US 11,894,872 B2
Route selection in optical networks based on machine learning
Prasenjeet Acharjee, Bangalore (IN); Sai Kishore Bhyri, Bangalore (IN); and Lavan Kumar Peechara, Bangalore (IN)
Assigned to CISCO TECHNOLOGY, INC., San Jose, CA (US)
Filed by Cisco Technology, Inc., San Jose, CA (US)
Filed on Nov. 16, 2021, as Appl. No. 17/527,598.
Prior Publication US 2023/0155677 A1, May 18, 2023
Int. Cl. H04B 10/079 (2013.01); G06N 20/00 (2019.01); H04B 10/25 (2013.01); G06N 7/01 (2023.01)
CPC H04B 10/0795 (2013.01) [G06N 7/01 (2023.01); G06N 20/00 (2019.01); H04B 10/25 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method comprising:
obtaining a plurality of attributes characterizing an optical network, the optical network comprising a plurality of network nodes connected by a plurality of optical links;
at a first network node among the plurality of network nodes, calculating a plurality of cost values for sending data from the first network node to one or more next hop network nodes that are connected to the first network node, wherein a particular cost value among the plurality of cost values is associated with a probability of success of sending the data to a particular next hop network node among the one or more next hop network nodes based on a particular permutation of the plurality of attributes characterizing the optical network;
at the first network node, generating a routing table correlating a plurality of permutations of the attributes with each next hop network node based on the plurality of cost values; and
detecting at least one new network node in the optical network from a new permutation of the attributes characterizing the optical network.