A Computação em Nuvem (CN) é um dos temas mais abordados por profissionais de TI atualmente. Com um forte apelo econômico, a CN torna possível a ideia da computação como uma utilidade, na qual recursos computacionais (processamento e armazenamento, por exemplo) podem ser consumidos e pagos com a mesma conveniência que a energia elétrica. Com este novo paradigma, uma empresa, ao iniciar suas atividades, não necessita mais investir antecipadamente um alto capital em equipamentos de TI. Os recursos computacionais são adquiridos conforme são necessários e o consumidor paga apenas pelo que utiliza. Esta pesquisa traz uma contribuição para as organizações e para o meio acadêmico, uma vez que analisa a adoção da CN por empresas brasileiras. A pesquisa abrange empresas privadas de diversos portes e setores que tenham adotado pelo menos um serviço de TI no modelo de CN. O modelo de pesquisa foi elaborado com base nos objetivos específicos, os quais se originaram das lacunas existentes sobre o uso de serviços de CN no Brasil. A pesquisa utilizou uma amostra não probabilística contendo 96 casos, os quais contemplaram aspectos do respondente, da organização e do serviço de CN mais importante para a organização. Os dados foram coletados por meio de um questionário e tratados estatisticamente usando técnicas não paramétricas e Análise de Agrupamentos. A pesquisa se caracteriza por ser exploratória, verificando frequências e ligações entre as características organizacionais e os serviços de CN. A pesquisa identificou as características dos serviços de CN utilizados no Brasil e o grau de aderência de cada serviço à definição de CN proposta. Adicionalmente, foram apresentadas as relações entre as características organizacionais e as características dos serviços de CN. Além disso, foi possível identificar três grupos distintos de empresas, em relação às características dos serviços de CN utilizados, e descrever às características organizacionais e dos serviços associados a cada grupo. Finalmente, a CN foi discutida à luz das Teorias de Terceirização. / Cloud Computing (CC) is one of the most discussed topics among IT professionals today. With a strong economic appeal, CC makes possible the idea of computing as a utility, in which computing resources (processing power and storage, for example) can be consumed and paid with the same convenience as electricity. In this new paradigm, a startup company does not need up-front capital to invest in advanced IT assets. The computing resources are acquired as needed and the customer pays only for what is used. This research makes an important contribution to organizations and academia, since it analyzes CC adoption by Brazilian companies. The survey covers private companies of all sizes and sectors that have adopted at least one IT service in CC model. The research model was designed based on the research specific objectives, which were made from the gaps of CC services usage in Brazil. This paper used a not randomly picked sample with 96 cases, which specified aspects of the respondent, organization and the most important CC service to the organization. Data was collected through a questionnaire and statistically analyzed using nonparametric techniques and Cluster Analysis. This research is characterized as exploratory, checking frequencies and links between organizational characteristics and CC services characteristics. This research identified the characteristics of CC services used in Brazil and the compliance degree of each service to the proposed CC definition. Additionally, we presented and discussed the relationships between organizational characteristics and characteristics of CC services. Furthermore, it was possible to identify three distinct groups of companies in relation to the characteristics of CC services they use, and describe organizational characteristics and services associated with each group. Finally, CC was discussed in the light of the Outsourcing Theories.

