Thesis (M.A. (Information Studies)) -- University of Limpopo, 2020 / International, national and local public and private sectors are shifting into Cloud Computing (CC). This paradigm shift is fuelled by technological and transformational changes of CC in every sector, including libraries. Presently in South Africa, some libraries still operate on the traditional ICT based desktop applications, whereas some hardly notice that CC is part of their daily activities such as carrying out transactions in the cloud services like emailing on Gmail. There is a major gap in terms of adopting and understanding CC technology in public libraries. Hence the study proposed to describe and explore the application and understanding of CC in Polokwane Municipal libraries. The study identified CC tools used by librarians and determined the level of librarians’ knowledge and understanding of CC. The study further measured perceptions of librarians towards CC and established factors influencing the use of CC in libraries. The researcher used a mixed-methods research approach and case study research design, located within postpositivism and interpretivism paradigm. The study was a census in nature because of the small population. Data was collected using questionnaire and interviews from 30 respondents who were librarians and participants who were library managers. Collected data were analysed through descriptive statistics and thematic data analysis. Findings from the study reveal that librarians are not fully using CC but use some of the CC applications such as google scholar, without having detailed knowledge and understanding. The study further found out that Polokwane Municipal libraries fail to adopt CC as a result of limited budget and poor internet connection. The study recommends intensive study on factors influencing adoption of CC, workshops and training for librarians, and initiatives on fundraising within these libraries.

Jährlich sterben weltweit 1,35 Millionen Menschen durch Verkehrsunfälle. Ob Cloud-Computing zu einer Reduzierung dieser Zahl beitragen wird, wird in der vorliegenden Arbeit untersucht. Zunächst werden Cloud-Anwendungen ermittelt, welche im Straßenverkehr verwendet werden und Einfluss auf die Straßenverkehrssicherheit haben. Anschließend wird deren genauer Einfluss auf die Straßenverkehrssicherheit durch die Betrachtung von Stu-dienergebnissen, Herstellerangaben sowie eigenen Kalkulationen untersucht. Zudem werden die Gefahren von Cyberangriffen und Netzausfällen für die ermittelten Anwendungen analysiert. Es folgt eine kritische Diskussion sowie die Zusammenfassung des Erarbeiteten: Cloud-Computing ermöglicht durch den einfachen, risikoarmen Zugang zu unlimitierten Rechenressourcen die Entwicklung und den Betrieb von Anwendungen, die Einfluss auf die Verkehrssicherheit nehmen. Es ist davon auszugehen, dass die Anwendungen bei einer weiter voranschreitenden Felddurchdringungsrate positiven Einfluss auf die Straßenverkehrssicherheit in Deutschland und anderen Industriestaaten nehmen und damit aktiv zur Reduzierung der Anzahl Verkehrstoter und -verletzter beitragen werden. Cloud-Computing wird somit ein indirekt positiver Einfluss auf die Straßenverkehrssicherheit zugeschrieben. / 1.35 million people die in traffic accidents worldwide every year. Whether cloud computing contributes to a reduction of this number is examined in the present work. First, cloud com-puting applications are identified, which are used in road traffic and have an impact on traffic safety. The exact influence on traffic safety is then examined by considering study results, manufacturer information and through own calculations. In addition, the dangers of cyber-attacks and network failures are examined in the context of the identified applications. This is followed by a critical discussion and a summary of what has been worked out: Cloud computing enables the development and operation of applications that affect traffic safety through simple, low-risk access to unlimited computing resources. It can be assumed that the applica-tions will have a positive influence on traffic safety in Germany and other industrialized countries and will thus actively contribute to reducing the number of deaths and injuries, given that the penetration rate is further increasing. Cloud computing is thus attributed an indirect positive influence on road safety.

