Method and apparatus for graph neural network based virtual network management
AssigneePostech Research and Business Development Foundation
InventorsWon Ki HONG, Jae Hyoung YOO, Hee Gon KIM
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Abstract
A method for graph neural network-based virtual network management may comprise: preprocessing collected network data; converting node and edge data among the data for each category generated in the preprocessing step into a graph; learning the network data expressed in a matrix generated in the step of converting into the graph using a graph neural network (GNN); and learning node state information for each node generated through the learning using the GNN using a feedforward neural network (FNN) together with service list data.
Claims20
A method for graph neural network-based virtual network management, comprising the steps of:
- preprocessing collected network data;
- converting node and edge data among the data for each category generated in the preprocessing step into a graph;
- learning the network data expressed in a matrix generated in the step of converting into the graph using a graph neural network (GNN);
- and
- learning node state information for each node generated through the learning using the GNN using a feedforward neural network (FNN) together with service list data.
An apparatus for graph neural network-based virtual network management, comprising:
- a preprocessing unit to preprocess collected network data;
- a conversion unit to convert node and edge data among the data for each category generated in the preprocessing unit into a graph;
- a first learning unit to learn the network data expressed in a matrix generated in the conversion unit using a graph neural network (GNN);
- and
- a second learning unit to learn node state information for each node generated through the first learning unit using a feedforward neural network (FNN) together with service list data.
Dependencies are inferred from the claim text.