Titre :

Toward Run-time Coordination of Reconfiguration Requests in Cloud Computing Systems

Auteur(s) :

Farhat, Salman [Auteur]
Self-adaptation for distributed services and large software systems [SPIRALS]
Université de Lille
Bliudze, Simon [Auteur]
Self-adaptation for distributed services and large software systems [SPIRALS]
Université de Lille
Duchien, Laurence [Auteur]
Self-adaptation for distributed services and large software systems [SPIRALS]
Université de Lille
Kouchnarenko, Olga [Auteur]
Franche-Comté Électronique Mécanique, Thermique et Optique - Sciences et Technologies (UMR 6174) [FEMTO-ST]

Éditeur(s) ou directeur(s) scientifique(s) :

Sung-Shik Jongmans

Titre de la manifestation scientifique :

COORDINATION 2023 - 25th International Conference on Coordination Models and Languages

Ville :

Lisbon

Pays :

Portugal

Date de début de la manifestation scientifique :

2023-06-19

Éditeur :

Springer Nature Switzerland

Date de publication :

2023-04-22

Mot(s)-clé(s) en anglais :

Concurrent Component-based Systems
Variability Models
Self-Configuration
Dynamic Reconfiguration

Discipline(s) HAL :

Informatique [cs]/Génie logiciel [cs.SE]

Résumé en anglais : [en]

Cloud applications and cyber-physical systems are becoming increasingly complex, requiring frequent reconfiguration to adapt to changing needs and requirements. Existing approaches compute new valid configurations either ...
Lire la suite >Cloud applications and cyber-physical systems are becoming increasingly complex, requiring frequent reconfiguration to adapt to changing needs and requirements. Existing approaches compute new valid configurations either at design time, at runtime, or both. However, these approaches can lead to significant computational or validation overheads for each reconfiguration step. We propose a component-based approach that avoids computational and validation overheads using a representation of the set of valid configurations as a variability model. More precisely, our approach leverages feature models to automatically generate, in a component-based formalism called JavaBIP, run-time variability models that respect the feature model constraints. Produced run-time variability models enable control over application reconfiguration by executing reconfiguration requests in such a manner as to ensure the (partial) validity of all reachable configurations. We evaluate our approach on a simple web application deployed on the Heroku cloud platform. Experimental results show that the overheads induced by generated run-time models on systems involving up to 300 features are negligible, demonstrating the practical interest of our approach.Lire moins >

Langue :

Anglais

Comité de lecture :

Oui

Audience :

Internationale

Vulgarisation :

Non

Projet ANR :

ULNE
Ingénierie et Innovation par les sciences physiques, les savoir-faire technologiques et l'interdisciplinarité

Commentaire :

Part 6: Run-Time Changes

Collections :

• Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189

Source :

Harvested from HAL