Publications associées à Cross-chain payment protocols with success guarantees

Publications associées (16)

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

Leaderless consensus

Rachid Guerraoui, Vincent Gramoli, Mihail Igor Zablotchi, Karolos Antoniadis, Gauthier Jérôme Timothée Voron

Classic synchronous consensus algorithms are leaderless in that processes exchange proposals, choose the maximum value and decide when they see the same choice across a couple of rounds. Indulgent consensus algorithms are typically leader-based. Although t ...

ACADEMIC PRESS INC ELSEVIER SCIENCE2023

Leaderless Consensus

Rachid Guerraoui, Vincent Gramoli, Mihail Igor Zablotchi, Karolos Antoniadis

Classical synchronous consensus algorithms are leaderless: processes exchange their proposals, retain the maximum value and decide when they see the same choice across a couple of rounds. Indulgent consensus algorithms are more robust in that they only req ...

IEEE COMPUTER SOC2021

The Performance of Byzantine Fault Tolerant Blockchains

Vincent Gramoli

Blockchains have captured the attention of many, resulting in an abundance of new systems available for use. However, selecting an appropriate blockchain for an application is challenging due to the lack of comparative information discussing core metrics s ...

IEEE2020

Genuinely Distributed Byzantine Machine Learning

Rachid Guerraoui, El Mahdi El Mhamdi, Sébastien Louis Alexandre Rouault, Le Nguyen Hoang, Arsany Hany Abdelmessih Guirguis

Machine Learning (ML) solutions are nowadays distributed, according to the so-called server/worker architecture. One server holds the model parameters while several workers train the model. Clearly, such architecture is prone to various types of component ...

Association for Computing Machinery2020

Private and Secure Distributed Learning

Georgios Damaskinos

The ever-growing number of edge devices (e.g., smartphones) and the exploding volume of sensitive data they produce, call for distributed machine learning techniques that are privacy-preserving. Given the increasing computing capabilities of modern edge de ...

EPFL2020

Scalable Byzantine Reliable Broadcast

Rachid Guerraoui, Matej Pavlovic, Dragos-Adrian Seredinschi, Matteo Monti

Byzantine reliable broadcast is a powerful primitive that allows a set of processes to agree on a message from a designated sender, even if some processes (including the sender) are Byzantine. Existing broadcast protocols for this setting scale poorly, as ...

Schloss Dagstuhl--Leibniz-Zentrum fer Informatik2019

Scaling Byzantine Fault Tolerance

Matej Pavlovic

Online services are becoming more and more ubiquitous and keep growing in scale. At the same time, they are required to be highly available, secure, energy-efficient, and to achieve high performance. To ensure these (and many other) properties, replication ...

EPFL2019

AGGREGATHOR: Byzantine Machine Learning via Robust Gradient Aggregation

Rachid Guerraoui, El Mahdi El Mhamdi, Sébastien Louis Alexandre Rouault, Arsany Hany Abdelmessih Guirguis, Georgios Damaskinos

We present AGGREGATHOR, a framework that implements state-of-the-art robust (Byzantine-resilient) distributed stochastic gradient descent. Following the standard parameter server model, we assume that a minority of worker machines can be controlled by an a ...

2019

The Impact of RDMA on Agreement

Rachid Guerraoui, Mihail Igor Zablotchi

Remote Direct Memory Access (RDMA) is becoming widely available in data centers. This technology allows a process to directly read and write the memory of a remote host, with a mechanism to control access permissions. In this paper, we study the fundamenta ...

2019

Asynchronous Byzantine Machine Learning (the case of SGD)

Rachid Guerraoui, El Mahdi El Mhamdi, Mahsa Taziki, Rhicheek Patra, Georgios Damaskinos

Asynchronous distributed machine learning solutions have proven very effective so far, but always assuming perfectly functioning workers. In practice, some of the workers can however exhibit Byzantine behavior, caused by hardware failures, software bugs, c ...

2018

Timing Analysis of Leader-Based and Decentralized Byzantine Consensus Algorithms

André Schiper, Martin Hutle, Fatemeh Borran

We compare in an analytical way two leader-based and decentralized algorithms (that is, algorithms that do not use a leader) for Byzantine consensus with strong validity. We show that for \emph{the algorithms we analyzed}, in most cases, the decentralized ...

IEEE2011

Names Trump Malice: Tiny Mobile Agents Can Tolerate Byzantine Failures

Rachid Guerraoui

We introduce a new theoretical model of ad hoc mobile computing in which agents have severely restricted memory, highly unpredictable movement and no initial knowledge of the system. Each agent’s memory can store O(1) bits, plus a unique identiﬁer, and O(1 ...

2009

Abstractions for asynchronous distributed computing with malicious players

In modern distributed systems, failures are the norm rather than the exception. In many cases, these failures are not benign. Settings such as the Internet might incur malicious (also called Byzantine or arbitrary) behavior and asynchrony. As a result, and ...

EPFL2008

The Perfectly-Synchronized Round-based Model of Distributed Computing

Rachid Guerraoui, Bastian Pochon

The perfectly-synchronized round-based model provides the powerful abstraction of crash-stop failures with atomic and synchronous message delivery. This abstraction makes distributed programming very easy.We describe a technique to automatically transform ...

2007

Soft real-time analysis of asynchronous agreement algorithms using Petri nets

A distributed algorithm comprises a collection of sequential-code entities, which are spread over different computers connected to a network. The process of designing a distributed algorithm is influenced by the assumptions we make on the computational env ...

EPFL1998