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PEOPLE@HES-SO – Annuaire et Répertoire des compétences
PEOPLE@HES-SO – Annuaire et Répertoire des compétences

PEOPLE@HES-SO
Annuaire et Répertoire des compétences

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Abdennadher Nabil

Abdennadher Nabil

Professeur HES ordinaire

Compétences principales

IoT Internet Of Things

Distributed and Parallel Computing

Edge and Cloud Computing

Cloud Continuum

  • Contact

  • Enseignement

  • Recherche

  • Publications

  • Conférences

Contrat principal

Professeur HES ordinaire

Bureau: A401

Haute école du paysage, d'ingénierie et d'architecture de Genève
Rue de la Prairie 4, 1202 Genève, CH
hepia
Domaine
Technique et IT
Filière principale
Informatique et systèmes de communication
BA HES-SO en Architecture - Haute école du paysage, d'ingénierie et d'architecture de Genève
  • Cloud Computing
  • Distributed Systems
MSc HES-SO en Engineering - HES-SO Master
  • Internet of Things
MA BFH/HES-SO en Architecture - HES-SO Master
  • Advanced Cloud Computing

En cours

EXPOSITION - Programme de recherche - Projets phares 2023
AGP

Rôle: Co-requérant(s)

Requérant(e)s: VS - Institut Energie et environnement, Roduit Pierre, VS - Institut Energie et environnement

Financement: HES-SO Rectorat

Description du projet : EXPOSITION ' EXperimentation PlatfOrm for Smart-dIsTricts: from buildings to secure grId OperatioN La lutte contre le réchauffement climatique est le plus grand défi de ce début du 21ème siècle. L'utilisation de l'énergie (bâtiments, transports, industrie, etc.) étant la source majoritaire des émissions de CO2, la transition énergétique est cruciale pour limiter ce réchauffement. Au niveau suisse, la stratégie énergétique 2050 a pour but de décarboner l'énergie tout en se passant de l'énergie nucléaire. Le potentiel limité de l'extension de l'hydroélectricité et de la géothermie pour la production électrique, associé à la faible popularité des éoliennes, fait que le développement des nouvelles énergies renouvelables se fait principalement par des installations photovoltaïques (PV) décentralisées. Ce développement, couplé à l'électrification de la mobilité et du chauffage (pompes à chaleur) provoquent de gros pics de consommation et de production qui commencent à mettre le réseau électrique de distribution à rude épreuve. Ceux-ci surchargent les composants du réseau et provoquent en effet des sur- ou sous-tensions qui impactent la sécurité d'exploitation et obligent les gestionnaires des réseaux de distribution (GRD) à déployer des solutions de trois types : le renforcement des composants passifs du réseau (câbles et transformateurs), l'ajout de composants actifs (batteries, transformateurs réglables, compensateurs réactifs) ou la gestion de la flexibilité chez le client (capacité à varier la puissance de consommation ou de production d'électricité sans impacter significativement le confort). D'un autre côté, la problématique des risques de pénuries d'énergie a explosé aux yeux de nos confédérés. La conjoncture actuelle (guerre d'Ukraine) a montré la dépendance d'approvisionnement de la Suisse à des pays plus ou moins amis. Cette insécurité subsistera encore de longues années, car l'augmentation des capacités de production en Suisse et en Europe prendra du temps. De plus, la problématique du creux de production hivernal nécessitera une augmentation des capacités de stockage. Les barrages et batteries ne pouvant fournir les réserves nécessaires en Suisse et en Europe, le gaz de synthèse (Power to Gas : P2G) continuera à se développer pour permettre de stocker les énergies conséquentes nécessaires, tout en limitant l'utilisation des énergies fossiles. Les réseaux de distribution seront impactés par l'utilisation de couplage chaleur-force (CCF) utilisant ce gaz de synthèse en hiver pour produire de l'électricité, tout en injectant la chaleur produite dans les réseaux de chaleur à distance (CAD). Même si les risques de blackouts électriques restent faibles, des pénuries d'énergie signifient que moins d'installations sont disponibles pour réguler le réseau et ainsi les éviter, augmentant la probabilité qu'ils adviennent. Les risques de pénurie requièrent aussi des solutions de gestion de la réduction de la consommation plus fine que le délestage alterné de zones de desserte tel que proposé au dernier niveau du plan OSTRAL. Par ailleurs, quatre facteurs sont en train de modifier radicalement l'usage des réseaux de distribution à savoir : (i) la décentralisation de la production, (ii) le développement de nouvelles formes de consommation tels les véhicules électriques (VE), (iii) le développement des regroupements de consommation propre (RCP) et (iv) l'introduction massive des compteurs intelligents (80% des ménages suisses devraient en être équipés d'ici 2027). Ces quatre facteurs offrent un environnement propice au développement et déploiement de nouvelles solutions, technologies et services, empreints de digitalisation et qui accroissent la robustesse du système énergétique. Sur ces problématiques de digitalisation, de résilience, de convergence et de flexibilité des réseaux, la HES-SO est bien positionnée. En collaboration avec ses multiples partenaires de terrain, elle est active dans de nombreux projets de recherche et de

Equipe de recherche au sein de la HES-SO: Mokhles-Gerami Adeleh , Grammatikos Plouton , Ferrez Pierre , Gantel Laurent , Gabioud Dominique , Abdennadher Nabil , Perez Yohann , Fracheboud Thierry , Chételat Jérôme , Bozorg Mokhtar , Pouget Julien , Marazzi Sofia , Bacher Jean-Philippe , Guo Baoling , Graber Romain , Tomasini Luca , Darbellay Laurent , Giraldi Antoine , Sossan Fabrizio , Roduit Pierre

Partenaires académiques: FR - EIA - Institut ENERGY; VS - Institut Energie et environnement; HEPIA inTECH; iE; Roduit Pierre, VS - Institut Energie et environnement

Durée du projet: 01.01.2024 - 31.05.2025

Montant global du projet: 500'000 CHF

Statut: En cours

NORA - Noise Radar

Rôle: Co-requérant(s)

Requérant(e)s: Meleder Glenn, Securaxis

Financement: Innosuisse

Description du projet :

Urban environments are exposed to high noise levels that have an impact on human health. Road traffic is a prominent factor of noise pollution. The NORA project aims to address this problem by developing an adaptive cloud-edge platform based on FPGA devices for smart cities by combining IoT, acoustic and AI.

Equipe de recherche au sein de la HES-SO: Upegui Posada Andres , Abdennadher Nabil , Berthet Quentin , Poleggi Marco Emilio

Partenaires académiques: Lissek Hervé, EPFL

Partenaires professionnels: Meleder Glenn, Securaxis

Durée du projet: 01.02.2021 - 31.12.2023

Montant global du projet: 686'605 CHF

Url du site du projet: https://lsds.hesge.ch/nora-noise-radar-distributed-acoustic-sensor-network-for-traffic-noise-impact-measurement/

Statut: En cours

sMart EDge fabric for Iot Applications (MEDinA)

Rôle: Requérant(e) principal(e)

Financement: Innosuisse

Description du projet :

MEDInA will enable the creation of low cost IoT selfadaptive Machine Learning based applications by developing an Intelligence as Service (InaaS) framework. InaaS will provide a shareable edge/cloud platform that supports ML Modules running on edges, improved by cloud, able to self-adapt locally.

