RL-ACK: A Reinforcement Learning-Based Adaptive ACK Framework for Heterogeneous Smart Kitchen IoT Networks
This paper proposes RL-ACK, a reinforcement learning–based adaptive acknowledgment framework implemented at the edge router that reduces latency, control-plane overhead, reliability violations, and utilization pressure, and maintains Tier 1 deadline-compliant delivery above 95% under high network utilization.