The master’s thesis deal with design and realization of measuring station, which process data from environmental sensors in IoT environment. Thesis includes research of sensors, cloud services for IoT, microcontrollers and environmental data available online. Thesis contains detailed procedure for realization of designed system, including code description for microcontrollers STM32W55 and STM32 B-L475E-IOT01A2 Discovery kit, configuration of IBM Watson IoT Platform cloud service and procedure for correct programming of Node-RED application responsible for logic of whole system. Source code, which might be used for simple implementation of designed system, is attached to the master’s thesis.

Cloud datacenters comprise hundreds or thousands of disparate application services, each having stringent performance and availability requirements, sharing a finite set of heterogeneous hardware and software resources. The implication of such complex environment is that the occurrence of performance problems, such as slow application response and unplanned downtimes, has become a norm rather than exception resulting in decreased revenue, damaged reputation, and huge human-effort in diagnosis. Though causes can be as varied as application issues (e.g. bugs), machine-level failures (e.g. faulty server), and operator errors (e.g. mis-configurations), recent studies have attributed capacity-related issues, such as resource shortage and contention, as the cause of most performance problems on the Internet today. As cloud datacenters become increasingly autonomous there is need for automated performance diagnosis systems that can adapt their operation to reflect the changing workload and topology in the infrastructure. In particular, such systems should be able to detect anomalous performance events, uncover manifestations of capacity bottlenecks, localize actual root-cause(s), and possibly suggest or actuate corrections. This thesis investigates approaches for diagnosing performance problems in cloud infrastructures. We present the outcome of an extensive survey of existing research contributions addressing performance diagnosis in diverse systems domains. We also present models and algorithms for detecting anomalies in real-time application performance and identification of anomalous datacenter resources based on operational metrics and spatial dependency across datacenter components. Empirical evaluations of our approaches shows how they can be used to improve end-user experience, service assurance and support root-cause analysis. / Cloud Control (C0590801)

En este artículo, se propone una arquitectura tecnológica que permite a las empresas que tienen implementado SAP ERP, exponer y consumir los servicios del ERP On-Premise a través de una plataforma cloud utilizando un agente de integración en la red corporativa privada. Esta propuesta tecnológica permite optimizar los tiempos de respuesta de los procesos de negocios implementados en un ERP. Esto se realiza a través del uso de los componentes de integración (SAP Cloud Connector o SAP Web Dispatcher), los cuales orquestan la conexión entre el ERP y el SCP (SAP Cloud Platform) a través de su acción como proxys inversor. La arquitectura tecnológica propuesta está compuesta por cinco capas: clientes, plataforma de servicios SCP, punto de integración, ERP On Premise y base de datos. Finalmente, a través de un caso de estudio, se determinó que el proceso de gestión de las reservas redujo su índice de errores en un 18% y el costo asociado a los actores del proceso disminuyó en un 25% permitiendo evidenciar que la propuesta cumple con los objetivos trazados. / In this article, a technological architecture is proposed that allows companies that have SAP ERP implemented to expose and consume ERP On-Premise services through a cloud platform using an integration agent in the private corporate network. This technological proposal allows optimizing the response times of the business processes implemented in an ERP. This is done through the use of integration components (SAP Cloud Connector or SAP Web Dispatcher), which orchestrate the connection between the ERP and the SCP (SAP Cloud Platform) through their action as investor proxies. The proposed technological architecture is composed of five layers: clients, SCP service platform, integration point, ERP On Premise and database. Finally, through a case study, it was determined that the reserve management process reduced its error rate by 18% and the cost associated with the actors in the process decreased by 25%, allowing evidence that the proposal complies with the objectives set.In this article, a technological architecture is proposed that allows companies that have SAP ERP implemented to expose and consume ERP On-Premise services through a cloud platform using an integration agent in the private corporate network. This technological proposal allows optimizing the response times of the business processes implemented in an ERP. This is done through the use of integration components (SAP Cloud Connector or SAP Web Dispatcher), which orchestrate the connection between the ERP and the SCP (SAP Cloud Platform) through their action as investor proxies. The proposed technological architecture is composed of five layers: clients, SCP service platform, integration point, ERP On Premise and database. Finally, through a case study, it was determined that the reserve management process reduced its error rate by 18% and the cost associated with the actors in the process decreased by 25%, allowing evidence that the proposal complies with the objectives set. / Tesis

