Publications associées à Réseau métropolitain

Leaderless consensus

Rachid Guerraoui, Gauthier Jérôme Timothée Voron, Vincent Gramoli, Mihail Igor Zablotchi, Karolos Antoniadis, Antoine Philippe Matthieu Desjardins

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

Critical node selection method for efficient Max-Pressure traffic signal control in large-scale congested networks

Nikolaos Geroliminis, Dimitrios Tsitsokas, Anastasios Kouvelas

Decentralized signal control of congested traffic networks based on the Max-Pressure (MP) controller is theoretically proven to maximize throughput, stabilize the system and balance queues for single intersections under specific conditions. However, its pe ...

2022

LENA: Communication-Efficient Distributed Learning with Self-Triggered Gradient Uploads

Martin Jaggi, Sebastian Urban Stich, Hossein Shokri Ghadikolaei

In distributed optimization, parameter updates from the gradient computing node devices have to be aggregated in every iteration on the orchestrating server. When these updates are sent over an arbitrary commodity network, bandwidth and latency can be limi ...

MICROTOME PUBLISHING2021

Analyzing and Protecting Communication Metadata

Ludovic Barman

Most communication systems (e.g., e-mails, instant messengers, VPNs) use encryption to prevent third parties from learning sensitive information. However, encrypted communications protect the contents but often leak metadata: the amount of data sent and th ...

EPFL2021

Consensus Control for Decentralized Deep Learning

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

Decentralized training of deep learning models enables on-device learning over networks, as well as efficient scaling to large compute clusters. Experiments in earlier works reveal that, even in a data-center setup, decentralized training often suffers fro ...

JMLR-JOURNAL MACHINE LEARNING RESEARCH2021

Empirical observations of multi-modal network-level models: Insights from the pNEUMA experiment

Nikolaos Geroliminis, Emmanouil Barmpounakis

Multi-modal interactions at the network-level remain unexplored due to the lack of highresolution data for all transportation modes involved. The current work investigates the effect of multi-modal interactions at space-mean network speed for each mode usi ...

2021

Drone-aided Localization in LoRa IoT Networks

Dario Floreano, Alexandru Rusu, Fabrizio Schiano, Giuseppe Cocco

Besides being part of the Internet of Things (IoT), drones can play a relevant role in it as enablers. The 3D mobility of UAVs can be exploited to improve node localization in IoT networks for, e.g., search and rescue or goods localization and tracking. On ...

IEEE2020

Annealing and Replica-Symmetry in Deep Boltzmann Machines

Emanuele Mingione, Diego Alberici

In this paper we study the properties of the quenched pressure of a multi-layer spin-glass model (a deep Boltzmann Machine in artificial intelligence jargon) whose pairwise interactions are allowed between spins lying in adjacent layers and not inside the ...

SPRINGER2020

Online Resource Inference in Network Utility Maximization Problems

Pascal Frossard, Stefano D'Aronco

The amount of transmitted data in computer networks is expected to grow considerably in the future, putting more and more pressure on the network infrastructures. In order to guarantee a good service, it then becomes fundamental to use the network resource ...

2019

Reliability Mechanisms for Controllers in Real-Time Cyber-Physical Systems

Maaz Mashood Mohiuddin

Cyber-physical systems (CPSs) are real-world processes that are controlled by computer algorithms. We consider CPSs where a centralized, software-based controller maintains the process in a desired state by exchanging measurements and setpoints with proces ...

EPFL2018