US 11,996,992 B2
Opportunistic placement of compute in an edge network
Ned M. Smith, Beaverton, OR (US); S M Iftekharul Alam, Hillsboro, OR (US); Satish Chandra Jha, Portland, OR (US); Vesh Raj Sharma Banjade, Portland, OR (US); Christian Maciocco, Portland, OR (US); Kshitij Arun Doshi, Tempe, AZ (US); Francesc Guim bernat, Barcelona (ES); and Nageen Himayat, Fremont, CA (US)
Assigned to Intel Corporation, Santa Clara, CA (US)
Filed by Intel Corporation, Santa Clara, CA (US)
Filed on Jun. 28, 2022, as Appl. No. 17/851,853.
Prior Publication US 2022/0329499 A1, Oct. 13, 2022
Int. Cl. H04L 41/16 (2022.01); H04L 41/12 (2022.01); H04L 41/5006 (2022.01); H04L 41/5009 (2022.01); H04L 41/5019 (2022.01)
CPC H04L 41/5019 (2013.01) [H04L 41/12 (2013.01); H04L 41/16 (2013.01); H04L 41/5006 (2013.01); H04L 41/5009 (2013.01)] 25 Claims
OG exemplary drawing
 
1. A node in an edge network, comprising:
a processor; and
memory to store instructions, which when executed by the processor, cause the node to:
access a service level agreement related to a workload, the workload to be orchestrated for a user equipment by the node;
modify an implementation of a machine learning model based on the service level agreement;
implement the machine learning model to identify resource requirements to execute the workload in a manner to satisfy the service level agreement;
initiate resource assignments from a resource provider, the resource assignments to satisfy the resource requirements;
construct a resource hierarchy from the resource assignments;
initiate execution of the workload using resources from the resource hierarchy; and
monitor and adapt execution of the workload based on the resource hierarchy in response to the execution of the workload.