Digital Twin for Optimization of Slicing-enabled Communication Networks: A Federated Graph Learning Approach

Keyphrases

• Learning Approaches 100%
• Communication Networks 100%
• Digital Twin 100%
• Graph Learning 100%
• Quality of Service 20%
• Resource Management 20%
• Service Level 20%
• Large-scale Networks 20%
• Graph Representation 20%
• Network Dynamics 20%
• Dedicated Resource 20%
• Network Architecture 20%
• Virtual Network 20%
• Quality of Service Guarantee 20%
• Optimal Resource Allocation 20%
• Dynamic Performance 20%
• Model Privacy 20%
• Quality of Service Metrics 20%
• Network Topology 20%
• Federated Learning 20%
• Underlying Network 20%
• Network Slicing 20%
• Network Slice 20%
• Physical Network 20%
• Supervision Methods 20%
• Euclidean Graphs 20%
• Non-Euclidean 20%
• Digital Twin Framework 20%
• Topological Structure 20%
• Resource Configuration 20%
• Self-supervision 20%
• Gaussian Differential Privacy 20%
• Digital Replica 20%

Computer Science

• Communication Network 100%
• Learning Approach 100%
• Federated Graph 100%
• Digital Twin 100%
• Quality of Service 50%
• Resource Allocation 16%
• Network Dynamic 16%
• Network Architecture 16%
• Virtual Network 16%
• Service Requirement 16%
• Generalizability 16%
• Network Topology 16%
• Graph Representation 16%
• Underlying Network 16%
• Network Slicing 16%
• Physical Network 16%
• Federated Learning 16%
• Differential Privacy 16%
• Dynamic Performance 16%
• Resource Configuration 16%
• Topological Structure 16%