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Intelligent Collaborative Scheduling Enabled Communication-Computing Integration in Multi-Layer Satellite Networks
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DOI：10.1109/TCOMM.2025.3591166.png)
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Abstract
En 中文
Equipping satellites with computing resources to ensure efficient mission completion has become a pivotal trend in multi-layer satellite networks (MLSNs). The uneven spatial distribution of missions and computing resources across satellites necessitates advanced scheduling of communication and computing resources through satellite collaboration. However, the intricate interactions between communication and computing resources, the dynamic mission arrivals and computing resources, and the difficulty of collaboration across different layers in MLSNs present significant challenges for effective scheduling. This paper proposes a collaborative scheduling framework for low Earth orbit (LEO) and medium Earth orbit (MEO) satellites to support communication-computing integration in the MLSN. To adapt to network dynamics, we introduce a federated aggregation matrix and propose an intelligent MEO-LEO collaborative scheduling algorithm that optimizes the decision-making process under uncertain mission arrivals. Additionally, we design a distributed LEO-LEO collaborative scheduling algorithm that leverages the synergy between inter-satellite communication and computing resources to enhance scheduling capabilities and create communication-computing resource chains that meet mission requirements. Extensive simulations demonstrate that our proposed collaborative scheduling framework significantly enhances the scheduling capability of the MLSN.
Keywords:
Multi-layer satellite networks
satellite communication-computing integration
distributed resource scheduling
federated reinforcement learning
Journal
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8.3
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1.2W
Citations:
3.6W