Publications associées à The Failure Detector Abstraction

Planetary-Scale Byzantine Fault Tolerance

The scale and pervasiveness of the Internet make it a pillar of planetary communication, industry and economy, as well as a fundamental medium for public discourse and democratic engagement. In stark contrast with the Internet's decentralized infrastructur ...

EPFL2024

Scalable Metaprogramming in Scala 3

Nicolas Alexander Stucki

A metaprogrammer should be able to reason about the semantics of the generated code. Multi-stage programming introduced an elegant and powerful solution to this problem. It follows a semantically driven approach to code generation, where semantics are full ...

EPFL2023

Hypergraph-Based Fast Distributed AC Power Flow Optimization

Colin Neil Jones, Yingzhao Lian, Yuning Jiang, Xinliang Dai

This paper presents a novel distributed approach for solving AC power flow (PF) problems. The optimization problem is reformulated into a distributed form using a communication structure corresponding to a hypergraph, by which complex relationships between ...

IEEE2023

Building Strongly-Consistent Systems Resilient to Failures, Partitions, and Slowdowns

Cristina Basescu

Distributed systems designers typically strive to improve performance and preserve availability despite failures or attacks; but, when strong consistency is also needed, they encounter fundamental limitations. The bottleneck is in replica coordination, whi ...

EPFL2023

Reliable Microsecond-Scale Distributed Computing

Athanasios Xygkis

The landscape of computing is changing, thanks to the advent of modern networking equipment that allows machines to exchange information in as little as one microsecond. Such advancement has enabled microsecond-scale distributed computing, where entire dis ...

EPFL2023

Behavioral outcome of very preterm children at 5 years of age: Prognostic utility of brain tissue volumes at term-equivalent-age, perinatal, and environmental factors

Djalel Eddine Meskaldji, Laura Ioana Gui, Serafeim Loukas

ObjectivePrematurity is associated with a high risk of long-term behavioral problems. This study aimed to assess the prognostic utility of volumetric brain data at term-equivalent-age (TEA), clinical perinatal factors, and parental social economic risk in ...

WILEY2023

Hardware-Friendly Random Forest Classification of iEEG Signals for Implantable Seizure Detection

Alexandre Schmid, Keyvan Farhang Razi

Early and accurate detection of epileptic seizures is an extremely important therapeutic goal due to the severity of complications it can prevent. To this end, a low-power machine learning-based seizure detection implemented on an FPGA is proposed in this ...

IEEE2022

On Generalizations of Some Distance Based Classifiers for HDLSS Data

Soham Sarkar

In high dimension, low sample size (HDLSS) settings, classifiers based on Euclidean distances like the nearest neighbor classifier and the average distance classifier perform quite poorly if differences between locations of the underlying populations get m ...

Microtome Publishing2022

Classification of fall directions via wearable motion sensors

Mustafa Sahin Turan

Effective fall-detection and classification systems are vital in mitigating severe medical and economical consequences of falls to people in the fall risk groups. One class of such systems is based on wearable sensors. While there is a vast amount of acade ...

ACADEMIC PRESS INC ELSEVIER SCIENCE2022

Using Machine Learning to Predict Mortality for COVID-19 Patients on Day 0 in the ICU

Sahand Jamal Rahi, Nahal Mansouri

Rationale: Given the expanding number of COVID-19 cases and the potential for new waves of infection, there is an urgent need for early prediction of the severity of the disease in intensive care unit (ICU) patients to optimize treatment strategies.Objecti ...

FRONTIERS MEDIA SA2022

The Universal Gossip Fighter

Rachid Guerraoui, Anne-Marie Kermarrec, Anastasiia Kucherenko, Rafaël Benjamin Pinot

The notion of adversary is a staple of distributed computing. An adversary typically models “hostile” assumptions about the underlying distributed environment, e.g., a network that can drop messages, an operating system that can delay processes or an attac ...

IEEE2022

A framework for occupancy detection and tracking using floor-vibration signals

Ian Smith, Slah Drira

In sensed buildings, information related to occupant movement helps optimize important func-tionalities such as caregiving, energy management, and security enhancement. Typical sensing approaches for occupant tracking rely on mobile devices and cameras. Th ...

2022

Robustness and invariance properties of image classifiers

Apostolos Modas

Deep neural networks have achieved impressive results in many image classification tasks. However, since their performance is usually measured in controlled settings, it is important to ensure that their decisions remain correct when deployed in noisy envi ...

EPFL2022

Data-driven and Safe Networked Control with Applications to Microgrids

Mustafa Sahin Turan

Today, automatic control is integrated into a wide spectrum of real-world systems such as electrical grids and transportation networks. Many of these systems comprise numerous interconnected agents, perform safety-critical operations, or generate large amo ...

EPFL2022

Machine learning-derived gut microbiome signature predicts fatty liver disease in the presence of insulin resistance

Johan Auwerx, Dongryeol Ryu

A simple predictive biomarker for fatty liver disease is required for individuals with insulin resistance. Here, we developed a supervised machine learning-based classifier for fatty liver disease using fecal 16S rDNA sequencing data. Based on the Kangbuk ...

Nature Portfolio2022

Predicting Superagers by Machine Learning Classification Based on the Functional Brain Connectome Using Resting-State Functional Magnetic Resonance Imaging

Chang-Hyun Park

Superagers are defined as older adults who have youthful memory performance comparable to that of middle-aged adults. Classifying superagers based on the brain connectome using machine learning modeling can provide important insights on the physiology unde ...

OXFORD UNIV PRESS INC2021

Dynamic Byzantine Reliable Broadcast

Rachid Guerraoui, Dragos-Adrian Seredinschi, Jovan Komatovic, Andrei Tonkikh

Reliable broadcast is a communication primitive guaranteeing, intuitively, that all processes in a distributed system deliver the same set of messages. The reason why this primitive is appealing is twofold: (i) we can implement it deterministically in a co ...

Schloss Dagstuhl--Leibniz-Zentrum f{\"u}r Informatik2021

Using footstep-induced vibrations for occupant detection and recognition in buildings

Ian Smith, Yves Sylvain Gilles Reuland, Sai Ganesh Sarvotham Pai, Slah Drira

Occupant detection and recognition support functional goals such as security, healthcare, and energy management in buildings. Typical sensing approaches, such as smartphones and cameras, undermine the privacy of building occupants and inherently affect the ...

2021

Asynchronous distributed coordination and consensus with threshold logical clocks

Bryan Alexander Ford

Consensus protocols for asynchronous networks are usually complex and inefficient, leading practical systems to rely on synchronous protocols. The invention proposes an approach to simplify asynchronous consensus by building it atop a novel threshold logic ...

2021

A Low Power Multi-Class Migraine Detection Processor Based on Somatosensory Evoked Potentials

Mahsa Shoaran, Bingzhao Zhu, Zain Taufique

Migraine is a disabling neurological disorder that can be recurrent and persist for long durations. The continuous monitoring of the brain activities can enable the patient to respond on time before the occurrence of the approaching migraine episode to min ...

2021