PPO-STGNN: a proximal policy optimization approach with spatio-temporal graph neural networks for DAG task scheduling in cloud-edge-end computing.
Read the original at arxiv.org→arXiv:2609.03503v1 Announce Type: new Abstract: With the rapid development of the Internet of Things, computation intensive directed acyclic graph (DAG) tasks have become increasingly common in cloud-edge-end...
Original headline: "PPO-STGNN: A Proximal Policy Optimization Approach with Spatio-Temporal Graph Neural Networks for DAG Task Scheduling in Cloud-Edge-End Computing"
Coverage timeline
- Sep 4, 04:00 UTC arXiv cs.AI lead source PPO-STGNN: A Proximal Policy Optimization Approach with Spatio-Temporal Graph Neural Networks for DAG Task Scheduling in Cloud-Edge-End Computing