Processo de desenvolvimento e difusão de cloud computing: estudo sobre as redes de colaboração no Brasil

Com base no relatório de Projecto III para o Programa Doutoral em Avaliação de Tecnologia (2011-2012)

Cloud computing adoption - Determinants of cloud computing adoption by firms

Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Estatística e Gestão de Informação

Printed electronics for ubiquitous computing applications

Dissertação para obtenção do Grau de Doutor em Química

Chemical approaches to ubiquitous computing

Dissertação apresentada para obtenção do Grau de Doutor em Química, perfil de Química Física, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

Mainroad: Cloud computing

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

Estimating data divergence in cloud computing storage systems

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

Evaluation of pathogenic potential of Aeromonas spp. strains using in vitro methodologies

Dissertation to obtain a Master Degree in Molecular Genetics and Biomedicine

Personalization platform for multimodal ubiquitous computing applications

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

Transparency in project bond ratings: Assessment of rating methodologies and development of a proven rating simulator

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics

Narrative Bifurcation, Cloud Computing Interfaces and Hitchcok

From a narratological perspective, this paper aims to address the theoretical issues concerning the functioning of the so called «narrative bifurcation» in data presentation and information retrieval. Its use in cyberspace calls for a reassessment as a storytelling device. Films have shown its fundamental role for the creation of suspense. Interactive fiction and games have unveiled the possibility of plots with multiple choices, giving continuity to cinema split-screen experiences. Using practical examples, this paper will show how this storytelling tool returns to its primitive form and ends up by conditioning cloud computing interface design.

Heterogeneous computing with an algorithmic skeleton framework

The Graphics Processing Unit (GPU) is present in almost every modern day personal computer. Despite its specific purpose design, they have been increasingly used for general computations with very good results. Hence, there is a growing effort from the community to seamlessly integrate this kind of devices in everyday computing. However, to fully exploit the potential of a system comprising GPUs and CPUs, these devices should be presented to the programmer as a single platform. The efficient combination of the power of CPU and GPU devices is highly dependent on each device’s characteristics, resulting in platform specific applications that cannot be ported to different systems. Also, the most efficient work balance among devices is highly dependable on the computations to be performed and respective data sizes. In this work, we propose a solution for heterogeneous environments based on the abstraction level provided by algorithmic skeletons. Our goal is to take full advantage of the power of all CPU and GPU devices present in a system, without the need for different kernel implementations nor explicit work-distribution.To that end, we extended Marrow, an algorithmic skeleton framework for multi-GPUs, to support CPU computations and efficiently balance the work-load between devices. Our approach is based on an offline training execution that identifies the ideal work balance and platform configurations for a given application and input data size. The evaluation of this work shows that the combination of CPU and GPU devices can significantly boost the performance of our benchmarks in the tested environments, when compared to GPU-only executions.

Optimization of breast tomosynthesis image reconstruction using parallel computing

Breast cancer is the most common cancer among women, being a major public health problem. Worldwide, X-ray mammography is the current gold-standard for medical imaging of breast cancer. However, it has associated some well-known limitations. The false-negative rates, up to 66% in symptomatic women, and the false-positive rates, up to 60%, are a continued source of concern and debate. These drawbacks prompt the development of other imaging techniques for breast cancer detection, in which Digital Breast Tomosynthesis (DBT) is included. DBT is a 3D radiographic technique that reduces the obscuring effect of tissue overlap and appears to address both issues of false-negative and false-positive rates. The 3D images in DBT are only achieved through image reconstruction methods. These methods play an important role in a clinical setting since there is a need to implement a reconstruction process that is both accurate and fast. This dissertation deals with the optimization of iterative algorithms, with parallel computing through an implementation on Graphics Processing Units (GPUs) to make the 3D reconstruction faster using Compute Unified Device Architecture (CUDA). Iterative algorithms have shown to produce the highest quality DBT images, but since they are computationally intensive, their clinical use is currently rejected. These algorithms have the potential to reduce patient dose in DBT scans. A method of integrating CUDA in Interactive Data Language (IDL) is proposed in order to accelerate the DBT image reconstructions. This method has never been attempted before for DBT. In this work the system matrix calculation, the most computationally expensive part of iterative algorithms, is accelerated. A speedup of 1.6 is achieved proving the fact that GPUs can accelerate the IDL implementation.

