US 12,224,911 B2
Enhanced network automation
Bryan Dreyer, Bellevue, WA (US); Jason Nault, Issaquah, WA (US); William Roemhild, Sumner, WA (US); and Brent Smith, Arvada, CO (US)
Assigned to Level 3 Communications, LLC, Denver, CO (US)
Filed by Level 3 Communications, LLC, Broomfield, CO (US)
Filed on Aug. 24, 2023, as Appl. No. 18/455,409.
Claims priority of provisional application 63/373,547, filed on Aug. 25, 2022.
Prior Publication US 2024/0073101 A1, Feb. 29, 2024
Int. Cl. H04L 41/12 (2022.01); H04L 41/16 (2022.01)
CPC H04L 41/12 (2013.01) [H04L 41/16 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method for automating and testing communication network topologies, the method comprising:
identifying, by at least one processor of a device, templates comprising respective communication network topologies defining network devices, connections between the network devices, roles associated with the network devices, and performance tests for the communication network topologies;
selecting, by the at least one processor, a first template of the templates;
instantiating, by the at least one processor, based on the selection of the first template, an instance associated with generating a first communication network topology by establishing first connections between first network devices based on the first communication network topology and first roles associated with first network devices of the first communication network topology;
generating, by the at least one processor, performance test results for the first communication network topology based on performance of first performance tests defined by the first template;
determining, by the at least one processor, that the first communication network topology satisfies one or more performance criteria based on the generated performance test results; and
displaying, by the at least one processor and on a display device, the determination that the first communication network topology satisfies the one or more performance criteria,
wherein first test thresholds of the first performance tests are based on a machine learning model trained based on the communication network topologies and the performance tests.