Yi-Chun Chang

STQ-Scheduler: A Secure and Throughput-Aware Deep Reinforcement Learning Framework for QoE-Driven Resource Scheduling in Distributed Video Streaming Systems

STQ-Scheduler is proposed, a secure and throughput-aware deep reinforcement learning framework that integrates high-throughput data processing, Transformer-based QoE prediction, and Proximal Policy Optimization-based resource scheduling to ensure data quality and prevent data processing from becoming a bottleneck in distributed training.