The convergence of data, audio and video on IP networks is changing the way individuals, groups and organizations communicate. This diversity of communication media presents opportunities for creating synergistic collaborative communications. This form of collaborative communication is however not without its challenges. The increasing number of communication service providers coupled with a combinatorial mix of offered services, varying Quality-of-Service and oscillating pricing of services increases the complexity for the user to manage and maintain `always best' priced or performance services. Consumers have to manually manage and adapt their communication in line with differences in services across devices, networks and media while ensuring that the usage remain consistent with their intended goals. This dissertation proposes a novel user-centric approach to address this problem. The proposed approach aims to reduce the aforementioned complexity to the user by (1) providing high-level abstractions and a policy based methodology for automated selection of the communication services guided by high-level user policies and (2) providing services through the seamless integration of multiple communication service providers and providing an extensible framework to support the integration of multiple communication service providers. The approach was implemented in the Communication Virtual Machine (CVM), a model-driven technology for realizing communication applications. The CVM includes the Network Communication Broker, the layer responsible for providing a network-independent API to the upper layers of CVM. The initial prototype for the NCB supported only a single communication framework which limited the number, quality and types of services available. Experimental evaluation of the approach show the additional overhead of the approach is minimal compared to the individual communication services frameworks. Additionally the automated approach proposed out performed the individual communication services frameworks for cross framework switching.

Les systèmes modernes subissent des pressions pour s'adapter à leur environnement en constante évolution afin de rester utiles. Traditionnellement, cette adaptation a été gérée lors des temps morts du système. il y a une demande croissante d'automatiser ce processus et de le réaliser pendant le fonctionnement du système. Les systèmes auto-adaptatifs ont été introduits en tant que réalisation de systèmes s'adaptant en permanence. Les systèmes auto-adaptatifs peuvent modifier au moment de l'exécution leur comportement et / ou leur structure en fonction de leur perception de l'environnement, du système lui-même et de leurs exigences. L'objectif de ce travail est de réaliser l'auto-configuration, une propriété essentielle et essentielle des systèmes auto-adaptatifs. L'auto-configuration est la capacité de reconfiguration automatique et dynamique en réponse aux changements. Cela peut inclure l’installation, l’intégration, le retrait et la composition / décomposition d’éléments du système.Cette thèse présente le framework Dr-BIP, une extension du framework BIP pour la modélisation de systèmes à configuration automatique qui repose sur une approche basée sur un modèle et basée sur des composants et des connecteurs pour prescrire des systèmes. La combinaison de ces deux approches exploite les avantages de chacune d’elles, faisant de leur combinaison une méthodologie idéale pour la réalisation de systèmes complexes à configuration automatique.Un modèle de système Dr-BIP est un modèle d'exécution qui capture le système en cours d'exécution à trois niveaux d'abstraction différents, à savoir les variantes de comportement, de configuration et de configuration. La configuration du système est capturée par le composant et les connecteurs. Dans un système de composants et de connecteurs, la configuration automatique peut avoir trois niveaux de granularité différents, notamment la possibilité d'ajouter ou de supprimer des connecteurs, d'ajouter ou de supprimer des composants et d'ajouter ou de supprimer des sous-systèmes. Dr-BIP prend en charge l'ajout et le retrait explicites de composants et de sous-systèmes, mais l'ajout et le retrait implicites de connecteurs. Le principal avantage de compter sur une addition et une suppression implicites de connecteurs est la possibilité de garantir, par la construction, des topologies de configuration spécifiques.Pour capturer les trois niveaux d'abstraction, nous introduisons des motifs en tant que structures principales pour prescrire un système Dr-BIP à configuration automatique. Un motif définit un ensemble de composants qui évoluent en fonction de règles d'interaction et de reconfiguration. Un système est composé de plusieurs motifs pouvant éventuellement partager des composants et évoluer ensemble. Les règles d'interaction dictent la manière dont les composants composant le système peuvent interagir, tandis que les règles de reconfiguration dictent l'évolution de la configuration du système. Enfin, nous montrons que le cadre proposé est à la fois minimal et expressif en modélisant quatre systèmes différents à configuration automatique. Enfin, nous proposons un langage de modélisation pour codifier les concepts du cadre et fournir une implémentation d’interprète. / Modern systems are pressured to adapt in response to their constantly changing environment to remain useful. Traditionally, this adaptation has been handled at down times of the system. there is an increased demand to automate this process and achieve it whilst the system is running. Self-adaptive systems were introduced as a realization of continuously adapting systems. Self-adaptive systems are able to modify at runtime their behavior and/or structure in response to their perception of the environment, the system itself, and their requirements. The focus of this work is on realizing self-configuration, a key and essential property of self-adaptive systems. Self-configuration is the capability of reconfiguring automatically and dynamically in response to changes. This may include installing, integrating, removing and composing/decomposing system elements.This thesis introduces the Dr-BIP framework, an extension of the BIP framework for modeling self-configuring systems that relies on a model-based and component & connector approach to prescribe systems. The combination of both of these approaches exploits the benefits of each, making their combination an ideal methodology to realize complex self-configuring systems.A Dr-BIP system model is a runtime model which captures the running system at three different levels of abstraction namely behavior, configuration, and configuration variants. The system's configuration is captured by component and connectors. In a component and connector system, self-configuration can have three different levels of granularity which includes the ability to add or remove connectors, add or remove components, and add or remove subsystems. Dr-BIP supports explicit addition and removal of both components and subsystems, but implicit addition and removal of connectors. The main advantage of relying on an implicit addition and removal of connectors is the ability to guarantee by construction specific configuration topologies.To capture the three levels of abstraction, we introduce motifs as primary structures to prescribe a self-configuring Dr-BIP system. A motif defines a set of components that evolve according to interaction and reconfiguration rules. A system is composed of multiple motifs that possibly share components and evolve together. Interaction rules dictate how components composing the system can interact and reconfiguration rules dictate how the system configuration can evolve over time. Finally, we show that the proposed framework is both minimal and expressive by modeling four different self-configuring systems. Last but not least, we propose a modeling language to codify the framework concepts and provision an interpreter implementation.

