A ComputaÃÃo em Nuvem desponta como um paradigma de utilizaÃÃo de recursos computacionais segundo o qual infraestrutura de hardware, software e plataformas para o desenvolvimento de novas aplicaÃÃes sÃo oferecidas como serviÃos disponÃveis em escala global. Tais serviÃos sÃo disponibilizados por meio de datacenters de larga escala onde à recorrente o emprego de tecnologias de virtualizaÃÃo para o uso compartilhado de recursos. Neste contexto, a gerÃncia eficiente da infraestrutura do datacenter pode levar a eduÃÃes significativas de seus custos de operaÃÃo. Este trabalho apresenta uma estratÃgia de gerenciamento de infraestrutura de datacenters virtualizados que aplica tÃcnicas de monitoramento distribuÃdo combinadas a aÃÃes centralizadas de controle. Tal estratÃgia busca diminuir os efeitos de sobrecarga observados em modelos tradicionais de gerÃncia baseados em um nà controlador que acumula responsabilidades de controle e monitoramento. Por conseguinte, busca-se elevar o poder de escalabilidade da infraestrutura e melhorar sua eciÃncia energÃtica sem comprometer a Qualidade de ServiÃo (QoS) oferecida ao usuÃrio final. A anÃlise de desempenho da estratÃgia proposta à realizada atravÃs de mÃltiplos experimentos de simulaÃÃo realizados com ferramentas voltadas especificamente para a modelagem de nuvens computacionais e com suporte à representaÃÃo do consumo energÃtico da infraestrutura simulada.

Future networks will face major challenges in accommodating emerging and future networked applications. These challenges include significant architecture and management issues pertaining to future networks. In this thesis, we study several of these challenges including issues such as configurability, application-awareness, rapid application-creation and deployment and scalable QoS management. To address these challenges, we propose a novel Application-Oriented Network (AON) architecture as a converged computing and communication network in which application providers are able to flexibly configure in-network resources on-demand. The resources in AON are virtualized and offered to the application providers through service-oriented approaches. To enable large-scale experimentation with future network architectures and applications, in the second part of this thesis, we present the Virtualized Application Networking Infrastructure (VANI) as a prototype of an Application-Oriented Network. VANI utilizes a service-oriented control and management plane that provides flexible and dynamic allocation, release, program and configuration of resources used for creating applications or performing network research experiments from layer three and up. Moreover, VANI resources allow development of network architectures that require a converged network of computing and communications resources such as in-network processing, storage and software and hardware-based reprogrammable resources. We also present a Distributed Ethernet Traffic Shaping (DETS) system used in bandwidth virtualization in VANI and designed to guarantee the send and receive Ethernet traffic rates in VANI, in a computing cluster or a datacenter. The third part of this thesis addresses the problem of scalable QoS and admission control in service-oriented environments where a limited number of instances of service components are shared among different application classes. We first use Markov Decision Processes to find optimal solutions to this problem. Next we present a scalable and distributed heuristic algorithm able to guarantee probability of successful completion of a composite application. The proposed algorithm does not assume a specific distribution type for services execution times and applications request inter-arrival times, and hence is suitable for systems with stationary or non-stationary request arrivals. We use simulations and experimental measurements to show the effectiveness of the proposed solutions and algorithms in various parts of this thesis.

Future networks will face major challenges in accommodating emerging and future networked applications. These challenges include significant architecture and management issues pertaining to future networks. In this thesis, we study several of these challenges including issues such as configurability, application-awareness, rapid application-creation and deployment and scalable QoS management. To address these challenges, we propose a novel Application-Oriented Network (AON) architecture as a converged computing and communication network in which application providers are able to flexibly configure in-network resources on-demand. The resources in AON are virtualized and offered to the application providers through service-oriented approaches. To enable large-scale experimentation with future network architectures and applications, in the second part of this thesis, we present the Virtualized Application Networking Infrastructure (VANI) as a prototype of an Application-Oriented Network. VANI utilizes a service-oriented control and management plane that provides flexible and dynamic allocation, release, program and configuration of resources used for creating applications or performing network research experiments from layer three and up. Moreover, VANI resources allow development of network architectures that require a converged network of computing and communications resources such as in-network processing, storage and software and hardware-based reprogrammable resources. We also present a Distributed Ethernet Traffic Shaping (DETS) system used in bandwidth virtualization in VANI and designed to guarantee the send and receive Ethernet traffic rates in VANI, in a computing cluster or a datacenter. The third part of this thesis addresses the problem of scalable QoS and admission control in service-oriented environments where a limited number of instances of service components are shared among different application classes. We first use Markov Decision Processes to find optimal solutions to this problem. Next we present a scalable and distributed heuristic algorithm able to guarantee probability of successful completion of a composite application. The proposed algorithm does not assume a specific distribution type for services execution times and applications request inter-arrival times, and hence is suitable for systems with stationary or non-stationary request arrivals. We use simulations and experimental measurements to show the effectiveness of the proposed solutions and algorithms in various parts of this thesis.

