Francesco Malandrino

research

∙ 12/05/2022

Unexpectedly Useful: Convergence Bounds And Real-World Distributed Learning

Convergence bounds are one of the main tools to obtain information on th...

0 Francesco Malandrino, et al. ∙

research

∙ 12/02/2022

Matching DNN Compression and Cooperative Training with Resources and Data Availability

To make machine learning (ML) sustainable and apt to run on the diverse ...

0 Francesco Malandrino, et al. ∙

research

∙ 11/18/2022

Virtual Service Embedding with Time-Varying Load and Provable Guarantees

Deploying services efficiently while satisfying their quality requiremen...

0 Gil Einziger, et al. ∙

research

∙ 08/01/2022

Choose, not Hoard: Information-to-Model Matching for Artificial Intelligence in O-RAN

Open Radio Access Network (O-RAN) is an emerging paradigm, whereby virtu...

0 Jorge Martin-Perez, et al. ∙

research

∙ 07/13/2022

Performance and EMF Exposure Trade-offs in Human-centric Cell-free Networks

In cell-free wireless networks, multiple connectivity options and techno...

0 Francesco Malandrino, et al. ∙

research

∙ 02/23/2022

Energy-efficient Training of Distributed DNNs in the Mobile-edge-cloud Continuum

We address distributed machine learning in multi-tier (e.g., mobile-edge...

0 Francesco Malandrino, et al. ∙

research

∙ 01/19/2022

Flexible Parallel Learning in Edge Scenarios: Communication, Computational and Energy Cost

Traditionally, distributed machine learning takes the guise of (i) diffe...

0 Francesco Malandrino, et al. ∙

research

∙ 12/17/2021

A Belief Propagation Solution for Beam Coordination in MmWave Vehicular Networks

Millimeter-wave communication is widely seen as a promising option to in...

0 Zana Limani Fazliu, et al. ∙

research

∙ 07/31/2021

Eavesdropping with Intelligent Reflective Surfaces: Threats and Defense Strategies

Intelligent reflecting surfaces (IRSs) have several prominent advantages...

0 Francesco Malandrino, et al. ∙

research

∙ 07/06/2021

Edge-powered Assisted Driving For Connected Cars

Assisted driving for connected cars is one of the main applications that...

0 Francesco Malandrino, et al. ∙

research

∙ 07/05/2021

Towards Node Liability in Federated Learning: Computational Cost and Network Overhead

Many machine learning (ML) techniques suffer from the drawback that thei...

0 Francesco Malandrino, et al. ∙

research

∙ 06/21/2021

When Meta-Surfaces Meet Users: Optimization of Smart Radio Environments in 6G Sub-THz Communications

We consider a smart radio environment where meta-surfaces are employed t...

0 Alberto Tarable, et al. ∙

research

∙ 06/18/2021

V-Edge: Virtual Edge Computing as an Enabler for Novel Microservices and Cooperative Computing

As we move from 5G to 6G, edge computing is one of the concepts that nee...

0 Falko Dressler, et al. ∙

research

∙ 02/18/2021

Dynamic VNF Placement, Resource Allocation and Traffic Routing in 5G

5G networks are going to support a variety of vertical services, with a ...

0 Morteza Golkarifard, et al. ∙

research

∙ 02/05/2021

Network Support for High-performance Distributed Machine Learning

The traditional approach to distributed machine learning is to adapt lea...

0 Francesco Malandrino, et al. ∙

research

∙ 01/06/2021

Federated Learning at the Network Edge: When Not All Nodes are Created Equal

Under the federated learning paradigm, a set of nodes can cooperatively ...

0 Francesco Malandrino, et al. ∙

research

∙ 10/20/2020

Scheduling of Emergency Tasks for Multiservice UAVs in Post-Disaster Scenarios

Single-task UAVs are increasingly being employed to carry out surveillan...

0 Cristina Rottondi, et al. ∙

research

∙ 08/21/2020

An Edge-powered Approach to Assisted Driving

Automotive services for connected vehicles are one of the main fields of...

0 Francesco Malandrino, et al. ∙

research

∙ 07/21/2020

Graph-based Model for Beam Management in Mmwave Vehicular Networks

Mmwave bands are being widely touted as a very promising option for futu...

0 Zana Limani Fazliu, et al. ∙

research

∙ 05/19/2020

Mmwave Beam Management in Urban Vehicular Networks

Millimeter-wave (mmwave) communication represents a potential solution t...

0 Zana Limani, et al. ∙

research

∙ 02/18/2020

Active Learning-based Classification in Automated Connected Vehicles

Machine learning has emerged as a promising paradigm for enabling connec...

