Avec l’avènement de l’informatique en nuage, différents fournisseurs offrant des services en nuage et des interfaces de programmation d’applications (APIs) hétérogènes sont apparus. Cette hétérogénéité complique la mise en œuvre d’un système de multi-nuages interopérable. Parmi les solutions pour l’interopérabilité de multi-nuages, l’Ingénierie Dirigée par les Modèles (IDM) s’est révélée avantageuse. Cependant, la plupart des solutions IDM existantes pour l’informatique en nuage ne sont pas représentatives des APIs et manquent de formalisation. Pour remédier à ces limitations, je présente dans cette thèse une approche basée sur le standard Open Cloud Computing Interface (OCCI), les approches IDM et les méthodes formelles. Je fournis deux contributions qui sont mises en œuvre dans le contexte du projet OCCIware. Premièrement, je propose une approche basée sur la rétro-ingénierie pour extraire des connaissances des documentations textuelles ambiguës des APIs de nuages et améliorer leur représentation à l’aide des techniques IDM. Cette approche est appliquée à Google Cloud Platform (GCP), où je propose GCP Model, une spécification précise et basée sur les modèles, automatiquement déduite de la documentation textuelle de GCP. Deuxièmement, je propose le cadre fclouds pour assurer une interopérabilité sémantique entre plusieurs nuages, i.e., pour identifier les concepts communs entre les APIs et raisonner dessus. Le langage fclouds est une formalisation des concepts et de la sémantique opérationnelle d’OCCI en employant le langage de spécification formel Alloy. Pour démontrer l’efficacité du langage fclouds, je spécifie formellement treize APIs et en vérifie les propriétés. / With the advent of cloud computing, different cloud providers with heterogeneous cloud services and Application Programming Interfaces (APIs) have emerged. This heterogeneity complicates the implementation of an interoperable multi-cloud system. Among the multi-cloud interoperability solutions, Model-Driven Engineering (MDE) has proven to be quite advantageous and is the mostly adopted methodology to rise in abstraction and mask the heterogeneity of the cloud. However, most of the existing MDE solutions for the cloud are not representative of the cloud APIs and lack of formalization. To address these shortcomings, I present in this thesis an approach based on Open Cloud Computing Interface (OCCI) standard, MDE, and formal methods. I provide two major contributions implemented in the context of the OCCIware project. First, I propose an approach based on reverse-engineering to extract knowledge from the ambiguous textual documentation of cloud APIs and to enhance its representation using MDE techniques. This approach is applied to Google Cloud Platform (GCP), where I provide GCP Model, a precise model-driven specification for GCP that is automatically inferred from GCP textual documentation. Second, I propose the fclouds framework to achieve semantic interoperability in multi-clouds, i.e., to identify the common concepts between cloud APIs and to reason over them. The fclouds language is a formalization of OCCI concepts and operational semantics in Alloy formal specification language. To demonstrate the effectiveness of the fclouds language, I formally specify thirteen case studies and verify their properties.

As virtualization platforms or cloud computing have become more of a commodity, many more organizations have been utilizing them. Many organizations and technologies have emerged to fulfill those cloud needs. Cloud vendors provide similar services, but the differences can have significant impact on specific applications. Selecting the right provider is difficult and confusing because of the number of options. It can be difficult to determine which application characteristics will impact the choice of implementation. There has not been a concise process to select which cloud vendor and characteristics are best suited for the application requirements and organization requirements. This thesis provides a model that identifies crucial application characteristics, organization requirements and also characteristics of a cloud. The model is used to analyze the interaction of the application with multiple cloud platforms and select the best option based on a suitability score. Case studies utilize this model to test three applications against three cloud implementations to identify the best fit cloud implementation. The model is further validated by a small group of peers through a survey. The studies show that the model is useful in identifying and comparing cloud implementations with regard to application requirements.