Equipe de recherche au sein de la HES-SO: Abdennadher Nabil

Partenaires professionnels: Marc-Elian Bégin, SixSq; Olivier Gudet, SIG; Patrick Montier, Canton de Genève (Smart Geneva); Philippe Royer, Service de l'air, du bruit et des rayonnements non ionisants (SABRA)

Durée du projet: 01.07.2019 - 31.12.2021

Montant global du projet: 952'000 CHF

Url du site du projet: https://lsds.hesge.ch/smart-edge-fabric-for-iot-applications/

Statut: En cours

Terminés

Programme de soutien au dépôt de projets liés à l'obtention de fonds de tiers 2023. Innosuisse - DEMETER.
AGP

Rôle: Requérant(e) principal(e)

Financement: HES-SO Rectorat

Description du projet : Programme de soutien au dépôt de projets liés à l'obtention de fonds de tiers 2023. Innosuisse - DEMETER.

Equipe de recherche au sein de la HES-SO: El Maliki Tewfiq , Abdennadher Nabil

Partenaires académiques: hepia inIT

Durée du projet: 23.05.2023 - 31.12.2024

Montant global du projet: 15'000 CHF

Statut: Terminé

LASAGNE - digitaL frAmework for SmArt Grid and reNewable Energie. Prime FNS - LASAGNE
AGP

Rôle: Requérant(e) principal(e)

Financement: HES-SO Rectorat

Description du projet : The energy transition calls for smart meters to support microgrids. Apart from monitoring home appliances' power cycles, they will need to gather data about other households so as to predict/plan local and microgrid consumption/production. These novel smart meters (Grid Edge Devices: GED), will need to be managed in a collaborative fashion. We want to develop GEDs enhanced with collaborative AI algorithms which are the foundation to build context-aware and self-adaptive energy applications. In essence, we propose to develop a digitaL frAmework for SmArt Grid and reNewable Energies (LASAGNE) and involve four stakeholders: System Integrator, Independent Software Vendors, Edge Equipment Vendors and Need-Owners. LASAGNE will be empowered by marketplace features allowing stakeholders to implement their financial/technical interactions. To handle the energy transition in an acceptable way, we will consider both social and business perspectives in the development of our GED-based system.

Equipe de recherche au sein de la HES-SO: Abdennadher Nabil

Partenaires académiques: hepia inIT

Durée du projet: 12.04.2022 - 31.12.2023

Montant global du projet: 15'000 CHF

Statut: Terminé

SWARM - Smart and Widely-distributed Appliances for Renewable energy Management. Prime Eurostars - SWARM
AGP

Rôle: Requérant(e) principal(e)

Financement: HES-SO Rectorat

Description du projet : SWARM aims to provide new services such that users become active participants, thus becoming direct beneficiaries of a liberalized energy market. We achieve this goal by creating and demonstrating the Smart Energy Management Appliance (SEMA), an innovative connected energy product, which offers supply/usage prediction, flexibility and energy transaction negotiation while upholding grid stability. A marketplace platform will support the technical/financial interactions among involved stakeholders.

Equipe de recherche au sein de la HES-SO: Abdennadher Nabil

Partenaires académiques: hepia inIT

Durée du projet: 12.04.2022 - 31.12.2023

Montant global du projet: 7'500 CHF

Statut: Terminé

eScience Coordination Team eSCT
AGP

Rôle: Requérant(e) principal(e)

Financement: Université de Zürich; hepia inIT; hepia inIT

Description du projet : "The goal of the eScience Coordination Team (eSCT) project is to form a national coordination service that provides support for research computing in Switzerland. The aim is to unite and enrich current support expertise for computing in the scientific and research sector, and make this expertise available to a larger community through a sustainable operational model. The term `eScience' refers to activities in science that are related to the computation and storage, analysis and publication of data or to the simulation of scientific processes. The need to improve the support to eScience is growing and scientists require access to professionally supported information technology (IT) platforms in order to be competitive. The eSCT coordinates: The Science IT Network of Excellence (SciNeX), The Active Liaison Persons Network, and the SciNeX Local Nodes. The eSCT project builds on a number of past and current initiatives that have brought together those supporting research IT and eScience. This include, the Swiss MultiScience Compute Grid, and the subsequent Swiss Academic Compute Cloud project in the AAA/SWITCH program. The HES-SO/GE (LSDS) group participates in the eSCT project as a SciNex Specialist Support Unit."

Equipe de recherche au sein de la HES-SO: Boulmier Anthony Alain André , Pittet Flavia , Gindre Ludovic , Abdennadher Nabil , Tamone François , Dupuis Raoul , Poleggi Marco Emilio

Durée du projet: 01.07.2015 - 30.09.2019

Montant global du projet: 354'000 CHF

Statut: Terminé

IoT Week
AGP

Rôle: Requérant(e) principal(e)

Financement: hepia inIT; Location stands; Sponsors; Inscriptions conférence; hepia inIT

Description du projet : Organisation de la conférence IoT Week (http://iot-week.eu/). La HES-SO est l'un des co-organisateurs, avec l'IUT, IoT Forum et Mandat International. Cette conférence aura lieu du 6 au 9 Juin 2017 au CICG.

Equipe de recherche au sein de la HES-SO: Upegui Posada Andres , Fraternale-Baur Catherine , Kunikowski Joanna Hélèna Christelle , Boulmier Anthony Alain André , Inacio Anabela , Bechevet Delphine , Minelli Michaël , Abdennadher Nabil

Partenaires professionnels: Confédération Suisse

Durée du projet: 01.11.2016 - 31.08.2017

Montant global du projet: 364'575 CHF

Statut: Terminé

Cloud Based Design Support System for Urban Numeric Data
AGP

Rôle: Requérant(e) principal(e)

Financement: CTI; SEMO; SSIG - DIM Etat de genève; Arx IT

Description du projet : "iCeBOUND vise à mettre en place des applications d'aide à la décision pour le traitement de modèles numériques urbains 3D. L'objectif est de promouvoir le potentiel de l'énergie solaire thermique et photovoltaïque ainsi que les mesures topographiques fondées sur les systèmes de positionnement GNSS, en offrant des analyses de visibilité satellitaire. Les villes des pays développés sont aujourd'hui de plus en plus numérisées. Les modèles numériques urbains 3D constituent de nos jours des supports d'information très utiles pour différentes applications dans les domaines de l'ingénierie, de l'urbanisme et de l'architecture notamment. Mais, le potentiel de ces modèles numériques n'est pas exploité à sa juste valeur. Plusieurs applications peuvent en effet être développées à partir de ces modèles. L'analyse du potentiel solaire (solar mapping) et la visibilité satellitaire sont deux exemples types. Le solar mapping permet d'estimer les ombrages et de déterminer, ente autres, les zones pouvant être utilisées pour l'installation de panneaux solaires. La seconde application (visibilité satellitaire) permet de quantifier la couverture satellitaire au niveau d'une région donnée."

Equipe de recherche au sein de la HES-SO: Desthieux Gilles , Boulmier Anthony Alain André , White John , Abdennadher Nabil , Dubois Alain

Partenaires académiques: hepia inIT; Abdennadher Nabil, hepia inIT

Partenaires professionnels: SIG; CERN; OCEN - Office cantonal énergie

Durée du projet: 01.05.2014 - 01.05.2016

Montant global du projet: 335'875 CHF

Url du site du projet: https://lsds.hesge.ch/cloud-based-design-support-system-for-urban-numeric-data/

Statut: Terminé

Porting MetaPega on Venus-C platform
AGP

Rôle: Requérant(e) principal(e)

Financement: Engineering Ingegneria Informatica SpA (ENG)

Description du projet : Since 2003, The University of applied Sciences, western Switzerland (HES-SO, hepia Geneva) has been developing a volunteer computing middleware called XtremWebCH (XWCH: www.xtremwebch.net). XWCH has a rich API by which an XWCH client can submit either single tasks or parallel workflow -type applications to the coordinator. The parallel workflow type has been utilized in many collaborations, among them PHYLIB Phylogenetic computing package (http://www.phylip.com/), NeuroWeb (neural brain modeling application), MedGIFT medical image indexing system (http://medgift.hevs.ch) and radiotherapy dose calculation NeuRad. Several lessons have been learnt from these projects. The most important is node volatility: nodes currently connected are not dedicated to the XWCH platform. Although the number of nodes in which XWCH is installed is more than 1200 PCs, the real number of connected workers is often less than 700. Our goal in this project is to enable a stable platform for phylogeny computation such that some of the computing nodes are governed by our universities (XWCH platform), some by VENUS-C cloud platform (http://www.venus-c.eu/Pages/Home.aspx). This kind of combined high-throughput platform will meet the needs of our main case, MetaPIGA. MetaPIGA (www.metapiga.org) is a phylogeny inference package developed by the LANE lab of University of Geneva (http://genev.unige.ch/en/users/Michel-Milinkovitch/unit) for large-scale simulations.

