Abstract:
A method, a device, and a non-transitory storage medium are described in which multi-tiered networks and resource utilization-based provisioning service is provided. A multi-tiered mobile edge computing network that includes multiple mobile edge computing networks that are multi-tiered based on distance from a network edge includes a network device that selects a location to provision an application service for an end device based on a total resource utilization value and a performance metric associated with one or multiple candidate mobile edge computing networks.
Abstract:
A computer device receives user parameters for an Over-The-Air (OTA) update campaign. The parameters include a number of user equipment (UE) devices to receive an OTA update, a device type to receive the OTA update, a file size of an OTA update file, and a service level agreement parameter for the OTA update campaign. The computer device generates an estimate for conducting the OTA update campaign based on the user parameters and predicted network conditions, provides the estimate to a user, and receives a request for conducting the OTA update campaign using the user parameters. The request includes identifiers for the UE devices and the OTA update file. The computer device generates, based on the request, a schedule to perform the OTA update on the UE devices in accordance with the service level agreement parameter, and instructs the UE devices to perform the OTA update based on the schedule.
Abstract:
A Multi-access Edge Computing (“MEC”) controller may predict locations for a tracked UE at different future times, and may also predict content that the tracked UE may request at the different future times. The predictions may be based on MEC controller computing probabilities for the tracked UE being at the different locations at the different future times, and/or probabilities for the content that the tracked UE is likely to request at the different locations and/or future times. The MEC controller may identify a MEC device that provides extremely low latency service and/or optimally serves a network area that includes a predicted location. The MEC controller may issue a prefetch message to the MEC device that causes the MEC device to prefetch predicted content that the tracked UE is likely to request at the future time the tracked UE is likely to reach the predicted location.
Abstract:
A device receive property data associated with a coverage area of a mobile network, wherein the property data includes identification information and location information associated with the coverage area; receive load data associated with the coverage area; determine a load threshold associated with the coverage area; determine whether the load data satisfies the load threshold; identify, based on determining that the load data satisfies the load threshold, impacted user equipment associated with the coverage area, wherein the impacted user equipment is further identified based on the property data; identify an application network device associated with the coverage area and the impacted user equipment, wherein the application network device is further identified based on the property data; determine a corrective action based on the load data, the load threshold, and the application network device; and perform the corrective action in connection with the application network device.
Abstract:
A Multi-access Edge Computing (“MEC”) controller may predict locations for a tracked UE at different future times, and may also predict content that the tracked UE may request at the different future times. The predictions may be based on MEC controller computing probabilities for the tracked UE being at the different locations at the different future times, and/or probabilities for the content that the tracked UE is likely to request at the different locations and/or future times. The MEC controller may identify a MEC device that provides extremely low latency service and/or optimally serves a network area that includes a predicted location. The MEC controller may issue a prefetch message to the MEC device that causes the MEC device to prefetch predicted content that the tracked UE is likely to request at the future time the tracked UE is likely to reach the predicted location.
Abstract:
A method, a device, and a non-transitory storage medium are described in which multi-tiered networks and resource utilization-based provisioning service is provided. A multi-tiered mobile edge computing network that includes multiple mobile edge computing networks that are multi-tiered based on distance from a network edge includes a network device that selects a location to provision an application service for an end device based on a total resource utilization value and a performance metric associated with one or multiple candidate mobile edge computing networks.
Abstract:
A server device may receive content that was transmitted using a broadcast technique; track a quantity of user devices that have entered a particular area after the content has been received by the server device; determine, based on the tracking, that the quantity of user devices meets or exceeds a threshold quantity; and redistributing, by the server device and based on the determining, the content to one or more of the user devices that have entered the particular area after the content has been received by the server device.
Abstract:
A base station includes an antenna to receive frequency bands that include a first band associated with first signals carrying machine-two-machine (M2M) data and a second band associated with second signals carrying user equipment (UE) data. The base station further includes a baseband unit (BBU) that includes: a radio frequency (RF) interface configured to receive the first signals and the second signals, a digital front end (DFE) configured to generate first symbols based on the first signals and second symbols based on the second signals, a symbol processor configured to convert the first symbols into the M2M data and the second symbols into the UE data, and one or more processors configured to forward the M2M data to a first device and the UE data to a second device that differs from the first device.
Abstract:
A device may determine that a parameter of a base station, included in a network, is to be adjusted. The device may determine a first proposed adjustment based on a first SON algorithm associated with adjusting the parameter based on performance information of multiple base stations included in the network. The device may determine a second proposed adjustment based on a second SON algorithm associated with adjusting the parameter based on performance information of the base station. The device may determine a weight factor, associated with the base station, based on a relationship between the base station and one or more neighbor base stations included in the network. The device may determine a final adjustment based on the first proposed adjustment, the second proposed adjustment, and the weight factor. The device may cause the parameter of the base station to be adjusted based on the final adjustment.
Abstract:
A system may be configured to determine radio frequency (“RF”) transmission error types associated with a group of channels. Each channel may be associated with a particular remote radio node (“RRN”), of a group of RRNs, and a user device. The system may further modify subsequent RF communications between the RRNs and the user device, on a per-channel basis, and based on the determined transmission error types associated with each channel.