Embodiments are directed towards systems and methods for user plane function (UPF) and network slice load balancing within a 5G network. Example embodiments include systems and methods for load balancing based on current UPF load and thresholds that depend on UPF capacity; UPF load balancing using predicted throughput of new UE on the network based on network data analytics; UPF load balancing based on special considerations for low latency traffic; UPF load balancing supporting multiple slices, maintaining several load-thresholds for each UPF and each slice depending on the UPF and network slice capacity; and UPF load balancing using predicted central processing unit (CPU) utilization and/or predicted memory utilization of new UE on the network based on network data analytics.

A method for delivering quality of service to a moving user equipment in a computer network, the method including: identifying a moving user equipment on the computer network; predicting a path of travel for the user equipment; determining a load of a cell in the path of travel; determining a traffic action response based on the load of the cell; and providing the traffic action. A system for delivering quality of service to a moving user equipment in a computer network, the system including: a location module configured to identify a moving user equipment on the computer network; an analysis module configured to predict a path of travel for the user equipment; a load module configured to determine a load of a cell in the path of travel; and a traffic action module configured to determine a traffic action response based on the load of the cell and provide for the traffic action.

Embodiments are directed towards systems and methods for user plane function (UPF) and network slice load balancing within a 5G network. Example embodiments include systems and methods for load balancing based on current UPF load and thresholds that depend on UPF capacity; UPF load balancing using predicted throughput of new UE on the network based on network data analytics; UPF load balancing based on special considerations for low latency traffic; UPF load balancing supporting multiple slices, maintaining several load-thresholds for each UPF and each slice depending on the UPF and network slice capacity; and UPF load balancing using predicted central processing unit (CPU) utilization and/or predicted memory utilization of new UE on the network based on network data analytics.

A master node, a local node, a service assurance system, and a respective method performed thereby for predicting one or more metrics associated with a communication network are provided. The method performed by the master node operable in the communication network comprises receiving prediction(s) based on training data from local nodes in the communication network; and determining weight parameter(s) associated with the local nodes based on the current received prediction(s) and past received predictions. The method further comprises adjusting a respective local reporting policy for one or more local nodes based on the determined weight parameter(s).

A master node, a local node, a service assurance system, and a respective method performed thereby for predicting one or more metrics associated with a communication network are provided. The method performed by the master node operable in the communication network comprises receiving prediction(s) based on training data from local nodes in the communication network; and determining weight parameter(s) associated with the local nodes based on the current received prediction(s) and past received predictions. The method further comprises adjusting a respective local reporting policy for one or more local nodes based on the determined weight parameter(s).

Methods, systems and devices for network congestion control exploit the inherent burstiness of network traffic, using a wave-based characterization of network traffic and corresponding multiplexing methods and approaches.

Methods, systems and devices for network congestion control exploit the inherent burstiness of network traffic, using a wave-based characterization of network traffic and corresponding multiplexing methods and approaches.

Systems and methods for providing a guaranteed batch pool are described, including receiving a job request for execution on the pool of resources; determining an amount of time to be utilized for executing the job request based on available resources from the pool of resources and historical resource usage of the pool of resources; determining a resource allocation from the pool of resources, wherein the resource allocation spreads the job request over the amount of time; determining that the job request is capable of being executed for the amount of time; and executing the job request over the amount of time, according to the resource allocation.

Systems and methods for providing a guaranteed batch pool are described, including receiving a job request for execution on the pool of resources; determining an amount of time to be utilized for executing the job request based on available resources from the pool of resources and historical resource usage of the pool of resources; determining a resource allocation from the pool of resources, wherein the resource allocation spreads the job request over the amount of time; determining that the job request is capable of being executed for the amount of time; and executing the job request over the amount of time, according to the resource allocation.

In an electronic control unit, it is determine whether a data frame received from a different electronic control unit via a communication network is abnormal. A prediction data, which is predicted to be a normal data supposed to be included in the data frame determined to be abnormal, is generated by using a past data that is a data included in stored data frames, based on a stored prediction generation method. A prediction data frame including the prediction data is transmitted via the communication network.