Abstract: Systems and methods for dynamic utilization-based network slice allocation management for user equipment applications are provided. In some embodiments, a slice estimation engine may be implemented to evaluate the network traffic and other application activity data associated with an application running on the UE to determine an operating mode of the application. The slice estimation engine may trigger the UE to request an adjustment to its network slice allocation configurations based on the evaluation. To determine whether or not an application should be reconfigured for a new network slice, the slice estimation engine may evaluate processes that are running on the UE. The slice estimation engine may comprise one or more slice assessment algorithms that determine which slice from a set of available network slices would optimally serve the application based on the network traffic characteristics associated with the application's current mode of operation.

Abstract: The system obtains KPIs of the production RAN of the network and capabilities of multiple UEs interacting with the test RAN. The system creates a test case based on the KPIs and the capabilities of the multiple UEs interacting with the test RAN by: adjusting a type of traffic associated with the test RAN, adjusting traffic characteristics, and adjusting the capabilities of the multiple UEs interacting with the test RAN. The system runs a simulation of the test case interacting with the test RAN to obtain simulation KPIs. The system determines whether the simulation KPIs correspond to the KPIs associated with the production RAN. Upon determining that the simulation KPIs correspond to the KPIs of the production RAN, the system stores the test case in a database. Upon determining that the simulation KPIs do not correspond to the KPIs of the production RAN, the system adjusts the test case.

Abstract: Systems and methods for geolocation-based network slice allocations for dynamic edge computing resource management are provided. In some embodiments, a network function of an operator core network may orchestrate one or more service augmentation platforms on network edge servers based on identifying event(s) where UE use the telecommunications network to access cloud-based service from an edge server within a threshold proximity of the event(s). Orchestration of the service augmentation platform(s) may be based in part on determining a network service classification for the event(s) based on event data collected about the event(s). A network slice for accessing the service augmentation platforms may be granted to UE by the network function based in part on the UE geographic proximity to the location associated with the scheduled events. The network function may de-orchestrate the service augmentation platform based on the end of the event as indicated by the event data.

Abstract: Systems and methods for dynamic utilization-based network slice allocation management for user equipment applications are provided. In some embodiments, a slice estimation engine may be implemented to evaluate the network traffic and other application activity data associated with an application running on the UE to determine an operating mode of the application. The slice estimation engine may trigger the UE to request an adjustment to its network slice allocation configurations based on the evaluation. To determine whether or not an application should be reconfigured for a new network slice, the slice estimation engine may evaluate processes that are running on the UE. The slice estimation engine may comprise one or more slice assessment algorithms that determine which slice from a set of available network slices would optimally serve the application based on the network traffic characteristics associated with the application's current mode of operation.

Abstract: The system obtains KPIs of the production RAN of the network and capabilities of multiple UEs interacting with the test RAN. The system creates a test case based on the KPIs and the capabilities of the multiple UEs interacting with the test RAN by: adjusting a type of traffic associated with the test RAN, adjusting traffic characteristics, and adjusting the capabilities of the multiple UEs interacting with the test RAN. The system runs a simulation of the test case interacting with the test RAN to obtain simulation KPIs. The system determines whether the simulation KPIs correspond to the KPIs associated with the production RAN. Upon determining that the simulation KPIs correspond to the KPIs of the production RAN, the system stores the test case in a database. Upon determining that the simulation KPIs do not correspond to the KPIs of the production RAN, the system adjusts the test case.