Os Sistemas Distribuídos (SDs) tem apresentado uma crescente complexidade no seu gerenciamento, além de possuir a necessidade de garantir Qualidade de Serviço (QoS) aos seus usuários. A Computação Autonômica (CA) surge como uma forma de transformar os SDs em Sistemas Distribuídos Autonômicos (SDAs), com capacidade de auto-gerenciamento. Entretanto, não foi encontrado um processo de desenvolvimento de software, focado na criação de SDAs. Na grande maioria dos trabalhos relacionados, simplesmente é apresentado um SD, juntamente com qual aspecto da CA deseja-se implementar, a técnica usada e os resultados obtidos. Isso é apenas uma parte do desenvolvimento de um SDA, não abordando desde a definição dos requisitos até a manutenção do software. Mais importante, não mostra como tais requisitos podem ser formalizados e posteriormente solucionados por meio do auto-gerenciamento fornecido pela CA. Esta tese foca na proposta de um processo de desenvolvimento de software voltado para SDAs. Com esse objetivo, foram integradas diferentes áreas de conhecimento, compreendendo: Processo Unificado de Desenvolvimento de Software (PU), SDs, CA, Pesquisa Operacional (PO) e Avaliação de Desempenho de Sistemas Computacionais (ADSC). A prova de conceito foi feita por meio de três estudos de caso, todos focando-se em problemas NP-Difícil, são eles: (i) otimização off-line (problema da mochila com múltiplas escolhas), (ii) otimização online (problema da mochila com múltiplas escolhas) e (iii) criação do módulo planejador de um gerenciador autonômico, visando realizar o escalonamento de requisições (problema de atribuição generalizado). Os resultados do primeiro estudo de caso, mostram que é possível usar PO e ADSC para definir uma arquitetura de base para o SDA em questão, bem como reduzir o tamanho do espaço de busca quando o SDA estiver em execução. O segundo, prova que é possível garantir a QoS do SDA durante sua execução, usando a formalização fornecida pela PO e sua respectiva solução. O terceiro, prova que é possível usar a PO para formalizar o problema de auto-gerenciamento, bem como a ADSC para avaliar diferentes algoritmos ou modelos de arquitetura para o SDA. / Distributed Systems (DSs) have an increasing complexity and do not have their management, besides having a quality of service (QoS) to its users. Autonomic Computing (AC) emerges as a way of transforming the SDs into Autonomous Distributed Systems (ADSs), with a capacity for self-management. However, your software development process is focused on creating SDAs. In the vast majority of related works, simply an SD model, along with what aspect of the AC implement, a technique used and the results obtained. This is only a part of the development of an ADS, not approaching from an definition of requirements for a maintenance of software. More importantly, it does not show how such requirements can be formalized and subsequently solved through the self-management provided by AC. This proposal aims at a software development process for the DASs. To this end, different areas of knowledge were integrated, including: Unified Software Development Process (PU), SDs, CA, Operations Research (OR) and Computer Systems Performance Evaluation (CSPE). The proof of concept was made through three case studies, all focusing on NP-Hard problems, namely: (i) off-line optimization (problem of the backpack with multiple choices), (ii) (Problem of the backpack with multiple choices) and (iii) creation of the scheduling module of an autonomic manager, aiming to carry out the scheduling of requests (problem of generalized assignment). The results of the first case study show that it is possible to use OR and CSPE to define a base architecture for the DAS in question, as well as reduce the size of the search space when SDA is running. The second, proves that it is possible to guarantee the QoS of the DAS during its execution, using the formalization provided by the OR and its respective solution. The third, proves that it is possible to use the PO to formalize the self-management problem, as well as the ADSC to evaluate different algorithms or architecture models for the ADS.

