Publications related to Multi-access edge computing

M2SKD: Multi-to-Single Knowledge Distillation of Real-Time Epileptic Seizure Detection for Low-Power Wearable Systems

David Atienza Alonso, Amir Aminifar, Tomas Teijeiro Campo, Alireza Amirshahi, Farnaz Forooghifar, Saleh Baghersalimi

Integrating low-power wearable systems into routine health monitoring is an ongoing challenge. Recent advances in the computation capabilities of wearables make it possible to target complex scenarios by exploiting multiple biosignals and using high-perfor ...

2024

Scalable and Privacy-Preserving Federated Principal Component Analysis

Jean-Pierre Hubaux, Juan Ramón Troncoso-Pastoriza, Jean-Philippe Léonard Bossuat, Apostolos Pyrgelis, David Jules Froelicher, Joao André Gomes de Sá e Sousa

Principal component analysis (PCA) is an essential algorithm for dimensionality reduction in many data science domains. We address the problem of performing a federated PCA on private data distributed among multiple data providers while ensuring data confi ...

IEEE COMPUTER SOC2023

Caching and Neutrality

Pavlos Nikolopoulos, Muhammad Abdullah

We are used to defining network neutrality as absence of traffic differentiation, like policing or shaping. These mechanisms, however, are often not what determines end-users’ quality of experience (QoE). Most content today is accessed through edge caches, ...

ACM Association for Computing Machinery2023

Real-Time Personalized Atrial Fibrillation Prediction on Multi-Core Wearable Sensors

David Atienza Alonso, Amir Aminifar, Miguel Peon Quiros, Adriana Arza Valdes, Elisabetta De Giovanni

In the recent Internet-of-Things (IoT) era where biomedical applications require continuous monitoring of relevant data, edge computing keeps gaining more and more importance. These new architectures for edge computing include multi-core and parallel compu ...

2020

Mneme: A Mobile Distributed Ledger

Boi Faltings, Sujit Prakash Gujar, Dimitrios Chatzopoulos

Advances in mobile computing have paved the way for new types of distributed applications that can be executed solely by mobile devices on device-to-device (D2D) ecosystems (e.g., crowdsensing). More sophisticated applications, like cryptocurrencies, need ...

IEEE2020

Ontology-Based Resource Allocation for Internet of Things

Damiano Nunzio Arena, Zeinab Nezami

The Internet of Things has revolutionized the lifestyle in all aspects. Considering the huge number of connected objects and the plethora of real-time services, edge computing approaches have emerged. Resource allocation is one of the most important challe ...

SPRINGER INTERNATIONAL PUBLISHING AG2019

A Product Engine for Energy-Efficient Execution of Binary Neural Networks Using Resistive Memories

David Atienza Alonso, Marina Zapater Sancho, Pierre-Emmanuel Julien Marc Gaillardon, Xifan Tang, Yasir Mahmood Qureshi, Edouard Giacomin, João Miguel Morgado Pereira Vieira

The need for running complex Machine Learning (ML) algorithms, such as Convolutional Neural Networks (CNNs), in edge devices, which are highly constrained in terms of computing power and energy, makes it important to execute such applications efficiently. ...

2019

A randomised primal-dual algorithm for distributed radio-interferometric imaging

Yves Wiaux, Rafael Eduardo Carrillo Rangel, Jason Douglas McEwen

Next generation radio telescopes, like the Square Kilometre Array, will acquire an unprecedented amount of data for radio astronomy. The development of fast, parallelisable or distributed algorithms for handling such large-scale data sets is of prime impor ...

Ieee2016

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Multi-access edge computing

M2SKD: Multi-to-Single Knowledge Distillation of Real-Time Epileptic Seizure Detection for Low-Power Wearable Systems

Scalable and Privacy-Preserving Federated Principal Component Analysis

Caching and Neutrality

Real-Time Personalized Atrial Fibrillation Prediction on Multi-Core Wearable Sensors

Mneme: A Mobile Distributed Ledger

Ontology-Based Resource Allocation for Internet of Things

A Product Engine for Energy-Efficient Execution of Binary Neural Networks Using Resistive Memories

Learning-Based Hardware Design for Data Acquisition Systems

A randomised primal-dual algorithm for distributed radio-interferometric imaging

Making Crowdsensing Possible

Graph Chatbot

Chat with Graph Search

Real-Time Personalized Atrial Fibrillation Prediction on Multi-Core Wearable Sensors

Learning-Based Hardware Design for Data Acquisition Systems

Caching and Neutrality

M2SKD: Multi-to-Single Knowledge Distillation of Real-Time Epileptic Seizure Detection for Low-Power Wearable Systems

Scalable and Privacy-Preserving Federated Principal Component Analysis

Ontology-Based Resource Allocation for Internet of Things

Mneme: A Mobile Distributed Ledger

A randomised primal-dual algorithm for distributed radio-interferometric imaging

Making Crowdsensing Possible

A Product Engine for Energy-Efficient Execution of Binary Neural Networks Using Resistive Memories