943 resultados para Computação distribuída
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BRITTO, Ricardo S.; MEDEIROS, Adelardo A. D.; ALSINA, Pablo J. Uma arquitetura distribuída de hardware e software para controle de um robô móvel autônomo. In: SIMPÓSIO BRASILEIRO DE AUTOMAÇÃO INTELIGENTE,8., 2007, Florianópolis. Anais... Florianópolis: SBAI, 2007.
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The progresses of the Internet and telecommunications have been changing the concepts of Information Technology IT, especially with regard to outsourcing services, where organizations seek cost-cutting and a better focus on the business. Along with the development of that outsourcing, a new model named Cloud Computing (CC) evolved. It proposes to migrate to the Internet both data processing and information storing. Among the key points of Cloud Computing are included cost-cutting, benefits, risks and the IT paradigms changes. Nonetheless, the adoption of that model brings forth some difficulties to decision-making, by IT managers, mainly with regard to which solutions may go to the cloud, and which service providers are more appropriate to the Organization s reality. The research has as its overall aim to apply the AHP Method (Analytic Hierarchic Process) to decision-making in Cloud Computing. There to, the utilized methodology was the exploratory kind and a study of case applied to a nationwide organization (Federation of Industries of RN). The data collection was performed through two structured questionnaires answered electronically by IT technicians, and the company s Board of Directors. The analysis of the data was carried out in a qualitative and comparative way, and we utilized the software to AHP method called Web-Hipre. The results we obtained found the importance of applying the AHP method in decision-making towards the adoption of Cloud Computing, mainly because on the occasion the research was carried out the studied company already showed interest and necessity in adopting CC, considering the internal problems with infrastructure and availability of information that the company faces nowadays. The organization sought to adopt CC, however, it had doubt regarding the cloud model and which service provider would better meet their real necessities. The application of the AHP, then, worked as a guiding tool to the choice of the best alternative, which points out the Hybrid Cloud as the ideal choice to start off in Cloud Computing. Considering the following aspects: the layer of Infrastructure as a Service IaaS (Processing and Storage) must stay partly on the Public Cloud and partly in the Private Cloud; the layer of Platform as a Service PaaS (Software Developing and Testing) had preference for the Private Cloud, and the layer of Software as a Service - SaaS (Emails/Applications) divided into emails to the Public Cloud and applications to the Private Cloud. The research also identified the important factors to hiring a Cloud Computing provider
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In this work, we propose a solution to solve the scalability problem found in collaborative, virtual and mixed reality environments of large scale, that use the hierarchical client-server model. Basically, we use a hierarchy of servers. When the capacity of a server is reached, a new server is created as a sun of the first one, and the system load is distributed between them (father and sun). We propose efficient tools and techniques for solving problems inherent to client-server model, as the definition of clusters of users, distribution and redistribution of users through the servers, and some mixing and filtering operations, that are necessary to reduce flow between servers. The new model was tested, in simulation, emulation and in interactive applications that were implemented. The results of these experimentations show enhancements in the traditional, previous models indicating the usability of the proposed in problems of all-to-all communications. This is the case of interactive games and other applications devoted to Internet (including multi-user environments) and interactive applications of the Brazilian Digital Television System, to be developed by the research group. Keywords: large scale virtual environments, interactive digital tv, distributed
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Internet applications such as media streaming, collaborative computing and massive multiplayer are on the rise,. This leads to the need for multicast communication, but unfortunately group communications support based on IP multicast has not been widely adopted due to a combination of technical and non-technical problems. Therefore, a number of different application-layer multicast schemes have been proposed in recent literature to overcome the drawbacks. In addition, these applications often behave as both providers and clients of services, being called peer-topeer applications, and where participants come and go very dynamically. Thus, servercentric architectures for membership management have well-known problems related to scalability and fault-tolerance, and even peer-to-peer traditional solutions need to have some mechanism that takes into account member's volatility. The idea of location awareness distributes the participants in the overlay network according to their proximity in the underlying network allowing a better performance. Given this context, this thesis proposes an application layer multicast protocol, called LAALM, which takes into account the actual network topology in the assembly process of the overlay network. The membership algorithm uses a new metric, IPXY, to provide location awareness through the processing of local information, and it was implemented using a distributed shared and bi-directional tree. The algorithm also has a sub-optimal heuristic to minimize the cost of membership process. The protocol has been evaluated in two ways. First, through an own simulator developed in this work, where we evaluated the quality of distribution tree by metrics such as outdegree and path length. Second, reallife scenarios were built in the ns-3 network simulator where we evaluated the network protocol performance by metrics such as stress, stretch, time to first packet and reconfiguration group time
