US 11,671,480 B2
Network topology model generation and deployment for machine learning systems
Sebastian Jeuk, Munich (DE); Sridar Kandaswamy, San Jose, CA (US); and Gonzalo Salgueiro, Raleigh, NC (US)
Assigned to Cisco Technology, Inc., San Jose, CA (US)
Filed by Cisco Technology, Inc., San Jose, CA (US)
Filed on Jul. 30, 2021, as Appl. No. 17/390,527.
Prior Publication US 2023/0032585 A1, Feb. 2, 2023
Int. Cl. H04L 67/10 (2022.01); G06N 20/00 (2019.01); H04L 41/0893 (2022.01); H04L 41/5041 (2022.01)
CPC H04L 67/10 (2013.01) [G06N 20/00 (2019.01); H04L 41/0893 (2013.01); H04L 41/5041 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A system comprising:
one or more processors; and
one or more non-transitory computer-readable media storing computer-executable instructions that, when executed by the one or more processors, perform operations comprising:
receiving a logical topology model associated with a machine learning system, wherein the machine learning system includes a first machine learning component and a second machine learning component;
determining a first attribute associated with the first machine learning component of the machine learning system, and determining a second attribute associated with the second machine learning component of the machine learning system, wherein the first attribute and the second attribute include at least one of:
a type of machine learning model;
a machine learning algorithm; or
a scoring metric associated with the machine learning system;
determining a network topology within a computing environment, wherein the network topology is determined based at least in part on the logical topology model, the first attribute associated with the first machine learning component, and the second attribute associated with the second machine learning component,
determining a set of deployment instructions based on the network topology; and
transmitting the set of deployment instructions to one or more nodes within the computing environment.