Reinforcement Learning-Based Network Slicing Scheme for Optimized UE-QoS in Future Networks

Keyphrases

• Core Network 100%
• Learning-based 100%
• Future Networks 100%
• Network Slicing 100%
• Reinforcement Learning 100%
• User Quality-of-service 100%
• TORCH 100%
• User Association 66%
• Network Problems 66%
• Control Signal 66%
• Bandwidth Allocation 66%
• Virtual Machine Placement 66%
• Link Assignment 66%
• Placement Problem 66%
• Radio Access Network 66%
• Resource Allocation 33%
• Network Applications 33%
• Network Functions 33%
• User Traffic 33%
• Quality of Service Guarantee 33%
• Wireless Bandwidth 33%
• Reinforcement Learning Algorithm 33%
• Number of Users 33%
• Heterogeneous Networks 33%
• Control Plane 33%
• Link Bandwidth 33%
• Mixed-integer Nonlinear Problem 33%
• Assignment Problem 33%
• Dijkstra 33%
• Network Access 33%
• Computing Resource Allocation 33%
• Task Completion Time 33%
• E2E Network Slicing 33%
• Future Generation Network 33%
• VNF Placement 33%
• Deep Q-learning Network 33%
• User Plane 33%

Computer Science

• Quality of Service 100%
• Networking Function 100%
• Reinforcement Learning 100%
• Network Slicing 100%
• Radio Access Network 66%
• Bandwidth Allocation 66%
• Virtual Networks 66%
• Resource Allocation 33%
• Heterogeneous Network 33%
• Future Generation 33%
• Service Requirement 33%
• Learning Network 33%
• Generation Network 33%
• Link Bandwidth 33%
• Assignment Problem 33%
• Control Plane 33%
• Resource Allocation in Computing 33%
• Task Completion Time 33%
• Reinforcement Learning-Based Method 33%