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The frequency selective surfaces, or FSS (Frequency Selective Surfaces), are structures consisting of periodic arrays of conductive elements, called patches, which are usually very thin and they are printed on dielectric layers, or by openings perforated on very thin metallic surfaces, for applications in bands of microwave and millimeter waves. These structures are often used in aircraft, missiles, satellites, radomes, antennae reflector, high gain antennas and microwave ovens, for example. The use of these structures has as main objective filter frequency bands that can be broadcast or rejection, depending on the specificity of the required application. In turn, the modern communication systems such as GSM (Global System for Mobile Communications), RFID (Radio Frequency Identification), Bluetooth, Wi-Fi and WiMAX, whose services are highly demanded by society, have required the development of antennas having, as its main features, and low cost profile, and reduced dimensions and weight. In this context, the microstrip antenna is presented as an excellent choice for communications systems today, because (in addition to meeting the requirements mentioned intrinsically) planar structures are easy to manufacture and integration with other components in microwave circuits. Consequently, the analysis and synthesis of these devices mainly, due to the high possibility of shapes, size and frequency of its elements has been carried out by full-wave models, such as the finite element method, the method of moments and finite difference time domain. However, these methods require an accurate despite great computational effort. In this context, computational intelligence (CI) has been used successfully in the design and optimization of microwave planar structures, as an auxiliary tool and very appropriate, given the complexity of the geometry of the antennas and the FSS considered. The computational intelligence is inspired by natural phenomena such as learning, perception and decision, using techniques such as artificial neural networks, fuzzy logic, fractal geometry and evolutionary computation. This work makes a study of application of computational intelligence using meta-heuristics such as genetic algorithms and swarm intelligence optimization of antennas and frequency selective surfaces. Genetic algorithms are computational search methods based on the theory of natural selection proposed by Darwin and genetics used to solve complex problems, eg, problems where the search space grows with the size of the problem. The particle swarm optimization characteristics including the use of intelligence collectively being applied to optimization problems in many areas of research. The main objective of this work is the use of computational intelligence, the analysis and synthesis of antennas and FSS. We considered the structures of a microstrip planar monopole, ring type, and a cross-dipole FSS. We developed algorithms and optimization results obtained for optimized geometries of antennas and FSS considered. To validate results were designed, constructed and measured several prototypes. The measured results showed excellent agreement with the simulated. Moreover, the results obtained in this study were compared to those simulated using a commercial software has been also observed an excellent agreement. Specifically, the efficiency of techniques used were CI evidenced by simulated and measured, aiming at optimizing the bandwidth of an antenna for wideband operation or UWB (Ultra Wideband), using a genetic algorithm and optimizing the bandwidth, by specifying the length of the air gap between two frequency selective surfaces, using an optimization algorithm particle swarm
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
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Image segmentation is one of the image processing problems that deserves special attention from the scientific community. This work studies unsupervised methods to clustering and pattern recognition applicable to medical image segmentation. Natural Computing based methods have shown very attractive in such tasks and are studied here as a way to verify it's applicability in medical image segmentation. This work treats to implement the following methods: GKA (Genetic K-means Algorithm), GFCMA (Genetic FCM Algorithm), PSOKA (PSO and K-means based Clustering Algorithm) and PSOFCM (PSO and FCM based Clustering Algorithm). Besides, as a way to evaluate the results given by the algorithms, clustering validity indexes are used as quantitative measure. Visual and qualitative evaluations are realized also, mainly using data given by the BrainWeb brain simulator as ground truth
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The generation of electricity in Brazil is predominantly renewable, with internal hydraulic generation being more than 70% of its energy matrix. The electricity rationing occurred in 2001 due to lack of rain, led the country to increase the participation of alternative energy sources. This need for new sources of energy makes the regional potential to be exploited, which configures the change of generation model from centralized generation to distributed generation. Among the alternative sources of energy, the solar energy is presented as very promising for Brazil, given that most of its territory is located near to the equator line, which implies days with greater number of hours of solar radiation. The state of Rio Grande do Norte (RN) has one of the highest levels of solar irradiation of the Brazilian territory, making it eligible to receive investments for the installation of photovoltaic solar plants. This thesis will present the state-of-the-art in solar photovoltaic power generation and will examine the potential for generation of solar photovoltaic power in Brazil and RN, based on solarimetrics measurements conducted by various institutions and also measurements performed in Natal, the state capital
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Atualmente há uma grande preocupação em relação a substituição das fontes não renováveis pelas fontes renováveis na geração de energia elétrica. Isto ocorre devido a limitação do modelo tradicional e da crescente demanda. Com o desenvolvimento dos conversores de potência e a eficácia dos esquemas de controle, as fontes renováveis têm sido interligadas na rede elétrica, em um modelo de geração distribuída. Neste sentido, este trabalho apresenta uma estratégia de controle não convencional, com a utilização de um controlador robusto, para a interconexão de sistemas fotovoltaicos com à rede elétrica trifásica. A compensação da qualidade de energia no ponto de acoplamento comum (PAC) é realizada pela estratégia proposta. As técnicas tradicionais utilizam detecção de harmônicos, já neste trabalho o controle das correntes é feita de uma forma indireta sem a necessidade desta detecção. Na estratégia indireta é de grande importância que o controle da tensão do barramento CC seja efetuado de uma forma que não haja grandes flutuações, e que a banda passante do controlador em regime permanente seja baixa para que as correntes da rede não tenham um alto THD. Por este motivo é utilizado um controlador em modo dual DSM-PI, que durante o transitório se comporta como um controlador em modo deslizante SM-PI, e em regime se comporta como um PI convencional. A corrente é alinhada ao ângulo de fase do vetor tensão da rede elétrica, obtido a partir do uso de um PLL. Esta aproximação permite regular o fluxo de potência ativa, juntamente com a compensação dos harmônicos e também promover a correção do fator de potência no ponto de acoplamento comum. Para o controle das correntes é usado um controlador dupla sequencia, que utiliza o princípio do modelo interno. Resultados de simulação são apresentados para demonstrar a eficácia do sistema de controle proposto
