RL-ASL uses reinforcement learning to adaptively skip listening slots in TSCH networks, delivering up to 46% lower power consumption and 96% lower latency with near-perfect reliability.
A Survey on Machine Learning Software-Defined Wireless Sensor Networks (ML-SDWSNs): Current Status and Major Challenges
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RL-ASL: A Dynamic Listening Optimization for TSCH Networks Using Reinforcement Learning
RL-ASL uses reinforcement learning to adaptively skip listening slots in TSCH networks, delivering up to 46% lower power consumption and 96% lower latency with near-perfect reliability.