Abstract: A method for managing traffic processed by a target network function of a communication network is disclosed. The target network function transmits and receives traffic over a communication channel that carries traffic between network functions and application functions. The method, performed by a Data Analytics Function (DAF) of a communication network, comprises receiving information about traffic flows over the communication channel, establishing a priority amongst traffic flows over the communication channel, based on the received information, generating a recommendation for traffic processing on the basis of the established priority, and sending the generated recommendation to a function in the network that has a management responsibility for the target network function.

Abstract: A method performed by a node in a communications network for predicting energy usage in the communications network. The method comprises obtaining values of network parameters for a plurality of nodes in the communications network and corresponding energy usage measurements for the plurality of nodes, and obtaining a subset of the network parameters that are correlated with the energy usage measurements. The method then comprises training a first model using a first machine learning process to take as input the values of the subset of network parameters for the nodes in the plurality of nodes, and output a prediction of the corresponding energy usage measurements.

Abstract: A receptacle for seating at least a portion of a spirit level, straight edge tool or other hand tool is disclosed. The present disclosure also relates to a receptacle in which at least a portion of a spirit level, straight edge tool or other hand tool is seated and to a method for temporarily seating a spirit level, straight edge tool or other hand tool by placing at least a portion of the spirit level, straight edge tool or other hand tool into the receptacle. The receptacle can be prepared by injection molding or 3-D printing.

Abstract: A method of managing predicting anomalies in operation of a communications network. The method includes receiving network performance data, including network performance data received as time series of values representing monitored characteristics. The method also includes detecting a first anomaly in operation of the communications network and, from historical network performance data, determining if an instance of the first anomaly occurred in the past. If this is a first occurrence of the first anomaly, then based on network performance data received before detecting the first anomaly the method includes building a first model for predicting an instance of the first anomaly and deploying the first model to operate. An apparatus implementing the method is also disclosed.

Abstract: A method performed by a node in a communications network for predicting energy usage in the communications network. The method comprises obtaining values of network parameters for a plurality of nodes in the communications network and corresponding energy usage measurements for the plurality of nodes, and obtaining a subset of the network parameters that are correlated with the energy usage measurements. The method then comprises training a first model using a first machine learning process to take as input the values of the subset of network parameters for the nodes in the plurality of nodes, and output a prediction of the corresponding energy usage measurements.

Abstract: Systems and methods are described which provide cell data between radio network controllers including monitoring at least one cell being controlled by a first radio network controller, compiling cell data based on configuration changes to the at least one cell and transferring the compiled cell data to at least a second radio network controller connected to the first controller over an inter controller link.

Abstract: A telecommunications switching system (1) has a switch unit (2) having switches (9) controlled by local modules (10). These modules implement instructions which are either in-build or are received from remote modules (20) on machines (6, 7, 8) which communicate via a central router (3). This allows almost unlimited processing scalability and versatility. An application object base (21) has an object corresponding directly to a local module (10) or a subset thereof and a signal base (22) provides signal-level commands understood by the local module (10). A signal transfer function (23) on the remote machine (6), and a signal transfer function (11) on the switch unit (2) provide for direct transfer of signals in both directions. There is no need to modify the local modules (10) as the signal transfer function (11) is addressable as a local module and the remote aspect of the interaction is transparent to the local modules (10).