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20242026
most citedFollow-Me AI: Energy-Efficient User Interaction with Smart Environments

2 citations · 4 across the 3 of their papers we have counts for

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5 papers · 1 filter

cs.NI20252 cited

Agentic TinyML for Intent-aware Handover in 6G Wireless Networks

Alaa Saleh, Roberto Morabito, Sasu Tarkoma +3

As 6G networks evolve into increasingly AI-driven, user-centric ecosystems, traditional reactive handover mechanisms demonstrate limitations, especially in mobile edge computing an…

cs.NI2024

Future-Proofing Mobile Networks: A Digital Twin Approach to Multi-Signal Management

Roberto Morabito, Bivek Pandey, Paulius Daubaris +2

Digital Twins (DTs) are set to become a key enabling technology in future wireless networks, with their use in network management increasing significantly. We developed a DT framew…

cs.NI202313 cited

AI-native Interconnect Framework for Integration of Large Language Model Technologies in 6G Systems

Sasu Tarkoma, Roberto Morabito, Jaakko Sauvola

The evolution towards 6G architecture promises a transformative shift in communication networks, with artificial intelligence (AI) playing a pivotal role. This paper delves deep in…

cs.NI2023

Device Sampling and Resource Optimization for Federated Learning in Cooperative Edge Networks

Su Wang, Roberto Morabito, Seyyedali Hosseinalipour +2

The conventional federated learning (FedL) architecture distributes machine learning (ML) across worker devices by having them train local models that are periodically aggregated b…

cs.NI20235 cited

How Can AI be Distributed in the Computing Continuum? Introducing the Neural Pub/Sub Paradigm

Lauri Lovén, Roberto Morabito, Abhishek Kumar +3

This paper proposes the neural publish/subscribe paradigm, a novel approach to orchestrating AI workflows in large-scale distributed AI systems in the computing continuum. Traditio…