Abstract: A device may receive user device application performance logs, radio access network (RAN) performance logs, and multi-access edge computing (MEC) compute logs, and may train a machine learning model with the user device application performance logs, the RAN performance logs, and the MEC compute logs. The device may identify application capacity requirements and MEC compute requirements associated with images of RAN coverage areas of RANs, and may generate labeled and normalized images of RAN coverage areas. The device may receive real time MEC compute data, RAN performance data, and user device application data, and may identify one of the labeled and normalized images of the RAN coverage areas that matches a RAN coverage area of a particular RAN. The device may predict an application capacity and MEC compute requirements for the particular RAN, and may perform one or more actions based on the application capacity and the MEC compute requirements.

Abstract: An illustrative latency service system identifies, in response to a request by a user equipment (UE) device for performance of a distributed computing service, a latency performance level to which the UE device is subscribed. The system obtains real-time latency performance data for a distributed computing network that is to perform the distributed computing service for the UE device in response to the request, and, based on the real-time latency performance data, determines a characteristic of a geographic zone in which the UE device is located. The characteristic is associated with latency performance that the distributed computing network is capable of providing in the geographic zone. Based on the latency performance level and the characteristic of the geographic zone, the system arranges for the performance of the distributed computing service for the UE device by the distributed computing network. Corresponding methods and systems are also disclosed.

Abstract: An illustrative latency service system identifies, in response to a request by a user equipment (UE) device for performance of a distributed computing service, a latency performance level to which the UE device is subscribed. The system obtains real-time latency performance data for a distributed computing network that is to perform the distributed computing service for the UE device in response to the request, and, based on the real-time latency performance data, determines a characteristic of a geographic zone in which the UE device is located. The characteristic is associated with latency performance that the distributed computing network is capable of providing in the geographic zone. Based on the latency performance level and the characteristic of the geographic zone, the system arranges for the performance of the distributed computing service for the UE device by the distributed computing network. Corresponding methods and systems are also disclosed.