Telefonaktiebolaget Lm Ericsson (publ)

James O'Meara

Premnath Kandhasamy Narayanan

Hans Oskar Eriksson

Nipun Sharma

Tushar Sabharwal

Rakesh Bajpai

Mahmood Osorio

Eugene Gomes

Rajiv Bhardwaj

Paddy Farrell

Amy De Buitléir

Donald Stephen Staudte

Diego Martos

Armagan Uskudar

Michael Grimes

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.

Method and apparatus for managing prediction of network anomalies

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.

Management of traffic over a communication channel

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.

Energy usage in a communications network

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Athlone, Ireland

James O'Meara