Depuis une vingtaine d'années, les développements dans les technologies de l'information ont fait évoluer les paradigmes de l'informatique. L'arrivée d'approches telles que l'informatique diffuse ont fait émerger de nouvelles technologies permettant d'améliorer la qualité des interactions avec les systèmes informatisés. Toutefois, la démocratisation de l'informatique diffuse et la mise en place des espaces intelligents rencontrent un bon nombre de problèmes. Le nombre important de composantes matérielles et logicielles et leurs natures hétérogènes contribuent à la complexité de déploiement et de gestion de ces milieux, entraînant des coûts élevés. Cette thèse vise à contribuer à la gestion logicielle des espaces intelligents par la réduction de la complexité des tâches de gestion. Notre proposition consiste en une approche autonome de la gestion logicielle, fondée sur l'approche de l'informatique diffuse autonome. Dans le cadre de ce travail, nous proposons une solution utilisant les informations contextuelles des milieux, afin de déterminer quelle répartition des logiciels parmi les appareils des milieux correspond le mieux au besoin des applications, des caractéristiques propres des environnements et, non le moindre, des modalités et préférences d’interaction des utilisateurs de ces milieux. La solution proposée a été implémentée et évaluée à l’aide d’une série de tests et de mises en situation d’organisation logicielle / Since two decades, the developments in the information technologies have changed the computer science paradigms. The arrival of new approaches such as the pervasive computing create new technologies, which improved the quality of the interactions with the I.T. systems, However, the broad utilization of the pervasive computing and the development of smart spaces are facing several challenges. The large number of hardware and software components and their heterogeneous natures, contributes to the complexity of deploying and managing these environments, resulting in high costs. This thesis contributes to the software management of the smart spaces by reducing the complexity of the management tasks. Our proposal consists of an autonomic approach to software management based on the autonomic pervasive computing. As part of this work, we propose a solution using the environment’s contextual information to determine the software distribution among the environment’s devices, which best fits the needs of the software, environments and the interaction modalities and preferences of the environment’s users. The proposed solution was implemented and evaluated using a series of tests and software organization scenarios

Dans le contexte actuel de l’Internet, un enjeu de recherche majeur est de permettre aux applications et à leurs utilisateurs de disposer de systèmes de communication offrant une qualité de service (QdS) optimale. Ceci en fonction des ressources machine et réseau disponibles, dont les capacités et les performances, hétérogènes et variables, ne sont pas connues à l’avance. Le provisionnement optimal de la QdS dans ces futurs systèmes de communication autonomes nécessite d’une part la caractérisation des services et des ressources de communication disponibles, et d’autre part la prise en compte des expressions des besoins et des préférences des différents acteurs du système (utilisateurs, fournisseurs des services, etc.). Le sujet de la thèse porte sur la définition d’un cadre sémantique de QdS basé sur les ontologies pour la caractérisation des ressources et des services de communication dans le but de fournir la meilleure QdS au regard des besoins et des préférences des utilisateurs. Ce cadre sera utilisé dans la définition des objectifs et des contraintes de QdS et dans l’élaboration de modèles de décision. L'ensemble sera utilisé pour la mise en œuvre de QdS dans les systèmes de communication autonomes situés dans un contexte de réseaux domestiques / In the current context of the Internet, a major research challenge is to enable applications and users to have their communications systems with an optimal quality of service (QoS). Indeed, QoS provisioning should take into account the available machine and network resources, which capacities and performances are heterogeneous, variable, and not known in advance. The optimal QoS provisioning for the future autonomous communication systems requires the characterization of available services and communication resources and also taking into account the expressions of needs and preferences of different actors in the system (users, service providers, etc.). The subject of this thesis deals with the definition of a QoS ontology-based semantic framework for the characterization of network resources and communication services in order to provide better QoS according to the needs and preferences of users. This framewor! k will be used in the definition of objectives and QoS constraints as well as in the development of decision models in order to provide QoS for autonomous communication systems located in the context of home networks