Dans cette thèse, nous étudions la solution LOCARN : ''Low Opex & Capex Architecture for Resilient Networks''. LOCARN est une architecture de réseaux paquet alternative conçue dans une optique de simplicité de sa structure et ses mécanismes tout en permettant par sa conception la résilience et l'auto-adaptation des services de transport clients. Compte tenu de la complexification croissante des réseaux de transport opérateurs ces dernières décennies, nous prenons ces réseaux comme cas d'usage privilégié. Dans ce cadre, LOCARN permet une simplification considérable des composants et de leur gestion en comparaison des solutions actuelles des opérateurs – ce qui implique respectivement des réductions de CAPEX et d'OPEX. Dans le travail qui suit, nous présentons LOCARN techniquement et mettons en évidence ses intérêts pour les opérateurs par rapport aux autres technologies de transport. Puis, la question prioritaire étant la capacité de mise à l'échelle de LOCARN pour des réseaux de grandes dimensions, nous étudions cette question en détails ce qui nous permet d'établir que l'architecture est tout à fait capable de passer à l'échelle dans des réseaux de transport réalistes. En outre, pour améliorer les performances nous avons également spécifié et évalué deux améliorations de conception permettant à l'architecture de transporter d'un très grand nombre de services, les résultats obtenus sont très encourageants. / In this thesis, we study the LOCARN solution “Low Opex & Capex Architecture for Resilient Networks". LOCARN is an alternative packet network architecture that has been conceived with a special attention to the simplicity of its structure and mechanisms while allowing by design the resiliency and the self-adaptation of clients transportation services. Considering the growing complexification of operators transport networks during the last decades, we consider these latter as the privileged use case. In such a context, LOCARN would allow a drastical simplification of devices and their operation compared to common operator solutions – this involves respectively reductions of CAPEX and OPEX. In this work, we first present LOCARN technically and we bring out its interests for operators beside other transport technologies. Then, since the primary issue of LOCARN is it scalability for large networks, we study this point in details which allow us to establish that the architecture is altogether capable to scale in realistics transport networks. Moreover, to increase the performances we specified two design improvements allowing the architecture to transport a huge amount of clients, the obtained results are very encouraging.

