PRIL-M

Reinforcement learning optimizes TSCH networks for lower power and latency

Researchers have developed RL-ASL, a reinforcement learning framework designed to optimize listening slots in Time Slotted Channel Hopping (TSCH) networks. This adaptive approach dynamically decides whether to activate …