This literature review seeks to identify the major security issues and their solutions in cloud computing security as well as identifying areas for future research. Utilising a modified version of the approach suggested by Okoli and Schabram (2010) 52 articles were considered for the review, of which 26 were included in the final product. Although many security issues and solutions were identified it has become apparent that much of the research being done only relates to the theoretical side. Thus this review shows that while plenty of issues have been identified future research should focus more on the practical implications of these security risks. / Denna litteraturundersökning identifierar de huvudsakliga säkerhetsbristerna och de lösningar som åtfinns inom litteraturen om datormolnsäkerhet. Undersökningen använder sig av en modifierad version av metoden för litteraturundersökningar som skrivits av Okoli och Schabram (2010). Efter en första litteratursökning identifierades 52 artiklar som relevanta för undersökningen, av dessa 52 användes 26 i slutprodukten. Trots att flera olika säkerhetsbrister och lösningar för dessa identifierades var det uppenbart att mycket av forskningen enbart har teoretiska svar på bristerna. Undersökningen visar således att även om många hot har upptäckts av forskare saknas det forskning av de praktiska konsekvenserna av dessa brister.

Cloud computing has become a prominent paradigm to offer on-demand services for softwares, infrastructures and platforms. Cloud services are contracted by a service level agreement (SLA) between a cloud service provider (CSP) and a cloud service user (CSU) which contains service definitions, quality of service (QoS) parameters, guarantees and obligations. Cloud service providers mostly offer SLAs in descriptive format which is not directly consumable by a machine or a system. The SLA written in natural language may impede the utility of rapid elasticity in a cloud service. Manual management of SLAs with growing usage of cloud services can be a challenging, erroneous and tedious task especially for the CSUs acquiring multiple cloud services. The necessity of automating the complete SLA life cycle (which includes SLA description in machine readable format, negotiation, monitoring and management) becomes imminent due to complex requirements for the precise measurement of QoS parameters. Current approaches toward automating the complete SLA life cycle, lack in standardization, completeness and applicability to cloud services. Automation of different phases of the SLA life cycle (e.g. negotiation, monitoring and management) is dependent on the availability of a machine readable SLA. In this work, a structural specification for the SLAs in cloud computing (S3LACC in short) is presented which is designed specifically for cloud services, covers complete SLA life cycle and conforms with the available standards. A time efficient SLA negotiation technique is accomplished (based on the S3LACC) for concurrently negotiating with multiple CSPs. After successful negotiation process, next leading task in the SLA life cycle is to monitor the cloud services for ensuring the quality of service according to the agreed SLA. A distributed monitoring approach for the cloud SLAs is presented, in this work, which is suitable for services being used at single or multiple locations. The proposed approach reduces the number of communications of SLA violations to a monitoring coordinator by eliminating the unnecessary communications. The presented work on the complete SLA life cycle automation is evaluated and validated with the help of use cases, experiments and simulations.

Traffic modeling in computer networks has been researched for decades. A good model should reflect the features of real-world network traffic. With a good model, synthetic traffic data can be generated for experimental studies; network performance can be analysed mathematically; service provisioning and scheduling can be designed aligning with traffic changes. An important part of traffic modeling is to capture the dependence, either the dependence among different traffic flows or the temporal dependence within the same traffic flow. Nevertheless, the power of dependence models, especially those that capture the functional dependence, has not been fully explored in the domain of computer networks. This thesis studies copula theory, a theory to describe dependence between random variables, and applies it for better performance evaluation and network resource provisioning. We apply copula to model both contemporaneous dependence between traffic flows and temporal dependence within the same flow. The dependence models are powerful and capture the functional dependence beyond the linear scope. With numerical examples, real-world experiments and simulations, we show that copula modeling can benefit many applications in computer networks, including, for example, tightening performance bounds in statistical network calculus, capturing full dependence structure in Markov Modulated Poisson Process (MMPP), MMPP parameter estimation, and predictive resource provisioning for cloud-based composite services. / Graduate / 0984 / fdong@uvic.ca