Reconfigurable computing architectures combine the flexibility of software with the performance of custom hardware. Such architectures are of particular interest at the nanoscale level. We argue that a bottom-up self-assembled fabric of nodes will be easier and cheaper to manufacture, however, one has to make compromises with regards to the device regularity, homogeneity, and reliability. The goal of this thesis is to evaluate the performance and cost of a self-configurable computing architecture composed of simple reconfigurable nodes for unstructured and unknown fabrics. We built a software and hardware framework for this purpose. The framework enables creating an irregular network of compute nodes where each node can be configured as a simple 2-input, 4-bit logic gate. The compute nodes are organized hierarchically by sending a packet through a top anchor node that recruits compute nodes with a chemically-inspired algorithm. The nodes are then self-configured by means of a gate-level netlist describing any digital logic circuit. A topology-agnostic optimization algorithm inspired by simulated annealing is then initiated to self-optimize the circuit for latency. Latency comparisons between non-optimized, brute-force optimized and our optimization algorithm are made. We further implement the architecture in VHDL and evaluate hardware cost, area, and energy consumption. The simple on-chip topology-agnostic optimization algorithm we propose results in a significant (up to 50\%) performance improvement compared to the non-optimized circuits. Our findings are of particular interest for emerging nano and molecular-scale circuits.

Sandvik har utvecklat en teknik för att placera sensorer i rör. Denna teknik har stor marknadspotential och kan effektivisera många industriprocesser. Den färdiga tjänsten ska kunna strömma sensordata till molntjänster för analys och avläsning.Deras nuvarande system kräver idag manuell konfiguration på plats och är komplicerad att installera. Denna uppsats undersöker hur systemets utrustning kan konfigureras automatiskt och hur ett system för underliggande IT-tjänster skulle kunna fungera.En lösning presenteras där många delar av installationsprocessen har automatiserats, samt en skiss för ett underliggande system.Lösningen utvärderas genom att utföra en mätning av konfigureringskomplexitet. Slutsatsen av utvärderingen var att det utvecklade system hade utökad funktionalitet, jämfört med dagens manuella tillvägagångssätt, och var inte mer komplex att konfigurera. I många avseenden mindre komplex. / Sandvik has developed a technique to place sensors inside tubes. This technology has great market potential and can optimize many industrial processes. The finished product should be able to stream sensor data to cloudservices for analysis and reading.The current system requires manual configuration on-site and the installation is labor intensive. This thesis investigates how the system’s hardware can be configured atomically, and how a supporting IT-system could function.A solution is presented where large portion of the installation process has been automated, along with an outline for a supporting system.The solution is evaluated by performing a measurement of the configuration complexity. The evaluation shows that the developed system had increased functionality compared to today’s manual configuration, configuration complexity was not increased. In many aspects, the configuration complexity was reduced.

Large-scale virtualized data centers require cloud providers to implement scalable, autonomic, and energy-efficient cloud management systems. To address these challenges this thesis provides four main contributions. The first one proposes Snooze, a novel Infrastructure-as-a-Service (IaaS) cloud management system, which is designed to scale across many thousands of servers and virtual machines (VMs) while being easy to configure, highly available, and energy efficient. For scalability, Snooze performs distributed VM management based on a hierarchical architecture. To support ease of configuration and high availability Snooze implements self-configuring and self-healing features. Finally, for energy efficiency, Snooze integrates a holistic energy management approach via VM resource (i.e. CPU, memory, network) utilization monitoring, underload/overload detection and mitigation, VM consolidation (by implementing a modified version of the Sercon algorithm), and power management to transition idle servers into a power saving mode. A highly modular Snooze prototype was developed and extensively evaluated on the Grid'5000 testbed using realistic applications. Results show that: (i) distributed VM management does not impact submission time; (ii) fault tolerance mechanisms do not impact application performance and (iii) the system scales well with an increasing number of resources thus making it suitable for managing large-scale data centers. We also show that the system is able to dynamically scale the data center energy consumption with its utilization thus allowing it to conserve substantial power amounts with only limited impact on application performance. Snooze is an open-source software under the GPLv2 license. The second contribution is a novel VM placement algorithm based on the Ant Colony Optimization (ACO) meta-heuristic. ACO is interesting for VM placement due to its polynomial worst-case time complexity, close to optimal solutions and ease of parallelization. Simulation results show that while the scalability of the current algorithm implementation is limited to a smaller number of servers and VMs, the algorithm outperforms the evaluated First-Fit Decreasing greedy approach in terms of the number of required servers and computes close to optimal solutions. In order to enable scalable VM consolidation, this thesis makes two further contributions: (i) an ACO-based consolidation algorithm; (ii) a fully decentralized consolidation system based on an unstructured peer-to-peer network. The key idea is to apply consolidation only in small, randomly formed neighbourhoods of servers. We evaluated our approach by emulation on the Grid'5000 testbed using two state-of-the-art consolidation algorithms (i.e. Sercon and V-MAN) and our ACO-based consolidation algorithm. Results show our system to be scalable as well as to achieve a data center utilization close to the one obtained by executing a centralized consolidation algorithm.

