Topology Control

Topology control focuses on optimizing the structure of networks to improve performance metrics like stability, efficiency, and lifetime. Current research emphasizes applying reinforcement learning, particularly hierarchical and multi-agent approaches, and graph neural networks to manage complex network topologies, especially in power grids and UAV networks. These methods aim to address challenges such as congestion, dynamic changes, and security threats, leading to more robust and efficient network operation across various applications. The impact extends to improved resource management, enhanced security in critical infrastructure, and more effective data transmission in dynamic environments.