In this work high-resolution numerical simulation (Large-Eddie Simulation, LES) has been used to study the characteristic factors causing and influencing the development of moist convective clouds. Through this work a 1D cloud-model was derived from first principles to represent the vertical profile of individual convective clouds. A microphysics framework was implemented to ensure identical behaviour in LES and cloud-model integration where the microphysical processes represented are numerically integrated using a novel adaptive step microphysics integration which uses the physical speed at which a process takes place to adjust the integration step size (in space and time). This work also introduces a simple representation of cloud-droplet formation which allows for super-saturation to exist in-cloud and through this provide more physical representation of the in-cloud state. Together with high-resolution simulation of isolated individual and interacting multiple clouds in environmental conditions leading to shallow convection, the 1D cloud-model was used to infer that the principal influence on moist convective clouds is the entrainment of air from a cloud’s immediate environment which is significantly different from the environmental mean state. This suggests that convection parameterisations must represent the influence of moist convective downdrafts to properly predict the vertical structure of convective clouds so as to correctly predict the cloud-top height and vertical transport. Finally it was found that cloud-base radius is not in itself adequate as a means of classification for defining cloud-types as clouds with the same cloud-base radius showed large variation (≈ 600m) in cloud-top height. Based on simulations of individual convective clouds it was found that 3D simulations are necessary to capture the full dynamic behaviour of convective clouds (2D axisymmetric simulations have too little entrainment) and that agreement with the 1D cloud-model could only be found when entrainment was diagnosed from simulation instead of being parameterised by the traditional Morton-Turner model and only for 2D axisymmetric simulations, suggesting that the 1D cloud-model will require further extension or the diagnosis of entrainment improved.

The thesis deals with various aspects of running a web application written in PHP (programming language). It considers capabilities of different interpreters and it also compares some cloud-based services. In the practical part the thesis describes the design and implementation of a test application which was stepwise deployed to various environments where it was subjected to benchmark test. The description of deployment also depicts all the problems encountered on each platform. Finally various performance-affecting resources are discussed for the purpose of improving the application efficiency.

In my thesis, I focus on the operating system Google Chrome OS, determination of its characteristics, definition of target group of the operating system's users and comparison of available applications with those available for other operating systems. In the theoretical part, historical development of Google is analysed first, followed by the issue of Google Chrome web browser and analyse of the operating system Google Chrome OS. The practical part starts with evaluation of survey on the operating system Google Chrome OS and is followed by multi-criteria analysis of variants comparing various categories of applications available for the operating system Google Chrome OS and other operating systems, in this case represented by the operating system Microsoft Windows 8.1 and distribution of Linux operating system Ubuntu 14.04 LTS.

