Disruption-Tolerant Networks (DTN) allow communication between devices that lack end-to-end connectivity. Even though the mobility of devices in a DTN is frequently dynamic, most proposed DTN protocols are not adaptive. This work presents an ongoing research project that aims to find out to which extent context-based adaptation may be useful to improve DTN performance. We are convinced that, in highly predictive networks, metadata exchange is a crucial factor in supporting routing decisions and recognize context changes. This paper summarizes the efforts we have made so far and presents the next steps we plan to take towards the design and implementation of an adaptive framework.

Routing in Disruption-Tolerant Networks has been researched for over 15 years. Several proposed algorithms exploit the predictive behavior of mobile devices in order to maximize a desired metric (e.g., delivery probability) and minimize waste of resources. However, even devices that follow a highly predictive mobility model might have its behavior temporarily altered due to external events such as accidents, natural conditions, mechanical failures, etc. Some routing approaches for predictive networks are not able to make use of the available knowledge to support the routing decision. Others are not able to adapt under context change. In this work, we present the initial phase of our research and the necessary steps towards an adaptive DTN protocol for challenging networks that is able to exploit available knowledge and adapt under context changes.:I. Introduction II. Challenging Networks III. Challenges Towards an Adaptive Framework IV. Framework Design and Implementation V. Conclusion

Orientador: Frank José Affonso / Resumo: O cenário atual de desenvolvimento de software tem revelado um uso crescente de aplicações baseadas em serviços. Em um ambiente de computação distribuída, monitorar a qualidade de serviços para que essa aplicação não apresente algum tipo de anomalia ou interrupção pode ser considerada uma tarefa vital. Para isso, é necessário prover meios para o desenvolvimento de sistemas baseados em serviços capazes de observar seu estado interno de execução e/ou contexto ao qual estão inseridos e reagir diante de mudanças ou algum tipo de imprevisibilidade. Aplicações orientadas a serviços que permitem adaptação em tempo de execução podem ser classificadas como Self-Apps (do inglês, Self-adaptive Service-oriented Applications). Em função da complexidade intrínseca a esse tipo de aplicação, o uso de frameworks tem se mostrado uma alternativa viável por aliviar a carga cognitiva de desenvolvimento, a qual envolve o conhecimento de diversas áreas de pesquisa. Motivado por esse cenário, durante a realização deste trabalho foi conduzida uma revisão da literatura que engloba a condução de um mapeamento sistemático e consultas complementares em bases nacionais de teses e dissertações. Essa revisão permitiu obter um panorama detalhado referente ao estágio atual da pesquisa, seus desafios e as perspectivas futuras sobre frameworks para Self-Apps. Embasado nos resultados dessa revisão, o objetivo deste trabalho é o desenvolvimento do framework DynaMS (do inglês, Dynamic Deployment, QoS Metrics and S... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: The current software development scenario has shown a crescent usage of service-based applications. In a distributed computing environment, the monitoring of the service’s quality is a relevant task because aims to assure that it does not present any anomaly or interruption. To do so, it is necessary to provide means to develop service-based systems that are capable to observe their internal execution state and/or the context in which they are inserted and to react in face of changes or unforeseen circumstances. Service-oriented applications that are able to perform adaptation in runtime can be classified as Self-Apps (i.e., Self-adaptive Service-oriented Applications). Given the complexity involved in this type of application, the use of frameworks has been shown as a viable alternative to reduce the cognitive development load regarding the knowledge from different research areas. Motivated by this scenario, we conducted a literature review as a part of this work. This review includes a systematic mapping and complementary searches to national thesis and dissertations’ databases. This review provided us a detailed panorama about the current stage of research, its challenges and the future perspectives regarding frameworks for Self-Apps. Based on the results from this review, the purpose of this Master’s project is to present a framework called DynaMS (Dynamic Deployment, QoS Metrics and Semantic Search) to support the development of this type of application. In short, this f... (Complete abstract click electronic access below) / Mestre

Systematic Literature Reviews (SLR) are a powerful research tool to identify and select literature to answer a certain question. However, an approach to extract inherent analytical data in Systematic Literature Reviews’ multi-dimensional datasets was lacking. Previous Systematic Literature Review tools do not incorporate the capability of providing said analytical insight. Therefore, this thesis aims to provide a useful approach comprehending various algorithms and data treatment techniques to provide the user with analytical insight on their data that is not evident in the bare execution of a Systematic Literature Review. For this goal, a literature review has been conducted to find the most relevant techniques to extract data from multi-dimensional data sets and the aforementioned approach has been tested on a survey regarding Self-Adaptive Systems (SAS) using a web-application. As a result, we find out what are the most adequate techniques to incorporate into the approach this thesis will provide.