Equipe de recherche au sein de la HES-SO: Abdennadher Nabil

Partenaires académiques: hepia inIT

Durée du projet: 01.01.2012 - 31.01.2015

Montant global du projet: 31'982 CHF

Statut: Terminé

Swiss Academic Cloud
AGP

Rôle: Requérant(e) principal(e)

Financement: HES-SO Rectorat; hepia inIT; hepia inIT

Description du projet : "The project sustains the ongoing grid/cloud activities of the AAA/SWITCH program that are essential for the research communities. It bridges the activities that are expected to become relevant to the upcoming Informationsversorgungsprojekt [crus]. The project merges the contributions of the AAA/SWITCH projects, namely the Swiss Multi Science Computing Grid (SMSCG), the Academic Compute Cloud Provisioning and Usage and other related AAA/SWITCH projects (like VM-MAD, GridCertLib and RS-NAS), which conform with our mission. We focus on the sustainability of the computational service for our users and are, therefore, not pursuing any of the activities of these projects that are not directly contributing to this goal, e.g. like for example exploring next generation infrastructure technology."

Equipe de recherche au sein de la HES-SO: Abdennadher Nabil

Durée du projet: 01.05.2013 - 31.07.2014

Montant global du projet: 60'100 CHF

Statut: Terminé

CacHing Optimization In Cloud infrastructurE
AGP

Rôle: Requérant(e) principal(e)

Financement: HES-SO Rectorat

Description du projet : Nous proposons une nouvelle méthode pour améliorer la performance du caching dans une infrastructure Cloud en faisant usage d'algorithmes prédictifs et adaptatifs où le contenu de la mémoire cache est déterminé par la solution d'un modèle d'optimisation stochastique. La méthode utilise les informations des requêtes effectuées et les coûts spécifiques du cloud. L'objectif est de produire un algorithme qui conduit à l'optimisation globale du coût des opérations.

Equipe de recherche au sein de la HES-SO: Rappos Efstratios , Robert Stephan , Abdennadher Nabil

Partenaires académiques: IICT; hepia inIT; Abdennadher Nabil, hepia inIT

Durée du projet: 02.01.2013 - 31.07.2014

Montant global du projet: 154'000 CHF

Statut: Terminé

Swiss Multi-Sciences Cmmunity Grid
AGP

Rôle: Requérant(e) principal(e)

Financement: HES-SO Rectorat; hepia inIT; hepia inIT

Description du projet : The Swiss Multi-Science Computing Grid (SMSCG) is a project funded under the AAA/SWITCH program. The first phase of the project was from May 2008 to March 2010. The second phase (with stronger focus on infrastructure) was from April 2010 to December 2011. Phase-III, which started in Jannuary 2012 and will End in December 2012, focuses on user enabling and sustainability.

Equipe de recherche au sein de la HES-SO: Abdennadher Nabil

Durée du projet: 01.06.2012 - 31.01.2014

Montant global du projet: 41'500 CHF

Statut: Terminé

Multi-Site ARC services
AGP

Rôle: Requérant(e) principal(e)

Financement: HES-SO Rectorat; EIG - IMEC

Description du projet : The Multi-Site ARC services project aims at : 1.Extending the Swiss Multi-Science Grid (SMSCG) platform with a new node providing an access to a high-performance Linux cluster. 2.Integrating the XtremWeb-CH platform, developed partially in the context of the Virtual EZ Grid project, into the SMSCG platform. 3.Deploying three scientific applications on the SMSCG platform, and therefore making them available for the Swiss academy.

Equipe de recherche au sein de la HES-SO: Pontelandolfo Piero , Müller Henning , Abdennadher Nabil , Putzu Roberto , Eggel Ivan

Partenaires académiques: VS - Institut Informatique; hepia inIT; Abdennadher Nabil, hepia inIT

Durée du projet: 01.10.2010 - 31.12.2013

Montant global du projet: 136'700 CHF

Statut: Terminé

European Desktop Grid Initiative
AGP

Rôle: Requérant(e) principal(e)

Financement: FP7

Description du projet : EDGI will develop middleware that consolidates the results achieved in the EDGeS project concerning the extension of Service Grids with Desktop Grids (DGs) in order to support European Grid Initiative (EGI) and National Grid Initiative user communities that are heavy users of Distributed Computing Infrastructures (DCIs) and require an extremely large number of CPUs and cores. EDGI will go beyond existing DCIs that are typically cluster Grids and supercomputer Grids, and will extend them with public and institutional Desktop Grids and Clouds. EDGI will integrate software components of ARC, gLite, Unicore, BOINC, XWHEP, XTremWeb-CH, 3G Bridge, and Cloud middleware such as OpenNebula and Eucalyptus into SG-DG-Cloud platforms for service provision and as a result EDGI will extend ARC, gLite and Unicore Grids with volunteer and institutional DG systems.

Equipe de recherche au sein de la HES-SO: Abdennadher Nabil

Partenaires académiques: hepia inIT

Durée du projet: 01.04.2011 - 31.12.2013

Montant global du projet: 24'000 CHF

Statut: Terminé

Cloud Monitoring
AGP

Rôle: Co-requérant(s)

Requérant(e)s: IICT, Ehrensberger Jürgen, IICT

Financement: HES-SO Rectorat

Description du projet : Le Cloud Computing représente un changement de paradigme majeur pour les systèmes d'information. Afin de trouver un compromis optimal entre investissements et coût opérationnels, les entreprises seront appelées à utiliser des clouds hybrides, combinant une infrastructure privée (cloud privé) et des ressources publiques (cloud publics proposées par Amazon, Google, Microsoft, etc.). L'objectif du projet CloudMon est de développer un ensemble d'outils de monitoring qui permet à une PME ou entreprise de déployer de manière optimale des applications dans un cloud hybride. Concrètement, l'application à déployer est souvent représentée par un wokflow modélisant les interconnexions entre les différents modules de l'application. Les outils qui seront développés par le projet CloudMon permettront à l'utilisateur de configurer son application de manière optimale sur le cloud hybride. En d'autres termes, il s'agit de répartir les modules de l'application concernée entre le cloud public et le cloud privé.

