}ynamic Time-Expanded Graph (DTEG)-based \underline{O}ptimal \underline{T}opology \underline{D}esign (DoTD) algorithm to tackle these challenges effectively. We first formulate a novel space network topology optimization problem encompassing a multi-objective function -- maximize network capacity, minimize latency, and mitigate link churn -- under key inter-satellite link constraints. Our proposed approach addresses this optimization problem by transforming the objective functions and constraints into a time-dependent scoring function. This empowers each LEO satellite to assess potential connections based on their dynamic performance scores, ensuring robust network performance over time without scalability issues. Additionally, we provide proof of the score function's boundary to prove that it will not approach infinity, thus allowing each satellite to consistently evaluate others over time. For evaluation purposes, we utilize a realistic Mininet-based LEO satellite emulation tool that leverages Starlink's Two-Line Element (TLE) data. Comparative evaluation against two baseline methods -- Greedy and $+$Grid, demonstrates the superior performance of our algorithm in optimizing network efficiency and resilience.
format Preprint
id arxiv_https___arxiv_org_abs_2501_13280
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Time-Dependent Network Topology Optimization for LEO Satellite Constellations
Ron, Dara
Yusufzai, Faisal Ahmed
Kwakye, Sebastian
Roy, Satyaki
Sastry, Nishanth
Shah, Vijay K.
Networking and Internet Architecture
Today's Low Earth Orbit (LEO) satellite networks, exemplified by SpaceX's Starlink, play a crucial role in delivering global internet access to millions of users. However, managing the dynamic and expansive nature of these networks poses significant challenges in designing optimal satellite topologies over time. In this paper, we introduce the \underline{D}ynamic Time-Expanded Graph (DTEG)-based \underline{O}ptimal \underline{T}opology \underline{D}esign (DoTD) algorithm to tackle these challenges effectively. We first formulate a novel space network topology optimization problem encompassing a multi-objective function -- maximize network capacity, minimize latency, and mitigate link churn -- under key inter-satellite link constraints. Our proposed approach addresses this optimization problem by transforming the objective functions and constraints into a time-dependent scoring function. This empowers each LEO satellite to assess potential connections based on their dynamic performance scores, ensuring robust network performance over time without scalability issues. Additionally, we provide proof of the score function's boundary to prove that it will not approach infinity, thus allowing each satellite to consistently evaluate others over time. For evaluation purposes, we utilize a realistic Mininet-based LEO satellite emulation tool that leverages Starlink's Two-Line Element (TLE) data. Comparative evaluation against two baseline methods -- Greedy and $+$Grid, demonstrates the superior performance of our algorithm in optimizing network efficiency and resilience.
title Time-Dependent Network Topology Optimization for LEO Satellite Constellations
topic Networking and Internet Architecture
url https://arxiv.org/abs/2501.13280