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Your search keyword '"d'Orazio, Laurent"' showing total 6 results
Start Over Author "d'Orazio, Laurent" Topic [info]computer science [cs]
6 results on '"d'Orazio, Laurent"'

1. HeROfake: Heterogeneous Resources Orchestration in a Serverless Cloud – An Application to Deepfake Detection

Author

Lannurien, Vincent, d'Orazio, Laurent, Barais, Olivier, Bernard, Esther, Weppe, Olivier, Beaulieu, Laurent, Kacete, Amine, Paquelet, Stéphane, Boukhobza, Jalil, Domaine Hypermedia (IRT b<>com) (Hypermedia), Institut de Recherche Technologique b-com (IRT b-com), B<>COM [Cesson Sévigné], Equipe Software/HArdware and unKnown Environment inteRactions (Lab-STICC_SHAKER), Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance (Lab-STICC), École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT), École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne), Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Diversity-centric Software Engineering (DiverSe), Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-LANGAGE ET GÉNIE LOGICIEL (IRISA-D4), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), and Institute of Research and Technology b<>com, dedicated to digital technologies, funded by the French government through the ANR Investment referenced ANR-A0-AIRT-07

Subjects
serverless, allocation, workload characterization, deepfake, energy consumption, heterogeneous resources, GPU, [INFO]Computer Science [cs], scheduling, SLA, FPGA
Abstract

International audience; Serverless is a trending service model for cloud computing. It shifts a lot of the complexity from customers to service providers. However, current serverless platforms mostly consider the provider's infrastructure as homogeneous, as well as the users' requests. This limits possibilities for the provider to leverage heterogeneity in their infrastructure to improve function response time and reduce energy consumption. We propose a heterogeneity-aware serverless orchestrator for private clouds that consists of two components: the autoscaler allocates heterogeneous hardware resources (CPUs, GPUs, FPGAs) for function replicas, while the scheduler maps function executions to these replicas. Our objective is to guarantee function response time, while enabling the provider to reduce resource usage and energy consumption. This work considers a case study for a deepfake detection application relying on CNN inference. We devised a simulation environment that implements our model and a baseline Knative orchestrator, and evaluated both policies with regard to consolidation of tasks, energy consumption and SLA penalties. Experimental results show that our platform yields substantial gains for all those metrics, with an average of 35% less energy consumed for function executions while consolidating tasks on less than 40% of the infrastructure's nodes, and more than 60% less SLA violations.

Published
2023

2. ASSIST: Article eXtraction and statIstical AnalysiS

Author

Fouillé, Justine, Nguyen, Thi Lan Huong, Alix, Baptiste, Becker, Brett, Rochard, Matthieu, de Ribaupierre, Hélène, d'Orazio, Laurent, A Symbolic and Human-centric view of dAta MANagement (SHAMAN), GESTION DES DONNÉES ET DE LA CONNAISSANCE (IRISA-D7), Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), School of Computer Sciences & Informatics [Cardiff], and Cardiff University

Subjects
Data Extraction, Statistical Analysis, Data Analytic, [INFO]Computer Science [cs]
Abstract

International audience; There are fewer female authors than male authors in the field of scientific research. However, there is not yet a system that provides a way to analyze the data that is available, and to backup that claim. This paper illustrates the upgrade of a tool previously made, in order to make it more efficient and add new features. Such new features are the keywords cloud or the new statistical functionality. Sources, references and other information on the article will be displayed for each articles retrieved. Genders of the authors will be determined using a database linking first names to genders, to be able to get accurate statistics on a large number of gathered articles.

Published
2021

3. Cost models for distributed pattern mining in the cloud: application to graph patterns

Author

Aridhi, Sabeur, d'Orazio, Laurent, Maddouri, Mondher, Mephu Nguifo, Engelbert, Dorazio, Laurent, Nguifo, Engelbert Mephu, University of Trento [Trento], Université Blaise Pascal - Clermont-Ferrand 2 (UBP), Université de Tunis El Manar (UTM), and Taibah University

Subjects
[INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB], [INFO]Computer Science [cs]
Abstract