Equipe de recherche au sein de la HES-SO: Raileanu Laura Elena , Robert Stephan , Rubinstein Marcos , Ehrensberger Jürgen , Fatemi Nastaran , Rubinstein Scharf Abraham , Abdennadher Nabil

Partenaires académiques: IICT; hepia inIT; Ehrensberger Jürgen, IICT

Durée du projet: 01.07.2010 - 31.03.2013

Montant global du projet: 70'700 CHF

Statut: Terminé

From Prototype To Product
AGP

Rôle: Requérant(e) principal(e)

Financement: HES-SO Rectorat; EIG - INIT; 519,Economie d'entreprise; SIM-TIC; Interreg4

Description du projet : L'objectif stratégique du projet From-P2P est de produire, à partir d'un prototype existant appelé XtremWeb-CH (www.xtremwebch.net), développé depuis 2003 à la HES-SO (EIG, HEIG-VD et EI-ARC), un Système Distribué à Large Echelle (SDLE) grand public, sécurisé et attrayant. Un SDLE grand public signifie qu'il peut supporter des ordinateurs anonymes appartenant à des particuliers (et non pas uniquement des ordinateurs dédiés appartenant à des institutions). Un SDLE est sécurisé s'il apporte une solution efficace et simple à mettre en 'uvre aux problèmes de la sécurité liés à l'ordinateur du fournisseur et à l'application du client. Un SDLE est dit attrayant s'il est facile d'utilisation et s'il suscite l'intérêt du fournisseur des ressources informatiques (ordinateurs). Pour ce faire, il est important de tester le SDLE concerné dans le cadre de plusieurs applications concrètes appartenant à des domaines différents. L'effet direct du déploiement d'un tel SDLE, est de permettre l'exécution d'applications industrielles et médicales à haute performance qui restent jusqu'à ce jour peu accessibles étant donné les ressources de calcul qu'elles nécessitent. Ces applications à des plusieurs domaines tels que le biotechnologie et la médecine.

Equipe de recherche au sein de la HES-SO: Fragniere Emmanuel , Bilat Cédric , Grunenwald David , Moresino Francesco , Abdennadher Nabil , Senn Julien

Partenaires académiques: Info. Technique

Durée du projet: 01.01.2009 - 31.12.2011

Montant global du projet: 324'354 CHF

Statut: Terminé

Virtual Easy Grid
AGP

Rôle: Requérant(e) principal(e)

Financement: HES-SO Rectorat; EIG - INIT; 519,Economie d'entreprise; SIM-TIC; SWITCH; EIG - INIT

Description du projet : Five technical goals are targeted by the Virtual EZ-Grid project: 1. Construct a desktop grid infrastructure with more than 1.500 non dedicated desktop PCs to provide harvested CPU power for scientific research projects. 2. Implement a reliable platform by using virtual environments to support secure computing and remote check-pointing. By using Wake-On-LAN technology, this project will also provide a better control over environmental issues and energy consumption by running only the necessary PCs and shutting down unused PCs at night and during holidays. The proposed platform should give a non-intrusive and non-disturbing experience to the PC users. 3. Guarantee the security and privacy of both the PC user and the virtual CPU environment by using the virtual isolation layer property, certificate and proper authentication of grid user. 4. Provide a resource-credit system that can be used in the future to evaluate the potential resource-credit schemes that could be established and the relevant criteria that should be used to determine a 'fair' incentive taking into account the point of views of providers and consumers of virtual PC resources. 5. Evaluate objectives 1 through 4 in a real world setting with two biomedical applications. The benefit of reaching these goals is to provide a highly available, secure and inexpensive PC grid infrastructure to participating universities and research groups. Harvesting unused CPU cycles from farms of PCs with virtualization technology allows researchers to use their existing code on their existing platforms without any or with little modification. Furthermore, this project removes the boundary between participating universities by sharing resources and jobs. In addition to the technical issues, one also has to face the economic perception and provide incentives to offer one's own machine to the community. Defining good practices and convincing users and authorities that the grid concept is useful and can be gracefully deployed at the scale of the full institution, as well as external institutions, is also an important goal of this project. In this context, the results of the project could be deployed on a public computing platform (anonymous nodes). Although this issue is not considered as an objective of the project, it will be retained as a guideline of Virtual EZ Grid. Another goal to consider is the opening of the different middlewares that will be used in the framework of this project at the Swiss level, in accordance to the objectives of the Swiss National Grid association (SwiNG).

Equipe de recherche au sein de la HES-SO: Fragniere Emmanuel , Kunzli Pierre , Bilat Cédric , Moresino Francesco , Abdennadher Nabil , Senn Julien

Partenaires académiques: Info. Technique

Durée du projet: 01.11.2008 - 30.11.2010

Montant global du projet: 222'790 CHF

Statut: Terminé

NeuroWeb.ch
AGP

Rôle: Requérant(e) principal(e)

Financement: HES-SO Rectorat; Info. Technique; GE Haute école du paysage, d'ingénierie et d'architecture; SIM-TIC

Description du projet : Le projet NeuroWeb.ch se propose de développer un algorithme de construction de cartes neuronales spécialement adaptées aux crises d'épilepsie. Cet algorithme, basé sur des modèles stochastiques complexes sera distribué et déployé sur un Système Distribué à Large Echelle (SDLE) choisi à cet effet. Dans ce contexte, la problématique abordée dans ce projet est la 'grillification' de l'application de construction de cartes neuronales décrite précédemment : il s'agit d'adapter, porter et dimensionner l'application sur un SDLE (par exemple GRID).

Equipe de recherche au sein de la HES-SO: Laurent Maxence , Bilat Cédric , Abdennadher Nabil , Beurret Stéphane , Senn Julien

Partenaires académiques: EIG - INIT; Abdennadher Nabil, EIG - INIT

Durée du projet: 10.01.2007 - 31.12.2008

Montant global du projet: 198'900 CHF

Statut: Terminé

Porting Genetic Applications on Peer To Peer Platforms
AGP

Rôle: Requérant(e) principal(e)

Financement: HES-SO Rectorat; GE Haute école du paysage, d'ingénierie et d'architecture; HUG; GE Haute école du paysage, d'ingénierie et d'architecture

Description du projet : Ce projet se propose de porter et déployer une application de génération d'arbres phylogénétiques (arbre généalogique des espèces vivantes) sur un environnement de Peer-To-Peer (P2P) Computing choisi à cet effet. Cette application (appelée PHYLIP) consommatrice de temps processeur est utilisée par le laboratoire de virologie de l'Hôpital Universitaire de Genève (HUG) pour la reconstruction d'arbres phylogénétiques d'une variété de virus HIV (sida) répertoriés en Suisse. Ces analyses sont utilisées non seulement pour reconstruire l'historique des différentes "formes" que prend le virus mais aussi et surtout pour prévoir ses évolutions, et donc les traitements médicaux adéquats. Compte tenu de la faible "puissance de calcul" disponible au laboratoire de virologie, certains programmes de PHYLIP ne peuvent être exécutés avec un nombre important de séquences ADN de virus HIV. L'objectif n'est pas de développer une solution "clé en main" basée sur une architecture P2P mais de montrer l'apport du P2P Computing dans le contexte des applications visées. Les résultats seront utilisés par les partenaires du projet pour le montage de projets dont les objectifs sont plus ambitieux (CTI, FNRS, etc.). Le prototype développé doit permettre la génération de "grands" arbres phylogénétiques (des centaines de séquences de virus) en un temps relativement court.