ALMEIDA, Rodrigo Félix de. BenchXtend: uma ferramenta para medir a elasticidade de sistemas de banco de dados em nuvem. 2013. 87 f. Dissertação (Mestrado em ciência da computação)- Universidade Federal do Ceará, Fortaleza-CE, 2013. / Submitted by Elineudson Ribeiro (elineudsonr@gmail.com) on 2016-07-12T16:54:55Z No. of bitstreams: 1 2013_dis_rfalmeida.pdf: 2089098 bytes, checksum: 5261a9b1bad7546693a182bbdc551ea5 (MD5) / Approved for entry into archive by Rocilda Sales (rocilda@ufc.br) on 2016-07-21T16:12:56Z (GMT) No. of bitstreams: 1 2013_dis_rfalmeida.pdf: 2089098 bytes, checksum: 5261a9b1bad7546693a182bbdc551ea5 (MD5) / Made available in DSpace on 2016-07-21T16:12:56Z (GMT). No. of bitstreams: 1 2013_dis_rfalmeida.pdf: 2089098 bytes, checksum: 5261a9b1bad7546693a182bbdc551ea5 (MD5) Previous issue date: 2013 / Nos últimos anos, a computação em nuvem tem atraído a atenção tanto da indústria quanto do meio acadêmico, tornando-se comum encontrar na literatura relatos de adoção de computação em nuvem por parte de empresas e instituições acadêmicas. Uma vez que a maioria das aplicações em nuvem são orientadas a dados, sistemas de gerenciamento de bancos de dados são componentes críticos das aplicações. Novos sistemas de bancos de dados surgiram para atender a novos requisitos de aplicações altamente escaláveis em nuvem. Esses sistemas possuem diferenças marcantes quando comparados com sistemas relacionais tradicionais. Além disso, uma vez que elasticidade é um recurso chave da computação em nuvem e um diferencial desse paradigma, esses novos sistemas de bancos de dados também devem prover elasticidade. Juntamente com o surgimento desses novos sistemas, surge também a necessidade de avaliá-los. Ferramentas tradicionais de benchmark para bancos de dados não são suficientes para analisar as especificidades desses sistemas em nuvem. Assim, novas ferramentas de benchmark são necessárias para avaliar adequadamente esses sistemas em nuvem e como medir o quão elásticos eles são. Antes de avaliar e calcular a elasticidade desses sistemas, se faz necessária a definição de um modelo com métricas de elasticidade que façam sentido tanto para consumidores quanto provedores. Nesse trabalho apresentamos BenchXtend, uma ferramenta, que estende o Yahoo! Cloud Serving Benchmark (YCSB), para benchmarking e medição de elasticidade de bancos de dados em nuvem. Como parte desse trabalho, propomos um modelo com métricas a partir das perspectivas dos consumidores e dos provedores para medir a elasticidade. Por fim, avaliamos nossa solução através de experimentos e verificamos que nossa ferramenta foi capaz de variar a carga de trabalho, como esperado, e que nossas métricas conseguiram capturar a variação de elasticidade nos cenários analisados. / In recent years, cloud computing has attracted attention from industry and academic world, becoming increasingly common to find cases of cloud adoption by companies and research institutions in the literature. Since the majority of cloud applications are data-driven, database management systems powering these applications are critical components in the application stack. Many novel database systems have emerged to fulfill new requirements of high-scalable cloud applications. Those systems have remarkable differences when compared to traditional relational databases. Moreover, since elasticity is a key feature in cloud computing and it is a differential of this computing paradigm, novel database systems must also provide elasticity. Altogether with the emergence of these new systems, the need of evaluating them comes up. Traditional benchmark tools for database systems are not sufficient to analyze some specificities of these systems in a cloud. Thus, new benchmark tools are required to properly evaluate such cloud systems and also to measure how elastic they are. Before actually benchmarking and measuring elasticity of cloud database systems, it becomes necessary to define a model with elasticity metrics that makes sense both for consumers and providers. In this work we present BenchXtend, a tool, that extends Yahoo! Cloud Serving Benchmark (YCSB), to benchmark cloud database systems and to measure elasticity of such systems. As part of this work, we propose a model with metrics from consumer and provider perspectives to measure elasticity. Finally, we evaluated our solution by performing experiments and we verified that our tool could properly vary the load during execution, as expected, and that our elasticity model could capture the elasticity differences between the studied scenarios.

Technology has removed all political boundaries, and has significantly transformed the way business is conducted in the modern age. The world has become a global village in which, by the mere click of a mouse button, anyone can reach any market in any part of the world. This however, has introduced stiff competition among businesses worldwide for markets, where the most affected are SMEs in developing countries. Research has shown these SMEs lack capital to invest in IT in order to improve their competitive advantage. Cloud computing is an emerging computing paradigm, which has been touted as the panacea to help SMEs in developing countries become competitive. For SMEs to be globally competitive, they need to transform and adopt ICT, and use it effectively. A great deal of research has been carried out on the benefits and barriers to ICT adoption by SMEs in both developing and developed countries. The findings obtained from studies from a single country cannot be considered „one size fits all‟ and thus, cannot be applied to all countries, due to the difference in geopolitical and economic development trajectories. Zimbabwe is a developing country, and by virtue of its unique history cannot be compared to any other country in the world. This means that no research conducted outside the borders of Zimbabwe can truly be generalised to SMEs in the country. This study explored the readiness of SMEs in Bulawayo (Zimbabwe) to adopt cloud computing as a business strategy. The study used the NOIIE (which stands for National e-readiness, Organisational preparedness, Industrial relationships, Internal resistance and External influence) conceptual framework to assess the readiness of SMEs in Bulawayo in embracing cloud computing. The study undertook a positivist philosophy, underpinned by quantitative methodology. Questionnaires were sent to systematically sampled SMEs in order to answer the research questions. The data was then collected and analysed by SPSS. The findings revealed that most SMEs are notably young and small, and therefore not mature enough to have foundation for execution. The findings also revealed that top management in SMEs is either not willing to commit or do not have the resources to put in necessary infrastructure to migrate to cloud computing. This indicates a possible lack of awareness of the benefits of the cloud to SMEs. The government has not done enough to promote the use of cloud by SMEs. Power cuts and expensive Internet access exacerbate the plight of the SMEs to move to the cloud. Lack of visible cloud service providers makes the situation even worse. / Computing / M. Sc. (Computing)