L'Internet connaît à nouveau une expansion drastique. En plus des terminaux classiques, il permet aujourd'hui d'interconnecter toute sorte d'objets connectés permettant la capture d'événements depuis l'environnement considéré, mais également le contrôle à distance de cet environnement. Plusieurs milliards de ces objets sont ainsi amenés à l'horizon 2020 à contribuer à l'avènement de l'Internet des Objets (IoT). Ce paradigme, qui étend le concept de Machine-to-Machine (M2M), ouvre la voie à de nouveaux usages tels que la domotique, la télésurveillance, ou encore les usines du futur. Plusieurs architectures ont été proposées pour structurer l'IoT. Leur fondement est basé sur une vision en quatre niveaux : le niveau Équipement, qui comporte les objets connectés, le niveau Réseau contenant les différentes technologies nécessaires aux échanges, le niveau Intergiciel (ou Middleware) qui offre aux applications une couche d'abstraction des niveaux sous-jacents, et enfin le niveau Application qui consiste en l'ensemble des applications concourant, via leurs interactions avec les objets connectés, à la réalisation d'une activité métier. Nos travaux se positionnent au niveau Middleware sur la base de l'architecture définie dans le cadre des standards SmartM2M puis oneM2M. Plusieurs problématiques sont amenées à être (re)-posées dans ce contexte. Nous nous intéressons essentiellement à celle de la qualité de service (QoS - Quality of Service) exprimée par certaines applications métiers. Les solutions proposées en réponse à cette problématique concernent principalement le niveau Réseau. Au niveau Middleware, les standards se focalisent essentiellement sur la proposition d'architectures et de services fonctionnels. Les besoins non fonctionnels, typiquement orientés QoS, ne sont que peu ou pas considérés. Parallèlement, les solutions propriétaires ne considèrent pas l'évolution dynamique du contexte et des besoins. Face à ces limites, nous proposons une approche de gestion dynamique, i.e. durant l'exécution du système, et autonome induisant un minimum d'intervention humaine. La gestion proposée, guidée par des modèles, porte sur des actions de reconfiguration comportementales et structurelles touchant au trafic applicatif et/ou sur les ressources de niveau Middleware / The Internet is experiencing a drastic expansion again. In addition to conventional terminals, it now allows to interconnect all kinds of connected objects allowing the capture of events from the considered environment, but also the remote control of this environment. Billions of these objects are thus led in 2020 to contribute to the advent of the Internet of Things (IoT). This paradigm, which extends the Machine-to-Machine (M2M) concept, paves the way for new uses such as home automation, remote monitoring, or even the factories of the future. Several architectures have been proposed to structure the IoT. Their foundation is based on a vision in four levels: (1) Equipment level, which includes the IoT equipment, (2) Network level containing the various technologies for data exchanges, (3) Middleware level, which offers applications an abstraction layer for underlying levels, and finally, (4) Application level, which consists of the set of applications contributing, via their interactions with the connected objects, to the realization of a business activity. Our work is positioned at Middleware level and is based on the architecture defined in the SmartM2M and then oneM2M standards. Several challenges have to be (re)considered in this context. We are mainly interested in the Quality of Service (QoS) issue expressed by some business applications. Proposals addressing this issue essentially target the Network level. For the Middleware level, standards focus mainly on the proposal of architectures and functional services. The non-functional requirements, typically QoS, are little or not considered. Meanwhile, proprietary solutions do not consider the dynamic evolution of the context and requirements. In response to these limitations, we propose a dynamic management approach, i.e. during the execution of the system, and autonomous, i.e. without human intervention. The proposed management, guided by models, focuses on behavioural and structural reconfiguration actions related to application traffic and/or Middleware resources.

