Mediaspace scheduled maintenance: Aug 25, 2026 07:00 - 12:00 AM. During this time, videos will be temporarily unavailable. Check status updates.

Concept

Distributed algorithm

Related publications (28)

Hypergraph-Based Fast Distributed AC Power Flow Optimization

Colin Neil Jones, Yuning Jiang, Yingzhao Lian

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

Hybrid Flock - Formation Control Algorithms

Alcherio Martinoli, Cyrill Silvan Baumann

Two prominent categories for achieving coordinated multirobot displacement are flocking and navigation in formation. Both categories have their own body of literature and characteristics, including their respective advantages and disadvantages. While typic ...

Springer Nature Switzerland2022

The Price of Distributed: Rate Loss in the CEO Problem

Michael Christoph Gastpar, Alper Köse, Ahmet Arda Atalik

In the distributed remote (CEO) source coding problem, many separate encoders observe independently noisy copies of an underlying source. The rate loss is the difference between the rate required in this distributed setting and the rate that would be requi ...

2022

The Universal Gossip Fighter

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

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

Quantization for Distributed Processing and Learning of Structured Data

Isabela Cunha Maia Nobre

In the domains of machine learning, data science and signal processing, graph or network data, is becoming increasingly popular. It represents a large portion of the data in computer, transportation systems, energy networks, social, biological, and other s ...

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

Revisiting Tendermint: Design Tradeoffs, Accountability, and Practical Use

Rachid Guerraoui, Jovan Komatovic, Zarko Milosevic, Dragos-Adrian Seredinschi

Tendermint is a deterministic consensus protocol and is one of the most mature implementations of its kind. This implementation is used as the core for building State Machine Replication (SMR) platforms with Byzantine fault-tolerant (BFT) guarantees. A not ...

IEEE2022

Dynamic Byzantine Reliable Broadcast

Rachid Guerraoui, Jovan Komatovic, Dragos-Adrian Seredinschi

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

Microsecond Consensus for Microsecond Applications

Rachid Guerraoui, Mihail Igor Zablotchi, Athanasios Xygkis

We consider the problem of making apps fault-tolerant through replication, when apps operate at the microsecond scale, as in finance, embedded computing, and microservices apps. These apps need a replication scheme that also operates at the microsecond sca ...

USENIX ASSOC2020

The Hidden Complexity of Distributed Systems

Karolos Antoniadis

The field of distributed computing has a long history, of more than fifty years. During that time, our understanding of the field has improved immensely and a certain body of folklore beliefs has formed. However, such folklore beliefs are not necessarily a ...

EPFL2020

Online Distributed Learning Over Graphs With Multitask Graph-Filter Models

Ali H. Sayed, Roula Nassif

In this article, we are interested in adaptive and distributed estimation of graph filters from streaming data. We formulate this problem as a consensus estimation problem over graphs, which can be addressed with diffusion LMS strategies. Most popular grap ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

Distributed Coloring of Graphs with an Optimal Number of Colors

Etienne Michel François Bamas

This paper studies sufficient conditions to obtain efficient distributed algorithms coloring graphs optimally (i.e. with the minimum number of colors) in the LOCAL model of computation. Most of the work on distributed vertex coloring so far has focused on ...

SCHLOSS DAGSTUHL, LEIBNIZ CENTER INFORMATICS2019

Optimized Quantization in Distributed Graph Signal Filtering

Pascal Frossard, Isabela Cunha Maia Nobre

Distributed graph signal processing algorithms require the network nodes to communicate by exchanging messages in order to achieve a common objective. These messages have a finite precision in realistic networks, which may necessitate to implement message ...

2019

Rethinking General-Purpose Decentralized Computing

Bryan Alexander Ford, Eleftherios Kokoris Kogias, Georgia Fragkouli, Enis Ceyhun Alp

While showing great promise, smart contracts are difficult to program correctly, as they need a deep understanding of cryptography and distributed algorithms, and offer limited functionality, as they have to be deterministic and cannot operate on secret da ...

Association for Computing Machinery2019

Distributed Learning over Networks under Subspace Constraints

Ali H. Sayed, Stefan Vlaski, Roula Nassif

This work presents and studies a distributed algorithm for solving optimization problems over networks where agents have individual costs to minimize subject to subspace constraints that require the minimizers across the network to lie in a low-dimensional ...

IEEE2019

Optimized Quantization in Distributed Graph Signal Processing

Pascal Frossard, Isabela Cunha Maia Nobre

Distributed graph signal processing methods require that the graph nodes communicate by exchanging messages. These messages have a finite precision in a realistic network, which may necessitate to implement quantization. Quantization, in turn, generates er ...

IEEE2019

Monitoring distributed fragmented skylines

Odysseas Papapetrou

Distributed skyline computation is important for a wide range of domains, from distributed and web-based systems to ISP-network monitoring and distributed databases. The problem is particularly challenging in dynamic distributed settings, where the goal is ...

2018

The Complexity of Reliable and Secure Distributed Transactions

Jingjing Wang

The use of transactions in distributed systems dates back to the 70's. The last decade has also seen the proliferation of transactional systems. In the existing transactional systems, many protocols employ a centralized approach in executing a distributed ...

EPFL2018

Learning of robust spectral graph dictionaries for distributed processing

Pascal Frossard, Ntorina Thanou

We consider the problem of distributed representation of signals in sensor networks, where sensors exchange quantized information with their neighbors. The signals of interest are assumed to have a sparse representation with spectral graph dictionaries. We ...

SPRINGEROPEN2018

Distributed Signal Processing via Chebyshev Polynomial Approximation

Pascal Frossard, Pierre Vandergheynst, Daniel Kressner, David Shuman

Unions of graph multiplier operators are an important class of linear operators for processing signals defined on graphs. We present a novel method to efficiently distribute the application of these operators. The proposed method features approximations of ...

2018