13 citations · 29 across the 12 of their papers we have counts for
13 papers
MCCL: Measurement-based Collective Communication Library
Michele Ferrero, Gabriele Castellano, Paolo Medagliani +3
Collective communication is a critical performance bottleneck in large-scale distributed training. Existing libraries and synthesis frameworks compute open-loop schedules once, ass…
Autonomic Federated-Market Orchestration for the Edge-Cloud Continuum
Lauri Lovén, Roberto Morabito, Abhishek Kumar +3
The edge-cloud computing continuum demands self-management mechanisms that scale across autonomous administrative domains while honouring tenant- and operator-specified data sovere…
Bio-inspired Agentic Self-healing Framework for Resilient Distributed Computing Continuum Systems
Alaa Saleh, Praveen Kumar Donta, Roberto Morabito +6
Human biological systems sustain life through extraordinary resilience, continually detecting damage, orchestrating targeted responses, and restoring function through self-healing.…
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…
Sometimes Painful but Certainly Promising: Feasibility and Trade-offs of Language Model Inference at the Edge
Maximilian Abstreiter, Sasu Tarkoma, Roberto Morabito
The rapid rise of Language Models (LMs) has expanded the capabilities of natural language processing, powering applications from text generation to complex decision-making. While s…
Consolidating TinyML Lifecycle with Large Language Models: Reality, Illusion, or Opportunity?
Guanghan Wu, Sasu Tarkoma, Roberto Morabito
The evolving requirements of Internet of Things (IoT) applications are driving an increasing shift toward bringing intelligence to the edge, enabling real-time insights and decisio…
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…
Follow-Me AI: Energy-Efficient User Interaction with Smart Environments
Alaa Saleh, Praveen Kumar Donta, Roberto Morabito +2
This article introduces Follow-Me AI, a concept designed to enhance user interactions with smart environments, optimize energy use, and provide better control over data captured by…
Towards Message Brokers for Generative AI: Survey, Challenges, and Opportunities
Alaa Saleh, Roberto Morabito, Sasu Tarkoma +2
In today's digital world, Generative Artificial Intelligence (GenAI) such as Large Language Models (LLMs) is becoming increasingly prevalent, extending its reach across diverse app…
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…
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…
Edge AI Inference in Heterogeneous Constrained Computing: Feasibility and Opportunities
Roberto Morabito, Mallik Tatipamula, Sasu Tarkoma +1
The network edge's role in Artificial Intelligence (AI) inference processing is rapidly expanding, driven by a plethora of applications seeking computational advantages. These appl…
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…