LIVE PROGRAM (KEYNOTES)
FRIDAY, 18 JUNE 2021
10:00 AM - 10:30 AM (EDT)
Keynote 1: "Communication-Efficient and Distributed AI For and Over Wireless Networks," Mehdi Bennis, University of Oulu, Finland
10:30 AM - 11:00 AM (EDT)
Keynote 2: "Zero-touch Management and Orchestration of Network Slices in 5G and Beyond Networks," Adlen Ksentini, EURECOM, France
Moderators: Mustapha Benjillali, INPT, Morocco, and Hatim Chergui, CTTC, Spain
ON-DEMAND PROGRAM (TECHNICAL SESSION)
FRIDAY, 18 JUNE 2021, 12h30 PM (EDT)
- Paper 1: "On Cascaded Federated Learning for Multi-tier Predictive Models"
Authors: Abdulrahman Alabbasi (Ericsson Research, Sweden); Milad Ganjalizadeh (KTH-Ericsson, Sweden); Konstantinos Vandikas (Ericsson, Sweden); Marina Petrova (KTH Royal Institute of Technolgy, Sweden)
- Paper 2: "Decentralized Federated Learning for Road User Classification in Enhanced V2X Networks"
Authors: Luca Barbieri (Politecnico di Milano, Italy); Stefano Savazzi (Consiglio Nazionale delle Ricerche CNR, Italy); Monica Nicoli (Politecnico di Milano, Italy)
- Paper 3: "Energy-Efficient mmWave UDN Using Distributed Multi-Agent Deep Reinforcement Learning"
Authors: Jihoon Moon, Hyungyu Ju, Seungnyun Kim and Byonghyo Shim (Seoul National University, South Korea)
- Paper 4: "Energy-Efficient Edge Computing: When Lyapunov Meets Distributed Reinforcement Learning"
Authors: Mohamed Sana (CEA LETI Grenoble & University of Grenoble Alpes, France); Mattia Merluzzi (Sapienza University of Rome, Italy); Nicola di Pietro (Athonet, Italy); Emilio Calvanese Strinati (CEA-LETI, France)
- Paper 5: "Cooperative Edge Caching via Federated Deep Reinforcement Learning in Fog-RANs"
Authors: Min Zhang and Yanxiang Jiang (Southeast University, China); Fu-Chun Zheng (Harbin Institute of Technology, Shenzhen, China & University of York, United Kingdom (Great Britain)); Mehdi Bennis (Centre of Wireless Communications, University of Oulu, Finland); Xiaohu You (National Mobile communication Research Lab., Southeast University, China)
DAWN'Z 2021 is organized with the support of the Horizon 2020 ICT-20 project MonB5G (Grant No. 871780 )
