RELIABILITY-BASED SERVICE CHAIN INSTANCE SELECTION IN A 5G NETWORK

    公开(公告)号:US20230081375A1

    公开(公告)日:2023-03-16

    申请号:US17476011

    申请日:2021-09-15

    Abstract: Reliability-based service chain instance selection in a 5G network includes evaluating, for a service chain provided in a 5G network, the service chain comprising a series of network functions with processing hand-offs and take-overs therebetween, reliability of each service chain instance of a plurality of available service chain instances of the service chain, obtaining a service request for processing in the 5G network, the service request to be serviced by the service chain, selecting a service chain instance of the plurality of available service chain instances to process the service request, the selecting being based on the evaluated reliabilities of the plurality of available service chain instances, and invoking processing of the selected service chain instance to process the service request.

    TRANSLATING INPUTS FOR VOICE COMMUNICATION

    公开(公告)号:US20220005456A1

    公开(公告)日:2022-01-06

    申请号:US16918060

    申请日:2020-07-01

    Abstract: A method can include obtaining one or more gesture definitions. Each of the one or more gesture definitions can identify a correspondence between a set of gestures and a voice communication. The method can further include detecting that a mute function of a communication device is active. The mute function can prevent the communication device from transmitting audio data to one or more receiving devices. The method can further include obtaining gesture data from one or more input devices. The method can further include identifying a first gesture definition of the one or more gesture definitions. The identifying the first gesture definition can be based on the gesture data. The method can further include initiating a transfer of a first voice communication to the one or more receiving devices. The first voice communication can correspond to the first gesture definition.

    REVERSE PROXY INSPECTION FOR ENCRYPTED TRAFFIC IN AN EDGE-BASED NETWORK

    公开(公告)号:US20250063022A1

    公开(公告)日:2025-02-20

    申请号:US18451000

    申请日:2023-08-16

    Abstract: One embodiment of the invention provides a method for reverse proxy inspection (RPI) of encrypted traffic in an edge-based network. The method comprises sharing a first certificate from an RPI instance to an edge-based network gateway. The first certificate is issued to the RPI instance. The method further comprises receiving, at the RPI instance, an encrypted message with an initial layer of encryption and a subsequent layer of encryption. The initial layer is encrypted using a second certificate issued to an edge-based network device. The subsequent layer is encrypted using the first certificate. The method further comprises, at the RPI instance, authenticating the first certificate, and decrypting the subsequent layer using the first certificate, resulting in the encrypted message with the initial layer intact. The method further comprises, at the RPI instance, inspecting the encrypted message, and forwarding the encrypted message to a centralized hub.

    PATTERN RECOGNITION FOR IDENTIFYING INDISTINCT ENTITIES

    公开(公告)号:US20240135678A1

    公开(公告)日:2024-04-25

    申请号:US17960729

    申请日:2022-10-05

    CPC classification number: G06V10/764

    Abstract: Identifying an indistinct entity within an image can include generating by an image filter multiple gradients, each of which corresponds to one of a plurality of pixels of an image captured by an imager. The image can be searched for a likely repeating pattern. Responsive to detecting, based on the multiple gradients, a likely repeating pattern within the image, data structures can be generated, the data structures comprising a set of probabilistically weighted feature vectors corresponding to the likely repeating pattern. A machine learning model can classify each of the set of probabilistically weighted feature vectors. An identity of the likely repeating pattern can be output, the identity based on the machine learning model classifications of the probabilistically weighted feature vectors.

Patent Agency Ranking