Edge-cloud brings the computation power as close to the clients as possible. This reduces latencies and overall computation time in the cloud. Thanks to the mobile nature of clients we must be able to migrate tasks among different servers. The goal of this thesis is to examine possible problems in communication and propose the architecture of framework. Our framework uses gRPC and is written as module to it. It is platform independent, uses reliable communication and focuses on easy usage. We provide implementation of this framework with some example uses. 1

1 CHARLES UNIVERSITY IN PRAGUE Faculty of Law Barbora Studihradová General Data Protection Regulation: Challenges for the Cloud Master's thesis Master's thesis supervisor: JUDr. Magdaléna Svobodová, Ph.D. Department of European Law Date of completion (manuscript closure): 13 April 2018 2 General Data Protection Regulation: Challenges for the Cloud Abstract This thesis recognizes and analyses some of the fundamental challenges that the General Data Protection Regulation poses for cloud computing. Its aim is to answer the question whether the GDPR can be regarded as cloud friendly. The hypothesis that is proposed and tested is that it cannot be, since it includes concepts and wording that are impractical in cloud computing. This is assessed based on how different cloud computing services function. The thesis therefore lays down foundations of both legal and technical understanding of the data protection in the cloud in the first chapters. The analysis of the challenges then builds on this knowledge. The challenges of the GDPR for the cloud are divided into five groups. Firstly, what is regulated as personal data in the cloud is consider with regard to the concepts of anonymisation, pseudonymisation and encryption. Secondly, controller - processor relationship and their obligations in the complex cloud...

We present platooning as a special case of crowd-sensing framework. After offering a policy that governs platooning, we review common scenarios and components surrounding platooning. We present a prototype that illustrates efficiency of road usage and vehicle travel time derived from platooning. We have argued that beyond the commonly reported benefits of platooning, there are substantial savings in acquisition and processing of sensory data sharing the road. Our results show that data transmission can be reduced to low of 3% compared to normal data transmission using a platoon formation with sensor sharing.

Cloud computing has been advancing at an intense pace. It has become one of the most important research topics in computer science and information systems. Cloud computing offers enterprise-scale platforms in a short time frame with little effort. Thus, it delivers significant economic benefits to both commercial and public entities. Despite this, the security and subsequent incident management requirements are major obstacles to adopting the cloud. Current cloud architectures do not support digital forensic investigators, nor comply with today’s digital forensics procedures – largely due to the fundamental dynamic nature of the cloud. When an incident has occurred, an organization-based investigation will seek to provide potential digital evidence while minimising the cost of the investigation. Data acquisition is the first and most important process within digital forensics – to ensure data integrity and admissibility. However, access to data and the control of resources in the cloud is still very much provider-dependent and complicated by the very nature of the multi-tenanted operating environment. Thus, investigators have no option but to rely on the Cloud Service Providers (CSPs) to acquire evidence for them. Due to the cost and time involved in acquiring the forensic image, some cloud providers will not provide evidence beyond 1TB despite a court order served on them. Assuming they would be willing or are required to by law, the evidence collected is still questionable as there is no way to verify the validity of evidence and whether evidence has already been lost. Therefore, dependence on the CSPs is considered one of the most significant challenges when investigators need to acquire evidence in a timely yet forensically sound manner from cloud systems. This thesis proposes a novel architecture to support a forensic acquisition and analysis of IaaS cloud-base systems. The approach, known as Cloud Forensic Acquisition and Analysis System (Cloud FAAS), is based on a cluster analysis of non-volatile memory that achieves forensically reliable images at the same level of integrity as the normal “gold standard” computer forensic acquisition procedures with the additional capability to reconstruct the image at any point in time. Cloud FAAS fundamentally, shifts access of the data back to the data owner rather than relying on a third party. In this manner, organisations are free to undertaken investigations at will requiring no intervention or cooperation from the cloud provider. The novel architecture is validated through a proof-of-concept prototype. A series of experiments are undertaken to illustrate and model how Cloud FAAS is capable of providing a richer and more complete set of admissible evidence than what current CSPs are able to provide. Using Cloud FAAS, investigators have the ability to obtain a forensic image of the system after, just prior to or hours before the incident. Therefore, this approach can not only create images that are forensically sound but also provide access to deleted and more importantly overwritten files – which current computer forensic practices are unable to achieve. This results in an increased level of visibility for the forensic investigator and removes any limitations that data carving and fragmentation may introduce. In addition, an analysis of the economic overhead of operating Cloud FAAS is performed. This shows the level of disk change that occurs is well with acceptable limits and is relatively small in comparison to the total volume of memory available. The results show Cloud FAAS has both a technical and economic basis for solving investigations involving cloud computing.

