Attention-Enhanced DRPO Reinforcement Learning for SFC Routing and Deployment in Satellite-Terrestrial Integrated Networks

Global Load-Aware Routing Algorithm for Multi-Service LEO Networks: A Graph-Based DRL Approach

To address the challenges of multi-service congestion and load imbalance in Low Earth Orbit (LEO) networks, stemming from highly dynamic spatio-temporal characteristics and constrained link capacities, this paper proposes a joint optimization method for routing and load balancing based on Graph Neural Networks (GNN) an...

MAFRL: A Multi-Agent Flow-Balance Reinforcement Learning Framework for Resource Allocation in LEO Satellite Systems

Low Earth orbit (LEO) satellite systems are expected to deliver ubiquitous broadband connectivity, but their dynamic topology and limited on-board resources challenge beam hopping (BH) scheduling and inter-satellite load balancing. This paper proposes a multi-satellite cooperative BH algorithm based on multi-agent flow...

Data-Driven Lagrangian Optimization for O-RAN Efficiency

This letter presents a data-driven solution based on an energy-saving rApp that uses unsupervised learning to optimize cell switch-on/off decisions, enhancing the energy efficiency of Open Radio Access Network (O-RAN) networks while guaranteeing Quality of Service (QoS) in terms of outage probability. The proposed rApp...

Hierarchical Scheduling for Federated Learning Optimization over Deterministic Satellite Networks

Adaptive Traffic-Aware Routing for Dynamic LEO Satellite Networks

Low Earth orbit (LEO) satellite networks require adaptive routing because satellite mobility, inter-satellite link availability, and traffic congestion change over time. This paper proposes a double deep Q-Network-based traffic-aware routing method for dynamic LEO satellite networks. The routing agent selects the next-...

Symbiotic Value Capacity Optimization in Satellite-Terrestrial Integrated Communication and Computing Networks

Satellite-terrestrial integrated communication and computing network (STICCN) faces the core challenge of supporting highly heterogeneous tasks with differentiated requirements, under stringent dual constraints of communication and computing resources. Most existing scheduling schemes focus on macroscopic system perfor...