Abstract: A device may receive and store credentials identifying security levels of users for access to functionalities of an on-premises device, and may receive a credential of a user and a request to access a functionality of the on-premises device. The device may determine whether a security level of the credential matches a first security level of the credentials, and may reject the request when the security level fails to match the first security level. The device may determine, when the security level matches the first security level, whether a computing resource of the on-premises device matches a computing resource of the first security level, and may provide the user with access to the computing resource when the computing resource matches the computing resource of the first security level. The device may reject the request when the computing resource fails to match the computing resource of the first security level.

Abstract: A base station may include a processor configured to configure a default time period for periodic service requests for discontinuous reception (DRX) for user equipment (UE) devices serviced by the base station. The processor may be further configured to obtain a signal quality value for a UE device serviced by the base station; determine that the obtained signal quality value is less than a low signal quality threshold; and configure a longer time period for the periodic service requests for DRX for the UE device, in response to determining that the obtained signal quality value is less than the low signal quality threshold.

Abstract: A device may receive original data to be deidentified and may select one or more dictionaries, from a plurality of dictionaries, based on the original data. The device may sort the one or more dictionaries based on an output control key to generate one or more sorted dictionaries, and may hash the original data into one or more hash codes. The device may extract a sequence of a quantity of digits or characters, from each of the one or more hash codes, to generate one or more sequences, and may retrieve, from the one or more sorted dictionaries, one or more substitution values corresponding to the one or more sequences. The device may generate deidentified data based on the one or more substitution values, and may perform one or more actions based on the deidentified data.

Abstract: In some implementations, the techniques described herein relate to a system including: a group of one or more base stations; a radio controller communicatively coupled to the group of base stations and configured to self-identify a current location and identify permissible wireless frequencies based on the current location; a channel manager communicatively coupled to the radio controller configured to scan the permissible wireless channels, identify a subset of the permissible wireless channels within the permissible wireless frequencies, select a radio profile based on the subset of the permissible wireless channels, and transmit the radio profile to the base station; and a gateway communicatively coupled to the base station, the gateway configured to receive and transmit data from a satellite via wireless backhaul.

Abstract: A system described herein may receive a communication session request associated with a particular User Equipment (“UE”) and a network that includes a plurality of network slices. The communication session request may include a particular identifier, such as a Data Network Name (“DNN”) or other type of identifier. The system may output a request for network slice information, wherein the request includes the particular identifier; and may receive network slice information that indicates multiple network slices that were selected based on the particular identifier. A Unified Data Management function (“UDM”), Unified Data Repository (“UDR”), and/or other element of the network may provide such information. The system may identify network slice priority information that indicates relative priorities of the network slices, may select a particular network slice based on the network slice priority information, and may respond to the communication session request in accordance with the selected first network slice.

Abstract: One or more computing devices, systems, and/or methods for managing security associated with applications are provided. In an example, a central security gateway may determine first security policy information associated with a first application. The central security gateway may establish a first encrypted connection with a first device of the first application. The central security gateway may manage, based upon the first security policy information and using the first encrypted connection, security associated with the first application. The central security gateway may determine second security policy information associated with a second application. The central security gateway may establish a second encrypted connection with a second device of the second application. The central security gateway may manage, based upon the second security policy information and using the second encrypted connection, security associated with the second application.

Abstract: A system described herein may provide a technique for allocation and/or preemption of radio access network (“RAN”) resources in a wireless network based on Quality of Service (“QoS”)-related metrics associated with User Equipment (“UEs”) that are connected to, and/or are requesting connection to, a RAN. QoS-related metrics may include a network slice, a QoS Flow Identifier (“QFI”), other suitable metrics. A Slice-Based Priority (“SBP”) determine one or more priority (e.g., SBP) values for UEs connected to the one or more RANs, and/or for UEs requesting connection to such RANs. In addition to QoS-related metrics priority values may be determined based on RAN-related metrics, such as Allocation and Retention Priority (“ARP”) values associated with a UE. RANs may accordingly be able to allocate resources, accept or deny connection requests, and/or perform preemption based at least partly on slice-related QoS metrics, thus preserving end-to-end QoS parameters.

Abstract: A method, a system, and a non-transitory storage medium are described in which a AI-based self-management network service is provided. The AI-based self-management network service may include AI-based self-routing management, AI-based self-capacity management, and AI-based self-fault and recovery management for a self-managed network and services. The AI-based self-routing management service may calculate predicted utilization values of network resources of a network path, and calculate a predicted path weight based on the predicted utilization values. The AI-based self-fault and recovery management service may refine the identification of probable causes of failures and selection of recovery actions, and generate new probable causes of failures and new recovery actions based on a machine learning model.

Abstract: A cable identification system is provided. The cable identification system may include a laser pulse generator configured to emit laser pulses into the first optical-fiber cable segment. The cable identification system may include a polarization disturbance device configured to induce a change in polarization of a second optical-fiber cable segment via changing a position of the second optical-fiber cable segment. The cable identification system may include a polarization detection device configured to determine measures of polarization based upon backscattered light received from the first optical-fiber cable segment when the second optical-fiber cable segment has different positions. The polarization detection device may be configured to determine whether the first optical-fiber cable segment is connected to the second optical-fiber cable segment based upon the measures of polarization.

Abstract: A device described herein may maintain a distributed ledger that is also maintained by at least one other device, where the distributed ledger includes at least a particular record. The device may receive a first record and a second record for recordation to the distributed ledger, where the first and second records each include a reference to the particular record, and where the first and second records further respectively include first and second values. The device may compare, based on the first and second records each including the reference to the same particular record, the first value to the second value. The device may determine, based on the comparing, a sequence of the first and second records, and may maintain information indicating that the distributed ledger includes the first and second records. The information may further indicate the determined sequence of the first and second records.

