Modelling Feedback Control Loops for Self-Adaptive Systems

Feedback Control Loops (FCLs) are the heart of any self-adaptive sys- tem. Existing engineering approaches for building self-adaptive systems mask FCL by providing abstraction layers that hide the application complexity. In this paper, we investigate a model-driven approach for the engineering of FCLs whose archi- tecture is based on the Service Component Architecture (SCA) model. Our proposal consists in exploiting the data streaming model, to specify the characteristics of the control policies, and to generate FCLs of self-adaptive systems deployed in large- scale environment. We argue that the use of a data-oriented model for designing self-adaptive systems significantly increases FCL visibility

Requirements of the SALTY project

This document is the first external deliverable of the SALTY project (Self-Adaptive very Large disTributed sYstems), funded by the ANR under contract ANR-09-SEGI-012. It is the result of task 1.1 of the Work Package (WP) 1 : Requirements and Architecture. Its objective is to identify and collect requirements from use cases that are going to be developed in WP 4 (Use cases and Validation). Based on the study and classification of the use cases, requirements against the envisaged framework are then determined and organized in features. These features will aim at guide and control the advances in all work packages of the project. As a start, features are classified, briefly described and related scenarios in the defined use cases are pinpointed. In the following tasks and deliverables, these features will facilitate design by assigning priorities to them and defining success criteria at a finer grain as the project progresses. This report, as the first external document, has no dependency to any other external documents and serves as a reference to future external documents. As it has been built from the use cases studies that have been synthesized in two internal documents of the project, extracts from the two documents are made available as appendices (cf. appen- dices B and C)

Support intergiciel pour l'auto-adaptation stable dans les environnements ubiquitaires / A Framework for supporting a stable self-adaptation in ubiquitous environment

National audienceUbiquitous applications are characterized by fluctations of their execution context. Therefore, in order to behave accordingly to their context changes, context-aware system should adapt continously. The main concerns of this work is to handle stable self-adaptation problem for context-aware system. Modeling and processing of context information, are the cornerstone of any ubiquitous application. Exploitation of context information in a ubiquitous computing environment, remains a sensitive task because the context keeps evolving. In particular, existing approaches to self-adaptation systematically trigger recon gurations whenever the surrounding context changes, thus leading to a continuous instability of the system. Although some state-of-the-art middleware approaches de ne context regions to reduce this side-effect, context regions provide strict partitions of the context space, thus solving partially the problem. We believe that the solution of that problem lies on a smart composition of stabilizing algorithms. We suggest a composition model, to both manage the reactivity of stabilization mechanisms in a flexible manner, and improve the effectiveness of the stabilization. We also propose a conceptual architecture that supports our composition model and that guides the developer to the choice of the optimal pattern of composition. Finally, we validate our proposal with an evaluation based on a components based framework for the management of context information COSMOS (Context Entities Composition and Sharing).Les applications ubiquitaires sont caractérisées par la variation de leur contexte d'exécution. Le fonctionnement adéquat de telles applications requiert des adaptations continues sur la base des observations du contexte environnant. Ce mémoire adresse la problématique de la stabilisation des adaptations pour les systèmes sensibles au contexte. La modélisation et le traitement des informations de contexte, sont la pierre angulaire de toute application ubiquitaire. L'exploitation des informations de contexte dans un environnement ubiquitaire demeure une tâche sensible d'autant plus que, le contexte d'exécution évolue continuellement. En particulier, les approches existantes pour l'auto adaptation entraînent le déclenchement systématique de la reconfiguration du système chaque fois que le contexte environnant change, conduisant ainsi a une instabilité de ce dernier. Bien que dans l'état de l'art, il existe des approches logicielles qui suggèrent l'utilisation des régions de contexte pour juguler cet effet collatéral, cette technique qui suppose un partitionnement stricte de l'espace du contexte ne résout que partiellement le problème. Nous pensons que la solution à ce problème, réside dans la composition intelligente des algorithmes de stabilisation. Nous proposons un modèle de composition pour à la fois gérer de façon flexible, la réactivité des mécanismes de stabilisation, et améliorer l'efficacité du processus de stabilisation. Nous proposons également, une architecture conceptuelle sur laquelle s'appuie notre modèle de composition et qui permet d'orienter le développeur vers un choix optimal du patron de composition. Enfin, nous validons notre proposition par une évaluation basée sur un canevas logiciel à base de composants pour la gestion des informations de contexte COSMOS (Context Entities Composition and Sharing)

Construction flexible des boucles de contrôles autonomes pour les applications à large échelle

