Abstract: Adaptable resiliency for a virtualized radio access network (vRAN) framework is disclosed. A resiliency management component can determine vRAN topological adaptations that can reflect resiliency requirements of service instance(s). Accordingly, sufficient redundant vRAN components to satisfy the resiliency requirements can be deployed. However, unlike conventional redundancy techniques that can determine a highest level of redundancy and then apply that relative to all supported services, the disclosed subject matter can avoid over-deploying redundant vRAN components, e.g., redundant components exceeding the resiliency requirement of a service instance, resulting in lowered monetary and non-monetary costs to maintain a vRAN. Moreover, as the services change, the topology of the vRAN can be automatically adapted to purge excessive redundancies, add newly required redundancies, etc., which can facilitate propagating an adequate but lean vRAN topology that is sufficiently resilient.

Abstract: Aspects of the subject disclosure may include systems and methods, for example, including receiving a user input in natural language, retrieving a first answer including a list of a first number of documents relevant to the user input by searching indexed documents in a knowledge base, applying the first answer to a large language model reader, resulting in a second answer, re-ranking the first answer by using the second answer, resulting in a third answer including a re-ranked list of the first number of documents, and generating a final response including the second answer and one or more documents among the third answer.

Abstract: Aspects of the subject disclosure may include, for example, obtaining a request pertaining to an onboarding of an application supporting a communication network or system, based on the obtaining of the request, establishing a profile for the application, selecting first resources of a first cloud computing network to support the application, based on the selecting of the first resources, configuring at least one resource of the first resources based on the profile, and deploying a first instance of the application to utilize the first resources. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, determining whether a first device is communicating under a bandwidth surplus with a fixed network, wherein the bandwidth surplus results at least in part from use by the first device of one or more link aggregation groups, wherein the one or more link aggregation groups comprise one or more satellite broadband communication channels as well as licensed cellular wireless spectrum, unlicensed wireless spectrum, or a combination of the licensed cellular and unlicensed spectrum; determining whether a second device is communicating under a bandwidth deficit with the fixed network; and responsive to the first device communicating under the bandwidth surplus and responsive to the second device communicating under the bandwidth deficit, allocating at least a portion of the bandwidth surplus associated with the first device to the second device. Other embodiments are disclosed.

Abstract: The described technology is generally directed towards network slice pre-configuration for cellular communication systems, including 5G and subsequent generation cellular communication systems. Network equipment can be preconfigured to identify whether a network slice identifier included in a network communication belongs to a group of network slice identifiers. If so, the network equipment can process the network communication either according to a network slice rule that corresponds specifically to the network slice identifier, or according to a default group network slice rule for the group to which the network slice identifier belongs. Different groups of network slice identifiers can be associated with different sets of group network slice rules which can be arranged to reduce the work of setting up network slice identifiers in various network slicing scenarios.

Abstract: A model-driven system automatically deploys a virtualized service, including multiple service components, on a distributed cloud infrastructure. A master service orchestrator causes a cloud platform orchestrator to retrieve a cloud services archive file, extract a cloud resource configuration template and create cloud resources at appropriate data centers as specified. The master service orchestrator also causes a software defined network controller to retrieve the cloud services archive file, to extract a cloud network configuration template and to configure layer 1 through layer 3 virtual network functions and to set up routes between them. Additionally, the master service orchestrator causes an application controller to retrieve the cloud services archive file, to extract a deployment orchestration plan and to configure and start layer 4 through layer 7 application components and bring them to a state of operational readiness.

Abstract: The described technology is generally directed towards reducing unwanted cellular network activities, such as phantom 911 calls or other unwanted cellular network activities. Machine learning models described herein can be trained, using device level data and network level data, to identify devices that are likely to engage in an unwanted cellular network activity. A trained machine learning model can be deployed to identify devices, and devices identified by the trained machine learning model can be re-configured to prevent them from engaging in the unwanted cellular network activity. Devices likely to engage in the unwanted cellular network activity are thus identified and reconfigured to prevent future unwanted cellular network activity before it occurs.

Abstract: A processing system may apply a data set comprising utilization metrics of a cells of a cell sector to a throughput prediction model to obtain a first predicted throughput for the cell sector for a designated future time period and for all cells being in an active state. The processing system may generate a first modified data set simulating a first cell being placed in an inactive state, by distributing utilization metrics of the first cell over at least one additional cell, and may apply the first modified data set to the throughput prediction model to obtain a second predicted throughput. The processing system may then determine that the second predicted throughput meets a threshold throughput that is based on the first predicted throughput, and transmit at least one instruction to place the first cell in the inactive state for the designated future time period in response to the determining.

Abstract: Aspects of the subject disclosure may include, for example, a method in which a processing system determines that performance of a service is required at a first location in a smart community; identifies a robot to be transported, and determines whether physical transport or virtual transport is to be performed for the robot. If physical transport is to be performed, the system initiates communication with a robot transport controller to schedule the physical transport to the first location from a different second location. If virtual transport is to be performed, the processing system initiates communication with a radio access network (RAN) to schedule the virtual transport; the virtual transport includes configuring the robot at the first location. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, a device, including a processing system including a processor; and a memory that stores executable instructions that, when executed by the processing system, facilitate performance of operations of receiving an original audio signal for an interval; creating a time-series graphical image of the original audio signal for the interval; compressing the time-series graphical image, thereby creating a reduced resolution image; recreating a retrieved audio signal from the reduced resolution image; determining whether a comparison of the retrieved audio signal to the original audio signal meets a quality threshold; responsive to meeting the quality threshold, compressing the reduced resolution image further and repeating the recreating and determining steps; and transmitting a last reduced resolution image that meets the quality threshold. Other embodiments are disclosed.