Abstract: In some implementations, a network device may receive a subscription request to subscribe to receive notifications associated with context data related to a registered session associated with a user equipment (UE). The registered session may be associated with a reauthorization timer that is associated with triggering the network device to provide a request for reauthorization of the registered session. The network device may provide, based on an expiration of the reauthorization timer, the request for reauthorization of the registered session.

Abstract: A method, a system, and a non-transitory storage medium are described in which an discovery service is provided. The discovery service may provide a network device to request for binding information from a binding service function. The request may include information that indicates a type of policy control function. For example, the information may indicate a session management policy control function, an access management policy control function, or another dedicated type of policy control function.

Abstract: A method may include identifying a network slice to service an unmanned aerial vehicle (UAV) and assigning the identified network slice to the UAV. The method may also include receiving, from a user equipment (UE) device, a message intended for the UAV, transmitting the message to the UAV and receiving, from the UE device, information identifying an error rate associated with the message. The method may further include determining whether the error rate is greater than a threshold error rate and in response to determining that the error rate is greater than the threshold error rate, at least one of modifying a modulation and coding scheme (MCS) associated with transmitting the message to the UAV, or retransmitting the message to the UAV at least one time.

Abstract: A quality of service traffic steering approach for multi-access edge computing (MEC) environments is disclosed. In an embodiment, a network exposure function (NEF) or similar device (e.g., MEC controller or orchestrator) monitors a quality of service (QoS) of a data session between a user equipment (UE) and an application. The NEF then can determine when the QoS of the data session does not meet a requested service level agreement (SLA). When the SLA is not met, the NEF identifies a MEC host that meets the SLA using a database of MEC applications. Based on the identified MEC host, the NEF re-routes the data session to the MEC host.

Abstract: A device may process video data, with a feature extraction model, to generate features, and may process a customer identifier, with an embedding layer, to generate an input. The device may optimize model weights for a classifier model and a customizer model, and may process the features, with the classifier model, to generate general predictions. The device may process the features, the input, and the general predictions, with the customizer model, to generate customer predictions, and may calculate first errors for the general predictions. The device may calculate second errors for the customer predictions, and may train the classifier model and the feature extraction model with the first errors and the optimized model weights. The device may train the customizer model and the embedding layer with the second errors and the optimized model weights. The device may implement the trained classifier model, feature extraction model, customizer model, and embedding layer.

Abstract: A system described herein may receive ledger information based on contents of a distributed ledger maintained by a first set of nodes, receive communication information associated with the first set of nodes, and establish a second set of nodes. Establishing the second set of nodes may includes providing the ledger information to the second set of nodes, providing the communication information, associated with the first set of nodes, to the second set of nodes, and maintaining information that the second set of nodes are in a first state. After establishing the second set of nodes, the system may obtain sync information from the first set of nodes, provide the sync information to the second set of nodes, and based on providing the sync information to the second set of nodes, maintain information that the second set of nodes are in a second state.

Abstract: In some aspects, the techniques described herein relate to a method including: initiating a communication session between a user and an agent; generating an application link for the communication session, the application link associated with a co-browsing application; transmitting the application link to a client device associated with the user; receiving data from the client device via the co-browsing application executed in response to the application link and associating the data with the communication session; pre-populating a co-browsing session using the data; and synchronizing a display of pages between an agent emulator and the co-browsing application, wherein synchronizing includes rendering a given page on both the agent emulator and the co-browsing application and displaying an input received via the co-browsing application in the agent emulator.

Abstract: A system described herein may maintain a distributed ledger that includes records, such as Non-Fungible Tokens (“NFTs”), which may represent assets dynamic attributes. The system may record a first record, associated with a given asset, to a distributed ledger. The first record may include an identifier, such as an identifier associated with the asset. The system may receive a request to update the attributes of the asset, where the request may include the identifier. The request may include a hash of the previously recorded attributes of the asset, where such attributes may be maintained by an off-chain repository. The system may compare a hash of the attributes, as included in the first record, to the hash included in the request, and may authorize the recordation of a second record to the distributed ledger, including the updated attributes, when the hashes match.

Abstract: In some implementations, the techniques described herein relate to a system including: a base station; and a customer premises equipment (CPE) communicatively coupled to the base station via a wide area network (WAN) and to user equipment (UE) via a local area network (LAN). The CPE can transmit location requests to the UEs; receive location request responses from the UEs, wherein a given location request response in the location request responses includes a location and one or more measurement values generated by a respective UE; store the location request responses in a location database; identify highest accuracy location request responses for the UEs from the location request responses based on corresponding measurement values of the location request responses; compute a CPE location based on the highest accuracy location request responses, the CPE location including a latitude and longitude of the CPE; and transmit the CPE location to the base station.

Abstract: A device may receive video data identifying videos, and may process the video data with a machine learning model, to determine classifications. The device may generate labels for the videos, and may calculate event severity scores and event severity labels. The device may calculate event severity incoherence scores, and may calculate user feedback scores of users associated with the device. The device may determine reviewer mistrust scores, and may calculate time review scores. The device may calculate reviewer bias scores, and may determine relabeling scores for the videos based on the event severity incoherence scores, the user feedback scores, the reviewer mistrust scores, the time review scores, and the reviewer bias scores. The device may generate new labels for one or more of the videos based on the relabeling scores, and may retrain the machine learning model, with the new labels, to generate a retrained machine learning model.