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433documents trouvés

16468
01/03/2017

Automated and flexible composition based on abstract services for a better adaptation to user intentions

E.FKI, S.TAZI, K.DRIRA

SARA

Revue Scientifique : Future Generation Computer Systems, Vol.68, pp.376-390, Mars 2017 , N° 16468

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Abstract

In recent years, the composition of loosely coupled services with the aim of satisfying the user intention is a widely followed research topic. The composition of services implies the ability to select, coordinate, interact, and interoperate existing services. This is considered as a complex task. This complexity is mainly due to the large number of available services and their heterogeneity as they are created by different organizations. This complexity is increased when services must be dynamically and automatically composed to meet requirements which are not satisfied by existing services. In fact, an approach for service composition must offer the potential to achieve flexible and adaptable applications, by selecting and combining services based of the request and the context of the user. In this perspective, different approaches have been developed for services composition. However, most of the existing composition approaches tend to be static and not flexible in the sense that they do not have the ability to adapt to user requirements. To overcome these challenges, we propose a composition approach in which the generation of the composition schema is performed at runtime through the use of abstract services provided at design time. The composition process that we propose takes as input a structure of user requirements materialized by a graph of intentions and enriches this graph to explicit the implicit relationships. The enriched graph is used to generate an initial composition schema by building the control flow and selecting the appropriate abstract services. The selection of these services is based on the semantic matching and the degree of semantic affinity between abstract services. Then, the final composition schema is generated using a refinement mechanism of abstract services using semantic matching techniques and taking into account user context and constraints.

138480
14418
01/02/2017

On the design of a reward-based incentive mechanism for delay tolerant networks

T.SEREGINA, O.BRUN, R.ELAZOUZI, B.PRABHU

SARA, LIA Avignon

Revue Scientifique : IEEE Transactions on Mobile Computing, Vol.16, N°2, pp.453-465, Février 2017, doi 10.1109/TMC.2016.2546910 , N° 14418

Lien : http://hal.archives-ouvertes.fr/hal-01061348

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Abstract

A central problem in Delay Tolerant Networks (DTNs) is to persuade mobile nodes to participate in relaying messages. Indeed, the delivery of a message incurs a certain number of costs for a relay. We consider a two- hop DTN in which a source node, wanting to get its message across to the destination as fast as possible, promises each relay it meets a reward. This reward is the minimum amount that offsets the expected delivery cost, as estimated by the relay from the information given by the source (number of existing copies of the message, age of these copies). A reward is given only to the relay that is the first one to deliver the message to the destination. We show that under fairly weak assumptions the expected reward the source pays remains the same irrespective of the information it conveys, provided that the type of information does not vary dynamically over time. On the other hand, the source can gain by adapting the information it conveys to a meeting relay. For the particular cases of two relays or exponentially distributed inter-contact times, we give some structural results of the optimal adaptive policy.

138730
17006
31/01/2017

Mixed integer linear programming for quality of service optimization in Clouds

T.GUEROUT

SARA

Rapport LAAS N°17006, Janvier 2017, 15p.

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138712
17007
31/01/2017

ENDEAVOUR: D4.5: Implementation of the Selected Use Cases for the IXP Members

C.DIETZEL, M.ABT, M.CHIESA, P.OWEZARSKI

DE-CIX, UCL, SARA

Rapport de Contrat : H2020-ICT-2014-1 Project No. 644960, Janvier 2017, 16p. , N° 17007

Lien : https://hal.laas.fr/hal-01433130

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Abstract

Over the course of the ENDEAVOUR project the consortium developed a wide range of use cases as potential candidates to be implemented within the ENDEAVOUR prototype. After consolidating the most compelling use cases we implemented them into the ENDEAVOUR platform. To this end, the present deliverable showcases the implemented use cases of the ENDEAV- OUR platform for Internet eXchange Point (IXP) members. Each use case is demonstrated in a video. In addition, Deliverable 4.4 discusses the relevant use cases for IXP operators. In combination, these two deliverables reflect the current state of the ENDEAVOUR platform prototype. We present technical background necessary to understand the implementation of each use case, the high level implementation itself, as well as a workflow of each demonstration.

138714
17012
31/01/2017

ENDEAVOUR:Towards a flexible software-defined network ecosystem: Implementation of the Monitoring Platform

E.FERNANDES, G.BOETTGER, G.ANTICHI, R.LAPEYRADE, P.OWEZARSKI

Univ Quenn Mary, Londres, CAMBRIDGE, SARA

Rapport de Contrat : H2020-ICT-2014-1 Project No. 644960, Janvier 2017, 20p. , N° 17012

Lien : https://hal.laas.fr/hal-01433148

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Abstract

This is the accompanying report of the demonstrator of Work Package 3 for month 24, where the implementation of the ENDEAVOUR monitoring platform is documented. In this report, we briefly discuss the organization of the code development, we then describe the implementation of the ele- ments of the ENDEAVOUR monitoring platform, and finally, present and document the demonstrators.