Equipe de recherche au sein de la HES-SO: Abdennadher Nabil

Durée du projet: 03.01.2005 - 30.11.2006

Montant global du projet: 128'000 CHF

Statut: Terminé

2022

Optimal load balancing and assessment of existing load balancing criteria
Article scientifique ArODES

Anthony Boulmier, Nabil Abdennadher, Bastien Chopard

Journal of Parallel and Distributed Computing,  2022, vol. 169, pp. 211-225

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Résumé:

Parallel iterative applications often suffer from load imbalance, one of the most critical performance degradation factors. Hence, load balancing techniques are used to distribute the workload evenly to maximize performance. A key challenge is to know when to use load balancing techniques. In general, this is done through load balancing criteria, which trigger load balancing based on runtime application data and/or user-defined information. In the first part of this paper, we introduce a novel, automatic load balancing criterion derived from a simple mathematical model. In the second part, we propose a branch-and-bound algorithm to find the load balancing iterations that lead to the optimal application performance. This algorithm finds the optimal load balancing scenario in polynomial time while, to the best of our knowledge, it has never been addressed in less than an exponential time. Finally, we compare the performance of the scenarios produced by state-of-the-art load balancing criteria relative to the optimal load balancing scenario in synthetic benchmarks and parallel N-body simulations. In the synthetic benchmarks, we observe that the proposed criterion outperforms the other automatic criteria. In the numerical experiments, we show that our new criterion is, on average, 4.9% faster than state-of-the-art load balancing criteria and can outperform them by up to 17.6%. Moreover, we see in the numerical study that the state-of-the-art automatic criteria are at worst 26.43% slower than the optimum and at best 10% slower.

Toward informed partitioning for load balancing :
Article scientifique ArODES
a proof-of-concept

Anthony Boulmier, Nabil Abdennadher, Bastien Chopard

Journal of Computational Science,  2022, vol. 61, article no. 101644

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Résumé:

Most parallel applications suffer from load imbalance, a crucial performance degradation factor. In particle simulations, this is mainly due to the migration of particles between processing elements, which eventually gather unevenly and create workload imbalance. Dynamic load balancing is used at various iterations to mitigate load imbalance, employing a partitioning method to divide the computational space evenly while minimizing communications. In this paper, we propose a novel partitioning methodology called “informed partitioning”. It uses information based on the evolution of the computation to reduce the load balancing growth and the number of load balancing calls. In this paper, we illustrate informed partitioning by proposing a new geometric partitioning technique for particles simulations. This technique is derived from the well-known recursive coordinate bisection and employs the velocity of the particles to guide the bisection axis. To properly compare the performance of our new method with existing partitioning techniques during application execution, we introduce an effort metric based on a theoretical model of load balanced parallel application time. We propose a proof-of-concept of informed partitioning, through a numerical study, on three N-Body simulations with various particle dynamics, and we discuss its performance against popular geometric partitioning techniques. Moreover, we show that our effort metric can be used to rank partitioning techniques by their efficiency at any time point during the simulation. Eventually, this could be used to choose the best partitioning on the fly. In the numerical study, we report that our novel concept increases the performance of two experiments out of three by up to 76% and 15%, while being marginally slower by only 3% in one experiment. Also, we discuss the limitations of our implementation of informed partitioning and our effort metric.

2020

GPU-enabled shadow casting for solar potential estimation in large urban areas
Article scientifique ArODES
application to the solar cadaster of greater Geneva

Nabil Stendardo, Gilles Desthieux, Nabil Abdennadher, Peter Gallinelli

Applied Sciences,  2020, vol. 10(15), article no. 5361

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Résumé:

In the context of encouraging the development of renewable energy, this paper deals with the description of a software solution for mapping out solar potential in a large scale and in high resolution. We leverage the performance provided by Graphics Processing Units (GPUs) to accelerate shadow casting procedures (used both for direct sunlight exposure and the sky view factor), as well as use off-the-shelf components to compute an average weather pattern for a given area. Application of the approach is presented in the context of the solar cadaster of Greater Geneva (2000 km2). The results show that doing the analysis on a square tile of 3.4 km at a resolution of 0.5 m takes up to two hours, which is better than what we were achieving with the previous work. This shows that GPU-based calculations are highly competitive in the field of solar potential modeling.

Learning-based coordination model for spontaneous self-composition of reliable services in a distributed system
Article scientifique ArODES

Houssem Ben Mahfoudh, Giovanna Di Marzo Serugendo, Nabil Naja, Nabil Abdennadher

International Journal on Software Tools for Technology Transfer,  2020, vol. 22, pp. 417-436

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Résumé:

Context-aware, pervasive systems, mobile devices, intelligent virtual assistants activating services or controlling connected devices are pervading our everyday life. These systems rely on centralized services provided by servers in a cloud gathering all requests, performing pre-defined computations and involving pre-defined devices. Large-scale scenarios, involving unanticipated devices, adaptation to dynamically changing conditions, call for alternative solutions favoring edge computing and decentralized behavior. For several years, we have worked on a new type of applications, built and spontaneously composed on-demand. Applications arise from the interactions of multiple sensors and devices, working together as a decentralized collective adaptive system. Our solution relies on a learning-based coordination model providing decentralized communication platforms among agents working on behalf of heterogeneous devices. Each device provides few simple services and data regarding itself (properties and capabilities). In this article, we discuss first the design of complex services, arising from the spontaneous self-composition of simpler services. Second, we present our learning-based coordination model combining coordination and reinforcement learning, and how this approach ensures reliable self-composition of services in terms of functionality and expected quality of services. On the basis of a humanitarian scenario, we show the feasibility of the approach and discuss our current implementation. Preliminary results show convergence toward learning and correct functionality. Spontaneous self-composition and learning provide a self-adaptive solution for creating on-demand complex services evolving in highly dynamic scenarios comprising large numbers of connected devices.

2018

Solar cadaster of Geneva :
Chapitre de livre ArODES
a decision support system for sustainable energy management

Gilles Desthieux, Claudio Carneiro, Alberto Susini, Nabil Abdennadher, Anthony Boulmier, Alain Dubois, Reto Camponovo, David Beni, Matthieu Bach, Phelan Leverington, Eugenio Morello

From science to society  (8 p.). 2018,  Cham : Springer

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Résumé:

Cities play an increasingly important role with regards to energy transition. Main goal is to reach international and national (Swiss) targets related to energy efficiency and CO2 emission reduction. As a contribution to these global challenges, during the last 6 years the State of Geneva has been producing a detailed solar cadaster. In order to facilitate periodical updates of this solar cadaster, the iCeBOUND project was launched. Around 10 public and private stakeholders, all linked within the Geneva Territorial Information System (SITG), collaborated on the project. Its aim was to design and develop a cloud-based Decision Support System (DSS) that leverages 3D digital urban data with high computing performance, hence facilitating environmental analyses in large built areas, like solar energy potential assessment. As result of the project, an official geoportal and a newfangled public web interface were made widely available early 2017, so as to strengthen decision making with regards to solar installation investment.

Solar energy potential assessment on rooftops and facades in large built environments based on LiDAR data, image processing, and cloud computing :
Article scientifique ArODES
methodological background, application, and validation in Geneva (solar cadaster)

Gilles Desthieux, Claudio Carneiro, Reto Camponovo, Pierre Ineichen, Eugenio Morello, Anthony Boulmier, Nabil Abdennadher, Sébastien Dervey, Christoph Ellert

Frontiers in Built Environment,  2018, 4, 14

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Résumé:

The paper presents the core methodology for assessing solar radiation and energy production on building rooftops and vertical facades (still rarely considered) of the inner-city. This integrated tool is based on the use of LiDAR, 2D and 3D cadastral data. Together with solar radiation and astronomical models, it calculates the global irradiance for a set of points located on roofs, ground, and facades. Although the tool takes simultaneously roofs, ground, and facades, different methods of shadow casting are applied. Shadow casting on rooftops is based on image processing techniques. On the other hand, the assessment on facade involves first to create and interpolate points along the facades and then to implement a point-by-point shadow casting routine. The paper is structured in five parts: (i) state of the art on the use of 3D GIS and automated processes in assessing solar radiation in the built environment, (ii) overview on the methodological framework used in the paper, (iii) detailed presentation of the method proposed for solar modeling and shadow casting, in particular by introducing an innovative approach for modeling the sky view factor (SVF), (iv) demonstration of the solar model introduced in this paper through applications in Geneva’s building roofs (solar cadaster) and facades, (v) validation of the solar model in some Geneva’s spots, focusing especially on two distinct comparisons: solar model versus fisheye catchments on partially inclined surfaces (roof component); solar model versus photovoltaic simulation tool PVSyst on vertical surfaces (facades). Concerning the roof component, validation results emphasize global sensitivity related to the density of light sources on the sky vault to model the SVF. The low dense sky model with 145 light sources gives satisfying results, especially when processing solar cadasters in large urban areas, thus allowing to save computation time. In the case of building facades, introducing weighting factor in SVF calculation leads to outputs close to those obtained by PVSyst. Such good validation results make the proposed model a reliable tool to: (i) automatically process solar cadaster on building rooftops and facades at large urban scales and (ii) support solar energy planning and energy transition policies.

