{"id":925,"date":"2017-09-21T14:13:24","date_gmt":"2017-09-21T12:13:24","guid":{"rendered":"https:\/\/samovar2022.int-evry.fr\/index.php\/2017\/09\/21\/supporter-lallocation-des-ressources-cloud-dans-les-processus-metiers-configurables\/"},"modified":"2020-09-04T18:46:08","modified_gmt":"2020-09-04T16:46:08","slug":"supporter-lallocation-des-ressources-cloud-dans-les-processus-metiers-configurables","status":"publish","type":"post","link":"https:\/\/samovar.telecom-sudparis.eu\/index.php\/2017\/09\/21\/supporter-lallocation-des-ressources-cloud-dans-les-processus-metiers-configurables\/","title":{"rendered":"\u00ab Supporter l’Allocation des Ressources Cloud dans les Processus M\u00e9tiers Configurables \u00bb"},"content":{"rendered":"

Soutenance de th\u00e8se de Madame Emna HACHICHA<\/strong>
\nQuand: <\/strong> le vendredi 22 septembre 2017 \u00e0 14h00
\nO\u00f9: <\/strong> A003, \u00e0 T\u00e9l\u00e9com SudParis, 9 rue Charles Fourier 91011 Evry<\/p>\n

Membres du jury :<\/strong><\/p>\n\n\n\n\n\n\n\n\n\n
M. Walid GAALOUL<\/td>\n Professeur, T\u00e9l\u00e9com SudParis, FRANCE – Directeur de th\u00e8se<\/td>\n<\/tr>\n
M. Claude GODART<\/td>\n Professeur, Universit\u00e9 de Lorraine, Polytech Nancy (Ex-ESSTIN), FRANCE – Rapporteur<\/td>\n<\/tr>\n
Mme Salima BENBERNOU<\/td>\n Professeur, Universit\u00e9 Paris Descartes , FRANCE – Rapporteur<\/td>\n<\/tr>\n
Mme Daniela GRIGORI<\/td>\n Professeur, Universit\u00e9 Paris Dauphine, FRANCE – Examinateur<\/td>\n<\/tr>\n
M. Amel MAMMAR<\/td>\n Ma\u00eetre de conf\u00e9rences, T\u00e9l\u00e9com SudParis, FRANCE – Examinateur<\/td>\n<\/tr>\n
M. Nejib BEN HADJ-ALOUANE<\/td>\n Professeur, Universit\u00e9 Tunis El Manar, FRANCE – Examinateur<\/td>\n<\/tr>\n
M. Kais KLAI<\/td>\n Ma\u00eetre de conf\u00e9rences, Universit\u00e9 Paris 13, FRANCE – Examinateur<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