Cloud computing has gained popularity due to its ability to simplify IT infrastructure, reduce costs, and provide remote access. Among EU countries and company sizes, Sweden stands out with the highest rate of cloud computing adoption. However, there is a lack of concrete research in the literature focusing on the determinants of cloud computing adoption specifically by large companies in Sweden. Previous studies have examined cloud adoption from various perspectives, with a particular emphasis on small and medium-sized enterprises (SMEs) rather than large companies. Additionally, technology-related determinants have received more attention compared to those related to business, conceptualization, and application domains. To address this knowledge gap, this research aims to investigate the determinants of CC adoption in large companies in Sweden. The research question was formulated as follows: What are the determinants of cloud computing adoption in large companies in Sweden? Case study was selected as the research strategy, and the data was collected through semi-structured interviews and analyzed through thematic analysis. Semi-structured interviews were conducted with employees working at a large company in Sweden, who have experience in the IT and cloud computing field. The TOE framework was used to categorize the determinants as sub-themes into three themes: technology context, organization context, and environment context. In Company X, 30 determinants were found, with 20 aligning with previous literature. These included factors such as security, compatibility, scalability, top management support, and competitive pressure. Additionally, 10 new determinants were identified, including robustness, perceived usefulness, innovativeness, knowledge and training, and geographical locations/data centers. The experience and lessons learned from Company X could assist other companies to have better preparation for cloud adoption by understanding the significance of various potential determinants and underlying problems.

Indiana University-Purdue University Indianapolis (IUPUI) / Growth of interest and need for many-core systems have steadily increased over the recent years. Industry trends lead many-core systems to become increasingly larger and more complex. Because of these realities it is important to researchers, academia, and industry that the design of these many-core systems be straightforward and comprehensive. There is a need for a many-core simulator that can be simple to use and learn from for students, dynamic and capable of emulating large systems for researchers, and flexible with fast turnover for industry designers. At the same time, as many-core systems have been becoming popular and complex, and hence their design, the long standing field of Cloud Computing has become more prevalent and feasible to use. Such cloud computing platforms as Windows Azure allow for the easy access and use of resources that in the past were simply not available to ordinary users. Large tasks can be performed in SaaS Cloud Computing models and be accessible from a small, lightweight device using nothing more than a web browser. As a solution to the needs for designing future many-core systems, we present a Many-Core Simulator on Azure Cloud Computing Platform called M3C Simulator. This is targeted at teaching, research, and industry and as such needs to be easy to use, flexible, and powerful. The Could Computing service model meets all these needs. This thesis discusses overall design of the M3C Simulator and how it leverages Cloud Computing resources, the simple-to-use and understand Interface layout, and the software design including program flow and dynamic compilation.

No keywords provided in dissertation / Cloud Computing has gained traction since its emergence and client organisations that want to benefit from the Cloud are looking for ways to migrate their on-premise applications to the Cloud. To assist client organisations with migration projects, researchers and practitioners have proposed various Cloud migration approaches. However, these approaches differ in applicability depending on the type of application being migrated and the Cloud Service Provider where the application is being migrated to. The various approaches to Cloud migration create complexity in Cloud migration decisions as client organisations have to consider various approaches depending on the migration project. The purpose of this dissertation is to create a universal Cloud migration approach that can be applied to every Cloud migration project. In this dissertation, a cloud migration decision framework is proposed; namely, A Holistic Cloud Migration Decision Framework (HCMDF). The research strategy that was followed is Design Science Research (DSR) and was selected since the output of the research is going to be an Information Technology (IT) research artefact. By applying the DSR strategy, the HCMDF was successfully developed and evaluated in the real world using an adaptive case study. The analysis of the results indicated that the HCMDF solves Cloud migration problem and that it can be applied to every Cloud migration project. Throughout the evaluation, areas of improvement were identified and these will be considered in future research. / School of Computing / M. Tech (Information Technology)