2016

Computational fluid dynamics as a tool to predict the air pollution dispersion in a neighborhood :
Article scientifique ArODES
a research project to improve the quality of life in cities

Gilles Triscone, Nabil Abdennadher, Christophe Balistreri, Olivier Donzé, D. Greco, Patrick Haas, H. Haas-Pekoz, T. Mohamed-Nour, Pierre Munier, Piero Pontelandolfo, Roberto Putzu, Jacques Richard, H. Sthioul, Nicolas Delley, D. Choffat, Elena-Lavinia Niederhäuser, Roger Schaer, Henning Müller, Jean Decaix, Sylvain Richard, Cécile Münch-Alligné, P. Kunz, F. Despot

International Journal of Sustainable Development and Planning,  2016, vol. 11, no. 4, pp. 546-557

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Résumé:

In large cities, pollution composed of many different chemical components and small particles is an important public health problem that affects especially children and people presenting breathing difficulties. One challenge for public authorities is to respect the norms given by the central state, but how? Today, concrete methods for reducing pollution are perceived by the majority of citizens as constraints. However, the authorities have the possibility of modifying the wind’s action by imposing architectural constraints, such as building emplacement and roof structure. This is the main objective of the Geneva ‘Clean City’ project financed by the University of Applied Sciences Western Switzerland. ‘Clean City’ focuses its research on one of Geneva’s polluted neighborhood called Pâquis, which is situated directly on the Geneva lake front. The project attempts to understand the dispersion of pollution from an experimental and a numerical point of view. After validation of the technique for a simple case, we compare environmental measurements on a 1/500 3D scale model of the Pâquis installed in an instrumented wind tunnel with Computational Fluid Dynamics (CFD) simulation obtained with the help of cloud computing.

2009

Advances in grid and pervasive computing :
Livre ArODES
4th international conference, GPC 2009, Geneva, Switzerland, May 4-8, 2009, proceedings

Nabil Abdennadher, Dana Petcu

2009,  Berlin, Heidelberg : Springer,  XIV, 484 p.

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Résumé:

This book constitutes the refereed proceedings of the 4th International Conference on Grid and Pervasive Computing, GPC 2009, held in Geneva, Switzerland, in May 2009. The 42 revised full papers presented were carefully reviewed and selected from 112 submissions. The papers are organized in topical sections on grid economy, grid security, grid applications, middleware, scheduling, load balancing, pervasive computing, sensor networks, peer-to peer as well as fault tolerance.

2024

Smart cooperatives:
Conférence ArODES
adapting smart grid concepts to agricultural cooperatives

Francisco Mendonca, Nabil Abdennadher, Giovanna Di Marzo

Proceedings of the 10th World Congress on Electrical Engineering and Computer Systems and Science, 19-21 August 2024, Barcelona, Spain

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Résumé:

This paper introduces a novel approach to creating cooperation-optimized farming groups called Smart Cooperatives. These groups leverage advancements in smart agricultural technologies to address critical challenges in the agricultural sector, including water scarcity, market access limitations, and the adverse impacts of climate change and geopolitical tensions. Through a detailed analysis of current farming practices and organizational methods, Smart Cooperatives are proposed as a transformative model that combines the principles of smart grids from the electrical sector with the unique needs of agriculture. This model aims to foster enhanced collaboration among farmers, equitable resource distribution, and stronger market presence by utilizing data-driven methodologies for grouping farmers based on both intrinsic and extrinsic characteristics. By examining potential counterarguments and challenges, the paper highlights the importance of accessibility, adaptability, and scalability in implementing Smart Cooperatives. Concluding with a call for further research and a pilot questionnaire aimed at refining the model and understanding farmer needs, this study presents Smart Cooperatives as a promising avenue towards sustainable, resilient, and cooperative farming futures, potentially reshaping the agricultural landscape in the face of global uncertainties.

Developing card-based surveys :
Conférence ArODES
focus group insights for smart grid prosumer optimization

Emmanuel Fragnière, Sarah Sandoz, Nabil Abdennadher, Francesco Moresino

Proceedings of the 12th International Conference on Smart Grid (icSmartGrid)

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Résumé:

This study presents a novel approach to developing effective surveys for optimizing residential micro-grid configurations, integrating insights from focus group research. The development of card-based questionnaires allows for the collection of qualitative feedback, which in turn enables the understanding of prosumer (i.e., producer/consumer) preferences and the improvement of microgrid design. By integrating insights from focus groups, we construct card-based questionnaires that capture the nuances of prosumer perspectives on energy infrastructure, pricing mechanisms, information sharing, community engagement, regulations, and governance. The methodology employed three key phases: ethnographic surveys to identify salient attributes, combining technical and social attributes through interviews and focus groups, and conjoint analysis to quantify attribute importance. In this paper, a previous ethnographic survey was employed to develop a card-based questionnaire for use in a subsequent conjoint analysis survey. This research contributes to the development of optimized micro-smart grid configurations that are conducive to widespread adoption and sustainability.

Towards enhancing trustworthy data accessibility in the crop commodity sector with LLMs
Conférence ArODES

Abir Chebbi, Guido Kniesel, Nabil Abdennadher, Giovanna Di Marzo Serugendo, Tewfiq El-Maliki

Proceedings of 2024 11th IEEE Swiss Conference on Data Science (SDS), 30-31 May 2024, Zurich, Switzerland

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Résumé:

The volatile nature of the global crop commodity market necessitates advanced analytical tools to enable stakeholders to make informed decisions based on timely and accurate data. However, the complex and diverse nature of agricultural data and crop commodities, often presented in unstructured formats, pose significant challenges in extracting meaningful insights.This paper examines the use of Large Language Models to enhance Named Entity Recognition techniques specifically designed for the crop commodity market. We investigate the efficacy of these models in effectively tagging and categorizing essential information such as agricultural products, vessel movements, and trade flows. Our findings suggest that while fine-tuned base models deliver high precision, LLMs like GPT-4 and Claude v2 offer comparable performance without the need for additional training on new entities.Nonetheless, deploying these advanced technologies raises issues concerning system reliability, robustness, and explainability. Addressing these challenges is crucial for maintaining the trustworthiness of NLP-powered systems in the crop commodity sector. This paper presents a preliminary design for increasing Trust in these automated systems.