Introdução: A adoção de um Sistema de Arquivamento e Distribuição de Imagens (PACS, do inglês Picture Archiving and Communication System) é condição fundamental para a estruturação de um ambiente radiológico sem filme. Um PACS é composto basicamente por equipamentos e sistemas informatizados interconectados em rede, direcionados à aquisição, armazenamento (ou arquivamento), recuperação e apresentação de imagens médicas aos especialistas responsáveis por avaliá-las e laudá-las. A computação em nuvem vem ao encontro dos PACS e surge como uma maneira de simplificar o compartilhamento de imagens entre organizações de saúde e promover a virtualização de espaços físicos e para garantir o seu funcionamento ininterrupto.Objetivo: Este estudo teve como objetivo implementar um PACS simplificado em ambiente cloud computing privado, com foco nas funcionalidades de arquivamento e disponibilização de imagens médicas e avaliar questões de segurança e performance. Metodologia: As imagens que compuseram o PACS do ambiente cloud foram obtidas através do PACS físico atualmente em uso no Centro de Ciência das Imagens e Física Médica do Hospital das Clinicas da Faculdade de Medicina de Ribeirão Preto - CCIFM/HCFMRP. Para os procedimentos da avaliação de segurança foram construídos cenários que possibilitavam a: 1) anominização de dados de identificação dos pacientes através de criptografia computacional em base de dados utilizando o algoritmo de criptografia Advanced Encryption Standard - AES, 2) transferência de imagens médicas seguras através de conexão com a Internet utilizando Virtual Network Private - VPN sobre o protocolo Internet Protocol Security - IPSec (VPN/IPSec) e 3) envio seguro através de tunelamento baseado em Secure Shell - SSH. Resultados: Foi identificada uma queda de performance no envio de informações para a nuvem quando submetidos aos níveis de segurança propostos, sugerindo a relação entre aumento de segurança e perda de performance, apontando para a necessidade de estudos de desempenho quando da condução de projetos envolvam a adoção em ambientes clínicos de solução PACS baseada em cloud computing. / Introduction: the adoption of a PCAS (Picture Archiving and Communication System) is fundamental for the structuring of a radiological environment without film. A PACS comprises, essentially, hardware and information systems interconnected in a network, oriented towards acquisition, storage (or archiving), retrieving and presentation of medical images to specialists entrusted with analyzing and assessing them. Cloud computing comes to support of PCAS, simplifying medical imaging sharing between health care organizations and promoting the virtualization of physical infrastructure to assure uninterrupted availability of the PCAS. Goal: This study aimed to implement a simplified PCAS in a private cloud computing environment, and subsequently to evaluate its security and performance. Methodology: The images that formed the new PCAS were obtained from the exiting PCAS of Centro de Ciência das Imagens e Física Médica of Hospital das Clinicas da Faculdade de Medicina de Ribeirão Preto - CCIFM/HCFMRP. To evaluate its security, scenarios were built within the following framework: 1) patient identification data anonymization through computational database cryptography, using the AES (Advanced Encription Standards) algorithm ; 2) transfer of encrypted medical images on the Internet using VPN (Virtual Private Network) over IPSec (Internet Protocol Security); and 3) safe traffic through Secure Shell (SSH) tunneling. Results: There was a performance drop on traffic of information to the cloud under the proposed security levels that suggests a relationship between increase in security and loss of performance, pointing to the need for performance studies when the project involving driving adoption in clinical environments PACS solution based on cloud computing.

Global warming theories continue to overestimate their predictions of increased mean global temperatures (Hudson 1991). This would imply that some other influence is counteracting the global warming influences; i.e. a cooling effect. Cloud albedo characteristics are currently being researched to determine the impact clouds have on the net cooling of the atmosphere in relation to the global warming theory. These characteristics are influenced by the type, size, composition, and abundance of aerosol particles that act as cloud condensation nuclei. This study employs Tandem Differential Mobility Analyzer (TDMA) data collected in the vicinity of Japan during the Asian Aerosol Characterization Experiment (ACE-Asia) to investigate the influence of aerosol concentration and composition on the light scattering properties of clouds. Measurements of particle size (Dp), particle growth factor (GF), and relative humidity (RH) yield critical supersaturations (Sc) with the assumption that the soluble part of the particle is composed primarily of one substance. This indirect composition analysis allows us to determine whether the aerosol was internally mixed (particles have uniform composition and yield a single-peak distribution or similar growth factors) or externally mixed (different particles have different compositions yielding multiple peaks in the distribution). Through the use of calculated supersaturations, we can gain insight into cloud droplet activation properties of the samples for various aerosol types, which ultimately allows us to look at the influence of these particles on albedo characteristics of clouds formed by these particles.

The research presented in this thesis involves the study of ice cloud microphysical and optical properties using both hyperspectral and narrowband infrared spectral data. First, ice cloud models are developed for the Infrared Atmospheric Sounding Interferometer (IASI) instrument onboard the METOP-A satellite, which provide the bulk-scattering properties of these clouds for the 8461 IASI channels between 645 and 2760 cm-1. We investigate the sensitivity of simulated brightness temperatures in this spectral region to the bulk-scattering properties of ice clouds containing individual ice crystal habits as well as for one habit distribution. The second part of this thesis describes an algorithm developed to analyze the sensitivity of simulated brightness temperatures at 8.5 and 11.0 µm to changes in effective cloud temperature by adjusting cloud top height and geometric thickness in a standard tropical atmosphere. Applicability of using these channels in a bi-spectral approach to retrieve cirrus cloud effective particle size and optical thickness is assessed. Finally, the algorithm is applied to the retrieval of these ice cloud properties for a case of single-layered cirrus cloud over a tropical ocean surface using measurements from the Moderate Resolution Infrared Spectroradiometer (MODIS). Cloud top height and geometric thickness in the profile are adjusted to assess the influence of effective cloud temperature on the retrieval.

