US 12,119,989 B2
System and method for configuring network elements in a design network topology
Vijay Anantha Murthy, Austin, TX (US)
Assigned to KEYSIGHT TECHNOLOGIES, INC., Santa Rosa, CA (US)
Filed by Keysight Technologies, Inc., Santa Rosa, CA (US)
Filed on Oct. 29, 2021, as Appl. No. 17/513,957.
Prior Publication US 2023/0133057 A1, May 4, 2023
Int. Cl. H04L 41/0816 (2022.01); G06N 3/04 (2023.01); H04L 41/08 (2022.01); H04L 41/0866 (2022.01); H04L 41/12 (2022.01)
CPC H04L 41/0816 (2013.01) [G06N 3/04 (2013.01); H04L 41/0866 (2013.01); H04L 41/0886 (2013.01); H04L 41/12 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A system for configuring network elements in a design network topology, the system comprising:
a topologies database for storing a plurality of previously determined network topologies;
a configurations database for storing previously determined configurations of the network elements in the previously determined network topologies, respectively;
a processing unit; and
a non-transitory memory for storing instructions that, when executed by the processing unit, cause the processing unit to:
receive an image of a design network topology comprising a plurality of network elements, wherein the design network topology provides at least one of structural or logical arrangements of the plurality of network elements in a communication network;
attempt to retrieve design data from the received image corresponding to the design network topology using a constellation-based model and using a supervised machine learning algorithm when the design data cannot be retrieved using the constellation-based model, depending on a format of the received image;
when the design data can be retrieved, query the topologies database using the design data to find a previously determined network topology that substantially matches the design network topology, and identify configurations for network elements in the matching network topology in the configurations database;
when the design data cannot be retrieved, predict a network topology using an unsupervised machine learning algorithm, and identify configurations for network elements in the predicted network topology in the configurations database;
determine design configurations for the network elements of the design network topology from the identified configurations;
translate the design configurations of the network elements to a standard format; and
push the translated design configurations to at least one of actual network elements or virtual network elements corresponding to the network elements.