Quantum Annealing-Based Algorithm for Efficient Coalition Formation Among LEO Satellites

Fuente: arXiv
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Auteurs principaux: Venkatesh, Supreeth Mysore, Macaluso, Antonio, Nuske, Marlon, Klusch, Matthias, Dengel, Andreas
Format: Preprint
Publié: 2024
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author Venkatesh, Supreeth Mysore
Macaluso, Antonio
Nuske, Marlon
Klusch, Matthias
Dengel, Andreas
author_facet Venkatesh, Supreeth Mysore
Macaluso, Antonio
Nuske, Marlon
Klusch, Matthias
Dengel, Andreas
contents The increasing number of Low Earth Orbit (LEO) satellites, driven by lower manufacturing and launch costs, is proving invaluable for Earth observation missions and low-latency internet connectivity. However, as the number of satellites increases, the number of communication links to maintain also rises, making the management of this vast network increasingly challenging and highlighting the need for clustering satellites into efficient groups as a promising solution. This paper formulates the clustering of LEO satellites as a coalition structure generation (CSG) problem and leverages quantum annealing to solve it. We represent the satellite network as a graph and obtain the optimal partitions using a hybrid quantum-classical algorithm called GCS-Q. The algorithm follows a top-down approach by iteratively splitting the graph at each step using a quadratic unconstrained binary optimization (QUBO) formulation. To evaluate our approach, we utilize real-world three-line element set (TLE/3LE) data for Starlink satellites from Celestrak. Our experiments, conducted using the D-Wave Advantage annealer and the state-of-the-art solver Gurobi, demonstrate that the quantum annealer significantly outperforms classical methods in terms of runtime while maintaining the solution quality. The performance achieved with quantum annealers surpasses the capabilities of classical computers, highlighting the transformative potential of quantum computing in optimizing the management of large-scale satellite networks.
format Preprint
id arxiv_https___arxiv_org_abs_2408_06007
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Quantum Annealing-Based Algorithm for Efficient Coalition Formation Among LEO Satellites
Venkatesh, Supreeth Mysore
Macaluso, Antonio
Nuske, Marlon
Klusch, Matthias
Dengel, Andreas
Quantum Physics
Computational Complexity
Discrete Mathematics
Multiagent Systems
The increasing number of Low Earth Orbit (LEO) satellites, driven by lower manufacturing and launch costs, is proving invaluable for Earth observation missions and low-latency internet connectivity. However, as the number of satellites increases, the number of communication links to maintain also rises, making the management of this vast network increasingly challenging and highlighting the need for clustering satellites into efficient groups as a promising solution. This paper formulates the clustering of LEO satellites as a coalition structure generation (CSG) problem and leverages quantum annealing to solve it. We represent the satellite network as a graph and obtain the optimal partitions using a hybrid quantum-classical algorithm called GCS-Q. The algorithm follows a top-down approach by iteratively splitting the graph at each step using a quadratic unconstrained binary optimization (QUBO) formulation. To evaluate our approach, we utilize real-world three-line element set (TLE/3LE) data for Starlink satellites from Celestrak. Our experiments, conducted using the D-Wave Advantage annealer and the state-of-the-art solver Gurobi, demonstrate that the quantum annealer significantly outperforms classical methods in terms of runtime while maintaining the solution quality. The performance achieved with quantum annealers surpasses the capabilities of classical computers, highlighting the transformative potential of quantum computing in optimizing the management of large-scale satellite networks.
title Quantum Annealing-Based Algorithm for Efficient Coalition Formation Among LEO Satellites
topic Quantum Physics
Computational Complexity
Discrete Mathematics
Multiagent Systems
url https://arxiv.org/abs/2408.06007