Abstract: The technologies described herein are generally directed to detecting reflective surfaces for use reflecting a signal from access point equipment to destination equipment in advanced networks, e.g., at least a fifth generation (5G) network. For example, a method described herein can include receiving a request, from access point equipment, to establish a communications session between the access point equipment and destination equipment. The method can further include based on a source of surface information, predicting that a transient reflective surface is going to be located at a first geographic location and is going to be usable by the access point equipment to reflect a signal to the destination equipment, resulting in reflected path information corresponding to a reflected path for the communications session. Further, the method can include, in response to the request, communicating to the access point equipment, the reflected path information.

Abstract: Gateway certificate management can include detecting, at a gateway device located at a premises, a connection between the gateway device and a user device located at the premises. The connection can be created to request communications between the user device and a resource that is not located at the premises. The gateway device can determine if a certificate should be issued for the communications and can analyze a profile associated with the user device and a context associated with the communications, wherein the context comprises information identifying a type of data to be communicated via the communications. The gateway device can generate the certificate, the certificate including custom certificate data including communication context data that defines the type of data. The gateway device can enable the communications to allow the user device to communicate with the resource via the gateway device to send and receive the type of data.

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 of: receiving, from a user interface, a sample input format specification and output format specification for transforming data; searching a repository for a tag and associated data; merging or updating the sample input format specification and the output format specification with the associated data responsive to finding the tag in the repository, thereby creating updated data; providing the updated data as a prompt to a large language model; receiving a response to the prompt from the large language model; verifying that the response is satisfactory; and storing a context comprising the tag, the updated data and the response in the repository. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, a non-transitory machine-readable medium comprising executable instructions that, when executed by a processing system including a processor, facilitate performance of operations, the operations comprising: receiving by a selected one of a plurality of containers incoming traffic from a legacy application, the legacy application having been associated with a migrated application prior to the migrated application having been installed on a Software as a Service (SaaS) cloud infrastructure, the incoming traffic comprising a first instruction to perform a first legacy operation; mapping the first legacy operation of the legacy application to a replacement instruction for the migrated application by receiving data from the selected container and assigning the replacement instruction to replace the first instruction; and communicating with the migrated application on the SaaS cloud infrastructure, the communicating comprising sending to the migrated appli

Abstract: Aspects of the subject disclosure may include, for example, transmitting a first value for a first parameter to a first user equipment, wherein the first parameter pertains to a first number of scans to be performed by the first user equipment to detect a first signal having a first frequency within a first frequency band as part of a first scanning procedure, and transmitting a second value for a second parameter to the first user equipment, wherein the second parameter pertains to a first amount of time that the first user equipment is to wait between the first scanning procedure and a second scanning procedure, the second scanning procedure pertaining to detection of the first signal having the first frequency within the first frequency band. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, generating a management manifest for a network function (NF) software application, wherein the NF software application is to be deployed in a cloud computing environment, based on the generating the management manifest, deriving a software package that includes the NF software application and the management manifest, and causing the software package to be outputted for deployment in the cloud computing environment, wherein inclusion of the management manifest with the NF software application in the software package facilitates utilization of the management manifest for monitoring and management of a system that results from deployment of the NF software application in the cloud computing environment. Other embodiments are disclosed.

Abstract: Concepts and technologies disclosed herein are directed to autonomous vehicle pairing management. According to one aspect disclosed herein, a fleet pairing management application executed by a processor of an autonomous vehicle can initiate a fleet pairing process with a plurality of other autonomous vehicles, each of which can execute one of a plurality of other fleet pairing management applications. The fleet pairing management application can send, over a network, an initiate network pairing request to the plurality of other autonomous vehicles. The fleet pairing management application can receive a confirm network pairing response from at least one other autonomous vehicle of the plurality of other autonomous vehicles. A fleet can then be established. The fleet can include the autonomous vehicle and the at least one other autonomous vehicle of the plurality of other autonomous vehicles. The autonomous vehicles in the fleet can then share data among the fleet.

Abstract: Aspects of the subject disclosure may include, for example, obtaining a first indication of a first vulnerability in a first communication network or system, based on the obtaining of the first indication, analyzing the first vulnerability, based on the analyzing, determining that the first vulnerability is a vulnerability of first impression, based on the determining, generating a first solution to the first vulnerability utilizing machine learning, artificial intelligence, or a combination thereof, and based on the generating, implementing the first solution as part of the first communication network or system to address the first vulnerability in the first communication network or system. Other embodiments are disclosed.

Abstract: A processing system including at least one processor may obtain data associated with a user, the data associated with the user including at least one of: visual data captured via at least one camera associated with the user or audio data captured via at least one microphone associated with the user, detect at least one trauma event of at least one defined trauma event type in at least one of the visual data or the audio data via at least one classification model, determine, responsive to detecting the at least one trauma event, a stress score based upon at least a portion of the data associated with the user in accordance with a stress prediction model, and generate an alert in response to the stress score exceeding a threshold.

Abstract: An audio generation system is provided to enable coordinated control of multiple IoT devices for audio collection and distribution of one or more audio sources according to location and user preference. The audio generation system enables a location sensitive acoustic control of sound, both as a shaped envelope for a particular source, and as an individualized experience. The audio generation system also facilitates an interactive visual system for visualization and manipulation of the audio environment including via the use of augmented reality and/or virtual reality to depict soundscapes. The audio generation system can also facilitate a system for improving and achieving an audio environment (sound influence zone) and an intuitive way to understand where sounds will be heard.