This research focuses on the development and validation of an autonomic security management (ASM) framework to proactively protect distributed systems (DSs) from a wide range of cyber assaults with little or no human intervention. Multi-dimensional cyber attack taxonomy was developed to characterize cyber attack methods and tactics against both a Web application (Web-app) and an industrial control system (ICS) by accounting for their impacts on a set of system, network, and security features. Based on this taxonomy, a normal region of system performance is constructed, refined, and used to predict and identify abnormal system behavior with the help of forecasting modules and intrusion detection systems (IDS). Protection mechanisms are evaluated and implemented by a multi-criteria analysis controller (MAC) for their efficiency in eliminating and/or mitigating attacks, maintaining normal services, and minimizing operational costs and impacts. Causes and impacts of unknown attacks are first investigated by an ASM framework learning module. Attack signatures are then captured to update IDS detection algorithms and MAC protection mechanisms in near real-time. The ASM approach was validated within Web-app and ICS testbeds demonstrating the effectiveness of the self-protection capability. Experiments were conducted using realworld cyber attack tools and profiles. Experimental results show that DS security behavior is predicted, detected, and eliminated thus validating our original hypothesis concerning the self-protection core capability. One important benefit from the self-protection feature is the cost-effective elimination of malicious requests before they impede, intrude or compromise victim systems. The ASM framework can also be used as a decision support system. This feature is important especially when unknown attack signatures are ambiguous or when responses selected automatically are not efficient or are too risky to mitigate attacks. In this scenario, man-in-the-loop decisions are necessary to provide manual countermeasures and recovery operations. The ASM framework is resilient because its main modules are installed on a master controller virtual machine (MC-VM). This MC-VM is simple to use and configure for various platforms. The MC-VM is protected; thus, even if the internal network is compromised, the MC-VM can still maintain “normal” self-protection services thereby defending the host system from cyber attack on-thely.

Increasingly, software needs to dynamically adapt its behavior at run-time in response to changing conditions in the supporting computing infrastructure and in the surrounding physical environment. Adaptability is emerging as a necessary underlying capability, particularly for highly dynamic systems such as context-aware or ubiquitous systems. By automating tasks such as installation, adaptation, or healing, Autonomic Computing envisions computing environments that evolve without the need for human intervention. Even though there is a fair amount of work on architectures and their theoretical design, Autonomic Computing was criticised as being a \hype topic" because very little of it has been implemented fully. Furthermore, given that the autonomic system must change states at runtime and that some of those states may emerge and are much less deterministic, there is a great challenge to provide new guidelines, techniques and tools to help autonomic system development. This thesis shows that building up on the central ideas of Model Driven Development (Models as rst-order citizens) and Software Product Lines (Variability Management) can play a signi cant role as we move towards implementing the key self-management properties associated with autonomic computing. The presented approach encompass systems that are capable of modifying their own behavior with respect to changes in their operating environment, by using variability models as if they were the policies that drive the system's autonomic recon guration at runtime. Under a set of recon guration commands, the components that make up the architecture dynamically cooperate to change the con guration of the architecture to a new con guration. This work also provides the implementation of a Model-Based Recon guration Engine (MoRE) to blend the above ideas. Given a context event, MoRE queries the variability models to determine how the system should evolve, and then it provides the mechanisms for modifying the system. / Cetina Englada, C. (2010). Achieving Autonomic Computing through the Use of Variability Models at Run-time [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/7484

La communication Machine-to-Machine (M2M) est l'un des principaux fondements de l'Internet des Objets (IoT). C'est un phénomène qui a évolué discrètement au cours du temps et vient d’émerger à la surface pour do! nner naissance à une explosion de nouveaux usages et services. Capteurs, actionneurs, tags, véhicules et objets intelligents ont tous la possibilité de communiquer. Le nombre de connexions M2M est en constante augmentation et il est prévu de voir des milliards d’objets connectés dans un futur proche. Les applications M2M offrent des avantages dans divers domaines à savoir les villes intelligentes, les voitures connectées, les usines du futures, l’agriculture de précision, l’environnement, la santé, etc. La croissance rapide de cet écosystème est entrain de conduire le M2M vers un avenir prometteur. Cependant, les opportunités d'expansion des marchés M2M ne sont pas évidentes. En effet, un ensemble de challenges doivent être surmontés afin de permettre un déploiement à grande échelle dans des domaines diverses et variés à savoir les défis d’interopérabilité, de complexité et de scalabilité. Actuellement, le marché du M2M souffre d'une fragmentation verticale importante touchant la majorité des domaines industriels. En effet, diverses solutions propriétaires ont été conçues pour répondre à des applications spécifiques engendrant ainsi un sérieux problème d''interopérabilité. Pour adresser ce challenge, nous