Denna avhandling utforskar den komplexa interaktionen mellan virtualiseringstekniker och prestanda för molnapplikationer. Genom att utvärdera hypervisor- och containerbaserade metoder skapar vi en teoretisk grund för att förstå rollen för virtualisering i modern molnbaserad miljö. Genom en metodisk förstudie och implementeringen av virtuella instanser samlar vi omfattande data om CPU-användning, nätverkstrafik, lagring och genomströmning, vilket avslöjar viktiga insikter. Resursanvändningen påverkas framför allt av hur databelastning ser ut, där resursintensiva uppgifter påverkar både hypervisor och containerinstanser. Studien visar att valet mellan hypervisor och containerteknik kan bero vissa användningsfall, vilket kräver ytterligare optimering. Att isolera tekniker på separata EC2- instanser ger bra kontroll men kräver löpande justeringar för varierande prestandamätningar. Slutsatserna hjälper till att förstå virtualiserings inverkan på molnapplikationer och betonar de avgörande rollerna för lagringshantering, nätverksdynamik och databelastning. Den här avhandlingen tar inte bara upp viktiga frågor, utan den lägger också grunden för framtida forskning som förutser förbättrad effektivitet och prestanda i virtualiserade molnmiljö. / This thesis explores the complex interaction between virtualization technologies and cloud application performance. By evaluating hypervisor and container-based approaches, we establish a theoretical foundation for understanding virtualization's role in modern cloud computing. Through a methodical pre-study and the implementation of virtual instances, we gather extensive data on CPU utilisation, network traffic, storage, and throughput to reveal key insights. Workloads notably impact resource usage, with resource-intensive tasks affecting both hypervisor and container instances. The study suggests that the choice between hypervisor and container technologies may depend on certain use cases, prompting further optimization. Isolating technologies on separate EC2 instances provides control but demands ongoing refinement for varied performance metrics. Conclusions contribute to understanding virtualization's impact on cloud applications, emphasising the critical roles of workload, network dynamics, and storage management. This thesis not only addresses key questions but also sets the stage for future explorations, promising enhanced performance and efficiency in virtualized cloud environments.

A framework for the quantitative analysis of performance, security and database management within a network system (e.g. a cloud computing platform) is presented within this research. Our study provides a methodology for modelling and quantitatively generating significant metrics needed in the evaluation of a network system. To narrow this research, a study is carried-out into the quantitative modelling and analysis of performance, security and database management trade-offs in cloud computing platforms, based on Stochastic Activity Networks (SANs) and combined metrics. Cloud computing is an innovative distributed computing archetypal based on the infrastructure of the internet providing computational power, application, storage and infrastructure services. Security mechanisms such as: batch rekeying, intrusion detection, encryption/decryption or security protocols come at the expense of performance and computing resources consumption. Furthermore, database management processing also has an adverse effect on performance especially in the presence of big data. Stochastic Activity Networks (SANs) that offer synchronisation, timeliness and parallelism are proposed for the modelling and quantitative evaluations of ‘optimal’ trade-offs involving performance, security and database management. Performance modelling and analysis of computer network systems has mostly been considered of utmost importance. Quantification of performance for a while has been assessed using stochastic models with a rising interest in the quantification of security stochastic modelling being applied to security problems. Quantitative techniques that includes analytical valuations founded on queuing theory, discrete-event simulations and correlated approximations have been utilised in the examination of performance. Security suffers from the point that no interpretations can be made in an optimal case. The most consequential security metrics are in analogy with reliability metrics. The express rate at which data grows increases the prominence for research into the design and development of cloud computing models that manages the workload intensity and are suitable for data exploration. Handling big data especially within cloud computing is a resource consuming, time-demanding and challenging task that necessitates titanic computational infrastructures to endorse successful data exploration. We present an improved Security State Transition Diagram (SSTD) by adding a new security state (Failed/Freeze state). The presence of this new security state signifies a security position of the computing network system were the implemented security countermeasures cannot handle the security attacks and the system fails completely. In a more sophisticated security system, when the security countermeasure(s) cannot in any form categorise the security attack, the network system is moved to the Failed/Freeze security state. At this security state, the network system can only resume operation when restored by the system administrator. In this study, we propose a cloud computing system model, defined security countermeasures and evaluated the optimisation problems for the trade-offs between performance, security and database management using SANs formalism. We designed, modelled and implemented dependency within our presented security system, developing interaction within the security countermeasures using our proposed Security Group Communication System (SGCS). The choice of Petri-Nets enables the understanding and capturing of specified metrics at different stages of the proposed cloud computing model. In this thesis, an overview of cloud computing including its classification and services is presented in conjunction with a review of existing works of literature. Subsequently, a methodology is proposed for the quantitative analysis of our proposed cloud computing model of performance-security-database trade-offs using Möbius simulator. Additionally, numerical experiments with relevant interpretations are presented and appropriate interpretations are made. We identified that there are system parameters that can be used to optimise the presented abstract combined metrics but they are optimal for neither performance or security or database management independently. Founded on the proposed quantitative simulation model framework, reliable numerical experiments were observed and indicated scope for further extensions of this work. For example, the use of Machine Learning (ML) or Artificial Intelligence (AI) in the predictive and prevention aspects of the security systems.