138728
17010
31/01/2017

Proceedings of the 1st ACM SAC Conference Track on Software-intensive Systems-of-Systems (SiSoS 2017): 32nd ACM SIGAPP Symposium On Applied Computing

F.OQUENDO, K.DRIRA, A.LEGAY, T.BATISTA

Univ Bretagne Sud, SARA, INRIA Rennes, UFRN, Brésil

Ouvrage (éditeur) : Proceedings of the 1st ACM SAC Conference Track on Software-intensive Systems-of-Systems (SiSoS 2017): 32nd ACM SIGAPP Symposium On Applied Computing, Janvier 2017 , N° 17010

Lien : https://hal.archives-ouvertes.fr/hal-01445350

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138723
17001
24/01/2017

Towards an autonomic approach for software defined networks: an overview

S.BOUZGHIBA, H.DAHMOUNI, A.RACHDI, J.M.GARCIA

INPT, Rabat, QoS Design, SARA

Ouvrage (contribution) : Advances in Ubiquitous Networking 2, Springer, N°ISBN 978-981-10-1626-4, Janvier 2017, pp.149-161 , N° 17001

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Abstract

Under the new paradigm Software Defined Networking (SDN), which involves decoupling control plane from data plane, and allowing control planes to be deployed on external servers, our main goal is to propose an overview of architecture that can effectively solve problems of network QoS caused by this separation. The overall objective is to study and evaluate the use of SDN networks as a cornerstone of a communication system that can effectively support distributed applications whose needs change over time. In this paper, we focus, in particular, on the controller placement problem in SDN, optimizing the latency, resilience, reliability, scalability and other network performance. The technical solutions to these problems will be studied to identify the components of SDN that can be improved.

138619
17017
10/01/2017

Plateforme de calcul parallèle "Design for Demise"

B.PLAZOLLES

CDA

Doctorat : Université de Toulouse III - Paul Sabatier, 10 Janvier 2017, 202p., Président: T.GAYRAUD, Rapporteurs: D.DEFOUR, R.MOLINA, Examinateurs: M.BALAT-PICHELIN, P.COCQUEREZ, Directeurs de thèse: D.EL BAZ, M.SPEL , N° 17017

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138893
16476
15/12/2016

Towards autonomic and cognitive IoT systems, application to patients’ treatments management

E.MEZGHANI

SARA

Doctorat : INSA de Toulouse, 15 Décembre 2016, 181p., Président: M.MOSBAH, Rapporteurs: M.LAMOLLE, M.MRISSA, Examinateurs: M.DA SILVEIRA, W.GAALOUL, C.PRUSKI, Directeurs de thèse: K.DRIRA, E.EXPOSITO , N° 16476

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Résumé

La prolifération des objets connectés ainsi que le développement du web et des applications mobiles contribuent à la numérisation de l'univers. Par ailleurs, l’adoption des objets connectés favorise la collecte en temps réel des données du monde physique, ce qui offre des nouvelles opportunités pour les entreprises à prendre des décisions plus précises au bon moment. Par contre, l’intégration des objets connectés engendre un ensemble de défis liés à la complexité des systèmes connectés, à la gestion des big data, ainsi qu’à leur hétérogénéité. Pour gérer la complexité de conception, nous proposons d'automatiser la gestion des systèmes connectés en se basant sur l’informatique autonomique. Cependant, l'informatique autonomique seule ne suffit pas pour le développement des systèmes intelligents permettant de générer les décisions. Par conséquent, nous proposons une méthodologie collaborative pour la conception des systèmes autonomique cognitive intégrant des objets connectés. Cette méthodologie englobe un ensemble de patrons de conception dont nous avons défini pour modéliser la coordination dynamique des processus autonomiques pour gérer l’évolution des besoins du système, et pour enrichir les systèmes avec des propriétés cognitives qui permettent de comprendre les données et de générer des nouvelles connaissances. Notre objectif consiste à aider l'architecte à choisir le patron ou la combinaison des patrons pour concevoir une architecture flexible capable de répondre aux besoins complexes du système. De plus, pour gérer les problèmes liés à la gestion des big data et à la scalabilité du système, nous proposons une plate-forme sémantique supportant le traitement des grandes quantités de données afin d’intégrer des sources de données distribuées et hétérogènes déployées sur le cloud pour générer des connaissances qui seront exposées en tant que service (KaaS). L'architecture proposée étend les architectures de référence proposées par le NIST, décrivant le big data et cloud, avec un modèle sémantique qui permet aux machines de comprendre les données reçues, les préparer et les harmoniser pour une meilleure analyse et visualisation. Plus précisément, nous avons instancié notre KaaS dans le domaine médical pour la gestion de l’évolution de l’état du patient et la détection des anomalies personnalisées au bon moment. Ainsi, nous avons élaboré le Wearable Healthcare Ontology (WH_O) décrivant les caractéristiques des dispositifs utilisés pour mesurer les signes vitaux du patient. En se basant sur des technologies de big data, nous avons proposé une implémentation du KaaS adoptant une combinaison des patrons de conception proposés pour le développement des systèmes intelligents. Nous avons également évalué la performance de la plate-forme sur le cloud en termes de temps de réponse et de scalabilité. Finalement, pour développer des systèmes intelligents, nous proposons d'enrichir notre KaaS avec des nouvelles fonctionnalités cognitives représentant la connaissance médicale et le processus de personnalisation pour automatiser la prise de décision. Ainsi, une méthode pour extraire et formaliser les connaissances médicales en collaborant avec des experts est proposée. L’application de cette méthodologie génère un modèle sémantique flexible nommé Treatment Plan Ontology (TPO) qui décrit les interventions médicales et les règles de décision pour le traitement d’une maladie chronique. Ainsi, nous avons proposé un algorithme de planification qui intègre TPO avec DrugBank afin de fournir des décisions personnalisées par rapport au profil du patient. Nous avons évalué l’algorithme de planification et la flexibilité de TPO en simulant des cas cliniques réels et en comparant les recommandations générées à ce que les experts déclarent. En variant la configuration des ressources allouées (CPU et mémoire), nous avons évalué la performance du système sur le cloud et fourni des recommandations selon les besoins du système.

