Asha S

Predictive Latency-Aware Federated Deep Reinforcement Learning for Adaptive Task Scheduling in IoT-Enabled Fog Computing

Experimental evaluation under dynamic IoT workloads demonstrates significant reductions in average task latency and response time compared with FCFS, Round Robin, centralized DQN, and conventional federated reinforcement learning schedulers.