Cloud computing allows user access to virtual services (applications, servers and devices, digital storage and service packages sources) through a network using a web browser. Cloud computing is rapidly growing and has become an attractive and affordable service model among organizations. It has many benefits but is also associated with many risks and security challenges. In cloud computing users can connect with any device and use virtual computing services at any time and from anywhere, which has brought new challenges for enterprise security. The problem of securing data in the cloud and building trust in the cloud computing environment has become a widely discussed and important issue.This research aims to investigate how enterprises deal with security problems and protect their data in the cloud through security measures and processes. It also investigates what processes could be adapted to the security environment. To achieve this, an empirical study was performed. The empirical study consisted of interviews with a number of enterprises that use cloud computing in their business, with the purpose to give a deep picture of how they handle security issues related to their cloud services.During the empirical study it could be found differences and similarities in the security measures used by the different organizations, depending on the size of the organization and the type of services used or provided by the organizations. Information security should be managed in a series of processes or procedures, linked together in an environment such as the Information security management system (ISMS). On the basis of the evaluation of the interviews and literature, a cloud environment with different security processes is defined.

From start-ups and small businesses to enterprises, cloud computing significantly impacts their operations. Many studies and research projects on cloud computing have been carried out to assess the impact of how organizations deliver IT services. This study has been conducted in organizations in Rwanda, one of the fastest-growing African countries in the ICT sector, which is turning the nation into a knowledge-based economy. Cloud computing provides several advantages to organizations, and the future also seems promising. However, organizations face several risks and challenges in using this technology. Therefore, they must be aware of challenges when migrating the workload to the cloud. This may alleviate not only the challenges but also create a graceful transition to the cloud. Therefore, this study will measure the perceptions of the challenges and benefits of using cloud computing technology in organizations in Rwanda. As the study shows, the major challenge organizations face is a shortage of cloud experts in the industry. The study revealed that migration is complex and risky, data security and privacy are concerns, and a high-speed internet connection is required and costly. The benefits include: minimizing IT costs with a pay-as-you-go model, better performance and speed, flexibility and scalability as the needs change, collaboration, and communication in the organization. It was concluded that, as cloud computing technology is a new concept to organizations, challenges in its implementation may occur. To help Rwanda's ICT sector grow, policymakers, organization managers, and executives should develop a comprehensive solution policy to address these challenges.