In recent years, the demand for data center computing has increased significantly due to the growing popularity of cloud applications and Internet-based services. Today's large data centers host hundreds of thousands of servers and the peak power rating of a single data center may even exceed 100MW. The combined electricity consumption of global data centers accounts for about 3% of worldwide production, raising serious concerns about their carbon footprint. The utility providers and governments are consistently pressuring data center operators to reduce their carbon footprint and energy consumption. While these operators (e.g., Apple, Facebook, and Google) have taken steps to reduce their carbon footprints (e.g., by installing on-site/off-site renewable energy facility), they are aggressively looking for new approaches that do not require expensive hardware installation or modification. This dissertation focuses on developing algorithms and systems to improve the sustainability in data centers without incurring significant additional operational or setup costs. In the first part, we propose a provably-efficient resource management solution for a self-managed data center to cap and reduce the carbon emission while maintaining satisfactory service performance. Our solution reduces the carbon emission of a self-managed data center to net-zero level and achieves carbon neutrality. In the second part, we consider minimizing the carbon emission in a hybrid data center infrastructure that includes geographically distributed self-managed and colocation data centers. This segment identifies and addresses the challenges of resource management in a hybrid data center infrastructure and proposes an efficient distributed solution to optimize the workload and resource allocation jointly in both self-managed and colocation data centers. In the final part, we explore sustainable resource management from cloud service users' point of view. A cloud service user purchases computing resources (e.g., virtual machines) from the service provider and does not have direct control over the carbon emission of the service provider's data center. Our proposed solution encourages a user to take part in sustainable (both economical and environmental) computing by limiting its spending on cloud resource purchase while satisfying its application performance requirements.

This master’s thesis evaluates automatic data annotation and machine learning predictions of iron ore pellets using tools provided by Amazon Web Services (AWS) in the cloud. The main tool in focus is Amazon SageMaker which is capable of automatic data annotation as well as building, training and deploying machine learning models quickly. Three different models was trained using SageMakers built in semantic segmentation algorithm, PSP, FCN and DeepLabV3. The dataset used for training and evaluation contains 180 images of iron ore pellets collected from LKAB’s experimental blast furnace in Luleå, Sweden. The Amazon Web Services solution for automatic annotation was shown to be of no use when annotating microscopic images of iron ore pellets. Ilastik which is an interactive learning and segmentation toolkit showed far superiority for the task at hand. Out of the three trained networks Fully-Convolutional Network (FCN) performed best looking at inference and training times, it was the quickest network to train and performed within 1% worse than the fastest in regard to inference time. The Fully-Convolutional Network had an average accuracy of 85.8% on the dataset, where both PSP & DeepLabV3 was showing similar performance. From the results in this thesis it was concluded that there are benefits of running deep neural networks as a cloud service for analysis and management ofiron ore pellets.

This thesis covers the theme of cloud integration platforms as a service with Ida Infronts information and task management system iipax one. The premise of this thesis is to research the most optimal cloud integration platform and find what cloud-based functions that are useful for iipax one. Using a cloud integration platform with iipax one could be beneficial for the users as it allows them to automate simple repetitive tasks. But choosing an integration platform is not a simple undertaking as there are many available platforms, all with their own unique features. To find a suitable platform first we investigated potential platforms which revealed Power Automate, Zapier and IFTTT as candidates. Our comparison based on a literature study showed that Power Automate is most suitable for iipax one. Finally, we created a prototype implementation to integrate iipax one with Power Automate. The conclusion is that Power Automate is the best suited platform for iipax one. Although Zapier is a close second. For the useful functions we concluded that it is more important with templates that users can adopt rather than a multitude of triggers and actions.

