Abstract: The described technology is generally directed towards a cellular network area optimizer. The area optimizer observes cellular network conditions at multiple radio access network (RAN) nodes within a target area. Based on observed conditions, the area optimizer applies a set of parameter values at the multiple RAN nodes. The set of parameter values enhances the overall throughput, while maintaining or improving connection retainability and accessibility, of the multiple RAN nodes under the observed conditions. The area optimizer learns different sets of parameter values to apply in response to different observed conditions by making parameter value adjustments and observing the effect of the adjustments on overall throughput of the RAN nodes in the target area.

Abstract: A method may include receiving current environment condition information associated with an extended reality device; receiving historical environment condition information associated with the extended reality device; based on current environment condition information and the historical environment condition information, determining one or more adjustments to meet a performance threshold for rendering objects on the an extended reality device or using the an extended reality device; and sending instructions to implement the one or more adjustments to meet the performance threshold for rendering objects on the extended reality device or using the extended reality device.

Abstract: Aspects of the subject disclosure may include, for example, a method that includes receiving user input to configure a secure storage unit (SSU) having a first portion attached to a network and storing encrypted data, a second portion attached to the network and storing unencrypted data, and a third portion attachable to the network. The user input defines a security level for each portion. The method also includes receiving a data object for storage in the SSU, and determining a data security level for the data object; the data security level is determined by user input regarding the data object and/or analysis of the data object by the processing system, and the analysis includes analysis of attributes of the data object and/or content of the data object. The method further includes storing the data object in the SSU according to the data security level. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, receiving network-related information associated with a first RAN that includes a first RIC, obtaining, from an artificial intelligence (AI) model synchronization system associated with a second RAN, data relating to an AI model deployed by a second RIC of the second RAN, determining, based on the data relating to the AI model and the network-related information associated with the first RAN, that the AI model can be leveraged by the first RAN to improve network performance of the first RAN, performing synchronization with the AI model synchronization system to obtain the AI model, responsive to the determining that the AI model can be leveraged by the first RAN to improve the network performance of the first RAN, and causing the first RIC to deploy the AI model in the first RAN after the performing the synchronization. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, determining a personalized cloud service requirement based on a user identity and proximity to a first location. A first edge network is configured based on the personalized cloud service requirement and the first location, and the user is provided with access to a personalized cloud service via the configured first edge network according to their proximity to the first location. A second, different location is determined, and a second edge network is configured based on the personalized cloud service requirement and according to the second location. The user is provided with access to the personalized cloud service via the configured second edge network according to their proximity to the second location. In this manner, the edge network may be reconfigured to effectively follow the user, thereby extending remote access to a consistent, personalized cloud service. Other embodiments are disclosed.

Abstract: Security rules to apply to resources, including virtual machines (VMs), in the cloud and on network edges can be learned, determined, and tested. A security management component (SMC) can analyze information relating to data traffic associated with a group of resources associated with a tenant. The analysis can comprise an artificial intelligence analysis. Ingress/egress of the data traffic to/from resources of the group of resources initially can be controlled based on a group of security rules selected by the tenant. Based on a result of the analyzing, SMC can determine a modified group of security rules to apply to the group of resources to control ingress/egress of subsequent data traffic to/from the resources, wherein the result of the analyzing can indicate respective first relationships determined between respective resources and respective second relationships determined between the respective resources and respective network addresses associated with the cloud network.

Abstract: Aspects of the subject disclosure may include, for example, a plurality of accounting nodes, each accounting node being associated with a service node of a communication network, each accounting node being configured to collect data usage information for a network segment of the communication network including an associated service node, and an accounting server in data communication with accounting nodes of the plurality of accounting nodes, the accounting server configured to receive from the accounting nodes the data usage information for each service node and determine billing for data usage of each network segment. Other embodiments are disclosed.

Abstract: The disclosed technology is directed towards associating a rescue tag with a victim in need of rescue, in which the rescue tag collects condition (biological state) data associated with the victim and provides a location of the rescue tag. The location data is maintained in association with the condition data. A responder makes a request to output the condition data, and in response, the responder's device is presented with an augmented reality display that shows the victim condition data relative to the location data. Multiple victims can be efficiently triaged, with more urgent victims highlighted via augmented reality for more urgent treatment. Filtering as requested by a responder can present augmented reality display for only a subset of the victims. Also described is the use of an aerial vehicle to assist the responders and/or a command center; the aerial vehicle can act as an edge node for efficient communication.

Abstract: Managing prefix lists at edge devices can include detecting, at an edge device, a traffic flow that can include a packet that specifies a destination address. The edge device can measure a bandwidth associated with the traffic flow, identify a flow bandwidth threshold defined for the edge device, and determine if the bandwidth associated with the traffic flow satisfies the flow bandwidth threshold. If a determination is made that the bandwidth associated with the traffic flow satisfies the flow bandwidth threshold, the edge device can include the destination address in a prefix list stored at the edge device. If a determination is made that the bandwidth associated with the traffic flow does not satisfy the flow bandwidth threshold, the edge device can omit the destination address from the prefix list stored at the edge device.