A new MDA-SOA based framework for intercloud interoperability

Cloud computing has been one of the most important topics in Information Technology which aims to assure scalable and reliable on-demand services over the Internet. The expansion of the application scope of cloud services would require cooperation between clouds from different providers that have heterogeneous functionalities. This collaboration between different cloud vendors can provide better Quality of Services (QoS) at the lower price. However, current cloud systems have been developed without concerns of seamless cloud interconnection, and actually they do not support intercloud interoperability to enable collaboration between cloud service providers. Hence, the PhD work is motivated to address interoperability issue between cloud providers as a challenging research objective. This thesis proposes a new framework which supports inter-cloud interoperability in a heterogeneous computing resource cloud environment with the goal of dispatching the workload to the most effective clouds available at runtime. Analysing different methodologies that have been applied to resolve various problem scenarios related to interoperability lead us to exploit Model Driven Architecture (MDA) and Service Oriented Architecture (SOA) methods as appropriate approaches for our inter-cloud framework. Moreover, since distributing the operations in a cloud-based environment is a nondeterministic polynomial time (NP-complete) problem, a Genetic Algorithm (GA) based job scheduler proposed as a part of interoperability framework, offering workload migration with the best performance at the least cost. A new Agent Based Simulation (ABS) approach is proposed to model the inter-cloud environment with three types of agents: Cloud Subscriber agent, Cloud Provider agent, and Job agent. The ABS model is proposed to evaluate the proposed framework.

Identificação das práticas de inovação aberta nas parcerias estratégicas: avaliação realizada com prestadores de cloud computing

No atual contexto da inovação, um grande número de estudos tem analisado o potencial do modelo de Inovação Aberta. Neste sentido, o autor Henry Chesbrough (2003) considerado o pai da Inovação Aberta, afirma que as empresas estão vivenciando uma “mudança de paradigma” na maneira como desenvolvem os seus processos de inovação e na comercialização de tecnologia e conhecimento. Desta forma, o modelo de Inovação Aberta defende que as empresas podem e devem utilizar os recursos disponíveis fora das suas fronteiras sendo esta combinação de ideias e tecnologias internas e externas crucial para atingir uma posição de liderança no mercado. Já afirmava Chesbrough (2003) que não se faz inovação isoladamente e o próprio dinamismo do cenário atual reforça esta ideia. Assim, os riscos inerentes ao processo de inovação podem ser atenuados através da realização de parcerias entre empresas e instituições. A adoção do modelo de Inovação Aberta é percebida com base na abundância de conhecimento disponível, que poderá proporcionar valor também à empresa que o criou, como é o caso do licenciamento de patentes. O presente estudo teve como objetivo identificar as práticas de Inovação Aberta entre as parcerias mencionadas pelas empresas prestadoras de Cloud Computing. Através da Análise de Redes Sociais foram construídas matrizes referentes às parcerias mencionadas pelas empresas e informações obtidas em fontes secundárias (Sousa, 2012). Essas matrizes de relacionamento (redes) foram analisadas e representadas através de diagramas. Desta forma, foi possível traçar um panorama das parcerias consideradas estratégicas pelas empresas entrevistadas e identificar quais delas constituem, de fato, práticas de Inovação Aberta. Do total de 26 parcerias estratégicas mencionadas nas entrevistas, apenas 11 foram caracterizadas como práticas do modelo aberto. A análise das práticas conduzidas pelas empresas entrevistadas permite verificar algumas limitações no aproveitamento do modelo de Inovação Aberta. Por fim, são feitas algumas recomendações sobre a implementação deste modelo pelas pequenas e médias empresas baseadas em tecnologias emergentes, como é o caso do conceito de cloud computing.

Marine Protected Areas (MPAs): Methodologies for assessment

Marine Protected Areas are an effective way of protecting biodiversity, with potential socio-economic benefits including the enhancement of local fisheries and maintenance of ecosystem services. However, local fishing communities often fear short-term revenue losses and thus may oppose marine protected areas creation. This work includes a review of the need of having management effectiveness evaluation and its importance in providing useful information for stakeholders. Therefore, evaluation methodologies are presented and assessed in order to suggest possible approaches to the Berlengas MPA. In this case, an indicator-based approach can be relevant as a starting point, providing already some insights about the management effectiveness of Berlengas MPA. It also supports the development of a more ambitious approach such as a bio-economic model.