US 12,335,152 B2
Modifying network routing and bandwidth balancing for lower latency and high quality fair traffic
Faisal A. Qureshi, Kirkland, WA (US)
Assigned to HOURGLASS SOFTWARE LLC, Dover, DE (US)
Filed by Hourglass Software LLC, Dover, DE (US)
Filed on Sep. 11, 2023, as Appl. No. 18/464,359.
Claims priority of provisional application 63/484,691, filed on Feb. 13, 2023.
Prior Publication US 2024/0275726 A1, Aug. 15, 2024
Int. Cl. H04L 47/125 (2022.01); H04L 45/02 (2022.01); H04L 45/125 (2022.01); H04L 47/127 (2022.01)
CPC H04L 47/125 (2013.01) [H04L 45/08 (2013.01); H04L 45/125 (2013.01); H04L 47/127 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A system comprising at least one processor, wherein the at least one processor is configured to:
based on network routing data comprising network quality data representative of a network quality applicable to a wide area network and using machine learning applied to historical network routing data, other than the network routing data, classify available routes between a source node on the wide area network and a destination node on the wide area network, resulting in classified available routes;
based on the network routing data and using a result of the machine learning applied to the historical network routing data, determine bandwidth allocations applicable to the classified available routes, resulting in predicted bandwidth allocations;
based on the classified available routes and the predicted bandwidth allocations, set a route for data transmitted from the source node to the destination node; and
based on the route and using machine learning applied to past routes, other than the route, set a bandwidth for the route that has been determined to satisfy a defined wide area network quality criterion applicable to the wide area network.