La couche Infrastructure- as-a-Service (IaaS) de Cloud Computing offre un service de déploiement des images de machines virtuelles (VMIs) à la demande. Ce service fournit une plate-forme flexible pour les utilisateurs de cloud computing pour développer , déployer et tester leurs applications. Le déploiement d'une VMI implique généralement le démarrage de l'image, l'installation et la configuration des paquets de logiciels. Dans l'approche traditionnelle, lorsqu'un utilisateur de cloud demande une nouvelle plate-forme, le fournisseur de cloud sélectionne une image de modèle approprié pour cloner et déployer sur ​​les nœuds de cloud​​. L'image de modèle contient des paquets de logiciel pré-installés. Si elle ne correspond pas aux exigences, alors elle sera personnalisée ou la nouvelle image sera créé à partir de zéro pour s'adapter à la demande. Dans le cadre de la gestion des services de cloud, l'approche traditionnelle face aux questions difficiles de la manipulation de la complexité de l'interdépendance entre les paquets de logiciel, mise à l'échelle et le maintien de l' image déployée à l'exécution. Les fournisseurs de cloud souhaitent automatiser ce processus pour améliorer la performance de processus d'approvisionnement des VMIs, et de donner aux utilisateurs de cloud plus de flexibilité pour la sélection ou la création des images appropriées, tout en maximisant les avantages pour les fournisseurs en termes de temps, de ressources et de coût opérationnel. Cette thèse propose une approche pour gérer l'interdépendance des paquets de logiciels, pour modéliser et automatiser le processus de déploiement VMIs, et pour soutenir la reconfiguration VMIS à l'exécution, appelée l'approche dirigée par les modèle (Model-Driven approach). Nous nous adressons particulièrement aux défis suivants: (1) la modélisation de la variabilité des configurations d'image de machine virtuelle, (2) la réduction la quantité de transfert de données à travers le réseau, (3) l'optimisation de la consommation d'énergie des machines virtuelles; (4) la facilité à utiliser pour les utilisateurs de cloud; (5) l'automatisation du déploiement des VMIs; (6) le support de la mise à l'échelle et la reconfiguration de VMIS à l'exécution; (7) la manipulation de la topologie de déploiement complexe des VMIs . Dans notre approche, nous utilisons des techniques d'ingénierie dirigée par les modèles pour modéliser les représentations d'abstraction des configurations de VMI, le déploiement et les processus de reconfiguration d'image de machine virtuelle. Nous considérons que les VMIS comme une gamme de produits et utiliser les modèles de caractère pour représenter les configurations de VMIs. Nous définissons également le déploiement, les processus de reconfiguration et leurs facteurs (par exemple: les images de machines virtuelles, les paquets de logiciel, la plate-forme, la topologie de déploiement, etc.) comme les modèles. D'autre part, l'approche dirigée par les modèles s'appuie sur les abstractions de haut niveau de la configuration de VMIs et le déploiement de VMIs pour rendre la gestion d'images virtuelles dans le processus d'approvisionnement pour être plus flexible et plus facile que les approches traditionnelles. / The Cloud Computing Infastructure-as-a-Service (IaaS) layer provides a service for on demand virtual machine images (VMIs) deployment. This service provides a flexible platform for cloud users to develop, deploy, and test their applications. The deployment of a VMI typically involves booting the image, installing and configuring the software packages. In the traditional approach, when a cloud user requests a new platform, the cloud provider selects an appropriate template image for cloning and deploying on the cloud nodes. The template image contains pre-installed software packages. If it does not fit the requirements, then it will be customized or the new one will be created from scratch to fit the request. In the context of cloud service management, the traditional approach faces the difficult issues of handling the complexity of interdependency between software packages, scaling and maintaining the deployed image at runtime. The cloud providers would like to automate this process to improve the performance of the VMIs provisioning process, and to give the cloud users more flexibility for selecting or creating the appropriate images while maximizing the benefits for providers intern of time, resources and operational cost. This thesis proposes an approach to manage the interdependency of the software packages, to model and automate the VMIs deployment process, to support the VMIs reconfiguration at runtime, called the Model-Driven approach. We particularly address the following challenges: (1) modeling the variability of virtual machine image configurations; (2) reducing the amount of data transfer through the network; (3) optimizing the power consumption of virtual machines; (4) easy-to-use for cloud users; (5) automating the deployment of VMIs; (6) supporting the scaling and reconfiguration of VMIs at runtime; (7) handling the complex deployment topology of VMIs. In our approach, we use Model-Driven Engineering techniques to model the abstraction representations of the VMI configurations, the deployment and the reconfiguration processes of virtual machine image. We consider the VMIs as a product line and use the feature models to represent the VMIs configurations. We also define the deployment, re-configuration processes and their factors (e.g. virtual machine images, software packages, platform, deployment topology, etc.) as the models. On the other hand, the Model-Driven approach relies on the high-level abstractions of the VMIs configuration and the VMIs deployment to make the management of virtual images in the provisioning process to be more flexible and easier than traditional approaches.