All developers understand the benefits of testing their code to ensure its functionality. Today’s market is moving further towards design principles where testing is a central or driving force during development. This puts a certain pressure on academia to supply these skills to their students.Recently the course II1302 Projects and project methods at the Royal Institute of Technology in Kista made a concerted effort to introduce the students of the course to these modern concepts. This thesis investigates how areas of testing can effectively be introduced to the students in the course, utilizing a tailored example that takes the area of testing into particular consideration and how to automate it via DevOps-tools provided by a cloud-based service. Further, it also makes an attempt to provide additional material to be used for teaching testing in conjunction with the example provided.The case study covers the development of an example application, meant to mirror a typical student project. It also covers how this was used for teaching the students about the testing areas considered. The covered testing areas include unit testing, integration testing and UI testing. With these given testing areas, the application and an associated learning module was developed for each area in question. Relevant standards, strategies and approaches was also identified for each of these areas.The thesis also presents important properties to take into consideration when developing similar examples in the future, based on the experiences obtained during the study. These include needs such as understandable by inexperienced students, applicability outside the course, adherence to established standards, tools that are simple to use and an architectural structure that allows for testing.Some improvements are also recommended: the students would benefit from learning software testing from an early stage of their studies. The content of the learning modules should also be brought to the students earlier in the course, so it can be applied in their projects at an early stage as well.Further research is also recommended to evaluate the suitability of using other cloud-based environments instead, and to evaluate the applicability of the learning modules for students of varying disabilities. / Alla utvecklare förstår fördelarna med att testa kod för att garantera dess funktionalitet. Dagens industri går i en riktning där testning spelar en central del av design under utveckling av mjukvara. Denna tendens lägger en viss press på högskolan att lära ut dessa erfarenheter till dess studenter.På senare tid har kursen II1302 Projekt och projektmetoder på Kungliga Tekniska Högskolan i Kista tagit en stor ansats för att introducera sina studenter inför dessa moderna koncept. Denna uppsats undersöker hur testningsområdet effektivt kan introduceras till studenterna inom denna kurs, genom att utnyttja ett egengjort exempel som har området i fokus, samt att automatisera detta via DevOps-verktyg tillhandahållna av molnbaserade tjänster. Dessutom görs även en ansats för att tilldela ytterligare material som kan användas för att lära ut testning av mjukvara i samband med det givna exemplet.Fallstudien omfattar utvecklingen av en exempelapplikation, som var avsedd att likna ett typiskt studentprojekt. Den täcker även hur denna användes för att lära ut de betraktade testningsområdena till studenterna. De täckta områdena av testning inkluderar enhetstestning, integrationstestning och testning av användargränssnitt. Med dessa givna testningsområden utvecklades både applikationen och dess associerade lärmoduler för vardera testningområde i fråga. Relevanta standarder, strategier och metoder var också identifierade för vardera av dessa områden.Denna uppsats presenterar även ett antal viktiga egenskaper att hålla i åtanke vid utveckling av liknande exempel i framtiden, baserat på erfarenheterna från studien. Detta inkluderar behov som tillgänglighet för mindre erfarna studenter, applicerbarhet utanför själva kursen, tillämpning av etablerade standarder, utnyttjande av lättanvända verktyg och en arkitektur som tillåter testning.Några förbättringar föreslås även: studenterna skulle gynnas av att lära sig om mjukvarutestning i ett tidigt skede av sina studier. Innehållet i lärmodulerna bör även presenteras för studenterna tidigare i kursen för att kunna appliceras i deras projekt.Ytterligare forskning rekommenderas även för att utvärdera andra lämpliga molnbaserade miljöer, samt för att utvärdera tillämpbarheten av lärmodulerna hos studenter med inlärningssvårigheter.