avons conçu, développer et expérimenté la plateforme OM2M offrant une architecture opérationnelle, flexible et extensible pour l'interopérabilité M2M conforme à la norme SmartM2M. Pour supporter les environnements contraints, nous avons proposé une nouvelle convention de nommage basée sur une structure de ressources non-hiérarchique permettant d’optimiser la taille des messages échangés. Pour assurer l’interopérabilité sémantique entre les applications et les machines, nous avons proposé l'ontologie IoT-O. Cette dernière est composée de cinq modèles de base représentant les capteurs, les actionneurs, les observations, les actuations et les web ! services pour permettre de converger rapidement vers un vocabulaire commun pour l'IoT. Une plateforme M2M horizontale permet d'interconnecter des machines hétérogènes largement distribués et qui évoluent fréquemment en fonction des changements de l’environnement. Maintenir ces systèmes complexes en vie est coûteux en termes de temps et d'argent. Pour adresser ce challenge, nous avons conçu, développé et intégré le framework FRAMESELF afin d'ajouter des capacités d'autogestion aux systèmes M2M basées sur le paradigme de l'informatique autonome. En étendant le modèle d'architecture de référence MAPE-K, notre solution permet d'adapter dynamiquement le comportement de la plateforme OM2M par en fonctions des changements du contexte et des politiques haut niveaux. Nous avons défini un ensemble de règles sémantiques pour faire du raisonnement sur l'ontologie IoT-O en tant que modèle de connaissance. Notre objectif est de permettre la découverte automatique entre les machines et les applications à travers un appariement sémantique et une reconfiguration dynam! ique de l'architecture des ressources. L’interopérabilité et l’autogestion ouvrent la voie à un déploiement de masse des systèmes M2M. Par contre, ces derniers se basent sur l'infrastructure actuelle d'internet qui n'a jamais été conçu pour ce genre de d'utilisation ce qui pose de nouvelles exigences en termes de scalabilité. Pour adresser ce challenge, nous avons conçu, simulé et validé l'approche OSCL proposant une nouvelle topologie de réseau maillé M2M comme alternative à l'approche centralisée actuelle. OSCL s'appuie sur les techniques de routage centrées sur l'information favorisant les communications à sauts multiples et un cache distribué pour une meilleure dissémination des données. Nous avons développé le simulateur OSCLsim pour valider l'approche proposée.[...] / Machine-to-Machine (M2M) is one of the main features of Internet of Things (IoT). It is a phenomenon that has been proceeding quietly in the background, and it is coming into the surface, where explosion of usage scenarios in businesses will happen. Sensors, actuators, tags, vehicles, and intelligent things all have the ability to communicate. The number of M2M connections is continuously increasing, and it has been predicted to see billions of machines interconnected in a near future. M2M applications provide advantages in various domains from smart cities, factories of the future, connected cars, home automation, e-health to precision agriculture. This fast-growing ecosystem is leading M2M towards a promising future. However, M2M market expansion opportunities are not straightforward. A set of challenges should be overcome to enable M2M mass-scale deployment across various industries including interoperability, complexity, and scalability issues. Currently, the M2M market is suffering from a high vertical fragmentation affecting the majority of business sectors. In fact, various vendor-specific M2M solutions have been designed independently for specific applications, which led to serious interoperability issues. To address this challenge, we designed, implemented, and experimented with the OM2M platform offering a flexible and extensible operational architecture for M2M interoperability compliant with the SmartM2M standard. To support constrained environments, we proposed an efficient naming convention relying on a non-hierarchical resource structure to reduce the payload size. To reduce the semantic gap between applications and machines, we proposed the IoT-O ontology for an effective semantic interoperability. IoT-O consists of five main parts, which are sensor, actuator, observation, actuation and service models and aims to quickly converge to a common IoT vocabulary. An interoperable M2M service platform enables one to interconnect heterogeneous devices that are widely distributed and frequently evolving according to their environment changes. Keeping M2M systems alive is costly in terms of time and money. To address this challenge, we designed, implemented, and integrated the FRAMESELF framework to retrofit self-management capabilities in M2M systems based on the autonomic computing paradigm. Extending the MAPE-K reference architecture model, FRAMESELF enables one to dynamically adapt the OM2M system behavior according to high level policies how the environment changes. We defined a set of semantic rules for reasoning about the IoT-O ontology as a knowledge model. Our goal is to enable automatic discovery of machines and applications through dynamic reconfiguration of resource architectures. Interoperability and self-management pave the way to mass-scale deployment of M2M devices. However, current M2M systems rely on current internet infrastructure, which was never designed to address such requirements, thus raising new requirements in term of scalability. To address this challenge, we designed, simulated and validated the OSCL overlay approach, a new M2M meshed network topology as an alternative to the current centralized approach. OSCL relies on the Named Data Networking (NDN) technique and supports multi-hop communication and distributed caching 5 to optimize networking and enhance data dissemination. We developed the OSCLsim simulator to validate the proposed approach. Finally, a theoretical model based on random graphs is formulated to describe the evolution and robustness of the proposed system.

