STGNN

PPO-STGNN: A Proximal Policy Optimization Approach with Spatio-Temporal Graph Neural Networks for DAG Task Scheduling in Cloud-Edge-End Computing

A new reinforcement learning algorithm called PPO-STGNN is proposed to improve scheduling of computation-intensive DAG tasks across cloud, edge, and end devices by jointly modeling task dependencies and heterogeneous infrastructure using spatio-temporal graph neural networks and proximal policy optimization.