PhD position in autonomous radio receivers at CITI Lab

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University

INSA de Lyon, Lyon, France

Doctoral School

ED 160 EEA de Lyon

Laboratory

CITI

Title

Study and development of architectures of radio receivers autonomous in energy and their mechanisms of wake-up and energy harvesting

Abstract

The main scientific challenge of the thesis is to propose an autonomous wake-up radio architecture, i.e. an ultra-low power receiver supplied by the RF harvested or transferred energy and independent from the connected object’s main power supply. More thoroughly, the aim of this subject is to explore new solutions based on autonomous wake-up radio receivers taking into account limitations as size, technologies, operating conditions, etc., in order to provide one (or several) operational prototype(s). The proposed solutions will not exclusively be evaluated and optimized in terms of energy consumption, but also will take into account the communication performance such as the sensitivity and the robustness in terms of false wake-ups.

Supervisors

Guillaume Villemaud (HDR, 50%), Florin Hutu (50%)

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CITI Talk: “Heavy tailed distributions characterisations and examples of applications in channel modeling”, Prof Nourddine Azzaoui (Université Blaise Pascal), 14h00 in TD-C

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Title

Heavy tailed distributions characterisations and examples of applications in channel modeling

Speaker

Associate Professor Nourddine Azzaoui

Date

16th March 2018

Time/Place

14h00 in TD-C.

Abstract

Currently, we are witnessing the proliferation of wireless sensor networks and the superposition of several communicating objects which have an heterogeneous nature. The advent of Internet of Things networks as well as the increasing demand for improved quality and services will increase the complexity of communications and puts a strain on current techniques and models. Indeed, they must firstly adapt to the temporal and spatial evolution and secondly, they must take into account the rare and unpredictable events that can have disastrous consequences for decision-making. This talk provides an overview of the various spectral techniques used in litterature describe a communication channel having an impulsive behavior. This is mainly motivated by the historical success of interactions between probabilities, statistics and the world of communications, information theory and signal processing. The presentation will be divided into two parts: the first is devoted to the synthesis of various developments on alpha-stable variables and processes in a purely mathematical mind. The second part will be devoted to applications in the context of communications. The two sides will combine two fundamentally linked aspects: first, a theoretical approach, necessary for a good formalization of problems and identifying the best solutions. Secondly, the use of these models in real work of channel modelling.


PhD Defence: “Middleware and programming models for multi-robot systems”, Stefan-Gabriel Chitic, Vitrine/RobIot room, Chappe Building, 15th of March 2018, at 10h:30

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Title

Middleware and programming models for multi-robot systems

Abstract

Despite many years of work in robotics, there is still a lack of established software architecture and middleware for multi-robot systems. A robotic middleware should be designed to abstract the low-level hardware architecture, facilitate communication and integration of new software. This PhD thesis is focusing on middleware for multi-robot system and how we can improve existing frameworks for fleet purposes by adding multi-robot coordination services, development and massive deployment tools. We expect robots to be increasingly useful as they can take advantage of data pushed from other external devices in their decision making instead of just reacting to their local environment (sensors, cooperating robots in a fleet, etc).

This thesis first evaluates one of the most recent middleware for mobile robot(s), Robot operating system (ROS) and continues with a state of the art about the commonly used middlewares in robotics. Based on the conclusions, we propose an original contribution in the multi-robot context, called SDfR (Service discovery for Robots), a service discovery mechanism for Robots. The main goal is to propose a mechanism that allows highly mobile robots to keep track of the reachable peers inside a fleet while using an ad-hoc infrastructure. Another objective is to propose a network configuration negotiation protocol. Due to the mobility of robots, classical peer to peer network configuration techniques are not suitable. SDfR is a highly dynamic, adaptive and scalable protocol adapted from Simple Service Discovery Protocol (SSDP). We conduced a set of experiments, using a fleet of Turtlebot robots, to measure and show that the overhead of SDfR is limited.