En el Perú, la calidad de los servicios de salud es un requisito constante para la población como también una prioridad. “El 49% de los peruanos considera que los servicios de salud son muy malos, mientras que el 47% piensa que son regulares y únicamente el 4% asegura que sí son buenos”. (Datum Internacional S.A, 2017) Por ello, se considera que los grandes problemas del sector salud están en la prestación de servicios y no realmente en el financiamiento del sector; esto produce que los procesos de atención médica sean poco sostenibles. Adicional a ello, La Encuesta Nacional de Satisfacción de Usuarios en Salud del 2015 reveló que existen problemas muy críticos que resolver, como por ejemplo manifiesta que “El tiempo de espera para ser atendido en un consultorio, ha aumentado con respecto a 2014 cuando se registró un tiempo promedio de 81 minutos de espera, ahora el tiempo es de 104 minutos”. (Gestión, 2016) En base a la información mencionada anteriormente, se propone mejorar el servicio de atención ambulatoria mediante un modelo tecnológico de servicio de información farmacológica ambulatoria utilizando una plataforma cloud; esta propuesta permitirá brindar información, administrar los datos de enfermedades comunes y migrarlos a la nube para integrarlos mediante una interfaz desarrollada en una plataforma cloud. Con esta solución se estima reducir la asistencia a los servicios de salud y minimizar los tiempos de espera a una respuesta de una enfermedad común, ya que la información será expuesta en una aplicación móvil. / In Peru, the quality of health services is a constant requirement and a priority for the population. "49% of Peruvians believe that health services are very bad, while 47% think they are good." (Datum International S.A., 2017) Therefore, we confirm that the main problems in the health sector are in the quality of services and not how much can they spend in the sector; this makes health care processes unsustainable. In addition, the National Health Users Satisfaction Survey of 2015 revealed that there are very critical problems that need to be resolved, for example, by stating that "the waiting time to be treated in a clinic has increased compared to 2014 when an average of time of 81 minutes waiting, now the time is 104 minutes. "(Gestión, 2016) Based on the information mentioned above, the best ambulatory care service is offered through an ambulatory mobile pharmacological information service application using the platform cloud; this proposal is useful because we can manage common disease data and migrates to the cloud to integrate into a platform developed in platform cloud. With this solution, it is possible to reduce attendance to health services and minimize waiting times for the response of a common disease, since the information was exposed in a mobile application. / Tesis

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Traditional database management systems are designed for general purpose data handling, and fail to work efficiently with time-series data due to characteristics like high volume, rapid ingestion rates, and a focus on temporal relationships. However, what is a best solution is not a trivial question to answer. Hence, this thesis aims to analyze four different Database Management Systems (DBMS) to determine their suitability for managing time series data, with a specific focus on Internet of Things (IoT) applications. The DBMSs examined include PostgreSQL, TimescaleDB, ClickHouse, and InfluxDB. This thesis evaluates query performance across varying dataset sizes and time ranges, as well as the implementational complexity of each DBMS. The benchmarking results indicate that InfluxDB consistently delivers the best performance, though it involves higher implementational complexity and time consumption. ClickHouse emerges as a strong alternative with the second-best performance and the simplest implementation. The thesis also identifies potential biases in benchmarking tools and suggests that TimescaleDB's performance may have been affected by configuration errors. The findings provide significant insights into the performance metrics and implementation challenges of the selected DBMSs. Despite limitations in fully addressing the research questions, this thesis offers a valuable overview of the examined DBMSs in terms of performance and implementational complexity. These results should be considered alongside additional research when selecting a DBMS for time series data. / Traditionella databashanteringssystem är utformade för allmän datahantering och fungerar inte effektivt med tidsseriedata på grund av egenskaper som hög volym, snabba insättningshastigheter och fokus på tidsrelationer. Dock är frågan om vad som är den bästa lösningen inte trivial. Därför syftar denna avhandling till att analysera fyra olika databashanteringssystem (DBMS) för att fastställa deras lämplighet för att hantera tidsseriedata, med ett särskilt fokus på Internet of Things (IoT)-applikationer. De DBMS som undersöks inkluderar PostgreSQL, TimescaleDB, ClickHouse och InfluxDB. Denna avhandling utvärderar sökprestanda över varierande datamängder och tidsintervall, samt implementeringskomplexiteten för varje DBMS. Prestandaresultaten visar att InfluxDB konsekvent levererar den bästa prestandan, men med högre implementeringskomplexitet och tidsåtgång. ClickHouse framstår som ett starkt alternativ med näst bäst prestanda och är enklast att implementera. Studien identifierar också potentiella partiskhet i prestandaverktygen och antyder att TimescaleDB:s prestandaresultat kan ha påverkats av konfigurationsfel. Resultaten ger betydande insikter i prestandamått och implementeringsutmaningar för de utvalda DBMS. Trots begränsningarna i att fullt ut besvara forskningsfrågorna erbjuder studien en värdefull översikt. Dessa resultat bör beaktas tillsammans med ytterligare forskning vid val av ett DBMS för tidsseriedata.