The growing popularity of multi-tenant, cloud-based computing platforms is increasing interest in resource allocation models that permit flexible sharing of the underlying infrastructure. This thesis introduces a novel IO resource allocation model that better captures the requirements of paying tenants sharing a physical infrastructure. The model addresses a major concern regarding application performance stability when clients migrate from a dedicated to a shared platform. Specifically, while clients would like their applications to behave similarly in both situations, traditional models of fairness, like proportional share allocation, do not exhibit this behavior in the context of modern multi-tiered storage architectures. We also present a scheduling algorithm, the Reward Scheduler, that implements the new allocation policy, by rewarding clients with better runtime characteristics, resulting in benefits to both the clients and the service provider. Moreover, the Reward scheduler also supports weight-based capacity allocation subject to a minimum reservation and maximum limitation on the IO allocation for each task. Experimental results indicate that the proposed algorithm proportionally allocates the system capacity in proportion to their entitlements.

Cloud computing innebär användning av datorresurser som är tillgängliga via ett nätverk, oftast Internet och är ett område som har vuxit fram i snabb takt under de senaste åren. Allt fler företag migrerar hela eller delar av sin verksamhet till molnet. Sogeti i Borlänge har behov av att migrera sina utvecklingsmiljöer till en molntjänst då drift och underhåll av dessa är kostsamma och tidsödande. Som Microsoftpartners vill Sogeti använda Microsoft tjänst för cloud computing, Windows Azure, för detta syfte. Migration till molnet är ett nytt område för Sogeti och de har inga beskrivningar för hur en sådan process går till. Vårt uppdrag var att utveckla ett tillvägagångssätt för migration av en IT-lösning till molnet. En del av uppdraget blev då att kartlägga cloud computing, dess beståndsdelar samt vilka för- och nackdelar som finns, vilket har gjort att vi har fått grundläggande kunskap i ämnet. För att utveckla ett tillvägagångssätt för migration har vi utfört flera migrationer av virtuella maskiner till Windows Azure och utifrån dessa migrationer, litteraturstudier och intervjuer dragit slutsatser som mynnat ut i ett generellt tillvägagångssätt för migration till molnet. Resultatet har visat att det är svårt att göra en generell men samtidigt detaljerad beskrivning över ett tillvägagångssätt för migration, då scenariot ser olika ut beroende på vad som ska migreras och vilken typ av molntjänst som används. Vi har dock utifrån våra erfarenheter från våra migrationer, tillsammans med litteraturstudier, dokumentstudier och intervjuer lyft vår kunskap till en generell nivå. Från denna kunskap har vi sammanställt ett generellt tillvägagångssätt med större fokus på de förberedande aktiviteter som en organisation bör genomföra innan migration. Våra studier har även resulterat i en fördjupad beskrivning av cloud computing. I vår studie har vi inte sett att någon tidigare har beskrivit kritiska framgångsfaktorer i samband med cloud computing. I vårt empiriska arbete har vi dock identifierat tre kritiska framgångsfaktorer för cloud computing och i och med detta täckt upp en del av kunskapsgapet där emellan. / Cloud computing involves the use of computer resources that are available through a network, usually the Internet and it is an area that has grown rapidly in recent years. More and more companies move entire or part of their operations to the cloud.Sogeti in Borlänge needs to move their development environments to a cloud service as operating and maintaining of these are costly and time-consuming. As a Microsoft Partner, Sogeti wants to use Microsoft´s services for cloud computing, Windows Azure, for this purpose. Migration to the cloud is a new area for Sogeti and they do not have any descriptions of how this process works.Our mission was to develop an approach for the migration of an IT-solution to the cloud. Part of the mission included the identifying of cloud computing, its components, benefits and drawbacks, which lead to us acquiring basic knowledge of the subject.To develop an approach to migration, we performed several migrations of virtual machines to Windows Azure, and based on these migrations, literature studies and interviews we drew conclusions that resulted in an overall approach for migration to the cloud.The results have shown that it is difficult to make a general but detailed description of an approach to migration, as the scenario looks different depending on what to migrate and what type of cloud service is used. However, based on our experiences from our migrations, along with literature, documents and interviews we have lifted our knowledge to a general level. From this knowledge, we have compiled a general approach with greater focus on the preparatory activities that an organization should implement before migration.Our studies also resulted in an in-depth description of cloud computing. In our studies we did not find previous works in which the critical success factors have been described in the context of cloud computing. In our empirical work, we identified three critical success factors for cloud computing and in doing so covered up some of the knowledge gap in between.