Context Hadoop is an open-source software framework developed for distributed storage and distributed processing of large sets of data. The implementation of the Hadoop MapReduce algorithm on virtualized shared storage by eliminating the concept of Hadoop Distributed File System (HDFS) is a challenging task. In this study, the Hadoop MapReduce algorithm is implemented on the Compuverde software that deals with virtualized shared storage of data. Objectives In this study, the effect of using virtualized shared storage with Hadoop framework is identified. The main objective of this study is to design a method to implement the Hadoop MapReduce algorithm on Compuverde software that deals with virtualized shared storage of big data. Finally, the performance of the MapReduce algorithm on Compuverde shared storage (Compuverde File System - CVFS) is evaluated and compared to the performance of the MapReduce algorithm on HDFS. Methods Initially a literature study is conducted to identify the effect of Hadoop implementation on virtualized shared storage. The Compuverde software is analyzed in detail during this literature study. The concepts of the MapReduce algorithms and the functioning of HDFS are scrutinized in detail. The next main research method that is adapted for this study is the implementation of a method where the Hadoop MapReduce algorithm is applied on the Compuverde software that deals with the virtualized shared storage by eliminating the HDFS. The next step is experimentation in which the performance of the implementation of the MapReduce algorithm on Compuverde shared storage (CVFS) in comparison with implementation of the MapReduce algorithm on Hadoop Distributed File System. Results The experiment is conducted in two different scenarios namely the CPU bound scenario and I/O bound scenario. In CPU bound scenario, the average execution time of WordCount program has a linear growth with respect to size of data set. This linear growth is observed for both the file systems, HDFS and CVFS. The same is the case with I/O bound scenario. There is linear growth for both the file systems. When the averages of execution time are plotted on the graph, both the file systems perform similarly in CPU bound scenario(multi-node environment). In the I/O bound scenario (multi-node environment), HDFS slightly out performs CVFS when the size of 1.0GB and both the file systems performs without much difference when the size of data set is 0.5GB and 1.5GB. Conclusions The MapReduce algorithm can be implemented on live data present in the virtualized shared storage systems without copying data into HDFS. In single node environment, distributed storage systems perform better than shared storage systems. In multi-node environment, when the CPU bound scenario is considered, both HDFS and CVFS file systems perform similarly. On the other hand, HDFS performs slightly better than CVFS for 1.0GB of data set in the I/O bound scenario. Hence we can conclude that distributed storage systems perform similar to the shared storage systems in both CPU bound and I/O bound scenarios in multi-node environment.

Combining human welder (with intelligence and sensing versatility) and automated welding robots (with precision and consistency) can lead to next generation intelligent welding systems. In this dissertation intelligent welding robots are developed by process modeling / control method and learning the human welder behavior. Weld penetration and 3D weld pool surface are first accurately controlled for an automated Gas Tungsten Arc Welding (GTAW) machine. Closed-form model predictive control (MPC) algorithm is derived for real-time welding applications. Skilled welder response to 3D weld pool surface by adjusting the welding current is then modeled using Adaptive Neuro-Fuzzy Inference System (ANFIS), and compared to the novice welder. Automated welding experiments confirm the effectiveness of the proposed human response model. A virtualized welding system is then developed that enables transferring the human knowledge into a welding robot. The learning of human welder movement (i.e., welding speed) is first realized with Virtual Reality (VR) enhancement using iterative K-means based local ANFIS modeling. As a separate effort, the learning is performed without VR enhancement utilizing a fuzzy classifier to rank the data and only preserve the high ranking “correct” response. The trained supervised ANFIS model is transferred to the welding robot and the performance of the controller is examined. A fuzzy weighting based data fusion approach to combine multiple machine and human intelligent models is proposed. The data fusion model can outperform individual machine-based control algorithm and welder intelligence-based models (with and without VR enhancement). Finally a data-driven approach is proposed to model human welder adjustments in 3D (including welding speed, arc length, and torch orientations). Teleoperated training experiments are conducted in which a human welder tries to adjust the torch movements in 3D based on his observation on the real-time weld pool image feedback. The data is off-line rated by the welder and a welder rating system is synthesized. ANFIS model is then proposed to correlate the 3D weld pool characteristic parameters and welder’s torch movements. A foundation is thus established to rapidly extract human intelligence and transfer such intelligence into welding robots.