Indoor Positioning System (IPS) are becoming more common in many areas such as retail, warehouses, smart facilities, and manufacturing.In recent years, Bluetooth Low Energy (BLE)-based IPS has become increasingly popular due to its low cost and low energy consumption. One of the more recent updates, Bluetooth 5.1, provides the ability to compute the location using Angle of Arrival (AoA) or Angle of Departure (AoD). These new features have allowed for better positioning accuracies, where AoA-based positioning has shown sub-meter accuracy. An application area for BLE-based IPS is retail stores where the technology can benefit both the store and its customers. This thesis investigates how to populate a database to be used with an IPS in a real-life store. The assumption is that customers will have BLE equipped devices and run an application that will send the properly formatted BLE advertisements, such that an BLE IPS can locate the user in the store. Additionally, we assume that the application can use the device's e-compass or other means to determine in which direction the user's device is oriented. Based on the position and orientation of the user, the software is assumed to access a database to know what item(s) are near the customer. However, the question remains of how did this data get into the database? This degree project explores this in detail and assesses the amount of time and effort needed to populate this database and the amount of time and effort needed to keep this database up to date. This project followed an iterative Design Science Research (DSR) methodology where the artifact is the database. A relational database was used as they are widely used and joins can easily be performed and it is easy to modify existing tables. The application was developed in Spring Boot and React. Amazon Web Services (AWS) was used to host and provide the necessary services for the database and application. The result showed that the estimated time needed to populate the database in a supermarket with a sales area of 5300 m2, 36623 products, and 220 containers is 106.64 hours and 107.13 hours in the worst case assuming a walking speed of 1.4 m s-1. Updating a product would take 10.34 s and 10.37 s if the time it takes for a staff member to walk to the place where the product is located is excluded. / Inomhuspositioneringssystem (IPS) har blivit allt vanligare inom många områden. De senaste åren har Bluetooth Low Energy (BLE)-baserad inomhuspositionering blivit mer populärt på grund av egenskaper som låg kostnad och låg energikonsumption. En av de senaste versionerna; Bluetooth 5.1 kan beräkna positionen med hjälp av ankomstvinkeln (eng. Angle of Arrival (AoA)) och utgångsvinkeln (eng. Angle of Departure (AoD)). Angle of Arrival (AoA)-baserad positionering kan uppnå en noggrannhet under 1 m. Ett Bluetooth Low Energy (BLE)-baserat IPS kan tillämpas i butiker där det kan gynna både butikens medarbetare och dess kunder. Detta examensarbete kommer att undersöka hur en databas som ska användas med ett IPS i en butik kan populeras. Antagandet i detta projekt är att kunderna kommer ha BLE utrustade enheter som kör ett program som tillåter att användaren kan lokalisera sig i butiken. Dessutom antar vi att applikationen kan använda enhetens e-kompass eller annan hårdvara för att kunna avgöra i vilken riktning användarens enhet är orienterad. Baserat på användarens position och riktning, antas det att mjukvaran kan komma åt databasen och veta vilka produkter som ligger i närheten av kunden. Dock kvarstår frågan: Hur sparades denna data i databasen? Det här examensarbetet kommer alltså att undersöka hur en databas i en butik kan vara uppbyggd om vi utgår från antagandet att BLE är tillämpat i butiken. Vi kommer även bedöma hur mycket tid som krävs för att populera en databas och hålla denna databas uppdaterad. Ett iterativ arbetsätt tillämpades i examensarbetet. I projektet användes en relationsdatabas eftersom det är enkelt att utföra join-operationer och uppdatera tabbeller i databasen. Applikationen som skapades tillhandahåller funktioner för att spara, uppdatera, radera och söka produkter i databasen. Frontend var kodad i React och backend var kodad i Spring Boot. Amazon Web Services (AWS) molntjänser och deras verktyg användes för att köra applikationen och databasen. Resultatet visade att populera en databas med produkter i en mataffär med en säljyta på 5300 m2, 36623 produkter, och 220 behållare (hyllor, kylskåp, etc.) tog 106.64 timmar i bästa fall och 107.13 timmar i värsta fall om vi antar en gångfart i 1.4 m s-1.

