A Novel Medium Access Policy Based on Reinforcement Learning in Energy-Harvesting Underwater Sensor Networks

Keyphrases

• Access Policy 100%
• Allocation Method 25%
• Available Energy 50%
• Channel Condition 25%
• Cluster Head 25%
• Cluster Interaction 25%
• Communication Time 25%
• Energy Harvesting 100%
• Energy Harvesting Efficiency 25%
• Environment Condition 25%
• First Node Dead 25%
• Medium Access 100%
• Multi-agent Reinforcement Learning 25%
• Numerical Results 25%
• Operational Lifetime 25%
• Piezoelectric Energy Harvesting 50%
• Policy-based 100%
• Reinforcement Learning 100%
• Reinforcement Learning Algorithm 25%
• Scheduling Approach 25%
• Sea Environment 25%
• Slot Allocation 50%
• Spatial Uncertainty 25%
• Stochastic Model 25%
• Sub-sea 25%
• Underwater Missions 25%
• Underwater Sensor Networks 100%
• Underwater Wireless Sensor Networks 50%

Engineering

• Available Energy 33%
• Cluster Communication 16%
• Cluster Head 16%
• Energy Harvesting 100%
• Harvesting Efficiency 16%
• Metrics 16%
• Nodes 100%
• Piezoelectric 33%
• Reinforcement Learning 100%
• Sea Environment 16%
• Sensor Network 100%
• Stochastic Model 16%
• Wireless Sensor Network 16%

Computer Science

• Allocation Method 50%
• Channel Condition 50%
• cluster-head 50%
• Environment Condition 50%
• Multi-Agent Reinforcement Learning 50%
• Reinforcement Learning 100%
• Sensor Networks 100%
• Stochastic Model 50%
• Wireless Sensor Network 50%