Multi-agent reinforcement learning based computation offloading and resource allocation for LEO Satellite edge computing networks

Computer Science

• Bandwidth Allocation 33%
• Battery Capacity 33%
• Computation Offloading 100%
• Edge Computing 100%
• Energy Consumption 66%
• Energy Minimisation 33%
• Ground Terminal 100%
• Minimization Problem 33%
• Mobile Terminal 33%
• Multi-Access Edge Computing 33%
• Multi-Agent Deep Reinforcement Learning 33%
• Multi-Agent Reinforcement Learning 100%
• Optimization Algorithm 33%
• Reinforcement Learning 33%
• Resource Allocation 100%
• Terrestrial Network 33%

Engineering

• Battery Capacity 25%
• Edge Computing 100%
• Energy Engineering 50%
• Energy Minimisation 25%
• Ground Terminal 75%
• Limitations 25%
• Low Earth Orbit 100%
• Minimization Problem 25%
• Mobile Edge Computing 25%
• Mobile Terminal 25%
• Reinforcement Learning 100%
• Remote Area 25%
• Simulation Result 25%
• Tasks 25%
• Terrestrial Network 25%