This thesis investigates the application of autonomic management to a distributed storage system. Effects on performance and resource consumption were measured in experiments, which were carried out in a local area test-bed. The experiments were conducted with components of one specific distributed storage system, but seek to be applicable to a wide range of such systems, in particular those exposed to varying conditions. The perceived characteristics of distributed storage systems depend on their configuration parameters and on various dynamic conditions. For a given set of conditions, one specific configuration may be better than another with respect to measures such as resource consumption and performance. Here, configuration parameter values were set dynamically and the results compared with a static configuration. It was hypothesised that under non-changing conditions this would allow the system to converge on a configuration that was more suitable than any that could be set a priori. Furthermore, the system could react to a change in conditions by adopting a more appropriate configuration. Autonomic management was applied to the peer-to-peer (P2P) and data retrieval components of ASA, a distributed storage system. The effects were measured experimentally for various workload and churn patterns. The management policies and mechanisms were implemented using a generic autonomic management framework developed during this work. The motivation for both groups of experiments was to test management policies with the objective to avoid unsatisfactory situations with respect to resource consumption and performance. Such unsatisfactory situations occur when either the P2P layer or the data retrieval mechanism is configured statically. In a statically configured P2P system two unsatisfactory situations can be identified. The first arises when the frequency with which P2P node states are verified is low and membership churn is high. The P2P node state becomes inaccurate due to a high membership churn, leading to errors during the routing process and a reduction in performance. In this situation it is desirable to increase the frequency to increase P2P state accuracy. The converse situation arises when the frequency is high and churn is low. In this situation network resources are used unnecessarily, which may also reduce performance, making it desirable to decrease the frequency. In ASA’s data retrieval mechanism similar unsatisfactory situations can be identified with respect to the degree of concurrency (DOC). The DOC controls the eagerness with which multiple redundant replicas are retrieved. An unsatisfactory situation arises when the DOC is low and there is a large variation in the times taken to retrieve replicas. In this situation it is desirable to increase the DOC, because by retrieving more replicas in parallel a result can be returned to the user sooner. The converse situation arises when the DOC is high, there is little variation in retrieval time and there is a network bottleneck close to the requesting client. In this situation it is desirable to decrease the DOC, since the low variation removes any benefit in parallel retrieval, and the bottleneck means that decreasing parallelism reduces both bandwidth consumption and elapsed time for the user. The experimental evaluations of autonomic management show promising results, and suggest several future research topics. These include optimisations of the managed mechanisms, alternative management policies, different evaluation methods, and the application of developed management mechanisms to other facets of a distributed storage system. The findings of this thesis could be exploited in building other distributed storage systems that focus on harnessing storage on user workstations, since these are particularly likely to be exposed to varying, unpredictable conditions.