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One of the current challenges of Ubiquitous Computing is the development of complex applications, those are more than simple alarms triggered by sensors or simple systems to configure the environment according to user preferences. Those applications are hard to develop since they are composed by services provided by different middleware and it is needed to know the peculiarities of each of them, mainly the communication and context models. This thesis presents OpenCOPI, a platform which integrates various services providers, including context provision middleware. It provides an unified ontology-based context model, as well as an environment that enable easy development of ubiquitous applications via the definition of semantic workflows that contains the abstract description of the application. Those semantic workflows are converted into concrete workflows, called execution plans. An execution plan consists of a workflow instance containing activities that are automated by a set of Web services. OpenCOPI supports the automatic Web service selection and composition, enabling the use of services provided by distinct middleware in an independent and transparent way. Moreover, this platform also supports execution adaptation in case of service failures, user mobility and degradation of services quality. The validation of OpenCOPI is performed through the development of case studies, specifically applications of the oil industry. In addition, this work evaluates the overhead introduced by OpenCOPI and compares it with the provided benefits, and the efficiency of OpenCOPI s selection and adaptation mechanism
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The constant increase of complexity in computer applications demands the development of more powerful hardware support for them. With processor's operational frequency reaching its limit, the most viable solution is the use of parallelism. Based on parallelism techniques and the progressive growth in the capacity of transistors integration in a single chip is the concept of MPSoCs (Multi-Processor System-on-Chip). MPSoCs will eventually become a cheaper and faster alternative to supercomputers and clusters, and applications developed for these high performance systems will migrate to computers equipped with MP-SoCs containing dozens to hundreds of computation cores. In particular, applications in the area of oil and natural gas exploration are also characterized by the high processing capacity required and would benefit greatly from these high performance systems. This work intends to evaluate a traditional and complex application of the oil and gas industry known as reservoir simulation, developing a solution with integrated computational systems in a single chip, with hundreds of functional unities. For this, as the STORM (MPSoC Directory-Based Platform) platform already has a shared memory model, a new distributed memory model were developed. Also a message passing library has been developed folowing MPI standard
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In this work will applied the technique of Differential Cryptanalysis, introduced in 1990 by Biham and Shamir, on Papílio s cryptosystem, developed by Karla Ramos, to test and most importantly, to prove its relevance to other block ciphers such as DES, Blowfish and FEAL-N (X). This technique is based on the analysis of differences between plaintext and theirs respective ciphertext, in search of patterns that will assist in the discovery of the subkeys and consequently in the discovery of master key. These differences are obtained by XOR operations. Through this analysis, in addition to obtaining patterns of Pap´ılio, it search to obtain also the main characteristics and behavior of Papilio throughout theirs 16 rounds, identifying and replacing when necessary factors that can be improved in accordance with pre-established definitions of the same, thus providing greater security in the use of his algoritm
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With the advance of the Cloud Computing paradigm, a single service offered by a cloud platform may not be enough to meet all the application requirements. To fulfill such requirements, it may be necessary, instead of a single service, a composition of services that aggregates services provided by different cloud platforms. In order to generate aggregated value for the user, this composition of services provided by several Cloud Computing platforms requires a solution in terms of platforms integration, which encompasses the manipulation of a wide number of noninteroperable APIs and protocols from different platform vendors. In this scenario, this work presents Cloud Integrator, a middleware platform for composing services provided by different Cloud Computing platforms. Besides providing an environment that facilitates the development and execution of applications that use such services, Cloud Integrator works as a mediator by providing mechanisms for building applications through composition and selection of semantic Web services that take into account metadata about the services, such as QoS (Quality of Service), prices, etc. Moreover, the proposed middleware platform provides an adaptation mechanism that can be triggered in case of failure or quality degradation of one or more services used by the running application in order to ensure its quality and availability. In this work, through a case study that consists of an application that use services provided by different cloud platforms, Cloud Integrator is evaluated in terms of the efficiency of the performed service composition, selection and adaptation processes, as well as the potential of using this middleware in heterogeneous computational clouds scenarios
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)