Information technology (IT) in the recent decades has showcased immense evolution. This evolution has impacted not only the technological sector of the society but also the socio-political and economic sectors. One such archetype that has gained popular momentum in the recent years is cloud computing. Still in its developmental stages, cloud computing is the latest offspring of computing services and has invariably challenged the traditional aspects of computing services across the IT Organizations in the world. Thus, adopted by a number of developed as well as developing countries, cloud computing has played a crucial role in decreasing the overall cost pertinent to hardware, software and other services in organizations. However, issues such as data security and confidentiality, data availability, legal issues and unintelligent Service Level Agreements (SLAs) have questioned the reliability and credibility of cloud computing. This has resulted in lack of potential investments from major companies. The main aim of this research is to provide concrete reasons for the actively implementing cloud computing in IT Organizations. Qualitative approach and exploratory design are extensively used for data collection and analysis. Primary data is collected based on the views and opinions of IT experts and secondary data is collected from literary sources which invariably supports the primary data and maintains the credibility of the research.

This dissertation consists of three parts, each devoted to a particular issue of significant importance for satellite-based remote sensing of cirrus clouds. In the first part, we develop and present a fast infrared radiative transfer model on the basis of the adding-doubling principle. The model aims to facilitate the radiative transfer computations involved in hyperspectral remote sensing applications. The model is applicable to a variety of cloud conditions, including vertically inhomogeneous or multilayered clouds. It is shown that for hyperspectral applications the model is two order-of-magnitude faster than the well-known discrete ordinate transfer (DISORT) model, while maintains a similar accuracy. The second part is devoted to the investigation of uncertainties in the FSSP (Forward Scattering Spectrometer Probe) measurement of cloud extinction by small ice particles. First, the single-scattering properties of small ice particles in cirrus clouds are derived and compared to those of equivalent spheres according to various definitions. It is found that, although small ice particles in cirrus clouds are often “quasi-spherical”, their scattering phase functions and asymmetry factors are significant different from those of ice spheres. Such differences may lead to substantial underestimation of cloud extinction in FSSP measurement, if small ice particles are assumed to be spheres. In the third part, we present a comparison of cirrus cloud optical thickness retrievals from two important instruments, MODIS (Moderate Resolution Imaging Spectrometer) and POLDER (Polarization and Directionality of Earth’s Reflection), on board NASA’s A-train satellite constellation. The comparison reveals a large difference. Several possible reasons are discussed. It is found that much of the difference is attributable to the difference between the MODIS and POLDER retrieval algorithm in the assumption of cirrus cloud bulk scattering properties. Potential implications of the difference for climate studies are investigated. An important finding is that the use of an unrealistic cirrus bulk scattering model might introduce artificial seasonal variation of cirrus optical thickness and shortwave radiative forcing into the retrieval.

The research presented in this thesis involves the study of ice cloud microphysical and optical properties using both hyperspectral and narrowband infrared spectral data. First, ice cloud models are developed for the Infrared Atmospheric Sounding Interferometer (IASI) instrument onboard the METOP-A satellite, which provide the bulk-scattering properties of these clouds for the 8461 IASI channels between 645 and 2760 cm-1. We investigate the sensitivity of simulated brightness temperatures in this spectral region to the bulk-scattering properties of ice clouds containing individual ice crystal habits as well as for one habit distribution. The second part of this thesis describes an algorithm developed to analyze the sensitivity of simulated brightness temperatures at 8.5 and 11.0 µm to changes in effective cloud temperature by adjusting cloud top height and geometric thickness in a standard tropical atmosphere. Applicability of using these channels in a bi-spectral approach to retrieve cirrus cloud effective particle size and optical thickness is assessed. Finally, the algorithm is applied to the retrieval of these ice cloud properties for a case of single-layered cirrus cloud over a tropical ocean surface using measurements from the Moderate Resolution Infrared Spectroradiometer (MODIS). Cloud top height and geometric thickness in the profile are adjusted to assess the influence of effective cloud temperature on the retrieval.

A code for the quasi-stationary solution of the coupled heat and mass transport equations for aerosols in a finite volume was developed. Both mass and heat are conserved effectively in the volume, which results in a competitive aerosol condensation growth computational model. A further model that couples this competitive aerosol condensation growth computational model with computational fluid dynamics (CFD) software (ANSYS FLUENT) enables the simulation of the realistic atmospheric environment. One or more air parcels, where the aerosols reside, are placed in a very big volume in order to mimic the large atmospheric environment. Mass (water vapor) and heat transportat between the air parcels and the environment facilitates the growth and prevents the parcels from unrealistically overheating. The suppression of cloud condensation nuclei (CCN) growth by high number densities was quantified by our model study. Model study with organic particles (Lmalic acid and maleic acid) indicates that when these organic species and ammonium sulfate are internally mixed, the particles can grow much more than if they are separately associated with distinct particles. Moreover, by using more multiple air parcels, which are randomly assigned with different initial relative humidity values according to a power law distribution, we studied the effects of atmospheric stochastic RH distribution on the growth of CCN.