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1.发明授权公开(公告)号：US11617090B2
公开(公告)日：2023-03-28
申请号：US17674358
申请日：2022-02-17
Applicant: Verizon Patent and Licensing Inc.
Inventor： Bhumip Khasnabish , Rohit Shirish Saraf
Abstract: Provided are systems and methods for performing dynamic spectrum allocation and state shifting in order to provide high quality stateful services to user equipment (“UE”) that access the stateful services from different network locations. The dynamic spectrum allocation and state shifting may include tracking mobility of a UE accessing a stateful service using a first allocation of spectrum from a first Radio Access Network (“RAN”), predicting continued stateful service access via a second RAN, determining latency requirements of the stateful service, selecting a second allocation of spectrum at the second RAN with a frequency range that provides a first amount of latency, transferring the stateful service state to a Multi-Access Edge Computing (“MEC”) location that provides a second amount of latency for services accessed via the second RAN such that the first and second amounts of latency satisfy the performance requirements of the stateful service.
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2.发明申请公开(公告)号：US20220038534A1
公开(公告)日：2022-02-03
申请号：US16944737
申请日：2020-07-31
Applicant: Verizon Patent and Licensing Inc.
Inventor： Rohit Shirish Saraf , Bhumip Khasnabish , John Aceron
Abstract: Systems and methods described herein perform computer vision (CV) model training in a distributed edge network. Regional Multi-access Edge Compute (MEC) clusters are provided with a local copy of a CV model and a local synthetic training data generator. A MEC cluster receives client data requiring computer vision and applies the local copy of the CV model to the client data. The MEC cluster detects an exception to the local copy of the CV model and generates local synthetic training data for the exception. The MEC cluster updates, based on the local synthetic training data, the local copy of the CV model to form an updated local CV model. The MEC cluster sends the local synthetic training data and the updated local CV model to a central network. The central network uses the local synthetic training data to update a master CV model and any other interconnected CV models.
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3.发明申请公开(公告)号：US20210194988A1
公开(公告)日：2021-06-24
申请号：US16718676
申请日：2019-12-18
Applicant: Verizon Patent and Licensing Inc.
Inventor： Stephane Chaysinh , John A. Turato , Rohit Shirish Saraf
IPC: H04L29/08 , G06N20/00 , G06N5/04 , H04L12/911 , H04L12/24
Abstract: Provided are systems and methods that use artificial intelligence and/or machine learning to dynamically allocate services at different times and at different network edge locations within a Multi-Access Edge (“MEC”) enhanced network based on a multitude of factors that change the priorities of the services at the different times and at the different edge locations. For instance, a MEC controller, controlling the allocation of resources at a particular edge location, may modify the allocation of services at that particular edge location at different times based on time and/or location sensitive events that occur at different times and that relate to different services, changing usage patterns that are derived from prior service utilization, and/or categorization of the services as permanent, time insensitive, or other categories of services with permissions to execute at different times from different edge locations.
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4.发明授权公开(公告)号：US11575631B1
公开(公告)日：2023-02-07
申请号：US17402161
申请日：2021-08-13
Applicant: Verizon Patent and Licensing Inc.
Inventor： Rohit Shirish Saraf , Indraneel Sen , Yuk Lun Li , Dan Sun
IPC: H04L51/10 , H04L67/288 , H04L67/561 , H04L67/10
Abstract: A system may include a first device and a second device. The first device may be configured to select a second device for providing a first User Equipment device (UE) with media clips in accordance with Application Programming Interface (API) calls from a second UE. The second device may be configured to: receive a first API call from the second UE to generate and provide a media clip; generate the media clip; and send the generated media clip to the first UE.
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5.发明授权公开(公告)号：US11463517B2
公开(公告)日：2022-10-04
申请号：US16944737
申请日：2020-07-31
Applicant: Verizon Patent and Licensing Inc.
Inventor： Rohit Shirish Saraf , Bhumip Khasnabish , John Aceron
IPC: H04L67/1095 , G06N3/08 , G06K9/62 , G06N3/04 , H04L67/00
Abstract: Systems and methods described herein perform computer vision (CV) model training in a distributed edge network. Regional Multi-access Edge Compute (MEC) clusters are provided with a local copy of a CV model and a local synthetic training data generator. A MEC cluster receives client data requiring computer vision and applies the local copy of the CV model to the client data. The MEC cluster detects an exception to the local copy of the CV model and generates local synthetic training data for the exception. The MEC cluster updates, based on the local synthetic training data, the local copy of the CV model to form an updated local CV model. The MEC cluster sends the local synthetic training data and the updated local CV model to a central network. The central network uses the local synthetic training data to update a master CV model and any other interconnected CV models.
