PREDICTIVE RESOURCE ALLOCATION IN AN EDGE COMPUTING NETWORK UTILIZING MACHINE LEARNING
The present technology relates to improving computing services in a distributed network of remote computing resources, such as edge nodes in an edge compute network. In an aspect, the technology relates to a method that includes aggregating historical request data for a plurality of requests, wherei...
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Main Authors | , , , |
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Format | Patent |
Language | English |
Published |
14.03.2024
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Subjects | |
Online Access | Get full text |
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Summary: | The present technology relates to improving computing services in a distributed network of remote computing resources, such as edge nodes in an edge compute network. In an aspect, the technology relates to a method that includes aggregating historical request data for a plurality of requests, wherein the aggregated historical request data a time of the request, a location of a device from which the request originated, and/or a type of service being requested. The method also incudes training a machine learning model based on the aggregated historical request data; generating, from the trained machine learning model, a prediction for a type of service to be request; identifying an edge node, from a plurality of edge nodes, based on a physical location of the edge node; and based on predicted service, allocating computing resources for the computing service on the identified edge node. |
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Bibliography: | Application Number: US202318518701 |