Publications associées à When to Hedge in Interactive Services

PRO-Face C: Privacy-Preserving Recognition of Obfuscated Face via Feature Compensation

Touradj Ebrahimi, Lin Yuan, Xiao Pu, Hongbo Li, Yao Zhang

The advancement of face recognition technology has delivered substantial societal advantages. However, it has also raised global privacy concerns due to the ubiquitous collection and potential misuse of individuals' facial data. This presents a notable par ...

Ieee-Inst Electrical Electronics Engineers Inc2024

Planetary-Scale Byzantine Fault Tolerance

Matteo Monti

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

uKharon: A Membership Service for Microsecond Applications

Rachid Guerraoui, Javier Picorel Obando, Athanasios Xygkis, Antoine Murat

Modern data center fabrics open the possibility of microsecond distributed applications, such as data stores and message queues. A challenging aspect of their development is to ensure that, besides being fast in the common case, these applications react fa ...

USENIX Association2023

uBFT: Microsecond-Scale BFT using Disaggregated Memory

Rachid Guerraoui, Mihail Igor Zablotchi, Athanasios Xygkis, Naama Ben David, Antoine Murat

We propose uBFT, the first State Machine Replication (SMR) system to achieve microsecond-scale latency in data centers, while using only 2f+1 replicas to tolerate f Byzantine failures. The Byzantine Fault Tolerance (BFT) provided by uBFT is essential as pu ...

2023

Privatized graph federated learning

Ali H. Sayed, Stefan Vlaski, Elsa Rizk

Federated learning is a semi-distributed algorithm, where a server communicates with multiple dispersed clients to learn a global model. The federated architecture is not robust and is sensitive to communication and computational overloads due to its one-m ...

SPRINGER2023

Authenticated private information retrieval

Simone Maria Stefano Colombo, Kirill Nikitin, Bryan Alexander Ford, Henry Nathaniel Corrigan-Gibbs

This paper introduces protocols for authenticated private information retrieval. These schemes enable a client to fetch a record from a remote database server such that (a) the server does not learn which record the client reads, and (b) the client either ...

Usenix Assoc2023

Hardware and Software Support for RPC-Centric Server Architecture

Mark Johnathon Sutherland

Online services have become ubiquitous in technological society, the global demand for which has driven enterprises to construct gigantic datacenters that run their software. Such facilities have also recently become a substrate for third-party organizatio ...

EPFL2022

Oracular Byzantine Reliable Broadcast

Rachid Guerraoui, Matteo Monti, Manuel José Ribeiro Vidigueira, Martina Camaioni

Byzantine Reliable Broadcast (BRB) is a fundamental distributed computing primitive, with applications ranging from notifications to asynchronous payment systems. Motivated by practical consideration, we study Client-Server Byzantine Reliable Broadcast (CS ...

Schloss Dagstuhl - Leibniz-Zentrum für Informatik2022

Reinforcement Learning-Based Joint Reliability and Performance Optimization for Hybrid-Cache Computing Servers

David Atienza Alonso, Ali Pahlevan, Marina Zapater Sancho, Luis Maria Costero Valero, Darong Huang

Computing servers play a key role in the development and process of emerging compute-intensive applications in recent years. However, they need to operate efficiently from an energy perspective viewpoint, while maximizing the performance and lifetime of th ...

2022

GARFIELD: System Support for Byzantine Machine Learning (Regular Paper)

Rachid Guerraoui, Sébastien Louis Alexandre Rouault, Arsany Hany Abdelmessih Guirguis

We present GARFIELD, a library to transparently make machine learning (ML) applications, initially built with popular (but fragile) frameworks, e.g., TensorFlow and PyTorch, Byzantine–resilient. GARFIELD relies on a novel object–oriented design, reducing t ...

IEEE2021

Personalized Real-Time Federated Learning for Epileptic Seizure Detection

David Atienza Alonso, Amir Aminifar, Saleh Baghersalimi, Tomas Teijeiro Campo

Epilepsy is one of the most prevalent paroxystic neurological disorders. It is characterized by the occurrence of spontaneous seizures. About 1 out of 3 patients have drug-resistant epilepsy, thus their seizures cannot be controlled by medication. Automati ...

2021

Understanding and Mitigating Latency Variability of Latency-Critical Applications

Mia Primorac

A major theme of IT in the past decade has been the shift from on-premise hardware to cloud computing. Running a service in the public cloud is practical, because a large number of resources can be bought on-demand, but this shift comes with its own set of ...

EPFL2020

Single-server Multi-message Private Information Retrieval with Side Information: the General Cases

Michael Christoph Gastpar, Su Li

The single-server multi-message private information retrieval with side information problem is studied for general cases. In this problem, K independent messages are stored at a single server. One user initially has M messages as side information and wants ...

IEEE2020

Ensemble Distillation for Robust Model Fusion in Federated Learning

Tao Lin, Martin Jaggi, Sebastian Urban Stich, Lingjing Kong

Federated Learning (FL) is a machine learning setting where many devices collaboratively train a machine learning model while keeping the training data decentralized. In most of the current training schemes the central model is refined by averaging the par ...

2020

Efficient Protocols for Enforcing Causal Consistency in Geo-Replicated Key-Value Data Stores

Kristina Spirovska

Modern large-scale data platforms manage colossal amount of data, generated by the ever-increasing number of concurrent users. Geo-replicated and sharded key-value data stores play a central role when building such platforms. As the strongest consistency m ...

EPFL2020

Drowsy-DC: Data center power management system

Willy Zwaenepoel, Baptiste Joseph Eustache Lepers, Mathieu Paul Fernand Bacou

In a modern data center (DC), a large majority of costs arise from energy consumption. The most popular technique used to mitigate this issue is virtualization and more precisely virtual machine (VM) consolidation. Although consolidation may increase serve ...

IEEE2019

MAGNETIC: Multi-Agent Machine Learning-Based Approach for Energy Efficient Dynamic Consolidation in Data Centers

David Atienza Alonso, Ali Pahlevan, Marina Zapater Sancho, Kosar Haghshenas

Improving the energy efficiency of data centers while guaranteeing Quality of Service (QoS), together with detecting performance variability of servers caused by either hardware or software failures, are two of the major challenges for efficient resource m ...

2022

Formal Approaches to Querying Big Data in Shared-Nothing Systems

Bas Ketsman

To meet today's data management needs, it is a widespread practice to use distributed data storage and processing systems. Since the publication of the MapReduce paradigm, a plethora of such systems arose, but although widespread, the capabilities of these ...

ASSOC COMPUTING MACHINERY2019

Caching and Distributed Storage : Models, Limits and Designs

Saeid Sahraei

A simple task of storing a database or transferring it to a different point via a communication channel turns far more complex as the size of the database grows large. Limited bandwidth available for transmission plays a central role in this predicament. I ...

EPFL2018

Single-server Multi-message Private Information Retrieval with Side Information

Michael Christoph Gastpar, Su Li

We study the problem of single-server multi-message private information retrieval with side information. One user wants to recover N out of K independent messages which are stored at a single server. The user initially possesses a subset of M messages as s ...

IEEE2018