Harnessing AI and Confluent Technologies for Next-Generation 6G Networks
Paper in proceeding, 2025
This talk presents a new 6G network concept using artificial intelligence-based orchestration and combining radio fixed wireless, free-space optical, and wavelength-division multiplexed transport to enable energy-efficient, low-latency, highly available confluent mesh edge networking.
Software defined networking (SDN) and OpenFlow/GMPLS
Machine learning in optical communication networks
Fog/edge computing infrastructure and applications
Converged mobile and optical access networks
Availability/reliability/disaster recovery
Author
Paolo Monti
Chalmers, Electrical Engineering, Communication, Antennas and Optical Networks
Dan Kilper
Trinity College Dublin
Ioanna Mesogiti
OTE Group
Colm Browning
MBRYONICS Production
Carlos Natalino Da Silva
Chalmers, Electrical Engineering, Communication, Antennas and Optical Networks
Aleksandra Kaszubowska Anandarajah
Trinity College Dublin
Marco Ruffini
Trinity College Dublin
Opto-Electronics and Communications Conference, OECC
21668884 (ISSN) 21668892 (eISSN)
Vol. 2025
2025 30th OptoElectronics and Communications Conference (OECC) and 2025 International Conference on Photonics in Switching and Computing (PSC)
Sapporo, Japan,
Sapporo, Japan,
Subject Categories (SSIF 2025)
Other Electrical Engineering, Electronic Engineering, Information Engineering
Computer Sciences
Telecommunications
DOI
10.23919/OECC/PSC62146.2025.11111139