Le concept de pair à pair (P2P) a connu récemment de grands développements dans les domaines du partage de fichiers, du streaming vidéo et des bases de données distribuées. Le développement du concept de parallélisme dans les architectures de microprocesseurs et les avancées en matière de réseaux à haut débit permettent d'envisager de nouvelles applications telles que le calcul intensif distribué. Cependant, la mise en oeuvre de ce nouveau type d'application sur des réseaux P2P pose de nombreux défis comme l'hétérogénéité des machines, le passage à l'échelle et la robustesse. Par ailleurs, les protocoles de transport existants comme TCP et UDP ne sont pas bien adaptés à ce nouveau type d'application. Ce mémoire de thèse a pour objectif de présenter un environnement décentralisé pour la mise en oeuvre de calculs intensifs sur des réseaux pair à pair. Nous nous intéressons à des applications dans les domaines de la simulation numérique et de l'optimisation qui font appel à des modèles de type parallélisme de tâches et qui sont résolues au moyen d'algorithmes itératifs distribués or parallèles. Contrairement aux solutions existantes, notre environnement permet des communications directes et fréquentes entre les pairs. L'environnement est conçu à partir d'un protocole de communication auto-adaptatif qui peut se reconfigurer en adoptant le mode de communication le plus approprié entre les pairs en fonction de choix algorithmiques relevant de la couche application ou d'éléments de contexte comme la topologie au niveau de la couche réseau. Nous présentons et analysons des résultats expérimentaux obtenus sur diverses plateformes comme GRID'5000 et PlanetLab pour le problème de l'obstacle et des problèmes non linéaires de flots dans les réseaux. / The concept of peer-to-peer (P2P) has known great developments these years in the domains of file sharing, video streaming or distributed databases. Recent advances in microprocessors architecture and networks permit one to consider new applications like distributed high performance computing. However, the implementation of this new type of application on P2P networks gives raise to numerous challenges like heterogeneity, scalability and robustness. In addition, existing transport protocols like TCP and UDP are not well suited to this new type of application. This thesis aims at designing a decentralized and robust environment for the implementation of high performance computing applications on peer-to-peer networks. We are interested in applications in the domains of numerical simulation and optimization that rely on tasks parallel models and that are solved via parallel or distributed iterative algorithms. Unlike existing solutions, our environment allows frequent direct communications between peers. The environment is based on a self adaptive communication protocol that can reconfigure itself dynamically by choosing the most appropriate communication mode between any peers according to decisions concerning algorithmic choice made at the application level or elements of context at transport level, like topology. We present and analyze computational results obtained on several testeds like GRID’5000 and PlanetLab for the obstacle problem and nonlinear network flow problems.

