Telefonaktiebolaget Lm Ericsson (publ)

Pedro Henrique Gomes Da Silva

Mateus Santos

Allan Vidal

Rafia Inam

Ricardo Souza

Amadeu Do Nascimento Junior

Mateus Augusto Silva Santos

Nathan Saraiva De Sousa

Danny Lachos

Christian Esteve Rothenberg

A method performed by a first network node for a telecommunications network is provided. The method includes receiving a request for a network service. The method further includes dynamically mapping the request for the network service to an internal network slice instance based on unsupervised learning of historical data.

Network slice internal mapping using unsupervised learning and related apparatuses

A technique for anticipating impacts on service levels of one or more services provided to a User Equipment, UE, while the UE moves along a planned route is disclosed, wherein each of the one or more services is provided to the UE using a network slice in a network slicing based mobile communication system. A method implementation of the technique is performed by an anticipation component and comprises receiving (S) a service level anticipation request for the planned route of the UE, triggering (S) determining an expected impact on the service levels of the one or more services at one or more locations of the planned route, and triggering (S) sending a response to the service level anticipation request including information on the expected impact on the service levels.

Technique for anticipating service level impacts

A method for placing a virtual network function (VNF) in a datacenter system based on historical data. The method includes receiving, by a placement service from a client device, a VNF placement request that includes an identifier of the VNF, wherein the VNF placement request requests placement of an instantiation of the VNF with a node in a set of candidate nodes of the datacenter system; calculating, by the placement service, a set of similarity values between the set of candidate nodes of the datacenter system and the historical data, wherein the historical data represents previous placements of the VNF in the datacenter system, including performance indicators associated with these placements; and determining, by the placement service, a placement node from the set of candidate nodes for placing the instantiation of the VNF based on the set of similarity values.

Virtual network function placement in a cloud environment based on historical placement decisions and corresponding performance indicators

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SAO PAULO SP, Brazil

Pedro Henrique Gomes Da Silva