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 ...
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