Enhancing named entity recognition for agricultural commodity monitoring with large language models
Conférence ArODES

Abir Chebbi, Guido Kniesel, Nabil Abdennadher, Giovanna Dimarzo

Proceedings of the 4th Workshop on Machine Learning and Systems (EuroMLSys '24), 22 April 2024, Athens, Greece

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Résumé:

Agriculture, as one of humanity's most essential industries, faces the challenge of adapting to an increasingly data-driven world. Strategic decisions in this sector hinge on access to precise and actionable data. Governments, major agriculture companies, and farmers have expressed a need for worldwide monitoring of crop commodity quantities and prices. However, the complex and diverse nature of agricultural data and crop commodities, often presented in unstructured formats, pose significant challenges in extracting meaningful insights. This study delves into the effectiveness of Large Language Models, particularly in Named Entity Recognition, focusing on their ability to efficiently tag and categorize crucial information related to agriculture, vessel tracking, imports, and exports, thereby enhancing data accessibility. Our results indicate that while fine-tuning a base model achieves high precision, Large Language Models, particularly GPT-4 and Claude v2, demonstrate comparable performance with the added benefit of requiring no additional training for new entity recognition. This research highlights the promising role of Large Language Models in agricultural AI, suggesting their use as a scalable solution for real-time data analysis and decision support in agriculture.

2023

Towards a decentralised federated learning based compute continuum framework
Conférence ArODES

Mohamad Moussa, Philippe Glass, Nabil Abdennadher, Raphaël Couturier

Proceedings of the European Conference on Service-Oriented and Cloud Computing, 24-25 October 2023, Larnaca, Cyprus5

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Résumé:

The proliferation of sensing device technologies, and the growing demand for data intensive IoT applications calls for a seamless interconnection of IoT, edge and cloud resources in one computing system, to form a Compute Continuum, also referred to as edge-to-cloud. This paper targets self-adaptive Machine Learning applications that rely on data coming from IoT sensors. These applications are often “context-aware”, with high context sensitivity, different physical settings and complex usage patterns. Their intelligence, deployed on the edge, is updated on the fly. We present two Compute Continuum strategies for the deployment of such applications: (1) a centralised approach, which involves training a model on a centralised server, and (2) a decentralised approach using Federated Learning. The former approach involves centralising data from multiple sources onto a single server, while the latter locally decentralises both the training process and the aggregation and communication tasks across edge devices. In both cases the inference model is deployed on edge devices close to the collected data. The decentralised architecture relies on a coordination platform favouring self-adaptation and decentralised Federated Learning. Results show that the decentralised Federated Learning approach offers networking performances and privacy-preserving advantages compared to non-private centralised models, with a slight trade-off in prediction accuracy. According to our simulations, the deployment cost of the decentralised architecture is much lower than that of deployment on the centralised architecture.

A generic-based Federated Learning model for smart grid and renewable energy
Conférence ArODES

Mohamad Moussa, Nabil Abdennadher, Raphaël Couturier, Giovanna Di Marzo Serugendo

Proceedings of the 2023 22nd International Symposium on Parallel and Distributed Computing (ISPDC), 10-12 July 2023, Bucharest, Romania

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Résumé:

The liberalization of the electricity market and the expansion of new forms of electricity production and consumption are paving the way for new smart digital services. These new services will certainly be relying on a new generation of smart meter (SM) that will offer, among other things, prediction of consumption and production at both household and microgrid levels.These predictions can be obtained either through a generic model trained on data collected from all SMs, or through specific models developed for each SM based on its individual data. The benefit of the generic model is that it guarantees an optimal solution. However, its implementation is not possible for security reasons. The use of specific models requires managing a large number of SMs, which poses a significant challenge.This paper presents a Federated Learning (FL) approach, a decentralized privacy-preserving paradigm that achieves com-parable performance to the generic model, considering both consumption and production scenarios.The dataset, gathered from 1153 SMs over a period of 18 months, is provided by a Swiss Distribution System Operators (DSO). Although, data are individually collected per device, the generic model is trained to holistically process this data.Our experimental results demonstrate that our FL based Long Short-Term Memory (LSTM) model performs as well as the generic model and outperforms the specific models, while preserving data privacy and security.

Fostering “Energy Communities” :
Conférence ArODES
an ethnographic-SECI approach to user-centered residential micro-smart grid adoption

Emmanuel Fragniere, Sarah Sandoz, Nabil Abdennadher, Mohamad Moussa, Giovanna Di Marzo Serugendo, Philippe Glass

Proceedings of the 11th International Conference on Smart Grid (icSmartGrid), 4-7 June 2023, Paris, France

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Résumé:

This paper presents a user-centered approach to understanding the social context of smart residential microgrid adoption, with a focus on the SECI (Socialization, Externalization, Combination, and Internalization) model of knowledge creation. The objective is to identify the social characteristics that contribute to the social acceptance of smart residential microgrids, particularly from the perspective of prosumers interacting with AI. The study focuses on 12 Swiss smart grid stakeholders, including those who live in eco- neighborhoods, and own solar panels, plus three focus groups with experts. The study found that trust, community, and shared values are key social factors influencing the adoption of residential smart microgrids. Results also show how the SECI model could facilitate the creation and sharing of knowledge about energy management and sustainability practices, knowing that smart grids rely primarily on AI or explicit knowledge (Combination) and that successful implementation should as well, regarding this theory, focus on tacit knowledge (Socialization).

Improving the social acceptability of microgrids
Conférence ArODES

Emmanuel Fragniere, Sarah Sandoz, Nabil Abdennadher, Mohamad Moussa, Giovanna Di Marzo Serugendo, Philippe Glass

2023 11th International Conference on Smart Grid (icSmartGrid)

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Résumé:

The smart grid will have to occupy a prominent place in people's lives in the years to come, as the renewable energy mix desired by all governments implies a change of role from consumer to prosumer (contraction of the consumer to producer) of electricity. The adoption of micro smart grid technology, which links solar panels, batteries, and inverters to smart meters and power regulation algorithms, by a community (e.g., a residential sector), cannot be done automatically. This is what we studied in Switzerland, based on a qualitative survey (12 semi-structured interviews and 4 focus groups) to understand the psychological and social barriers, which prevent people from integrating such a technology. The results show that restraining forces are more important than driving forces and therefore that governments need to tackle the problem of social acceptance of smart grids before focusing on mainly technological aspects in their long-term energy and environmental policies.

2022

Edge-to-cloud solutions for self-adaptive machine learning-based IoT applications :
Conférence ArODES
a cost comparison

Marco Emilio Poleggi, Nabil Abdennadher, Raoul Dupuis, Francisco Mendonça

Proceedings of the 19th International Conference on the Economics of Grids, Clouds, Systems and Services, 13-15 September 2022, Izola, Slovenia

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Résumé:

Large-scale IoT applications based on machine learning (ML) demand both edge and cloud processing for, respectively, AI inference and ML training tasks. Context-aware applications also need self-adaptive intelligence which makes their architecture even more complex. Estimating the costs of operating such edge-to-cloud deployments is challenging. To this purpose, we propose a reference service-oriented event-driven system architecture for IoT/edge applications comprising a minimal set of components, mapped on available cloud services. We then propose a resource consumption model for estimating the cost of deploying and running self-adaptive AI-assisted IoT applications on selected edge-tocloud platforms. The model is evaluated in two scenarios: Road Traffic Management and Smart Grid. We finally provide some estimates showing how the expenditure breakdown varies significantly depending on the adopted platform: storage costs are dominant in Road Traffic Management for all providers, whereas either messaging or edge management costs may dominate the Smart Grid scenario, and, surprisingly, computing costs are almost negligible in all cases.

