Abstract: This work addresses an energy-minimized deadline-constrained task scheduling problem in human-cyber-physical systems. It consists of three subproblems: processor allocation, task sequencing, ...

Abstract: For dynamic task scheduling problems in cloud computing environments, we propose a deep reinforcement learning algorithm based on graph neural networks (GNN-PPO) that enables real-time ...