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Applications found in both large and small enterprises need a communication method in order to meet requirements of scalability and durability. Many communication methods exist, but the most well-used are message queues and message brokers. The problem is that there exist many different types of message queues and message brokers with their own unique design and implementation choices. These choices result in different parameter sets, which can be configured in order to meet requirements of for example high durability, throughput, and availability. This thesis tests two different message brokers, Apache Kafka and RabbitMQ, with the purpose of discussing and showing the impact on throughput and latency when using a variety of parameters. The experiments conducted are focused on two primary metrics, latency and throughput, with secondary metrics such as diskand CPU-usage. The parameters chosen for both RabbitMQ and Kafka are optimized for maximized throughput and decreased latency. The experiments conducted are tested on a cloud platform; Amazon Web Services. The results show that Kafka outshines RabbitMQ regarding throughput and latency. RabbitMQ is the most efficient in terms of quantity of data being written, while on the other hand being more CPU-heavy than Kafka. Kafka performs better than RabbitMQ in terms of the amount of messages being sent and having the shortest one-way latency. / Applikationer som finns i både komplexa och icke-komplexa system behöver en kommunikationsmetod för att uppfylla kriterierna för skalbarhet och hållbarhet. Många kommunikationsmetoder existerar, men de mest använda är meddelandeköer och meddelandemäklare. Problemet är att det finns en uppsjö av olika typer av meddelandeköer och meddelandemäklare som är unika med avseende på deras design och implementering. Dessa val resulterar i olika parametersatser som kan konfigureras för att passa olika kriterier, exempelvis hög hållbarhet, genomströmning och tillgänglighet. Denna avhandling testar två olika meddelandemäklare, Apache Kafka och RabbitMQ med syfte att diskutera och visa effekterna av att använda olika parametrar. De utförda experimenten är inriktade på två primära mätvärden, latens och genomströmning, med sekundära mätvärden som exempelvis diskanvändning och CPU-användning. De parametrar som valts för både RabbitMQ och Kafka optimeras med fokus på de primära mätvärdena. Experimenten som genomförs testades på en molnplattform; Amazon Web Services. Resultaten visar att Kafka presterar bättre än RabbitMQ när det kommer till genomströmning och latens. Gällande inverkan av Kafka och RabbitMQ på mängden skriven data, är RabbitMQ den mest effektiva, medan den å andra sidan är mer CPU-tung än Kafka.

Background: As cloud computing has risen over the last decades, there are several cloud services accessible on the market, users may prefer to select those that are more flexible and efficient. Based on the preceding, we chose to research to evaluate cloud services in terms of which would be better for the user in terms ofgetting the needed data from the chosen website and utilizing JMeter for performance testing. If we continue our thesis study by assessing the performance of different sample users using JMeter as the testing tool, it is appropriate for our thesis research subject. In this case, the user interfaces of GCP and AWS are compared while doing several compute engine-related operations. Objectives: This thesis aims to test the website performance after deploying in two distinct cloud platforms.After the creation of instances in AWS, a domain in GCP and also the bucket, the website files are uploaded into the bucket. The GCP and AWS instances are connected to the lifestyle store website. The performance testing on the selected website is done on both services, and then comparison ofthe outcomes of our thesis research using the testing tool Jmeter is done. Methods: In these, we choose experimentation as our research methodology,and in this, the task is done in two cloud platforms in which the website will be deployed separately. The testing tool with performance testing is employed. JMeter is used to test a website’s performance in both possible services and then to gather our research results, and the visualization of the results are done in an aggregate graph, graphs and summary reports. The metrics are Throughput, average response time, median, percentiles and standard deviation. Results: The results are based on JMeter performance testing of a selected web-site between two cloud platforms. The results of AWS and GCP can be shown in the aggregate graph. The graph results are based on the testing tool to determine which service is best for users to obtain a response from the website for requested data in the shortest amount of time. We have considered 500 and 1000 users, and based on the results, we have compared the metrics throughput, average response time, standard deviation and percentiles. The 1000 user results are compared to know which cloud platform performs better. Conclusions: According to the results from the 1000 users, it can be concluded that AWS has a higher throughput than GCP and a less average response time.Thus, it can be said that AWS outperforms GCP in terms of performance.