Malgré des avantages certains en terme d'adaptabilité et en gain de surface, la reconfiguration dynamique sur FPGA a du mal à être utilisée dans l'industrie. Le manque de moyens et de méthodes d'évaluation d'une telle architecture en est la cause majeure. Pire, aucun outil officiel ne permet aux développeurs de déterminer facilement un ordonnancement de la reconfiguration adapté pour une architecture donnée. Cette thèse s'inscrit dans ce contexte et propose une méthodologie de modélisation SystemC d'architectures reconfigurables dynamiquement. Cet outil d'aide à la conception permet de faire gagner un temps considérable lors de la phase de conception en fournissant une première estimation des performances et des ressources nécessaires au développement de l'architecture. Il permet également le développement et la validation de scénarios d'ordonnancement de la reconfiguration, tout en respectant les contraintes temps réel liées à l'application. Afin de valider notre modèle sur une application réelle, des IP de transcodage vidéo ont été développées et seront détaillées. Cette application consiste en la réalisation d'un transcodeur H.264/MPEG-2, rendu auto-adaptable grâce à l'utilisation de la reconfiguration dynamique. Ces travaux ont été menés dans le cadre du projet ARDMAHN financé par l'Agence Nationale de la Recherche portant la référence ANR-09-SEGI-001 / Despite clear benefits in terms of fexibility and surface efficiency, dynamic reconfiguration of FPGAs is still finding it hard to break through into massive industrial project. One of the main reasons is the lack of means and methods for evaluation of reconfigurable architectures. Worse, main FPGA vendors do not provide official tools allowing developers to easily determine an optimal scheduling reconfiguration for a specific architecture. Within this framework, the proposed research work described in this thesis proposes a methodology for modeling dynamically reconfigurable architectures based on SystemC. The proposed methodology allows designers to save significant time during the design phases of an application specific reconfigurable architecture by providing an initial estimate of performance and resources needed for its development. It also allows development and validation of scheduling reconfiguration scenarios, while respecting real-time constraints associated with the given application. To validate our methodology on a real application, video transcoding IP have been developed and tested. This application consists in the realization of a H.264/MPEG-2 transcoder made self-adaptable through the use of dynamic reconfiguration. This work was conducted as a part of the ARDMAHN project sponsored by the National Research Agency (Agence Nationale de Recheche) with the reference number ANR-09-SEGI-001

Les architectures reconfigurables à base de FPGA sont capables de fournir des solutions adéquates pour plusieurs applications vu qu'elles permettent de modifier le comportement d'une partie du FPGA pendant que le reste du circuit continue de s'exécuter normalement. Ces architectures, malgré leurs progrès, souffrent encore de leur manque d'adaptabilité fasse à des applications constituées de tâches matérielles de taille différente. Cette hétérogénéité peut entraîner de mauvais placements conduisant à une utilisation sous-optimale des ressources et par conséquent une diminution des performances du système. La contribution de cette thèse porte sur la problématique du placement des tâches matérielles de tailles différentes et de la génération efficace des régions reconfigurables. Une méthodologie et une couche intermédiaire entre le FPGA et l'application sont proposées pour permettre le placement efficace des tâches matérielles de tailles différentes sur des partitions reconfigurables de taille prédéfinie. Pour valider la méthode, on propose une architecture basée sur l'utilisation de la reconfiguration partielle afin d'adapter le transcodage d'un format de compression vidéo à un autre de manière souple et efficace. Une étude sur le partitionnement de la région reconfigurable pour les tâches matérielles de l'encodeur entropique (CAVLC / VLC) est proposée afin de montrer l'apport du partitionnement. Puis une évaluation du gain obtenu et du surcoût de la méthode est présentée / FPGA-based reconfigurable architectures can deliver appropriate solutions for several applications as they allow for changing the performance of a part of the FPGA while the rest of the circuit continues to run normally. These architectures, despite their improvements, still suffer from their lack of adaptability when confronted with applications consisting of variable size material tasks. This heterogeneity may cause wrong placements leading to a sub-optimal use of resources and therefore a decrease in the system performances. The contribution of this thesis focuses on the problematic of variable size material task placement and reconfigurable region effective generation. A methodology and an intermediate layer between the FPGA and the application are proposed to allow for the effective placement of variable size material tasks on reconfigurable partitions of a predefined size. To approve the method, we suggest an architecture based on the use of partial reconfiguration in order to adapt the transcoding of one video compression format to another in a flexible and effective way. A study on the reconfigurable region partitioning for the entropy encoder material tasks (CAVLC / VLC) is proposed in order to show the contribution of partitioning. Then an assessment of the gain obtained and of the method additional costs is submitted