Cloud-Technologien ermöglichen Endnutzern das flexible und bedarfsgerechte Beziehen von IT-Leistungen über das Internet. In einer Public Cloud können die Dienste oder Ressourcen von beliebigen Unternehmen und Endnutzern zeit- sowie ortsunabhängig verwendet werden. Nutzer von Cloud-basierten Softwareanwendungen haben keinen Einfluss auf die sachgerechte Verwaltung und Überwachung der darunterliegenden Cloud-Infrastruktur. Infolgedessen haben sie zunehmend Bedenken hinsichtlich der Sicherheit ihrer Daten oder in Bezug auf die Performance bzw. Verfügbarkeit des Dienstes. Um diese Bedenken abzubauen, müssen die nichtfunktionalen Eigenschaften eines Dienstes betrachtet werden, da sie dessen qualitative Wahrnehmung beeinflussen. Derzeit steht Endnutzern weder ein vollständiger Kriterienkatalog zur Bewertung von Cloud-Diensten als Orientierungshilfe zur Verfügung noch sind Cloud-Gütesiegel oder Zertifikate ausreichend verbreitet. Mangelnde Fachkenntnisse und verstreute oder nicht verfügbare Qualitätsinformationen führen dazu, dass Endnutzer die Dienstqualität nur erschwert oder gar nicht bewerten können. Das Ziel der Dissertation ist, Cloud-Nutzer bei der schnellen und umfangreichen Überwachung und Bewertung der Qualität ihrer Public-Cloud-Dienste zu unterstützen. Die Berücksichtigung der Nutzerinteressen und -bedürfnisse in Bezug auf die Dienstqualität steht dabei im Vordergrund. Die Untersuchung der verwandten Cloud-spezifischen Qualitätsmodelle hat gezeigt, dass die Modelle unvollständig sind und keine Aussagen zu deren Eignung und Akzeptanz aus Nutzersicht getroffen werden. Folglich werden in der Arbeit zunächst die nichtfunktionalen Qualitätsattribute von Softwareanwendungen identifiziert und nutzerfreundlich kategorisiert. Das daraus abgeleitete Modell bildet die Grundlage für ein Qualitätsinformationssystem, das Endnutzer künftig bei der kontinuierlichen Einschätzung der Qualität ihrer Dienste unterstützen soll. Darüber hinaus wird ein Konzept zur nutzerfreundlichen visuellen Aufbereitung der Qualitätsinformationen entwickelt. Es werden Empfehlungen zur Darstellung, Strukturierung und Verknüpfung der Informationen innerhalb des Systems gegeben. Jeder Nutzer kann individuell festlegen, über welche Qualitätseigenschaften er informiert werden möchte und wann die Qualität eines Dienstes als hoch eingeschätzt werden soll. Mit der prototypisch technischen Realisierung des Qualitätsinformationssystems werden die praktische Eignung des Qualitätsmodells und Konzeptes demonstriert. Ferner belegen die Ergebnisse von zwei Nutzerbefragungen, dass Cloud-Nutzer durch das Informationssystem bei der Qualitätsbewertung unterstützt werden und mit dem System grundsätzlich zufrieden sind.

Cloud computing has become a prominent paradigm to offer on-demand services for softwares, infrastructures and platforms. Cloud services are contracted by a service level agreement (SLA) between a cloud service provider (CSP) and a cloud service user (CSU) which contains service definitions, quality of service (QoS) parameters, guarantees and obligations. Cloud service providers mostly offer SLAs in descriptive format which is not directly consumable by a machine or a system. The SLA written in natural language may impede the utility of rapid elasticity in a cloud service. Manual management of SLAs with growing usage of cloud services can be a challenging, erroneous and tedious task especially for the CSUs acquiring multiple cloud services. The necessity of automating the complete SLA life cycle (which includes SLA description in machine readable format, negotiation, monitoring and management) becomes imminent due to complex requirements for the precise measurement of QoS parameters. Current approaches toward automating the complete SLA life cycle, lack in standardization, completeness and applicability to cloud services. Automation of different phases of the SLA life cycle (e.g. negotiation, monitoring and management) is dependent on the availability of a machine readable SLA. In this work, a structural specification for the SLAs in cloud computing (S3LACC in short) is presented which is designed specifically for cloud services, covers complete SLA life cycle and conforms with the available standards. A time efficient SLA negotiation technique is accomplished (based on the S3LACC) for concurrently negotiating with multiple CSPs. After successful negotiation process, next leading task in the SLA life cycle is to monitor the cloud services for ensuring the quality of service according to the agreed SLA. A distributed monitoring approach for the cloud SLAs is presented, in this work, which is suitable for services being used at single or multiple locations. The proposed approach reduces the number of communications of SLA violations to a monitoring coordinator by eliminating the unnecessary communications. The presented work on the complete SLA life cycle automation is evaluated and validated with the help of use cases, experiments and simulations.