Modern software systems are getting more complex. This is partly justified by the heterogeneity of technologies embedded to deliver services to the end client, the large-scale distribution of software pieces that intervene within a single application, or the requirements for adaptive software systems. In addition, the need for reducing the maintenance costs of software systems has led to the emergence of new paradigms to cope with the complexity of these software. Autonomic computing is a relatively new paradigm for building software systems which aims at reducing the maintenance cost of software by building autonomic software systems which are able to manage themselves with a minimal intervention of a human operator. However, building autonomic software raises many scientific and technological challenges. For example, the lack of visibility of the control system architecture in autonomic systems makes them difficult to maintain. Similarly, the lack of verification tools is a limitation for building reliable autonomic systems. The flexible management of non-functional-properties, or the traceability between the design and the implementation are other challenges that need to be addressed for building flexible autonomic systems. The main contribution of this thesis is CORONA. CORONA is a framework which aims at helping software engineers for building flexible autonomic systems. To achieve that goal, CORONA relies on an architectural description language which reifies the structure of the control system architecture. CORONA enables the flexible integration of non-functional-properties during the design of autonomic systems. It also provides tools for conflicts checking in autonomic systems architecture. Finally, the traceability between the design and the runtime implementation is carried out through the code generation of skeletons from architectural descriptions of control systems. These properties of the CORONA framework are exemplified through three case-studies.Les logiciels modernes sont de plus en plus complexes. Ceci est dû en partie à l'hétérogénéité des solutions misent en oeuvre, au caractère distribué des architectures de déploiement et à la dynamicité requise pour de tels logiciels qui devraient être capable de s'adapter en fonction des variations de leur contexte d'évolution. D'un autre coté, l'importance grandissante des contraintes de productivité dans le but de réduire les coûts de maintenance et de production des systèmes informatiques a favorisé l'émergence de nouveaux paradigmes pour répondre à la complexité des logiciels modernes. L'informatique des systèmes autonomes (Autonomic computing) s'inscrit dans cette perspective. Elle se propose entre autres de réduire le coût de maintenance des systèmes informatiques en développant des logiciels dits autonomes, c'est à dire dotés de la capacité de s'auto-gérer moyennant une intervention limité d'un opérateur humain. Toutefois, le développement de logiciels autonomes soulèvent de nombreux défis scientifiques et technologiques. Par exemple, l'absence de visibilité de la couche de contrôle dans les applications autonomes rend difficile leur maintenabilité, l'absence d'outils de vérification pour les architectures autonomes est un frein pour l'implémentation d'applications fiables, enfin, la gestion transparente des propriétés non-fonctionnelles et la traçabilité entre le design et l'implémentation sont autant de défis que pose la construction de logiciels autonomes flexibles. La principale contribution de cette thèse est CORONA. CORONA est un canevas logiciel qui vise à faciliter le développement de logiciels autonomes flexibles. Dans cet objectif, CORONA s'appuie sur un langage de description architecturale qui réifie les éléments qui forment la couche de contrôle dans les systèmes autonomes. CORONA permet l'intégration transparente des propriétés non-fonctionnelles dans la description architecturale des systèmes autonomes. il fournit aussi dans sa chaîne de compilation un ensemble d'outils qui permet d'effectuer des vérifications sur l'architecture des systèmes autonomes. Enfin, la traçabilité entre le design et l'implémentation est assurée par un mécanisme de génération des skeletons d'implémentation à partir d'une description architecturale. Les différentes propriétés de CORONA sont illustrées par trois cas d'utilisation

Context-aware Adaption Mechanisms for Pervasive And Ubiquitous Services - 4th International Workshop, CAMPUS 2011

International audienc

Context-aware Adaption Mechanisms for Pervasive And Ubiquitous Services - 4th International Workshop, CAMPUS 2011

International audienc

Author manuscript, published in "COMOREA- (PERCOM) (2010) 6" A Flexible Context Stabilization Approach for Self-Adaptive Application

Abstract—Pervasive applications are characterized by variations in their context of execution. Their correct behavior requires continuous adaptations, accordingly to changes observed in their environment. Some of the existing approaches tackle this problem by adding stabilization mechanisms on the decision making layer. In most cases it remains costly for applications to trigger decision making procedures, specially when application changes frequency is potentially high. We believe that, to provide more flexible and efficient contextaware applications, stabilization issues should be addressed separately from decision making issues. In this paper, we present a flexible stabilization approach as an elegant solution to that problem. I

Towards a Stable Decision-Making Middleware for Very-Large-Scale Self-Adaptive Systems

With the development of the communication infrastructures, the number of applications collaborating at large scale increases. To maintain, and continue to deliver services of good quality to the end-users, very-large-scale applications continuously adapt themselves, depending on the changes in their surrounding. Stabilization of the system thus becomes a keystone issue in the adaptation process, in order to reduce the system reconfiguration cost. Existing approaches, for the stabilization of very-large-scale systems, provide solutions that are partially efficient. For example, learning-based stabilization algorithms give good results in predicting application behaviors, but still suffer from their weak reactivity. In this paper, we propose an approach of combining different goals-oriented stabilization algorithms, in order to provide sustainable and efficient stabilization for large-scale systems