In today’s IT-landscape cloud computing is one of the hottest topics. There are many emerging uses and technologies for the cloud. Deployment of applications is one of the main usages of the cloud today. This has led to companies giving developers more responsibilities with deployment. Therefore, there is a need to update educations in computer science by including cloud deployment. For these reasons, this thesis attempts to give a reasonable proposal for how cloud deployment could be taught in a university course.A literature study was conducted to gather information about topics surrounding cloud deployment. These were topics like cloud computing, service models, building techniques and cloud services. Then a case study was conducted on three different cloud services, OpenShift, Cloud Foundry, and Heroku. This was to learn how to deploy. Lastly, two interviews and a survey were conducted with people that have an insight into the subject and could provide reasonable information.Based on our case study, interviews and survey we concluded a reasonable approach to how deployment with cloud services could be taught. It can be taught with a theoretical and practical part. The theoretical part could be a lecture introducing Heroku and OpenShift, followed by an assignment where students deploy an application to them. The reasons we recommend Heroku and OpenShift is for Heroku’s simple and fast deployment and OpenShift for being more educative.We also realized that cloud deployment would work best as a stand-alone course. Because during the degree project it became clear how broad cloud deployment is. / I dagens IT-miljö är molnet ett av de hetaste ämnena. Det finns många nya användningsområden och teknologier för molnet. Driftsättning av applikationer är ett av de viktigaste användningsområdena av molnet idag. Detta har lett till att företag ger utvecklare mer ansvar vid driftsättning. Därför är det nödvändigt att förändra utbildningar i datorvetenskap genom att inkludera driftsättning i molnmiljö. Av dessa skäl försöker denna avhandling ge ett rimligt förslag på hur driftsättning i molnmiljö kan läras ut på ett universitet.En litteraturstudie genomfördes för att samla information om ämnen som berör driftsättning i molnmiljö. Dessa var ämnen som molnet, servicemodeller, byggtekniker och molntjänster. Sedan genomfördes en fallstudie på tre olika molntjänster, OpenShift, Cloud Foundry och Heroku. Detta var för att lära sig hur man driftsätter. Slutligen genomfördes två intervjuer och en undersökning med personer som har insikt i ämnet och som kan ge rimlig information.Baserat på vår fallstudie, intervjuer och undersökning drog vi en slutsats för ett rimligt tillvägagångssätt för hur driftsättning i molnmiljö kunde läras ut. Det kan undervisas med en teoretisk och praktisk del. Den teoretiska delen kan vara en föreläsning som introducerar Heroku och OpenShift, följt av en uppgift där studenter driftsätter en applikation till dem. Anledningarna till att vi rekommenderar Heroku och OpenShift är för Heroku’s enkla och snabba driftsättning och OpenShift för att den är mycket mer lärorik.Vi insåg också att driftsättning i molnmiljö skulle fungera bäst som en fristående kurs. Eftersom det under examensprojektet blev klart hur brett driftsättning i molnmiljö är.

Cloud Computing (CC) is one of the fast growing computer network technologies and many companies offer their services through cloud network. Cloud Computing has many properties with respect to the existing traditional service provisions like scalability, availability, fault tolerance, capability and so on which are supported by many IT companies like Google, Amazon, Salesforce.com. These IT companies have more chances to adapt their services into a new environment, known as Cloud computing systems. There are many cloud computing services which are being provided by many IT companies.The purpose of this thesis is to investigate which cloud environment (public, private and hybrid) and services (Infrastructure as a Service, Software as a Service, and Platform as a Service) are suitable for Swedish Armed Forces (SWAF) with respect to performance, security, cost, flexibility and functionality. SWAF is using private (internal) cloud for communications where both sensitive and non-sensitive information are located in the internal cloud. There are problems like maintenance of hardware, cost issues and secure communication while maintaining the private cloud. In order to overcome those problems we have suggested a hybrid and community cloud environment and SaaS, IaaS, PaaS services for SWAF.For suggesting these cloud environments and cloud services we have performed a literature study and two empirical studies (survey and interviews) with different organizations.A new cloud model is designed based on the suggested cloud environment, separate storage spaces for sensitive and non-sensitive information, suitable services and an effective infrastructure for sharing the internal information for SWAF.

