Publications related to Metropolitan area network

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

Efficient Variance-Reduced Learning Over Multi-Agent Networks

Ali H. Sayed, Bicheng Ying, Kun Yuan

This work develops a fully decentralized variance-reduced learning algorithm for multi-agent networks where nodes store and process the data locally and are only allowed to communicate with their immediate neighbors. In the proposed algorithm, there is no ...

IEEE COMPUTER SOC2018

Adding flexibility to multi-tenant networks

Georgios Ioannidis

Cloud computing has been experiencing sharp development over the last years, leading to an increased demand for application migration to the cloud. Cloud providers, in an effort to attract more customers and earn their confidence, offer to tenants the illu ...

EPFL2018

Network utility maximization for delay-sensitive applications in unknown communication settings

Stefano D'Aronco

In the last decades the Internet traffic has greatly evolved. The advent of new Internet services and applications has, in fact, led to a significant growth of the amount of data transmitted, as well as to a transformation of the data type. As a matter of ...

EPFL2018

A Bayesian Bandit Approach to Adaptive Delay-based Congestion Control

Pascal Frossard, Stefano D'Aronco

Adapting the transmission rate of video telephony Internet applications in order to guarantee the maximal communication quality is still an open and extremely challenging problem. The congestion control algorithm, which is the algorithm responsible for adj ...

ASSOC COMPUTING MACHINERY2018

Irreducible network backbones: unbiased graph filtering via maximum entropy

Alessio Vincenzo Cardillo

Networks provide an informative, yet non-redundant description of complex systems only if links represent truly dyadic relationships that cannot be directly traced back to node-specific properties such as size, importance, or coordinates in some embedding ...

2017

Determinants of PhD holders' use of social networking sites: An analysis based on LinkedIn

Stefano Horst Baruffaldi

Social networking sites are an increasingly important tool for career development, especially for highly skilled individuals. Moreover, they may constitute valuable sources of data for scholars and policy makers. However, little research has been conducted ...

Elsevier2017

Analysing the Role of Social Visits on Migrants’ Social Capital: A Personal Network Approach

Gil Viry, Emmanuel Pierre Jean Ravalet

There are concerns that migrants may be embedded in far-flung networks with support being less collective. The spatial dispersion of their relatives and friends would result in fragmented networks with lower solidarity and lower mutual trust than densely c ...

2017

EMPoWER Hybrid Networks: Exploiting Multiple Paths over Wireless and ElectRical Mediums

Patrick Thiran, Julien Pierre Sacha Herzen, Christina Vlachou, Sébastien Christophe Henri

Several technologies, such as WiFi, Ethernet and power-line communications (PLC), can be used to build residential and enterprise networks. These technologies often co-exist; most networks use WiFi, and buildings are readily equipped with electrical wires ...

2016

Redundancy in Communication Networks for Smart Grids

Miroslav Popovic

Traditional electric power grids are currently undergoing fundamental changes: Representative examples are the increase in the penetration of volatile and decentralized renewable-energy sources and the emerging distributed energy-storage systems. These cha ...

EPFL2016

iPRP - the Parallel Redundancy Protocol for IP Networks: Protocol Design and Operation

Jean-Yves Le Boudec, Dan-Cristian Tomozei, Miroslav Popovic, Maaz Mashood Mohiuddin

Reliable packet delivery within stringent delay-constraints is of paramount importance to mission-critical computer applications with hard real-time constraints. Because retransmission and coding techniques counteract the delay requirements, reliability ma ...

Institute of Electrical and Electronics Engineers2016