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, Kommunikation, Antenner och Optiska Nätverk
Lena Wosinska
Chalmers, Elektroteknik, Kommunikation, Antenner och Optiska Nätverk
Paolo Monti
Chalmers, Elektroteknik, Kommunikation, Antenner och Optiska Nätverk
OECC/PSC 2019 - 24th OptoElectronics and Communications Conference/International Conference Photonics in Switching and Computing 2019
9784885523212 (ISBN)
2019 24th OptoElectronics and Communications Conference (OECC) and 2019 International Conference on Photonics in Switching and Computing (PSC)
Fukuoka, ,
Fukuoka, ,
Styrkeområden
Informations- och kommunikationsteknik
Ämneskategorier
Telekommunikation
DOI
10.23919/PS.2019.8817990