A deep reinforcement learning-based scheduling framework for real-time workflows in the cloud environment

Jiahui Pan, Yi Wei

Abstract: Highlights•A reinforcement learning based framework realizes dynamic workflow scheduling.•Introducing regularization enhances the robustness of the proposed algorithm.•We implement the key functions of the workflow simulator WorkflowSim in Python.•Experiments use real-world workflow benchmarks varying in structure and scale.