HRL-VNEAP applies hierarchical RL to dynamic VNE with alternative topologies and reports up to 20.7% higher acceptance ratio than strong baselines on realistic networks.
Ai-empowered virtual network embedding: A comprehen- sive survey,
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Hierarchical Reinforcement Learning for the Dynamic VNE with Alternatives Problem
HRL-VNEAP applies hierarchical RL to dynamic VNE with alternative topologies and reports up to 20.7% higher acceptance ratio than strong baselines on realistic networks.