When it comes to cloud services, security has many a times been the hot topic. This has been especially relevant within the payment card industry and the secure handling of payment card data. The Payment Card Industry Security Standards Council (the council) was formed in order to ensure a global enhancement of payment card data. The council has issued requirements that all companies that handle payment card data are obliged to follow. However, the council has become much more strict as of recently, creating an urgency to become compliant. Thus, cloud service providers (CSP) have constructed standardized, PCI DSS compliant products so as to relief such customers. Since this emerging market is somewhat new, this thesis has researched how CSPs should relate to products within that market and the potential customer base. The case study for this research was conducted at Tieto, an IT service company, and its standardized, PCI DSS compliant product TiCC. The study collected empirical data in the form of qualitative interviews as well as quantitative telephone interviews with companies within the payment card industry. The study came to the conclusion that there is a demand that is not being met within the payment card industry related to products that aid organizations to become PCI DSS compliant. Standardized products have been constructed so as to fit financial customers while overlooking the demand of another large customer base, retail. Additionally, the products are being tweaked and features are being added, thus providing customization. CSPs are striving for both standardization as well as customization, something that has been considered counterproductive. The existing demand is thus not met with the current supply in the market, which has both multiple competitors and heterogeneity in market demand. The above mentioned thus leaves room for market seizure, to create own rules and thus making all competitors irrelevant. A potential way of doing that is through mass customization by standardizing higher levels of cloud computing.

This thesis addresses the issue of adopting cloud computing in two aspects. The first being the procedure of choosing a commonality that constitutes the base of comparing the most appropriate cloud platform from identified parameters. The second being to find constraints of adopting cloud computing related to the commonality. This commonality was identified in form of a process that portrayed characteristics which made it suitable for identifying parameters and comparing two cloud platforms (Azure and AWS). The comparison of platforms based on the parameters; lock-in, standardization and data security led to conclusive remarks that discouraged any further effort on comparing cloud platforms. Lack of standards and lock-in that cannot be avoided are traits of the unfitting environment the cloud platforms constitute. Furthermore, it was concluded that the adoption constraints are first priority when it comes to adopting cloud computing. Instead of choosing the cloud platform with least amount of constraints, it is recommended to firstly focus on the adoption constraints. / Avhandlingen tar upp frågan om att införa molntjänster i två aspekter. Den första är proceduren att välja en gemensam nämnare som utgör basen för jämförelse av den lämpligaste moln plattformen. Den andra är att hitta begränsningar relaterat till införandet av molntjänster i samband med den gemensamma nämnaren. Denna gemensamma nämnare identifierades i form av en process inom en IT-avdelning som skildrar egenskaper vilket gjorde den lämplig för att hitta parametrar och jämföra två molnplattformar (Azure och AWS). Jämförelsen av plattformar baserades på parametrarna; lock-in, standardisering och datasäkerhet. Brist på standarder och lock-in som inte kan undvikas är egenskaper av den opassande miljön som molnplattformarna utgör. Dessutom drogs slutsatsen att de nämnda begränsningar är av första prioritet när det gäller att införa molntjänster. Istället för att välja en molnplattform med minsta möjliga begränsningar, är rekommendationen att först fokusera på begränsningarna.