ScaleDRL: A Scalable Deep Reinforcement Learning Approach for Traffic Engineering in SDN with Pinning Control

Computer Science

• Communication Network 16%
• Control Theory 33%
• Deep Reinforcement Learning 100%
• Distribution Information 16%
• Forwarding Path 16%
• Learning Approach 100%
• Learning Technology 16%
• Level Simulation 16%
• Machine Learning 16%
• Network Control 16%
• Network Topology 16%
• Network Traffic 16%
• Objective Function 16%
• Reinforcement Learning 16%
• Scheduling Problem 16%
• Shortest Path Algorithm 16%
• Software-Defined Networking 100%
• Traditional Method 16%
• Transmission Delay 16%