No / Cloud computing is increasingly attracting large attention both in academic research and in industrial initiatives. However, despite the popularity, there is a lack of research on the suitability of software tools and parameters for creating and deploying Cloud test beds. Virtualization and how to set up virtual environments can be done through software tools, which are available as open source, but there still needs to be work in terms of which tools to use and how to monitor parameters with the suitability of hardware resources available. This paper discusses the concepts of virtualization, as a practical view point, presenting an in-depth critical analysis of open source cloud implementation tools such as CloudStack, Eucalyptus, Nimbus, OpenStack, OpenNebula, OpenIoT, to name a few. This paper analyzes the various toolkits, parameters of these tools, and their usability for researchers looking to deploy their own Cloud test beds. The paper also extends further in developing an experimental case study of using OpenStack to construct and deploy a test bed using current resources available in the labs at the University of Bradford. This paper contributes to the theme of software setups and open source issues for developing Cloud test bed for deploying and constructing private Cloud test bed.

Cloud computing is a new paradigm that is changing the way we consume IT resources. One of the major changes is related to the pay-as-you-go pricing model. There are several kinds of cloud services being offered and the best option for software developers are Platform as a Service (PaaS). Even with cloud computing beeing a buzzword nowadays, there are few studies being developed to cover the way it will impact the software development. This thesis intents to contribute to fill this gap and provide the basis for new detailed studies about this subject. It presents an analysis about the main aspects in software delevopment that must be afected by the pay-as-you-go cloud model and highlights some of theses changes trough a case study. We noticed significant changes in the following areas: software pricing, performance benchmarks, software development estimation and requirements engineering. These changes are related to a new paradigm in which the IT resources used by software systems will directly impact the software price at all. This should also generate changes in how we deal with software optimization improvement. There is a large research field to be explored and this thesis contributes to point ou some directions. / Cloud Computing é um novo paradigma que está mudando a forma com que consumimos os recursos de TI. Uma das grandes mudanças está relacionada ao modelo de cobrança pay-asyou- go, em que se paga conforme o volume de recursos efetivamente consumidos. Há vários tipos de serviço oferecidos no ambiente cloud e a opção mais natural para os desenvolvedores de software são as Plataformas como Serviço (PaaS). Apesar de o tema cloud computing estar em evidência, há pouco ou nenhum estudo abordando o impacto deste modelo no desenvolvimento de software. O objetivo deste trabalho é contribuir para preencher esta lacuna e servir de base para que estudos mais detalhados sejam desenvolvidos. Para isto foi feita uma análise dos principais aspectos do desenvolvimento de software que serão afetados pelas plataformas pay-as-you-go de computação em nuvem, apontando itens específicos que sofrerão mudanças e evidenciando algumas destas mudanças através de um estudo de caso. Foram constatadas mudanças significativas em áreas relacionadas a precificação de software, benchmarks de desempenho, estimativas de desenvolvimento e engenharia de requisitos, sendo que esta última foi a que ficou mais evidente a partir do estudo de caso. Estas mudanças estão relacionadas a uma nova realidade em que o consumo racional dos recursos de TI tem impacto direto no preço do software, o que também deve gerar mudanças na forma como é tratada a otimização de código. O campo para novos estudos é vasto e este trabalho contribui para apontar alguns dos caminhos a seguir.