An Intelligent Deep Reinforcement Learning Framework for Online Virtual Network Embedding with Graph Convolutional Networks - Mrs. B.S.Sukanya, Dr. L. Sudha (Cuestiones de Fisioterapia, 2025)
The evolution of Virtual Network Embedding (VNE) has become a cornerstone in the optimization of resource allocation within dynamic and complex network environments. The existing research introduces InDS, a hybrid framework combining Deep Reinforcement Learning (DRL) with Graph Convolutional Networks (GCNs) to address the intricate challenges associated with VNE. InDS leverages an actor-critic model and integrates GCNs to extract rich network features, facilitating optimal decision-making for Virtual Network Requests (VNRs).