The problem that motivated the study was that the way in which juvenile sex offenders are configuring themselves, and the way that self-development is currently understood, potentially has negative implications for the way they may be treated in therapy. The Gestalt paradigm was the lens through which this phenomenon was explored. The research method was from a qualitative perspective and was an explorative and descriptive analysis of the factors that contribute to this self-configuration. Data was collected by way of unstructured and semi-structured interviews and systematically represented by the emergent themes. Results showed the factors that contribute to the self-configuration of the juvenile sex offender. Recommendations were made to the juveniles, their caretakers and the social workers. The researcher concluded that the Gestalt approach to self-configuration, with its emphasis on the field and relationships, provides a coherent lens through which to approach the phenomenon of juvenile sex offenders. / Social Work / M. Diac. (Play Therapy)

The problem that motivated the study was that the way in which juvenile sex offenders are configuring themselves, and the way that self-development is currently understood, potentially has negative implications for the way they may be treated in therapy. The Gestalt paradigm was the lens through which this phenomenon was explored. The research method was from a qualitative perspective and was an explorative and descriptive analysis of the factors that contribute to this self-configuration. Data was collected by way of unstructured and semi-structured interviews and systematically represented by the emergent themes. Results showed the factors that contribute to the self-configuration of the juvenile sex offender. Recommendations were made to the juveniles, their caretakers and the social workers. The researcher concluded that the Gestalt approach to self-configuration, with its emphasis on the field and relationships, provides a coherent lens through which to approach the phenomenon of juvenile sex offenders. / Social Work / M. Diac. (Play Therapy)

L’émergence de l’informatique dans les nuages met en avant de nombreux défis qui pourraient limiter l’adoption du paradigme Cloud. Tandis que la taille des données traitées par les applications Cloud augmente exponentiellement, un défi majeur porte sur la conception de solutions efficaces pour la gestion de données. Cette thèse a pour but de concevoir des mécanismes d’auto-adaptation pour des systèmes de gestion de données, afin qu’ils puissent répondre aux exigences des services de stockage Cloud en termes de passage à l’échelle, disponibilité et sécurité des données. De plus, nous nous proposons de concevoir un service de données qui soit à la fois compatible avec les interfaces Cloud standard dans et capable d’offrir un stockage de données à haut débit. Pour relever ces défis, nous avons proposé des mécanismes génériques pour l’auto-connaissance, l’auto-protection et l’auto-configuration des systèmes de gestion de données. Ensuite, nous les avons validés en les intégrant dans le logiciel BlobSeer, un système de stockage qui optimise les accès hautement concurrents aux données. Finalement, nous avons conçu et implémenté un système de fichiers s’appuyant sur BlobSeer, afin d’optimiser ce dernier pour servir efficacement comme support de stockage pour les services Cloud. Puis, nous l’avons intégré dans un environnement Cloud réel, la plate-forme Nimbus. Les avantages et les désavantages de l’utilisation du stockage dans le Cloud pour des applications réelles sont soulignés lors des évaluations effectuées sur Grid’5000. Elles incluent des applications à accès intensif aux données, comme MapReduce, et des applications fortement couplées, comme les simulations atmosphériques. / The emergence of Cloud computing brings forward many challenges that may limit the adoption rate of the Cloud paradigm. As data volumes processed by Cloud applications increase exponentially, designing efficient and secure solutions for data management emerges as a crucial requirement. The goal of this thesis is to enhance a distributed data-management system with self-management capabilities, so that it can meet the requirements of the Cloud storage services in terms of scalability, data availability, reliability and security. Furthermore, we aim at building a Cloud data service both compatible with state-of-the-art Cloud interfaces and able to deliver high-throughput data storage. To meet these goals, we proposed generic self-awareness, self-protection and self-configuration components targeted at distributed data-management systems. We validated them on top of BlobSeer, a large-scale data-management system designed to optimize highly-concurrent data accesses. Next, we devised and implemented a BlobSeer-based file system optimized to efficiently serve as a storage backend for Cloud services. We then integrated it within a real-world Cloud environment, the Nimbus platform. The benefits and drawbacks of using Cloud storage for real-life applications have been emphasized in evaluations that involved data-intensive MapReduce applications and tightly-coupled, high-performance computing applications.

