Machine Learning Methods for Slice Admission in 5G Networks
Paper i proceeding, 2019

The paper discusses how the slice admission problem can be aided by machine learning strategies. Results show that both supervised and reinforcement learning might lead to profit maximization while containing losses due to performance degradation.

virtualization

Data analytics for network control and management in optical core/data center networks

design

slice

control and management

Optical core/metro/data-center network architecture

Författare

Muhammad Rehan Raza

Kungliga Tekniska Högskolan (KTH)

Carlos Natalino Da Silva

Chalmers, Elektroteknik, Kommunikations- och antennsystem, Optiska nätverk

Lena Wosinska

Chalmers, Elektroteknik, Kommunikations- och antennsystem, Optiska nätverk

Paolo Monti

Chalmers, Elektroteknik, Kommunikations- och antennsystem, Optiska nätverk

OECC/PSC 2019 - 24th OptoElectronics and Communications Conference/International Conference Photonics in Switching and Computing 2019

2019 24th OptoElectronics and Communications Conference (OECC) and 2019 International Conference on Photonics in Switching and Computing (PSC)
Fukuoka, ,

Styrkeområden

Informations- och kommunikationsteknik

Ämneskategorier

Telekommunikation

DOI

10.23919/PS.2019.8817990

Mer information

Senast uppdaterat

2021-04-14