Abstract: Aspects of the subject disclosure may include, for example, a device having a processing system including a processor; and a memory that stores executable instructions that, when executed by the processing system, facilitate performance of operations including capturing images generated by a fiducial invoked on a user device; determining a context of the fiducial; detect an anomaly in the images based on the context; and responsive to detecting the anomaly, providing a notification of the anomaly. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, providing immersive media to a computing device over a network utilizing a first network slice, a first spectrum resource allocation, and/or a first RAT; obtaining a metaverse profile associated with the user, which includes information defining or associated with user capabilities and content presentable in the immersive media; processing or initiating a different network slice, a different spectrum resource allocation, and/or a different RAT based on the metaverse profile; and continuing providing the immersive media to the computing device. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, obtaining and aggregating first image content of an equipment site resulting in first aggregated image content, and providing the first aggregated image content to communication devices that render it on a respective display. Further embodiments include identifying first equipment from first user-generated input, and adjusting the first aggregated image content with a first equipment image resulting in second aggregated image content. Additional embodiments include identifying second equipment from second user-generated input, and adjusting the second aggregated image content with a second equipment image resulting in third aggregated image content.

Abstract: An example method for estimating a number of individuals present in a crowd includes generating a density map based on an image of a crowd, using a convolutional neural network, augmenting the density map with cellular signal processing data to produce an augmented density map, and estimating a number of individuals present in the crowd, based on the augmented density map.

Abstract: The concepts and technologies disclosed herein are directed to alarm correlation and ticketing for reconfigurable optical add/drop multiplexer (“ROADM”) networks. According to one aspect disclosed herein, a ROADM controller can create, based upon data associated with a plurality of ROADM network elements operating in a ROADM network, a graph of the plurality ROADM network elements. The ROADM controller can retrieve a plurality of alarms from at least a portion the plurality of ROADM network elements, associate the plurality of alarms with at least the portion of the plurality of ROADM network elements, and associate a direction of each alarm with a corresponding service direction. The ROADM controller can eliminate any alarms with a time stamp outside of a same time window. The ROADM controller can then determine that any remaining alarms are associated with a root cause of a failure within the ROADM network.

Abstract: A processing system may maintain a relationship graph that includes nodes and edges representing phone numbers and device identifiers having associations with the phone numbers. The processing system may obtain an identification of a first phone number or a first device identifier for a fraud evaluation and extract features from the relationship graph associated with at least one of the first phone number or the first device identifier. The plurality of features may include one or more device identifiers associated with the first phone number, or one or more phone numbers associated with the first device identifier. The processing system may then apply the features to a prediction model that is implemented by the processing system and that is configured to output a fraud risk value of the first phone number or the first device identifier and implement at least one remedial action in response to the fraud risk value.

Abstract: Aspects of the subject disclosure may include, for example, obtaining a reference data set comprising a plurality of reference data records, wherein the reference data set is associated with a cloud infrastructure, and wherein each of the reference data records comprises a reference network name associated with one of a plurality of reference networks that is configured within the cloud infrastructure and a corresponding reference Virtual Local Area Network (VLAN) identifier for the one of the plurality of reference networks that is configured within the cloud infrastructure; obtaining an input data set comprising a plurality of input data records, wherein the input data set is associated with the cloud infrastructure, and wherein each of the input data records comprises a network name associated with one of a plurality of networks that is being considered for configuration within the cloud infrastructure and a corresponding VLAN identifier for the one of the plurality of networks that is being considered for

Abstract: A method includes receiving a request for a communication session from a user device, identifying a first resource from a plurality of resources, wherein the first resource is associated with a first service control layer for a radio access network and wherein the plurality of resources includes at least one virtual network function (VNF), identifying a second resource from the plurality of resources, wherein the second resource is associated with a second service control layer for LTE core functions, identifying a third resource from the plurality of resources, wherein the third resource is associated with a third service control layer for content delivery, allocating a virtual machine to be used to instantiate the at least one VNF, instantiating the at least one VNF and establishing the communication session by facilitating communications between the first service control layer, the second service control layer and the third service control layer.

Abstract: The technologies described herein are generally directed to validating the integration of new carrier components at base station equipment, e.g., in a fifth generation (5G) network or other next generation networks. For example, a method described herein can include, confirming based on installation data, an installation milestone of an installation of a carrier component at base station equipment, resulting in a confirmed milestone. The method can further include, based on the confirmed milestone, identifying for an evaluation of the installation of the carrier component, a criterion associated with a characteristic of operation of the base station equipment. Further, the method can include based on a result of evaluation of the installation, sending, by the network equipment, a validation signal to the base station equipment indicating that the installation of the carrier component is validated.

Abstract: The system allows real time collection and processing of massive data from many network elements. It has an elastic architecture that scales horizontally to support different network sizes. The system in a uniform data format for downstream consumption. It employs a pub/sub data distribution mechanism that supports multiple concurrent downstream subscribers efficiently in real-time.

Abstract: Aspects of the subject disclosure may include, for example, obtaining a reference data set comprising a plurality of reference data records, wherein the reference data set is associated with a cloud infrastructure, and wherein each of the reference data records comprises a reference network name associated with one of a plurality of reference networks that is configured within the cloud infrastructure and a corresponding reference Virtual Local Area Network (VLAN) identifier for the one of the plurality of reference networks that is configured within the cloud infrastructure; obtaining an input data set comprising a plurality of input data records, wherein the input data set is associated with the cloud infrastructure, and wherein each of the input data records comprises a network name associated with one of a plurality of networks that is being considered for configuration within the cloud infrastructure and a corresponding VLAN identifier for the one of the plurality of networks that is being considered for