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Patent Agency Ranking
6.发明授权公开(公告)号：US11290891B2
公开(公告)日：2022-03-29
申请号：US16850507
申请日：2020-04-16
Applicant: Verizon Patent and Licensing Inc.
Inventor： Bhumip Khasnabish , Rohit Shirish Saraf
Abstract: Provided are systems and methods for performing dynamic spectrum allocation and state shifting in order to provide high quality stateful services to user equipment (“UE”) that access the stateful services from different network locations. The dynamic spectrum allocation and state shifting may include tracking mobility of a UE accessing a stateful service using a first allocation of spectrum from a first Radio Access Network (“RAN”), predicting continued stateful service access via a second RAN, determining latency requirements of the stateful service, selecting a second allocation of spectrum at the second RAN with a frequency range that provides a first amount of latency, transferring the stateful service state to a Multi-Access Edge Computing (“MEC”) location that provides a second amount of latency for services accessed via the second RAN such that the first and second amounts of latency satisfy the performance requirements of the stateful service.
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7.发明授权公开(公告)号：US11463554B2
公开(公告)日：2022-10-04
申请号：US16718676
申请日：2019-12-18
Applicant: Verizon Patent and Licensing Inc.
Inventor： Stephane Chaysinh , John A. Turato , Rohit Shirish Saraf
Abstract: Provided are systems and methods that use artificial intelligence and/or machine learning to dynamically allocate services at different times and at different network edge locations within a Multi-Access Edge (“MEC”) enhanced network based on a multitude of factors that change the priorities of the services at the different times and at the different edge locations. For instance, a MEC controller, controlling the allocation of resources at a particular edge location, may modify the allocation of services at that particular edge location at different times based on time and/or location sensitive events that occur at different times and that relate to different services, changing usage patterns that are derived from prior service utilization, and/or categorization of the services as permanent, time insensitive, or other categories of services with permissions to execute at different times from different edge locations.
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8.发明申请公开(公告)号：US20220174501A1
公开(公告)日：2022-06-02
申请号：US17674358
申请日：2022-02-17
Applicant: Verizon Patent and Licensing Inc.
Inventor： Bhumip Khasnabish , Rohit Shirish Saraf
Abstract: Provided are systems and methods for performing dynamic spectrum allocation and state shifting in order to provide high quality stateful services to user equipment (“UE”) that access the stateful services from different network locations. The dynamic spectrum allocation and state shifting may include tracking mobility of a UE accessing a stateful service using a first allocation of spectrum from a first Radio Access Network (“RAN”), predicting continued stateful service access via a second RAN, determining latency requirements of the stateful service, selecting a second allocation of spectrum at the second RAN with a frequency range that provides a first amount of latency, transferring the stateful service state to a Multi-Access Edge Computing (“MEC”) location that provides a second amount of latency for services accessed via the second RAN such that the first and second amounts of latency satisfy the performance requirements of the stateful service.
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公开(公告)号：US20220057791A1
公开(公告)日：2022-02-24
申请号：US16999187
申请日：2020-08-21
Applicant: Verizon Patent and Licensing Inc.
Inventor： Rohit Shirish Saraf , Bhumip Khasnabish
Abstract: A method, a device, and a non-transitory storage medium are described in which an edge computing-based teleoperations service is provided. An edge network device may select an active and one or multiple backup remote-controlling devices in support of a teleoperations service session. The edge network device may include artificial intelligence to learn remote-controlling functions based on communications relayed between a remote-controlled device and the active remote-controlling device. The edge network device may use the learned remote-controlling functions during a failover procedure or other triggering network event.
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公开(公告)号：US20210407683A1
公开(公告)日：2021-12-30
申请号：US16916946
申请日：2020-06-30
Applicant: Verizon Patent and Licensing Inc.
Inventor： Bhumip Khasnabish , Rohit Shirish Saraf
IPC: G16H50/30 , G16H40/67 , G16H50/20 , A61B5/0205
Abstract: A method, a system, and a non-transitory storage medium are described in which a health monitoring, analyzing, and response service is provided. The service may ingest monitoring information from end devices. The service may assign an adaptive weight value to each instance of monitoring information based on profile information pertaining to the end device. The profile information may include operational characteristics information and rating information. The service may aggregate the monitoring information based on the adaptive weight values to produce a weighted health or state value. The service may analyze and determine a health or condition of a person or object. The service may also generate response information reactive to the determined health or condition.
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