The last part of the thesis focuses on programming model based on timed automata. This type of programming has the benefits of having a model that can be verified and simulated before deploying the application on real robots. In order to enrich and facilitate the development of robotic applications, a new programming model based on timed automata state machines is proposed, called ROSMDB (Robot Operating system Model Driven Behaviour). It provides model checking at development phase and at runtime. This contribution is composed of several components: a graphical interface to create models based on timed automata, an integrated model checker based on UPPAAL and a code skeleton generator. Moreover, a ROS specific framework is proposed to verify the correctness of the execution of the models and to trigger alerts. Finally, we conduct two experiments: one with a fleet of Parrot drones and second with Turtlebots in order to illustrates the proposed model and its ability to check properties.

Jury

  •  Prof. Abderrafiaa KOUKAM, Université de Technologie de Belfort-Montbéliard (Reviewer)
  • Prof. Philippe LALANDA, Université́ Joseph Fourier, Saint-Martin-d’Hères (Reviewer)
  • Prof. Noury BOURAQADI, Institut Mines-Telecom, IMT Lille Douai (Member)
  • Dr. Stéphanie CHOLLET, ESISAR, Valence (Member)
  • Prof. Olivier SIMONIN, INSA Lyon (Supervisor)
  • Dr. Julien PONGE, INSA Lyon (Co-Supervisor)

Atelier Francophone sur la transparence et l’opacité des systèmes d’information

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Atelier Francophone sur la transparence et l’opacité des systèmes d’information
Le 23 Avril 2018 à Lyon
http://transparence.conf.citi-lab.fr/
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Aujourd’hui beaucoup de décisions prises dans la vie quotidienne sont
influencées par des informations provenant d’Internet; la gigantesque
masse de données associée ne sont cependant perçus qu’à travers le
prisme des algorithmes. En effet, qu’il s’agisse de résultats de
recherche sur le web ou d’itinéraires, nous avons tendance à ne pas
remettre en cause le résultat de ces algorithmes, malgré l’absence
d’information sur leur fonctionnement.

Ces algorithmes sont alimentés par une grande quantité d’information
incluant bien souvent des données à caractère personnel collectées avec
ou sans le consentement de l’Internaute. Le manque de transparence de
ces algorithmes et des informations qu’ils manipulent associés à leur
usage toujours plus innovant suscitent de nombreuses préoccupations de
la part du public. Leur introspection et la question de la conformité de
leur exécution face à l’éthique sont devenues des enjeux de société
majeurs. Plus généralement, cet atelier explorera les outils permettant
aux individus de questionner et comprendre les services qu’ils utilisent.

Cet atelier a pour vocation de constituer une communauté hautement
pluridisciplinaire et transversale autour de la transparence et de
l’opacité des systèmes d’information. Cette manifestation inclura des
présentations de conférenciers invités ainsi que l’animation d’une table
ronde sur le domaine.

Intervenants (confirmés):
* Nataliia Bielova (Chargée de Recherche, INDES research team, Inria, Sophia Antipolis)
* Nozha Boujemaa (Directrice de Recherche, Inria, Saclay)
* Aurélien Francillon (Enseignant-Chercheur, EURECOM, Sophia Antipolis)
* Sébastien Gambs (Enseignant-Chercheur, Université du Québec à Montréal, Canada)
* Oana Goga (Chargée de Recherche, CNRS, LIG, SLIDE research group, Grenoble)
* Erwan Le Merrer (Chercheur, Technicolor R&I, Rennes)
* Daniel Le Métayer (Directeur de Recherche, Inria, CITI, Privatics research group, Lyon)

Le programme courant est disponible ici :
http://transparence.conf.citi-lab.fr/

Localisation : INSA-Lyon, La Doua, Lyon

Inscription (gratuite) : http://transparence.conf.citi-lab.fr/faqs.html


CITI Talk: “Deep Learning: history, models & challenges, with an application in signal processing and mobile authentification”, Ass. Prof. Christian Wolf (INSA Lyon, CITI-LIRIS), 22/02/2018, TD C

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Title

Deep Learning: history, models & challenges, with an application in signal processing and mobile authentification

Abstract

Representation Learning (also known with its more popular title « Deep Learning ») consists in automatically learning layered and hierarchical representation with various layers abstraction from large amounts of data. This presentation will review the history of the field, the main actors and the major scientific challenges. We will first present a brief introduction into common deep models like convolutional neural networks and recurrent networks, before going more into detail of some selected applications in signal processing.