R\u00e9sum\u00e9 :<\/strong><\/p>\n

Les organisations adoptent de plus en plus les Syst\u00e8mes (PAIS) pour g\u00e9rer leurs processus m\u00e9tiers bas\u00e9s sur les services en utilisant les mod\u00e8les de processus appel\u00e9s \u00abmod\u00e8les de processus m\u00e9tiers\u00bb. Motiv\u00e9s par l\u2019adaptation aux exigences commerciales et par la r\u00e9duction des co\u00fbts de maintenance, les organisations externalisent leurs processus dans le Cloud Computing. Selon l’Institut NIST, Cloud Computing est un mod\u00e8le qui permet aux fournisseurs de partager leurs ressources et aux utilisateurs d\u2019y acc\u00e9der de mani\u00e8re pratique et \u00e0 la demande. Dans un tel environnement multi-tenant, l’utilisation de mod\u00e8les de processus configurables permet aux fournisseurs de processus Cloud de fournir un processus personnalisable qui peut \u00eatre configur\u00e9 par diff\u00e9rents tenants en fonction de leurs besoins. Un processus m\u00e9tier peut \u00eatre sp\u00e9cifi\u00e9 par plusieurs perspectives tel que la perspective de flux de contr\u00f4le, la perspective des ressources, etc. Plusieurs approches ont \u00e9t\u00e9 propos\u00e9es au niveau des premi\u00e8res perspectives, notamment le flux de contr\u00f4le. Cependant, la perspective ressource, qui est d’une importance \u00e9gale, \u00e9tait n\u00e9glig\u00e9e et pas explicitement d\u00e9finie. D\u2019un c\u00f4t\u00e9, la gestion de la perspective ressource sp\u00e9cifiquement l\u2019allocation des ressources Cloud est un th\u00e8me d\u2019actualit\u00e9 qui implique plusieurs recherches. La mod\u00e9lisation et la configuration des ressources sont une t\u00e2che sensible n\u00e9cessitant un travail intensif. Malgr\u00e9 l\u2019existence de diff\u00e9rentes approches, elles traitent principalement les ressources humaines plut\u00f4t que des ressources Cloud. D\u2019un autre c\u00f4t\u00e9, malgr\u00e9 le fait que le concept des mod\u00e8les de processus configurables est tr\u00e8s compl\u00e9mentaire au Cloud, la mani\u00e8re dont comment les ressources sont configur\u00e9es et int\u00e9gr\u00e9es est \u00e0 peine manipul\u00e9e. Les approches propos\u00e9es travaillant sur l\u2019extension de la configuration de ressources, ne couvrent pas les propri\u00e9t\u00e9s Cloud notamment l\u2019\u00e9lasticit\u00e9 et le partage. Pour r\u00e9pondre \u00e0 ces lacunes, nous proposons une approche pour supporter la mod\u00e9lisation et la configuration de l\u2019allocation des ressources Cloud dans les mod\u00e8les de processus configurables. Nous visons \u00e0 (1) d\u00e9finir une description unifi\u00e9e et formelle pour la perspective ressource, (2) assurer une allocation de ressource correcte, sans conflits et optimis\u00e9e, (3) Aider les fournisseurs de processus \u00e0 concevoir leur allocation de ressources configurable de mani\u00e8re fine afin d’\u00e9viter des r\u00e9sultats complexes et importants, et (4) Optimiser la s\u00e9lection des ressources Cloud par rapport aux exigences li\u00e9es aux propri\u00e9t\u00e9s Cloud (\u00e9lasticit\u00e9 et partage) et propri\u00e9t\u00e9s QoS. Pour ce faire, nous proposons d’abord un cadre s\u00e9mantique pour une description de ressources s\u00e9mantiquement enrichies dans les processus m\u00e9tiers visant \u00e0 formaliser les ressources Cloud consomm\u00e9es \u00e0 l’aide d’une base de connaissances partag\u00e9e. Ensuite, nous nous basons sur les processus m\u00e9tiers sociales pour fournir des strat\u00e9gies afin d’assurer une allocation de ressources contr\u00f4l\u00e9e sans conflits en termes de ressources. Par la suite, nous proposons une nouvelle approche qui \u00e9tend les mod\u00e8les de processus configurables pour permettre une allocation de ressources Cloud configurable. Notre objectif est de d\u00e9placer l’allocation de ressources Cloud du c\u00f4t\u00e9 des tenants vers le c\u00f4t\u00e9 du fournisseur de processus Cloud pour une gestion centralis\u00e9e des ressources. Apr\u00e8s, nous proposons des approches g\u00e9n\u00e9tiques qui visent \u00e0 choisir une configuration optimale des ressources d’une mani\u00e8re efficace sur le plan \u00e9nerg\u00e9tique en am\u00e9liorant les propri\u00e9t\u00e9s QoS. Afin de montrer l’efficacit\u00e9 de nos propositions, nous avons d\u00e9velopp\u00e9 concr\u00e8tement (1) une s\u00e9rie de preuves de concepts, en tant que partie de validation, pour aider \u00e0 concevoir des mod\u00e8les de processus et remplir une base de connaissances de mod\u00e8les de processus h\u00e9t\u00e9rog\u00e8nes avec des ressources Cloud et (2) ont effectu\u00e9 des exp\u00e9riences sur des mod\u00e8les de processus r\u00e9els \u00e0 partir de grands ensembles de donn\u00e9es.<\/p>\n

