Graph Attention-Driven Hierarchical Reinforcement Learning for Cloud Workflow Scheduling

A new arXiv paper proposes a hierarchical reinforcement learning method that uses graph attention to schedule workflows in cloud environments. The approach targets three competing goals at once: meeting deadlines, improving container utilization, and lowering energy use. It also accounts for unpredictable task runtimes, communication costs that depend on where tasks are placed, and the need to decide task assignment and container selection together.