Le contexte de ce travail de recherche se situe dans le domaine du génie logiciel, et vise plus spécifiquement les systèmes auto-adaptatifs (Self Adaptive Systems, SAS). Le travail de recherche vise les tous premiers stades du cycle de vie du développement logiciel : la phase de spécification des exigences (Requirements Engineering). Nous nous concentrons sur la définition et la modélisation des exigences (Elicitation) ainsi que sur leur vérification. La contribution globale de cette thèse est de proposer une approche intégrée pour la modélisation et la vérification des exigences des SAS à l'aide de techniques d'ingénierie des modèles (Model Driven Engineering, MDE). Nous prenons les exigences en entrée de notre processus et les divisons en exigences fonctionnelles et non fonctionnelles. Ensuite, nous appliquons un processus pour identifier les exigences qui sont adaptables et celles qui sont invariantes. Les progrès récents dans les techniques basées sur les buts en Ingénierie des Exigences nous ont poussé à intégrer ces techniques dans notre approche. En (Goal Oriented Requirements Engineering, GORE), les (Non Functional Requirements, NFR) sont exprimées sous la forme de buts, ce qui est beaucoup plus riche et complet dans la définition des relations entre les exigences. Ici, les exigences invariantes sont capturées par le concept de buts fonctionnels et les exigences adaptables sont capturées par le concept des buts non fonctionnels. Nous avons identifié quelques problèmes dans les méthodes classiques de modélisation des exigences et la vérification des propriétés. Ces approches ne tiennent pas compte des caractéristiques d'adaptabilité associées avec les systèmes auto-adaptatifs. Afin de valider notre approche, nous avons modélisé les exigences de deux études de cas et vérifié les exigences d'une étude de cas. / The overall contribution of this thesis is to propose an integrated approach for modeling and verifying the requirements of Self Adaptive Systems using Model Driven Engineering techniques. Model Driven Engineering is primarily concerned with reducing the gap between problem and software implementation domains through the use of technologies that support systematic transformation of problem level abstractions to software implementations. By using these techniques, we have bridged this gap through the use of models that describe complex systems at multiple levels of abstraction and through automated support for transforming and analyzing these models. We take requirements as input and divide it into Functional and Non Functional Requirements. We then use a process to identify those requirements that are adaptable and those that cannot be changed. We then introduce the concepts of Goal Oriented Requirements Engineering for modeling the requirements of Self Adaptive Systems, where Non Functional Requirements are expressed in the form of goals which is much more rich and complete in defining relations between requirements. We have identified some problems in the conventional methods of requirements modeling and properties verification using existing techniques, which do not take into account the adaptability features associated with Self Adaptive Systems. Our proposed approach takes into account these adaptable requirements and we provide various tools and processes that we developed for the requirements modeling and verification of Self Adaptive Systems. We validate our proposed approach by applying it on two different case studies in the domain of Self Adaptive Systems.

The development of self-adaptive software requires the engineering of an adaptation engine that controls and adapts the underlying adaptable software by means of feedback loops. The adaptation engine often describes the adaptation by using runtime models representing relevant aspects of the adaptable software and particular activities such as analysis and planning that operate on these runtime models. To systematically address the interplay between runtime models and adaptation activities in adaptation engines, runtime megamodels have been proposed for self-adaptive software. A runtime megamodel is a specific runtime model whose elements are runtime models and adaptation activities. Thus, a megamodel captures the interplay between multiple models and between models and activities as well as the activation of the activities. In this article, we go one step further and present a modeling language for ExecUtable RuntimE MegAmodels (EUREMA) that considerably eases the development of adaptation engines by following a model-driven engineering approach. We provide a domain-specific modeling language and a runtime interpreter for adaptation engines, in particular for feedback loops. Megamodels are kept explicit and alive at runtime and by interpreting them, they are directly executed to run feedback loops. Additionally, they can be dynamically adjusted to adapt feedback loops. Thus, EUREMA supports development by making feedback loops, their runtime models, and adaptation activities explicit at a higher level of abstraction. Moreover, it enables complex solutions where multiple feedback loops interact or even operate on top of each other. Finally, it leverages the co-existence of self-adaptation and off-line adaptation for evolution. / Die Entwicklung selbst-adaptiver Software erfordert die Konstruktion einer sogenannten "Adaptation Engine", die mittels Feedbackschleifen die unterliegende Software steuert und anpasst. Die Anpassung selbst wird häufig mittels Laufzeitmodellen, die die laufende Software repräsentieren, und Aktivitäten wie beispielsweise Analyse und Planung, die diese Laufzeitmodelle nutzen, beschrieben. Um das Zusammenspiel zwischen Laufzeitmodellen und Aktivitäten systematisch zu erfassen, wurden Megamodelle zur Laufzeit für selbst-adaptive Software vorgeschlagen. Ein Megamodell zur Laufzeit ist ein spezielles Laufzeitmodell, dessen Elemente Aktivitäten und andere Laufzeitmodelle sind. Folglich erfasst ein Megamodell das Zusammenspiel zwischen verschiedenen Laufzeitmodellen und zwischen Aktivitäten und Laufzeitmodellen als auch die Aktivierung und Ausführung der Aktivitäten. Darauf aufbauend präsentieren wir in diesem Artikel eine Modellierungssprache für ausführbare Megamodelle zur Laufzeit, EUREMA genannt, die aufgrund eines modellgetriebenen Ansatzes die Entwicklung selbst-adaptiver Software erleichtert. Der Ansatz umfasst eine domänen-spezifische Modellierungssprache und einen Laufzeit-Interpreter für Adaptation Engines, insbesondere für Feedbackschleifen. EUREMA Megamodelle werden über die Spezifikationsphase hinaus explizit zur Laufzeit genutzt, um mittels Interpreter Feedbackschleifen direkt auszuführen. Zusätzlich können Megamodelle zur Laufzeit dynamisch geändert werden, um Feedbackschleifen anzupassen. Daher unterstützt EUREMA die Entwicklung selbst-adaptiver Software durch die explizite Spezifikation von Feedbackschleifen, der verwendeten Laufzeitmodelle, und Adaptionsaktivitäten auf einer höheren Abstraktionsebene. Darüber hinaus ermöglicht EUREMA komplexe Lösungskonzepte, die mehrere Feedbackschleifen und deren Interaktion wie auch die hierarchische Komposition von Feedbackschleifen umfassen. Dies unterstützt schließlich das integrierte Zusammenspiel von Selbst-Adaption und Wartung für die Evolution der Software.

