RELAY Selection

Relay selection encompasses optimizing the choice of intermediate nodes in various communication networks to enhance performance metrics like throughput, latency, and energy efficiency. Current research focuses on developing efficient algorithms, including neural networks (e.g., CNNs, and attention mechanisms like RelayAttention), and hybrid models combining deep learning with classical optimization techniques to address challenges in diverse applications such as wireless powered communication and large language model serving. These advancements are significant for improving the reliability and performance of various systems, ranging from power grids protected by differential relays to Internet of Things networks and robotic control systems.