Context-aware trust metrics for non critical IoT applications :
Conférence ArODES
an intrinsic data quality approach

Francisco Mendonça, Nabil Abdennadher, Tewfiq El-Maliki, Marco Emilio Poleggi

Proceedings of the 2022 13th International Conference on Information and Communication Systems (ICICS), 21-23 June 2022, Irbid, Jordan

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Résumé:

Trust mechanisms are a promising solution to the security and reliability dilemma of city scale (smart city) IoT sensor deployments in non-critical scenarios. These deployments often employ low-cost sensor networks, where strict security policies are difficult to enforce, and whose IoT devices may exhibit incoherent sensing behavior. Because of the diverse disturbances that may affect the sensing data path, the integrity of the measurements has to be assessed by the data-consuming application, so that possibly misbehaving sensors and/or biased data can be identified. This paper proposes a trust model which assesses the trustworthiness of data collected from IoT sensors deployed at a city scale. The model is based on a set of context-aware trust metrics that leverage proximity information and context signatures. This intrinsic data-quality approach has the potentials to overcome the limitations of consensus-based metrics, which cannot easily detect anomalies affecting several neighbor sensors. Our new metrics are being validated over a real data-set coming from a wide LoRaWAN-based noise sensor deployment in a urban area.

2018

Coordination model with reinforcement learning for ensuring reliable on-demand services in collective adaptive systems
Conférence ArODES

Houssem Ben Mahfoudh, Giovanna Di Marzo Serugendo, Anthony Boulmier, Nabil Abdennadher

Lecture Notes in Computer Science ; Proceedings of International Symposium on Leveraging Applications of Formal Methods (ISoLA 2018), 5-9 November 2018, Limassol, Cyprus

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Résumé:

Context-aware and pervasive systems are growing in the market segments. This is due to the expansion of Internet of things (IoT) devices. Current solutions rely on centralized services provided by servers gathering all requests and performing pre-defined computations involving pre-defined devices. Large-scale IoT scenarios, involving adaptation and unanticipated devices, call for alternative solutions. We propose here a new type of services, built and composed on-demand, arising from the interaction of multiple sensors and devices working together as a decentralized collective adaptive system. Our solution relies on a bio-inspired coordination model providing a communication platform among multi-agent systems working on behalf of these devices. Each device provides few simple services and data regarding its environment. On-demand services derive from the collective interactions among multiple sensors and devices. In this article, we investigate the design and implementation of such services and define a new approach that combines coordination model and reinforcement learning, in order to ensure reliable services and expected quality of services (QoS), namely convergence of composition, of coherent result and convergence of learning. We present an IoT scenario showing the feasibility of the approach and preliminary results.

Solar cadaster as a decision support tool for sustainable energy management in urban areas :
Conférence ArODES
from the state of Geneva to the cross-border agglomeration

Gilles Desthieux, Claudio Carneiro, Reto Camponovo, Peter Galinelli, Nabil Abdennadher, Anthony Boulmier, Eugenio Morello, Phelan Leverington, Alberto Susini, Christelle Anthoine-Bourgeois, David Beni

Proceedings of 20. Status-Seminar "Forschen für den Bau im Kontext von Energie und Umwelt", Zurich, Switzerland, 6-7 September 2018

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Résumé:

The development of solar energy is particular relevant in cities that consume the major part of energy demand. Dense areas limit the incoming sunlight and the deployment of urban solar power plants. Therefore, it is essential to make available tools that model the solar energy accessibility in the urban fabric. Today‘s availability of 3D information about cities offers the possibility for such modelling, involving a whole procedure from data acquisition from Airborne Laser Scanning (ALS), also called Light Detection and Ranging (LiDAR), to the environmental analysis through the image processing of digital urban models. Building roofs, but also potential usable surfaces like car-port or highways roofs and walls are considered for potential energy production. Vertical or building facades, which are particularly interesting for the production of solar energy during the winter months, are becoming more and more promising through the improvement of solar panel efficiency and the innovative concepts of Nearly Zero Energy Buildings (nZEB) and Building Integrated PhotoVoltaics (BiPV) concepts. However, facade modelling for solar analysis is not as explored as for roofs, since it requires much more complex tools based on 3D GIS data. In this framework, the paper introduces a tool for assessing solar radiation and energy production on building rooftops and vertical facades of the inner-city. This integrated tool is based on the use of LiDAR, 2D and 3D cadastral data. The paper first presents the methodological background of the tool, its application in Geneva (solar cadaster available through a Web-based interface customized for the public). Then, it discusses about the opportunities and constraints for making the tool useful for the different stakeholder and practitioners involved in urban, energy and building planning.

Spatial services for decentralised smart green energy management
Conférence ArODES

Houssem Ben Mahfoudh, Giovanna Di Marzo Serugendo, Nabil Abdennadher, Andreas Rumsch, Andres Upegui

Proceedings of 2018 IEEE International Energy Conference (ENERGYCON), 3-7 June 2018, Limassol, Cyprus

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Résumé:

In neighbourhoods, the number of energy generators are growing. A main reason for this being the rise in people's energy needs and the possibility of local energy production. Future scenarios involve people's choices of energy type (mostly green) as well as sharing energy among neighbours. This article investigates the use of spatial services applied to a decentralised green energy management system. Spatial services are a new type of bio-inspired services spreading geographically across dispersed devices. They are agent-based and suitable for dynamically changing scenarios. We prototyped, implemented and deployed an energy management scenario involving a peer to peer innovative energy management system and a self-adaptive system. Preliminary results show the feasibility of the envisaged scenarios. Future work include investigating advanced peer to peer scenarios as well as enhancing current spatial services with reinforcement learning.

Adaptive security in cloud and edge networks :
Conférence ArODES
new iot security approach

Tewfiq El-Maliki, Nabil Abdennadher, Mohamed Nizar Bouchedakh

Proceedings of the 13th International Conference on Systems, ICONS 2018, 22-26 April 2018, Athens, Greece

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Résumé:

Edge and cloud networks have emerged during the rapid evolution of networking in the last years, mainly as part of Internet of Things network. Security has become a key issue for any huge deployment in this network. Moreover, data reliability combined with performance is really a challenging task, particularly to maintain survivability of the network. This paper addresses this task using an Adaptation Security Framework, which is an efficient edge-cloud security deployment capable of trading-off between security and performance. It is based on an autonomic computing security looped system, which fine-tunes security means based on the monitoring of the context. An evaluation of the approach is undergoing in the context of smart city through a simulation tool and real-world large deployment.

2014

Computational fluid dynamics as a tool to predict the air pollution dispersio in a neighborhood :
Conférence ArODES
a research project to improve the quality of life in cities

Gilles Triscone, Nabil Abdennadher, Christophe Balistreri, Olivier Donzé, Davide Greco, Patrick Haas, Hasret Haas-Peköz, Tamer Mohamed-Nour, Pierre Munier, Piero Pontelandolfo, Roberto Putzu, Hervé Sthioul, Nicolas Delley, David Choffat, Elena-Lavinia Niederhäuser, Roger Schaer, Henning Müller, Jean Decaix, Sylvain Richard, Cécile Münch-Alligné, Pierre Kunz, Fabienne Despot

Proceedings of Smart city expo world congress 2014

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Résumé:

In large cities, pollution composed of many different chemical components and small particles is an important public health problem that affects especially children and people presenting breathing difficulties. One challenge for public authorities is to respect the norms given by the central state, but how? Today, concrete methods for reducing pollution are perceived by the majority of citizens as constraints. However, the authorities have the possibility of modifying the wind's action by imposing architectural constraints, such as building emplacement and roof structure. This is the main objective of the Geneva "Clean City" project financed by the University of Applied Sciences Western Switzerland. "Clean City" focuses its research on one of Geneva’s polluted neighborhoods called Pâquis which is situated directly on the Geneva lake front. The project attempts to understand the dispersion of pollution from an experimental and a numerical point of view. After validation of the technique for a simple case, we compare environmental measurements on a 1/500 3D scale model of the Pâquis installed in an instrumented wind tunnel with Computational Fluid Dynamics (CFD) simulation obtained with the help of cloud computing. In Barcelona, we will show the first experimental measurements and simulated “Clean City” results.

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