Our society is increasingly demanding situation-aware smarter software (SASS) systems, whose goals change over time and depend on context situations. A system with such properties must sense their dynamic environment and respond to changes quickly, accurately, and reliably, that is, to be context-aware and self-adaptive. The problem addressed in this dissertation is the dynamic management of context information, with the goal of improving the relevance of SASS systems' context-aware capabilities with respect to changes in their requirements and execution environment. Therefore, this dissertation focuses on the investigation of dynamic context management and self-adaptivity to: (i) improve context-awareness and exploit context information to enhance quality of user experience in SASS systems, and (ii) improve the dynamic capabilities of self-adaptivity in SASS systems. Context-awareness and self-adaptivity pose signi cant challenges for the engineering of SASS systems. Regarding context-awareness, the rst challenge addressed in this dissertation is the impossibility of fully specifying environmental entities and the corresponding monitoring requirements at design-time. The second challenge arises from the continuous evolution of monitoring requirements due to changes in the system caused by self-adaptation. As a result, context monitoring strategies must be modeled and managed in such a way that they support the addition and deletion of context types and monitoring conditions at runtime. For this, the user must be integrated into the dynamic context management process. Concerning self-adaptivity, the third challenge is to control the dynamicity of adaptation goals, adaptation mechanisms, and monitoring infrastructures, and the way they a ect each other in the adaptation process. This is to preserve the eff ectiveness of context monitoring requirements and thus self-adaptation. The fourth challenge, related also to self-adaptivity,concerns the assessment of adaptation mechanisms at runtime to prevent undesirable system states as a result of self-adaptation. Given these challenges, to improve context-awareness we made three contributions. First, we proposed the personal context sphere concept to empower users to control the life cycle of personal context information in user-centric SASS systems. Second, we proposed the SmarterContext ontology to model context information and its monitoring requirements supporting changes in these models at runtime. Third, we proposed an effi cient context processing engine to discover implicit contextual facts from context information speci fied in changing context models. To improve self-adaptivity we made three contributions. First, we proposed a framework for the identi cation of adaptation properties and goals, which is useful to evaluate self-adaptivity and to derive monitoring requirements mapped to adaptation goals. Second, we proposed a reference model for designing highly dynamic self-adaptive systems, for which the continuous pertinence between monitoring mechanisms and both changing system goals and context situations is a major concern. Third, we proposed a model with explicit validation and veri cation (V&V) tasks for self-adaptive software, where dynamic context monitoring plays a major role. The seventh contribution of this dissertation, the implementation of Smarter-Context infrastructure, addresses both context-awareness and self-adaptivity. To evaluate our contributions, qualitatively and quantitatively, we conducted several comprehensive literature reviews, a case study on user-centric situation-aware online shopping, and a case study on dynamic governance of service-oriented applications. / Graduate