most citedZero-touch Continuous Network Slicing Control via Scalable Actor-Critic Learning

12 citations · 15 across the 6 of their papers we have counts for

collaborators

6 papers

cs.NI2022

A Federated DRL Approach for Smart Micro-Grid Energy Control with Distributed Energy Resources

Farhad Rezazadeh, Nikolaos Bartzoudis

The prevalence of the Internet of things (IoT) and smart meters devices in smart grids is providing key support for measuring and analyzing the power consumption patterns. This app…

cs.NI20223 cited

On the Specialization of FDRL Agents for Scalable and Distributed 6G RAN Slicing Orchestration

Farhad Rezazadeh, Lanfranco Zanzi, Francesco Devoti +3

Network slicing enables multiple virtual networks to be instantiated and customized to meet heterogeneous use case requirements over 5G and beyond network deployments. However, mos…

cs.NI2022

A Collaborative Statistical Actor-Critic Learning Approach for 6G Network Slicing Control

Farhad Rezazadeh, Hatim Chergui, Luis Blanco +2

Artificial intelligence (AI)-driven zero-touch massive network slicing is envisioned to be a disruptive technology in beyond 5G (B5G)/6G, where tenancy would be extended to the fin…

cs.NI2022

Actor-Critic-Based Learning for Zero-touch Joint Resource and Energy Control in Network Slicing

Farhad Rezazadeh, Hatim Chergui, Loizos Christofi +1

To harness the full potential of beyond 5G (B5G) communication systems, zero-touch network slicing (NS) is viewed as a promising fully-automated management and orchestration (MANO)…

cs.NI202112 cited

Zero-touch Continuous Network Slicing Control via Scalable Actor-Critic Learning

Farhad Rezazadeh, Hatim Chergui, Christos Verikoukis

Artificial intelligence (AI)-driven zero-touch network slicing is envisaged as a promising cutting-edge technology to harness the full potential of heterogeneous 5G and beyond 5G (…

cs.NI2021

Continuous Multi-objective Zero-touch Network Slicing via Twin Delayed DDPG and OpenAI Gym

Farhad Rezazadeh, Hatim Chergui, Luis Alonso +1

Artificial intelligence (AI)-driven zero-touch network slicing (NS) is a new paradigm enabling the automation of resource management and orchestration (MANO) in multi-tenant beyond…