Patent · US Active

Using graph neural networks to create table-less routers

US11310119B2 · kind B2 · utility

1Cited by

1References

20Claims

0Family size

Assignee

INDIAN INSTITUTE OF TECHNOLOGY BOMBAY · IN

Inventors

Abhiram Singh · Mumbai, IN
Sidharth Sharma · Mumbai, IN
Ashwin Gumaste · Richardson, US

Key dates

Filing date	Apr 30, 2020
Grant date	Apr 19, 2022
Priority date	—
Expiry date	Dec 30, 2040

Classification

Technology area (CPC H)Electricity
CPC primaryH04L2101/668
WIPO fieldDigital communication
WIPO sectorElectrical engineering

Abstract

Methods and apparatuses for using a neural network based model to predict an output port for a destination Internet Protocol (IP) address in a network are described. Some embodiments can construct an untrained model comprising a graph neural network (GNN), a first artificial feed-forward neural network (ANN), and a second ANN. Next, the embodiments can train the untrained model to obtain a trained model by: training the first ANN using at least IP addresses of destination nodes in the network, training the GNN using at least an adjacency matrix of the network and initial node features computed using the IP addresses of destination nodes in the network, and training the second ANN by combining the output of the first ANN and an output of the GNN using an attention mechanism. The embodiments can then use the trained model to predict the output port for the destination IP address.

Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.