L’évolution des infrastructures informatiques encourage la gestion séparée de l’infrastructure matérielle et de celle des logiciels. Dans cette direction, les infrastructures de cloud virtualisées sont devenues trés populaires. Parmi les différents modèles de cloud, les Infrastructures as a Service (IaaS) ont de nombreux avantages pour le fournisseur comme pour le client. Dans ce modèle de cloud, le fournisseur fournit ses ressources virtualisées et il est responsable de la gestion de son infrastructure. De son coté, le client gère son application qui est déployée dans les machines virtuelles allouées. Ces deux acteurs s’appuient généralement sur des systèmes d’administration autonomes pour automatiser les tâches d’administration. Réduire la quantité de ressources utilisées (et la consommation d’énergie) est un des principaux objectifs de ce modèle de cloud. Cette réduction peut être obtenue à l’exécution au niveau de l’application par le client (en redimensionnant l’application) ou au niveau du système virtualisé par le fournisseur (en regroupant les machines virtuelles dans l’infrastructure matérielle en fonction de leur charge). Dans les infrastructures de cloud traditionnelles, les politiques de gestion de ressources ne sont pas coopératives : le fournisseur ne possède pas d’informations détaillées sur les applications. Ce manque de coordination engendre des surcoûts et des gaspillages de ressources qui peuvent être réduits avec une politique de gestion de ressources coopérative. Dans cette thèse, nous traitons du problème de la gestion de ressources séparée dans un environnement de cloud virtualisé. Nous proposons un modèle de machines virtuelles élastiques avec une politique de gestion coopérative des ressources. Cette politique associe la connaissance des deux acteurs du cloud afin de réduire les coûts et la consommation d’énergie. Nous évaluons les bénéfices de cette approche avec plusieurs expériences dans un IaaS privé. Cette évaluation montre que notre politique est meilleure que la gestion des ressources non coordonnée dans un IaaS traditionnel, car son impact sur les performances est faible et elle permet une meilleure utilisation des ressources matérielles et logicielles. / Recent advances in computer infrastructures encourage the separation of hardware and software management tasks. Following this direction, virtualized cloud infrastructures are becoming very popular. Among various cloud models, Infrastructure as a Service (IaaS) provides many advantages to both provider and customer. In this service model, the provider offers his virtualized resource, and is responsible for managing his infrastructure, while the customer manages his application deployed in the allocated virtual machines. These two actors typically use autonomic resource management systems to automate these tasks at runtime. Minimizing the amount of resource (and power consumption) in use is one of the main services that such cloud model must ensure. This objective can be done at runtime either by the customer at the application level (by scaling the application) or by the provider at the virtualization level (by migrating virtual machines based on the infrastructure’s utilization rate). In traditional cloud infrastructures, these resource management policies work uncoordinated: knowledge about the application is not shared with the provider. This behavior faces application performance overheads and resource wasting, which can be reduced with a cooperative resource management policy. In this research work, we discuss the problem of separate resource management in the cloud. After having this analysis, we propose a direction to use elastic virtual machines with cooperative resource management. This policy combines the knowledge of the application and the infrastructure in order to reduce application performance overhead and power consumption. We evaluate the benefit of our cooperative resource management policy with a set of experiments in a private IaaS. The evaluation shows that our policy outperforms uncoordinated resource management in traditional IaaS with lower performance overhead, better virtualized and physical resource usage.