US 11,907,995 B2
Edge computing storage nodes based on location and activities for user data separate from cloud computing environments
Michael Charles Todasco, Santa Clara, CA (US); Patrick Babcock, Sturbridge, MA (US); and Avik Chatterjee, Phoenix, AZ (US)
Assigned to PAYPAL, INC., San Jose, CA (US)
Filed by PAYPAL, INC., San Jose, CA (US)
Filed on Jul. 30, 2021, as Appl. No. 17/390,590.
Prior Publication US 2023/0036623 A1, Feb. 2, 2023
Int. Cl. G06Q 30/0601 (2023.01); G06N 20/00 (2019.01); G06F 16/9035 (2019.01); G06F 16/27 (2019.01); G06Q 30/0207 (2023.01); G06Q 30/0202 (2023.01)
CPC G06Q 30/0631 (2013.01) [G06F 16/27 (2019.01); G06F 16/273 (2019.01); G06F 16/9035 (2019.01); G06N 20/00 (2019.01); G06Q 30/0202 (2013.01); G06Q 30/0224 (2013.01); G06Q 30/0633 (2013.01); G06Q 30/0639 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A service provider system comprising:
a non-transitory memory; and
one or more hardware processors coupled to the non-transitory memory and configured to read instructions from the non-transitory memory to cause the service provider system to perform operations comprising:
detecting a user within a geofenced proximity associated with a merchant location;
determining that a merchant device at the merchant location utilizes data associated with users to provide services to the users at the merchant location;
determining an edge computing system, separate from the merchant device, having an edge computing storage node within a distance to a geographic area corresponding to the merchant location, wherein the edge computing storage node comprises a cloud computing node for a cloud computing service on a network separate from the merchant device, and wherein the edge computing storage node is further separate from a central storage utilized by the user for the cloud computing service on the network;
determining a user profile for the user with the service provider system;
identifying one or more activities previously performed by the user within the geofenced proximity;
determining, using a machine learning (ML) model associated with the merchant location based on the user profile and the one or more activities, a data storage action between the edge computing storage node and the central storage, wherein the data storage action moves at least a portion of the data from the edge computing storage node to the central storage or moves at least a portion of the data from the central storage to the edge computing storage node; and
executing the data storage action between the edge computing storage node and the central storage.