As businesses are increasingly relying on the cloud to host their services, cloud providers are striving to offer guaranteed and highly-available resources. To achieve this goal, recent proposals have advocated to offer both computing and networking resources in the form of Virtual Data Centers (VDCs). However, to offer VDCs, cloud providers have to overcome several technical challenges. In this thesis, we focus on two key challenges: (1) the VDC embedding problem: how to efficiently allocate resources to VDCs such that energy costs and bandwidth consumption are minimized, and (2) the availability-aware VDC embedding and backup provisioning problem which aims at allocating resources to VDCs with hard guarantees on their availability. The first part of this thesis is primarily concerned with the first challenge. The goal of the VDC embedding problem is to allocate resources to VDCs while minimizing the bandwidth usage in the data center and maximizing the cloud provider's revenue. Existing proposals have focused only on the placement of VMs and ignored mapping of other types of resources like switches. Hence, we propose a new VDC embedding solution that explicitly considers the embedding of virtual switches in addition to virtual machines and communication links. Simulations show that our solution results in high acceptance rate of VDC requests, less bandwidth consumption in the data center network, and increased revenue for the cloud provider. In the second part of this thesis, we study the availability-aware VDC embedding and backup provisioning problem. The goal is to provision virtual backup nodes and links in order to achieve the desired availability for each VDC. Existing solutions addressing this challenge have overlooked the heterogeneity of the data center equipment in terms of failure rates and availability. To address this limitation, we propose a High-availability Virtual Infrastructure (Hi-VI) management framework that jointly allocates resources for VDCs and their backups while minimizing total energy costs. Hi-VI uses a novel technique to compute the availability of a VDC that considers both (1) the heterogeneity of the data center networking and computing equipment, and (2) the number of redundant virtual nodes and links provisioned as backups. Simulations demonstrate the effectiveness of our framework compared to heterogeneity-oblivious solutions in terms of revenue and the number of physical servers used to embed VDCs.

Multi-core technology is bringing parallel processing capabilities from servers to laptops and even handheld devices. At the same time, platform support for system virtualization is making it easier to consolidate server and client resources, when and as needed by applications. This consolidation is achieved by dynamically mapping the virtual machines on which applications run to underlying physical machines and their processing cores. Low cost processor and I/O virtualization methods efficiently scaled to different numbers of processing cores and I/O devices are key enablers of such consolidation. This dissertation develops and evaluates new methods for scaling virtualization functionality to multi-core and future many-core systems. Specifically, it re-architects virtualization functionality to improve scalability and better exploit multi-core system resources. Results from this work include a self-virtualized I/O abstraction, which virtualizes I/O so as to flexibly use different platforms' processing and I/O resources. Flexibility affords improved performance and resource usage and most importantly, better scalability than that offered by current I/O virtualization solutions. Further, by describing system virtualization as a service provided to virtual machines and the underlying computing platform, this service can be enhanced to provide new and innovative functionality. For example, a virtual device may provide obfuscated data to guest operating systems to maintain data privacy; it could mask differences in device APIs or properties to deal with heterogeneous underlying resources; or it could control access to data based on the ``trust' properties of the guest VM. This thesis demonstrates that extended virtualization services are superior to existing operating system or user-level implementations of such functionality, for multiple reasons. First, this solution technique makes more efficient use of key performance-limiting resource in multi-core systems, which are memory and I/O bandwidth. Second, this solution technique better exploits the parallelism inherent in multi-core architectures and exhibits good scalability properties, in part because at the hypervisor level, there is greater control in precisely which and how resources are used to realize extended virtualization services. Improved control over resource usage makes it possible to provide value-added functionalities for both guest VMs and the platform. Specific instances of virtualization services described in this thesis are the network virtualization service that exploits heterogeneous processing cores, a storage virtualization service that provides location transparent access to block devices by extending the functionality provided by network virtualization service, a multimedia virtualization service that allows efficient media device sharing based on semantic information, and an object-based storage service with enhanced access control.

Aus der Einführung: "Im Bereich der Informations- und Kommunikationstechnologien und im wissensintensiven Sektor finden sich häufig netzwerkartige Organisationsstrukturen, die durch informale Arbeitsorganisation und eine starke Betonung integrierter Kooperation unter Ausbildung unterschiedlicher Spezialisierungen [2] gekennzeichnet sind. Begleitet wird dieses Phänomen der Entgrenzung durch die Virtualisierung von Arbeitsplätzen oder Bürostandorten [15]. Ausgehend von der These, dass sich Organisationsformen von den traditionellen Formen hin zu kooperativen Strukturen fortentwickeln, schlagen wir vor, dass vor allem kreative und wissensintensive Prozesse durch Software unterstützt werden, welche die Besonderheiten dieser Arbeitsprozesse berücksichtigen."

