GNN-DRL cloud schedulers for DAG workflows degrade under topology shifts because structural mismatches disrupt message passing and policy generalization.
da Silva and Luiz Fernando Bittencourt
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
On the Role of DAG topology in Energy-Aware Cloud Scheduling : A GNN-Based Deep Reinforcement Learning Approach
GNN-DRL cloud schedulers for DAG workflows degrade under topology shifts because structural mismatches disrupt message passing and policy generalization.