0 Alaa Awad Abdellatif, et al. ∙

research

∙ 01/01/2020

Characterizing Delay and Control Traffic of the Cellular MME with IoT Support

One of the main use cases for advanced cellular networks is represented ...

0 Christian Vitale, et al. ∙

research

∙ 12/06/2019

OKpi: All-KPI Network Slicing Through Efficient Resource Allocation

Networks can now process data as well as transporting it; it follows tha...

0 Jorge Martin-Perez, et al. ∙

research

∙ 11/13/2019

MEC-based Collision Avoidance for Vehicles and Vulnerable Users

Collision avoidance is one of the most promising applications for vehicu...

0 Marco Malinverno, et al. ∙

research

∙ 10/08/2019

Reducing Service Deployment Cost Through VNF Sharing

Thanks to its computational and forwarding capabilities, the mobile netw...

0 Francesco Malandrino, et al. ∙

research

∙ 07/23/2019

An Optimization-enhanced MANO for Energy-efficient 5G Networks

5G network nodes, fronthaul and backhaul alike, will have both forwardin...

0 Francesco Malandrino, et al. ∙

research

∙ 05/24/2019

Service Shifting: a Paradigm for Service Resilience in 5G

Many real-world services can be provided through multiple virtual networ...

0 Francesco Malandrino, et al. ∙

research

∙ 05/14/2019

Multiservice UAVs for Emergency Tasks in Post-disaster Scenarios

UAVs are increasingly being employed to carry out surveillance, parcel d...

0 Francesco Malandrino, et al. ∙

research

∙ 04/01/2019

Getting the Most Out of Your VNFs: Flexible Assignment of Service Priorities in 5G

Through their computational and forwarding capabilities, 5G networks can...

0 Francesco Malandrino, et al. ∙

research

∙ 02/17/2019

Towards Failure Resiliency in 5G: Service Shifting

Many real-world services can be provided through multiple VNF graphs, co...

0 Francesco Malandrino, et al. ∙

research

∙ 01/01/2019

5G Traffic Forecasting: If Verticals and Mobile Operators Cooperate

In 5G research, it is traditionally assumed that vertical industries (a....

0 Francesco Malandrino, et al. ∙

research

∙ 12/29/2018

VNF Placement and Resource Allocation for the Support of Vertical Services in 5G Networks

One of the main goals of 5G networks is to support the technological and...

0 Satyam Agarwal, et al. ∙

research

∙ 11/29/2018

Planning UAV Activities for Efficient User Coverage in Disaster Areas

Climate changes brought about by global warming as well as man-made envi...

0 Francesco Malandrino, et al. ∙

research

∙ 09/23/2018

From Megabits to CPU Ticks: Enriching a Demand Trace in the Age of MEC

All the content consumed by mobile users, be it a web page or a live str...

0 Francesco Malandrino, et al. ∙

research

∙ 09/11/2018

Characterizing the Power Cost of Virtualization Environments

Virtualization is a key building block of next-generation mobile network...

0 Senay Semu Tadesse, et al. ∙

research

∙ 06/19/2018

Mining the Air -- for Research in Social Science and Networking Measurement

Smartphone apps provide a vitally important opportunity for monitoring h...

0 Scott Kirkpatrick, et al. ∙

research

∙ 04/14/2018

Area formation and content assignment for LTE broadcasting

Broadcasting and multicasting services in LTE networks are shaping up to...

0 Claudio Casetti, et al. ∙

research

∙ 04/14/2018

Optimization-in-the-Loop for Energy-Efficient 5G

We consider the problem of energy-efficient network management in 5G sys...

0 Francesco Malandrino, et al. ∙

research

∙ 04/14/2018

Cellular Network Traces Towards 5G: Usage, Analysis and Generation

Deployment and demand traces are a crucial tool to study today's LTE sys...

0 Francesco Malandrino, et al. ∙

research

∙ 04/14/2018

Scheduling Advertisement Delivery in Vehicular Networks

Vehicular users are emerging as a prime market for targeted advertisemen...

0 Gil Einziger, et al. ∙

research

∙ 03/23/2018

Performance Analysis of C-V2I-based Automotive Collision Avoidance

One of the key applications envisioned for C-V2I (Cellular Vehicle-to-In...

0 Marco Malinverno, et al. ∙

research

∙ 01/26/2018

Characterizing Docker Overhead in Mobile Edge Computing Scenarios

Mobile Edge Computing (MEC) is an emerging network paradigm that provide...

0 Giuseppe Avino, et al. ∙

research

∙ 01/22/2018

Virtualization-based Evaluation of Backhaul Performance in Vehicular Applications

Next-generation networks, based on SDN and NFV, are expected to support ...

0 Francesco Malandrino, et al. ∙

Francesco Malandrino

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