Abstract

Nowadays, the adoption of the Internet of Things (IoT) drastically witnesses an increase in different domains, and contributes to the fast digitalization of the universe. Henceforth, next generation of IoT-based systems are set to become more complex to design and manage. Collecting real-time IoT generated data unleashes a new wave of opportunities for business to take more precise and accurate decisions at the right time. Nonetheless, a set of challenges including the complexity of IoT-based systems and the management of the ensuing big and heterogeneous data as well as the system scalability; need to be addressed for the development of flexible smart IoT-based systems that drive the business decision-making. With respect to challenge which relates to the complexity of IoT management, we propose to automate the management of IoT-based systems based on an autonomic computing approach. However, autonomic computing alone is not enough for the development of smart IoT-based systems. Indeed, these systems should implement cognitive capabilities that allow them learning and generating decisions at the right time. Consequently, we propose a model-driven methodology for designing smart IoT-based systems. We defined within this methodology a set of autonomic cognitive design patterns that aim at (1) delineating the dynamic coordination of the management processes to deal with the system’s context changeability and requirements evolution at run-time, and (2) adding cognitive abilities to IoT-based systems to understand big data and interact with human through generating new insights. Our ultimate goal was to assist the architect when designing flexible smart IoT-based systems by selecting the right pattern or combination of patterns to solve complex requirements. With respect to challenges which relate to big data and scalability management, we propose a generic semantic big data platform that integrates heterogeneous distributed data sources deployed on the cloud, and generates knowledge that will be exposed as a service (Knowledge as a Service–KaaS). The proposed architecture represents an extension of the NIST Big Data and Cloud Computing reference architectures with a semantic layer that enables the machines collecting and interpreting the received data, curating and harmonizing it for better analytic and visualization. More specifically, we are interested in healthcare as an applicative domain. Thus, based on big data tools for data stream processing, we proposed a cognitive monitoring system implementing a combination of the proposed patterns for managing the patient health based on wearables and promptly detecting personalized anomalies. Hence, we elaborated the Wearable Healthcare Ontology (WH_O) for the integration of heterogeneous wearable data. The proposed system is deployed within the KaaS, and its performance (in terms of response time and scalability) when processing huge amount of heterogeneous data streams has been evaluated following different KaaS configurations. Finally, to provide smart IoT-based systems able to reason and generate recommendations, we enriched the proposed system with new cognitive mechanisms including the medical procedural knowledge and the personalization process. Thus, a methodology for extracting and formalizing the medical knowledge based on the collaboration of medical experts is proposed. The output of this methodology is a flexible semantic model named Treatment Plan Ontology (TPO) that describes the medical interventions. We also defined an Ontology-based planning algorithm that integrates TPO with external existing knowledge sources in order to provide personalized decisions concerning the patient treatment. We evaluated the proposed algorithm through simulating real clinical use cases and comparing the generated recommendations to the experts’ advice. We highlighted also the system performance on the cloud, and provided recommendations for selecting the appropriate IT configuration based on the system requirements.

Mots-Clés / Keywords
Big data; Gestion des systèmes médicaux; Informatique autonomique; Informatique cognitive; Système guidé par ontologie; Web sémantique;

138573
16500
01/12/2016

Proceedings of the European Colloquium on Software-intensive Systems-of-Systems (ECSoS 2016)

F.OQUENDO, M.A.BABAR, K.DRIRA, A.LEGAY

Univ Bretagne Sud, Adelaide, SARA, INRIA Rennes

Ouvrage (éditeur) : Proceedings of the European Colloquium on Software-intensive Systems-of-Systems (ECSoS 2016), Décembre 2016 , N° 16500

Lien : https://hal.archives-ouvertes.fr/hal-01445339

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138725
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