Verizon Patent and Licensing Inc.

Syed Rehman

Raghuram Parvataneni

Mahesh Chapalamadugu

John Patrick Hickey, Iii

Anil Krishna Guntupalli

Urvika Vummadisetty

Jyotsna Kachroo

Matthew Kapala

Bjorn Hjelm

Timothy E Coyle

Umesh Kumar Gupta

Deborah Lynn Liske

A device may receive network data identifying key performance indicators associated with a base station and user equipment (UEs), UE data identifying UE data records and UE locations, and geographic data identifying a geographic area and features of the geographic area. The device may correlate the network data, the UE data, and the geographic data to generate correlated data. The device may process, the correlated data, with a plurality of machine learning models, to generate a corresponding plurality of results, and may evaluate the plurality of results, with prediction models, to generate a set of results. The device may compare classification cost function weighted predictions and the set of results to generate comparisons, and may select a machine learning model, for the geographic area and from the plurality of machine learning models, based on the comparisons. The device may implement the machine learning model for the geographic area.

Systems and methods for selecting a machine learning model that predicts a subscriber network experience in a geographic area

A system described herein may monitor, on an ongoing basis, a Key Performance Indicators ('KPIs') associated with a wireless network. The system may receive, from a particular device, a monitoring policy specifying one or more criteria, and may compare the criteria associated with the monitoring policy to the monitored KPIs. The system may determine, based on the comparing, that the criteria associated with the monitoring policy is satisfied; may determine a particular subset of the monitored KPIs based on the monitoring policy and further based on determining that the criteria associated with the monitoring policy is satisfied; and may output the particular subset of the monitored KPIs to the second device. The system may monitor the wireless network via private interfaces that are not exposed to devices external to the wireless network.

Systems and methods for policy-based monitoring of network key performance indicators

A device may receive a consent address from a user device accessing an application that requires application data associated with consent of a user of the user device, and may provide, to the user device, a consent form associated with the consent address. The device may receive, from the user device, user authentication data provided via the consent form and via a first option or a second option, and may provide, to an application server device associated with the application, a notification indicating that the user authentication data was received. The device may provide, to a cloud service provider web services device, an authorization code and an authorization token based on providing the notification. The cloud service provider web services device may cause the application data to be provided to the application server device based on receiving the authorization code and the authorization token.

Systems and methods for obtaining consent for user data sharing by a network

A system described herein may record, to a distributed ledger, information associating a particular application with a particular set of Quality of Service ('QoS') information. A particular Multi-Access/Mobile Edge Computing (“MEC”) device operator system may access the distributed ledger to identify the information associating the particular application with the particular set of QoS information. The system may read, from the distributed ledger, MEC configuration information indicating that the MEC device operator system has configured one or more MEC devices, of a plurality of MEC devices to provide the particular application in accordance with the particular set of QoS information. The system may select a particular MEC device, from the plurality of MEC devices, based on a request and further based on the MEC configuration information, and may output an indication of the selected particular MEC device in response to the request.

Systems and methods for inter-operator edge discovery using distributed ledger system

A system described herein may maintain records, in a distributed ledger, that include parameters (e.g., Quality of Service ('QoS') parameters and/or Multi-Access/Mobile Edge Computing (“MEC”) device management parameters) that are associated with particular applications and/or MEC operator systems. The system may identify a particular record, from the distributed ledger, that is associated with a particular MEC operator system. The particular record may indicate a first set of MEC configuration parameters implemented by the MEC device operator system, and one or more triggers based on which the first set of MEC configuration parameters were implemented by the MEC device operator system. The system may record a set of modified application parameters, that are generated based on the identified first set of MEC configuration parameters and the one or more triggers, to the distributed ledger.

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Monmouth Junction, NJ, United States of America

Syed Rehman