Ces dernières années, les fournisseurs de cloud et les centres de données ont intégrés les FPGA dans leur environnement à des fins d'accélération. Cela est dû au fait que les accélérateurs à base de FPGA sont connus pour leur faible puissance et leurs bonnes performances par watt. En outre, l'introduction de la capacité de reconfiguration partielle dynamique (DPR) de certains FPGA incite les chercheurs de l'industrie et des universitaires à proposer des services de cloud FPGA virtualisés baser sur DPR. Dans la plupart des travaux existants, l'interconnexion entre les vFPGA repose soit sur les réseaux BUS ou OpenFlow. Cependant le bus et OpenFlow ne sont pas des solutions optimales pour la virtualisation.Dans cette thèse, nous avons proposé un NoC évolutif à l'exécution pour les accélérateurs basés sur FPGA virtualisés dans un cloud computing. Les composants NoC s'adapteront dynamiquement aux nombres d'accélérateurs virtualisés actifs en ajoutant et en supprimant des sous-noC. Pour minimiser la complexité de la conception de l'architecture NoC à un niveau inférieur (implémentation HDL), nous avons proposé un langage de modélisation unifié de haut niveau (UML) basé sur une ingénierie dirigée par les modèles. Une approche basée sur UML / MARTE et IP-XACT est utilisée pour définir les composants de la topologie NoC de haut niveau et générer les fichiers HDL requis. Les résultats des expériences montrent que le NoC évolutif à l'exécution peut réduire la consommation d'énergie de 17%. La caractérisation NoC sur la modélisation de haut niveau basée sur MDE réduit également le temps de conception de 25%. / In the last few years, cloud providers and data centers have been integrating FPGAs in their environment for acceleration purpose. This is due to the fact that FPGA based accelerator are known for their lower power and good performance per watt. Moreover, the introduction of the ability for dynamic partial reconfiguration (DPR) of some FPGAs trigger researchers in both industry and academics to propose DPR based virtualized FPGA (vFPGA) cloud services. In most of the existing works, the interconnection between the vFPGAs relies either on BUS or OpenFlow networks. However, both the bus and OpenFlow are not virtualization-aware and optimal solutions. In this thesis, we have proposed a virtualization-aware dynamically scalable NoC for virtualized FPGA accelerators in cloud computing. The NoC components will adapt to the number of active virtualized accelerator dynamically by adding and removing sub-NoCs. To minimize the complexity of NoC architecture design at a low level (HDL implementation), we have proposed a Model-Driven Engineering (MDE) based high-level unified modeling language (UML). A UML/MARTE and IP-XACT based approach are used to define the NoC Topology components at a high-level and generate the required HDL files. Experiment results show that the dynamically scalable NoC can reduce the power consumption by 17%. The MDE based high-level modeling based NoC characterization also reduce the design time by 25%.

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / A tese tem o objetivo de apresentar a Pedagogia Cemiterial como proposta de ação a ser desenvolvida no ensino básico. A metodologia escolhida fundamenta-se na metanálise de dados do Censo de 2010, referentes ao perfil religioso dos/das adolescentes brasileiros e na pesquisa etnográfica virtual, através do monitoramento de Páginas Comunitárias do Facebook ligadas ao incentivo e extinção do comportamento autolesivo e suicidário entre adolescentes brasileiros (as) de 13-17 anos de idade. A estrutura foi dividida em quatro capítulos distintos. O primeiro apresenta o indivíduo, na fase da adolescência, a partir do modelo bioecológico de Bronfenbrenner e como este se insere nos estágios da fé e o Deus Google. O segundo verifica a percepção de morte e morrer do/da adolescente virtualizado (a), bem como sua interação com as Páginas Comunitárias do Facebook associadas ao incentivo e extinção do comportamento autolesivo. O terceiro analisa a importância do Ensino Religioso como componente curricular compatível ao desenvolvimento do tema da morte e do morrer no espaço escolar através da Pedagogia Cemiterial. Por fim, o último capítulo propõe um modelo de ação para a aplicação da Pedagogia Cemiterial com adolescentes no espaço escolar. / The goal of this dissertation is to present the Cemeterial Pedagogy as a proposal for action to be developed in primary education. The methodology chosen is founded on the meta-analysis of data from the 2010 Census, regarding the religious profile of Brazilian adolescents and on the virtual ethnographic research, through the monitoring of Community Facebook pages connected to the encouragement and extinction of self-injurious and suicidal behavior among Brazilian adolescents ages 13 to 17. The structure was divided into four distinct chapters. The first presents the individual, in the adolescent phase, based on the bio-ecological model of Bronfenbrenner and how this adolescent inserts him/herself in the faith stages and the Google God. The second verifies the perception of death and dying of the virtualized adolescent as well as his or her interaction with Community Facebook pages associated to the encouragement and extinction of self-injurious behavior. The third analyzes the importance of Religious Education as a curricular component that is compatible to the development of the theme of death and dying in the school space through the Cemeterial Pedagogy. Finally, the last chapter proposes a model of action for the application of the Cemeterial Pedagogy with adolescents in the school space.