International audience; Recently, distributed pattern mining approaches have become very popular, especially in certain domains such as bioinformatics, chemoinformatics and social networks. In most cases, the distribution of the pattern mining process generates a loss of information in the output results. Reducing this loss may affect the performance of the distributed approach and thus, the monetary cost when using cloud environments. In this context, cost models are needed to help selecting the best parameters of the used approach in order to achieve a better performance especially in the cloud. In this paper, we address the multi-criteria optimization problem of tuning thresholds related to distributed frequent pattern mining in cloud computing environment while optimizing the global monetary cost of storing and querying data in the cloud. To achieve this goal, we design cost models for managing and mining graph data with large scale pattern mining framework over a cloud architecture. We define four objective functions, with respect to the needs of customers. We present an experimental validation of the proposed cost models in the case of distributed subgraph mining in the cloud.

Published
2015

4. Cost models for distributed pattern mining in the cloud: application to graph patterns

Author

Aridhi, Sabeur, D'Orazio, Laurent, Maddouri, Mondher, Mephu Nguifo, Engelbert, dOrazio, Laurent, Nguifo, Engelbert Mephu, University of Trento [Trento], Université Blaise Pascal - Clermont-Ferrand 2 (UBP), Université de Tunis El Manar (UTM), Taibah University, Laboratoire d'Informatique, de Modélisation et d'optimisation des Systèmes (LIMOS), SIGMA Clermont (SIGMA Clermont)-Université d'Auvergne - Clermont-Ferrand I (UdA)-Ecole Nationale Supérieure des Mines de St Etienne-Centre National de la Recherche Scientifique (CNRS)-Université Blaise Pascal - Clermont-Ferrand 2 (UBP), Université Blaise Pascal - Clermont-Ferrand 2 ( UBP ), and Université Tunis El Manar ( UTM )

Subjects
[ INFO.INFO-DB ] Computer Science [cs]/Databases [cs.DB], [ INFO ] Computer Science [cs], [INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB], [INFO]Computer Science [cs]
Abstract

International audience; Recently, distributed pattern mining approaches have become very popular, especially in certain domains such as bioinformatics, chemoinformatics and social networks. In most cases, the distribution of the pattern mining process generates a loss of information in the output results. Reducing this loss may affect the performance of the distributed approach and thus, the monetary cost when using cloud environments. In this context, cost models are needed to help selecting the best parameters of the used approach in order to achieve a better performance especially in the cloud. In this paper, we address the multi-criteria optimization problem of tuning thresholds related to distributed frequent pattern mining in cloud computing environment while optimizing the global monetary cost of storing and querying data in the cloud. To achieve this goal, we design cost models for managing and mining graph data with large scale pattern mining framework over a cloud architecture. We define four objective functions, with respect to the needs of customers. We present an experimental validation of the proposed cost models in the case of distributed subgraph mining in the cloud.

Published
2015

5. Xe journées francophones sur les Entrepôts de Données et l'Analyse en Ligne. EDA'14

Author

Elsa NEGRE, Orazio, Laurent D., Sandro Bimonte, Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision (LAMSADE), Université Paris Dauphine-PSL, and Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)

Subjects
[INFO]Computer Science [cs], Modélisation mathématique, ComputingMilieux_MISCELLANEOUS, Informatique décisionnelle
Abstract

National audience

Published
2014

6. Towards Data-and-Innovation Driven Sustainable and Productive Agriculture: BIO-AGRI-WATCH as a Use Case Study

Author

Asanee Kawtrakul, Hutchatai Chanlekha, Kitsana Waiyamai, Thanapat Kangkachit, Laurent d'Orazio, Dimitris Kotzinos, Dominique Laurent, Nicolas Spyratos, d'Orazio, Laurent, Kasetsart University (KU), Dhurakij Pundit University [Bangkok] (DPU), A Symbolic and Human-centric view of dAta MANagement (SHAMAN), GESTION DES DONNÉES ET DE LA CONNAISSANCE (IRISA-D7), Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Equipes Traitement de l'Information et Systèmes (ETIS - UMR 8051), Ecole Nationale Supérieure de l'Electronique et de ses Applications (ENSEA)-Centre National de la Recherche Scientifique (CNRS)-CY Cergy Paris Université (CY), and Université Paris-Sud - Paris 11 (UP11)

Subjects
[INFO]Computer Science [cs], [INFO] Computer Science [cs], ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2021

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