La motivation principale de cette thèse est de faire face à l'accroissement de la complexité des systèmes informatiques, qui, dans un futur proche ( de l'ordre de quelques années) risque fort d'être le principal frein à leur évolution et à leur développement. Aujourd'hui la tendance s'inverse et le coût de gestion humaine dépasse le coût des infrastructures matérielles et logicielles. De plus, l'administration manuelle de grands systèmes (applications distribuées, réseaux de capteurs, équipements réseaux) est non seulement lente mais aussi sujette à de nombreuses erreurs humaines. Un des domaines de recherche émergent est celui de l'informatique autonomique qui a pour but de rendre ces systèmes auto-gérés. Nous proposons une approche qui permet de décrire des politiques de gestion autonomiques de haut niveau. Ces politiques permettent au système d'assurer quatre propriétés fondamentales de l'auto-gestion: l'auto-guérison, l'auto-configuration, l'auto-protection et l'auto-optimisation. Nos contributions portent sur la spécification de diagrammes de description de politiques de gestion autonomiques appelés (S)PDD "(Sensor) Policy Description Diagrams". Ces diagrammes sont implémentés dans le gestionnaire autonomique TUNe et l'approche a été validée sur de nombreux systèmes: simulation électromagnétique répartie sur grille de calcul, réseaux de capteurs SunSPOT, répartiteur de calcul DIET. Une deuxième partie présente une modélisation mathématique de l’auto-optimisation pour un « datacenter ». Nous introduisons un problème de minimisation d’un critère intégrant d’une part la consommation électrique des équipements du réseau du « datacenter » et d’autre part la qualité de service des applications déployées sur le « datacenter ». Une heuristique permet de prendre en compte les contraintes dues aux fonctions de routage utilisées. / The main challenge of this thesis is to cope with the growing complexity of IT systems. In a near future (mainly the next few years) this complexity will prevent new developments and system evolutions. Today the trend is reversing and the managing costs are overtaking the hardware and software costs. Moreover, the manual administration of large systems (distributed applications, sensor networks, and network equipment) is not only slow but error-prone. An emerging research field called autonomic computing tries to bring up self-managed systems. We introduce an approach that enable the description of high level autonomic management policies. These policies allow the system to ensure four fundamental properties for self-management: self-healing, self-self-configuring, self-protecting and self-optimizing. We specify autonomic management Policy Description Diagrams (PDD) and implement them in Toulouse University Network (TUNe). We validated our approach on many systems: electromagnetic simulations distributed on computer grids (grid’5000), wireless sensor networks with SunSPOTs and the computing scheduler DIET. A second part of this thesis presents a mathematical modeling for self-optimizing datacenters. We introduce a minimization problem with a criterion integrating both the electrical consumption of the datacenter networking equipment and the quality of service of the deployed applications. A heuristic takes into account the routing functions used on the network.