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.
ELISE: A Reinforcement Learning Framework to Optimize the Slotframe Size of the TSCH Protocol in IoT Networks
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.NI 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
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.