Abstract :<\/strong><\/p>\n

Organizations are recently more and more adopting Process-Aware Information Systems (PAIS) for managing their service-based processes using process models referred to as business process models. Motivated by adapting to the rapid changing business requirements and reducing maintenance costs, organizations are outsourcing their processes in an important infrastructure which is Cloud Computing. According to the NIST Institute, Cloud Computing is a model that enables providers sharing their computing resources (e.g., networks, applications, and storage) and users accessing them in convenient and on-demand way with a minimal management effort. In such a multi-tenant environment, using configurable process models allows a Cloud process provider to deliver a customizable process that can be configured by different tenants according to their needs. A business process could be specified from various perspectives such as the control-flow perspective, the organizational perspective, the resource perspective, etc. Several approaches have been correctly proposed at the level of the first perspectives, in particular the control-flow, i.e., the temporal ordering of the process activities. Nevertheless, the resource perspective, which is of equal importance, has been neglected and poorly operated. The management of the resource perspective especially the Cloud resource allocation in business processes is a current interesting topic that increasingly involves many researches in both academics and industry. The design and configuration of resources are undoubtedly sensitive and labor-intensive task. On the one hand, the resource perspective in process models is not explicitly defined. Although many proposals exist in the literature, they all targeted human resources rather than Cloud resources. On the other hand, despite of the fact that the concept of configurable process models is highly complementary to Cloud Computing, the way in how resources can be configured and integrated is hardly handled. The few proposals, which have been suggested on extending configuration to resources, do not cover required Cloud properties such as elasticity or multi-tenancy. To address these limitations, we propose an approach for supporting the design and configuration of Cloud resource Allocation in configurable business process models. We target to (1) define a unified and formal description for the resource perspective, (2) ensure a correct, free-of-conflict and optimized use of Cloud resource consumption, (3) assist process providers to design their configurable resource allocation in a fine-grained way to avoid complex and large results, and (4) optimize the selection of Cloud resources with respect to the requirements related to Cloud properties (elasticity and shareability) and QoS properties. To do so, we first suggest a semantic framework for a semantically-enriched resource description in business processes aiming at formalizing the consumed Cloud resources using a shared knowledge base. Then, we build upon social business processes to provide strategies in order to ensure a controlled resource allocation without conflicts in terms of resources. Next, we propose a novel approach that extends configurable process models to permit a configurable Cloud resource allocation. Our purpose is to shift the Cloud resource allocation from the tenant side to the Cloud process provider side for a centralized resource management. Afterwards, we propose genetic-based approaches that aim at selecting optimal resource configuration in an energy efficient manner and to improve non-functional properties. In order to show the effectiveness of our proposals, we concretely developed (i) a set of proof of concepts, as a validation part, to assist the design of process models and populate a knowledge base of heterogeneous process models with Cloud resources, and (ii) performed experiments on real process models from large datasets.<\/p>\n","protected":false},"excerpt":{"rendered":"

Soutenance de th\u00e8se de Madame Emna HACHICHA Quand: le vendredi 22 septembre 2017 \u00e0 14h00 O\u00f9: A003, \u00e0 T\u00e9l\u00e9com SudParis, 9 rue Charles Fourier 91011 Evry Membres du jury : M. Walid GAALOUL Professeur, T\u00e9l\u00e9com SudParis, FRANCE – Directeur de th\u00e8se M. Claude GODART Professeur, Universit\u00e9 de Lorraine, Polytech Nancy (Ex-ESSTIN), FRANCE – Rapporteur Mme 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