In particular, we present a large-scale study, exploring the capability of temporal deep neural networks in interpreting natural human kinematics and introduce the first method for active biometric authentication with mobile inertial sensors. This work has been done in collaboration with Google, where the first-of-its-kind dataset of human movements has been passively collected by 1500 volunteers using their smartphones daily over several months. We propose an optimized shift-invariant dense convolutional mechanism (DCWRNN) and incorporate the discriminatively-trained dynamic features in a probabilistic generative framework taking into account temporal characteristics. Our results demonstrate, that human kinematics convey important information about user identity and can serve as a valuable component of multi-modal authentication systems.

Biography

Christian WOLF is associate professor (Maitre de Conférences, HDR) at INSA de Lyon and LIRIS UMR 5205, a CNRS laboratory, since 2005. He is interested in computer vision and machine learning, deep learning, especially in the visual analysis of complex scenes in motion: gesture and activity recognition and pose estimation. In his work he puts an emphasis on models of complex interactions, on structured models, graphical models and on deep learning. He received his MSc in computer science from Vienna University of Technology (TU Wien) in 2000, and a PhD in computer science from INSA de Lyon, France, in 2003. In 2012 he obtained the habilitation diploma, also from INSA de Lyon. Since September 2017 Christian is on leave at INRIA, at the chroma work group at the CITI laboratory (“délégation INRIA”).


CITI Talk: “Hybrid High Performance Systems for Ultrascale Architectures”, Professor Carlos J. Barrios H. (UIS), 20/02/2018, 11h, TD C

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Abstract
Ultrascale architectures involve large-scale complex systems joining parallel and distributed computing infrastructures joining technology trends (i.e. RISC/ CISIC/ASICS systems) ultrascale software and hybrid models (i.e. cloud/Edge and Fog)  that will be extended in different escenarios. Precisely, this complexity propose special challenges from different points of view: sustainability, scalability, dynamicity, energy-aware, usability, data management, dependability  and more, in a software and hardware relationship. This presentation shows some towards about this ultrscale architectures, observing the different challenges and how it is possible to threat some of them, depending the context a point of view software/hardware and application context.

Bio
Professor Carlos J. Barrios H. is Doctor in Computer Science of the Nice–Côte d’Azur University in France. Researcher in High Performance Computing and Large Scale Architectures, he works in projects associated with hybrid/high performance architectures for science and ultrascale systems involving design, performance evaluation and implementation mechanisms. From 2012, Professor Barrios is the director of the High Performance and Scientific Computing Center of the Universidad Industrial de Santander in Colombia and assistant professor of the same university. At same time, he is the general chair of the Advanced Computing Services for Latin America and Caribbean and he’s involved in different HPC collaboration networks between Europe and Latin America. Contact: cbarrios@uis.edu.co


CITI Talk: “Clustering and Data Anonymization by Mutual Information”, Pablo Piantanida, Associate Professor at CentraleSupélec, TD D

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Title
Clustering and Data Anonymization by Mutual Information

Abstract
In this talk, we first introduce  the Shannon theoretic
multi-clustering problem and investigate its properties, uncovering
connections with many other coding problems in the literature. The figure
of merit for this information-theoretic problem is mutual information, the
mathematical properties of which make the multi-clustering problem amenable
to techniques that could not be used in a general rate-distortion setting.
We start by considering the case of two sources, where we derive
singleletter bounds for the achievable region by connecting our setting to
hypothesis testing and pattern recognition recognition problems in the
information theory literature. We then generalize the problem setup to an
arbitrary number of sources and study a CEO problem with logarithmic loss
distortion and multiple description coding. Drawing from the theory of
submodular functions, we prove a tight inner and outer bound for the
resulting achievable region under a suitable conditional independence
assumption. Furthermore, we present a proof of the well-known two-function
case of a conjecture by Kumar and Courtade (2013), showing that the
dictator functions are essentially the only Boolean  functions maximizing
mutual information.  The key step in our proof is a careful analysis of the
Fourier spectrum of the two Boolean functions. Finally, we study
information-theoretic applications to the problem of statistical  data
anonymization via mutual information and deep learning methods in which the
identity of the data writer must remain private even from the learner.