Les vingt dernières années ont vu l’émergence de systèmes sans fil dans la vie de tous les jours. Ils ont rendu possible la création de technologies telles que les téléphones portables, le WiFi ou l’internet mobile qui sont maintenant tenus pour acquis dans la société actuelle. L’impact environnemental des technologies de l’information et des communications connaît une croissance exponentielle et a atteint l’impact de l’industrie du transport aérien. L’initiative d’informatique verte a été lancée en réponse à cette observation pour réduire de 15 à 30% les émissions de gaz à effet de serre en 2020 comparé aux prédictions faites en 2002 afin de garder le réchauffement climatique inférieur à 2°C. Dans cette thèse, nous avons étudié des techniques d’économie d’énergie dans les réseaux sans fil et comment elles interagissent entre elles afin de donner une vue holistique des réseaux verts. Nous prenons également en compte l’usage du spectre radio fréquence qui est le moyen le plus utilisé pour les communications entre systèmes sans fil et qui devient une ressource rare à cause du besoin grandissant de notre société pour de la bande passante en mobilité. Cette thèse suit les couches réseaux avant de remonter les piles matérielleset logicielles. Des contributions ont été apportées à la plupart des couches afin de proposer un réseau sans fil autonome où les noeuds peuvent collaborer pour améliorer les performances du réseau, réduire de façon globale l’utilisation du spectre radio tout en limitant la consommation énergétique du réseau. / The last twenty years saw the emergence of wireless systems in everyday’s life. They made possible technologies such as mobile phones, WiFi or mobile Internet which are now taken for granted in today’s society. The environmental impact of Information and Communications Technology (ICT) has been raising exponentially to equate the impact of the airline industry. The green computing initiative has been created in response to this observation in order to meet the 15%-30% reduction in green-house gases by 2020 compared to estimations made in 2002 to keep the global temperature increasebelow 2°C. In this thesis, we studied power-saving techniques in wireless networks and how they interact with each others to provide a holistic view of green networking. We also take into account the radio frequency resource which is the most commonly usedcommunication medium for wireless systems and is becoming a scarce resource due to our society’s ever-increasing need for mobile bandwidth. This thesis goes down the network stacks before going up the hardware and software stack. Contributions have been madeat most layers in order to propose an autonomic wireless network where nodes can work collaboratively to improve the network’s performance, globally reduce the radio frequency spectrum usage while also increasing their battery life.

This dissertation introduces, implements, and evaluates the novel concept of "Service Paths", which are system-level abstractions that capture and describe the dynamic dependencies between the different components of a distributed enterprise application. Service paths are dynamic because they capture the natural interactions between application services dynamically composed to offer some desired end user functionality. Service paths are distributed because such sets of services run on networked machines in distributed enterprise data centers. Service paths cross multiple levels of abstraction because they link end user application components like web browsers with system services like http providing communications with embedded services like hardware-supported data encryption. Service paths are system-level abstractions that are created without end user, application, or middleware input, but despite these facts, they are able to capture application-relevant performance metrics, including end-to-end latencies for client requests and the contributions to these latencies from application-level processes and from software/hardware resources like protocol stacks or network devices. Beyond conceiving of service paths and demonstrating their utility, this thesis makes three concrete technical contributions. First, we propose a set of signal analysis techniques called ``E2Eprof' that identify the service paths taken by different request classes across a distributed IT infrastructure and the time spent in each such path. It uses a novel algorithm called ``pathmap' that computes the correlation between the message arrival and departure timestamps at each participating node and detect dependencies among them. A second contribution is a system-level monitoring toolkit called ``SysProf', which captures monitoring information at different levels of granularity, ranging from tracking the system-level activities triggered by a single system call, to capturing the client-server interactions associated with a service paths, to characterizing the server resources consumed by sets of clients or client behaviors. The third contribution of the thesis is a publish-subscribe based monitoring data delivery framework called ``QMON'. QMON offers high levels of predictability for service delivery and supports utility-aware monitoring while also able to differentiate between different levels of service for monitoring, corresponding to the different classes of SLAs maintained for applications.