Joint works with Dr. Georg Pichler (TU Wien, Austria), Prof. Gerald Matz
(TU Wien, Austria),  Clément Feutry (CentraleSupélec, France) and Yoshua
Bengio (Montréal, Canada)

Short biography
Pablo Piantanida received both B.Sc. in Electrical
Engineering and B.Sc. in Mathematics degrees from the University of Buenos
Aires (Argentina) in 2003, and the Ph.D. from Université Paris-Sud (Orsay,
France) in 2007. Since October 2007 he has joined the Laboratoire des
Signaux et Systèmes (L2S), at CentraleSupélec together with CNRS (UMR 8506)
and Université Paris-Sud, as an Associate Professor of Network Information
Theory. He is an IEEE Senior Member, coordinator of the Information Theory
and its Applications group (ITA) at L2S, and  coordinator of the
International Associate Laboratory (LIA) of the CNRS “Information, Learning
and Control” with several institutions in Montréal and General Co-Chair of
the 2019 IEEE International Symposium on Information Theory (ISIT). His
research interests lie broadly in information theory and its interactions
with other fields, including multi-terminal information and Shannon theory,
machine learning, statistical inference, communication mechanisms for
security and privacy, and representation learning.

CITI Talk: “Distributed Hypothesis Testing over Multi-User Channels”, Prof. Michele Wigger (Telecom ParisTech), 10am, amphitheater Émilie du Châtelet (Marie Curie Library-INSA de Lyon)

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Abstract

As part of the internet of things (IoT), the number of sensor nodes that wish to communicate with each other has exploded and is expected to further increase dramatically. Such an increase of communication devices inherently leads to involved communication and hypothesis testing scenarios, and thus calls for new coding and testing strategies. The talk presents new strategies and corresponding error exponents for different network scenarios, and it proves information-theoretic optimality of the proposed strategies in some cases. Special attention is given to scenarios where information collected at a sensor is desired at multiple decision centres and where communication is multi-hop involving sensor nodes as relays. In these networks, sensors generally compete for network resources, and relay sensors can process received information with sensed information or forward intermediate decisions to other nodes. Depending on the studied error exponents, some of these intermediate decisions require special protection mechanisms when sent over the network. The talk is based on joint work with Sadaf Salehkalaibar, Roy Timo, and Ligong Wang.


CITI Talk: “Coding for Cloud-RAN Downlink Channels”, Prof. Gerhard Kramer (TU Munchen), 9am, amphitheater Émilie du Châtelet (Marie Curie Library-INSA de Lyon)

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Abstract

The downlink of a cloud radio accessnetwork (C-RAN) architecture can be modeled as a diamond network. The baseband unit (BBU) is connected to remote radio heads (RRHs) via fiber links that are modeled as rate-limited bit pipes. Bounds on the rates for reliable communication are evaluated for single-antenna RRHs. A lower bound is based on Marton’s coding, which facilitates dependence across the RRH signals. An upper bound uses Ozarow’s technique to augment the system with an auxiliary random variable. The bounds are studied over scalar Gaussian C-RANs and are shown to meet and characterize the capacity for interesting regimes of operation. The bounds are also evaluated for an abstract model: a noise-free binary adder channel (BAC). The capacity of the BAC is established for all ranges of bit-pipe capacities, which seems to yield a new combinatorial result on sum sets. This work is based on joint work with Shirin Saeedi Bidokhti and Shlomo Shamai.