Le développement récent des offres commerciales autour du cloud computing a fortement influé sur la recherche et le développement des plateformes de distribution numérique. Les fournisseurs du cloud offrent une infrastructure de distribution extensible qui peut être utilisée pour le stockage et le traitement des données.En parallèle avec le développement des plates-formes de cloud computing, les modèles de programmation qui parallélisent de manière transparente l'exécution des tâches gourmandes en données sur des machines standards ont suscité un intérêt considérable, à commencer par le modèle MapReduce très connu aujourd'hui puis par d'autres frameworks plus récents et complets. Puisque ces modèles sont de plus en plus utilisés pour exprimer les tâches de traitement de données analytiques, la nécessité se fait ressentir dans l'utilisation des langages de haut niveau qui facilitent la charge de l'écriture des requêtes complexes pour ces systèmes.Cette thèse porte sur des modèles et techniques d'optimisation pour le traitement efficace de grandes masses de données du Web sur des infrastructures à grande échelle. Plus particulièrement, nous étudions la performance et le coût d'exploitation des services de cloud computing pour construire des entrepôts de données Web ainsi que la parallélisation et l'optimisation des langages de requêtes conçus sur mesure selon les données déclaratives du Web.Tout d'abord, nous présentons AMADA, une architecture d'entreposage de données Web à grande échelle dans les plateformes commerciales de cloud computing. AMADA opère comme logiciel en tant que service, permettant aux utilisateurs de télécharger, stocker et interroger de grands volumes de données Web. Sachant que les utilisateurs du cloud prennent en charge les coûts monétaires directement liés à leur consommation de ressources, notre objectif n'est pas seulement la minimisation du temps d'exécution des requêtes, mais aussi la minimisation des coûts financiers associés aux traitements de données. Plus précisément, nous étudions l'applicabilité de plusieurs stratégies d'indexation de contenus et nous montrons qu'elles permettent non seulement de réduire le temps d'exécution des requêtes mais aussi, et surtout, de diminuer les coûts monétaires liés à l'exploitation de l'entrepôt basé sur le cloud.Ensuite, nous étudions la parallélisation efficace de l'exécution de requêtes complexes sur des documents XML mis en œuvre au sein de notre système PAXQuery. Nous fournissons de nouveaux algorithmes montrant comment traduire ces requêtes dans des plans exprimés par le modèle de programmation PACT (PArallelization ConTracts). Ces plans sont ensuite optimisés et exécutés en parallèle par le système Stratosphere. Nous démontrons l'efficacité et l'extensibilité de notre approche à travers des expérimentations sur des centaines de Go de données XML.Enfin, nous présentons une nouvelle approche pour l'identification et la réutilisation des sous-expressions communes qui surviennent dans les scripts Pig Latin. Notre algorithme, nommé PigReuse, agit sur les représentations algébriques des scripts Pig Latin, identifie les possibilités de fusion des sous-expressions, sélectionne les meilleurs à exécuter en fonction du coût et fusionne d'autres expressions équivalentes pour partager leurs résultats. Nous apportons plusieurs extensions à l'algorithme afin d’améliorer sa performance. Nos résultats expérimentaux démontrent l'efficacité et la rapidité de nos algorithmes basés sur la réutilisation et des stratégies d'optimisation. / The recent development of commercial cloud computing environments has strongly impacted research and development in distributed software platforms. Cloud providers offer a distributed, shared-nothing infrastructure, that may be used for data storage and processing.In parallel with the development of cloud platforms, programming models that seamlessly parallelize the execution of data-intensive tasks over large clusters of commodity machines have received significant attention, starting with the MapReduce model very well known by now, and continuing through other novel and more expressive frameworks. As these models are increasingly used to express analytical-style data processing tasks, the need for higher-level languages that ease the burden of writing complex queries for these systems arises.This thesis investigates the efficient management of Web data on large-scale infrastructures. In particular, we study the performance and cost of exploiting cloud services to build Web data warehouses, and the parallelization and optimization of query languages that are tailored towards querying Web data declaratively.First, we present AMADA, an architecture for warehousing large-scale Web data in commercial cloud platforms. AMADA operates in a Software as a Service (SaaS) approach, allowing users to upload, store, and query large volumes of Web data. Since cloud users support monetary costs directly connected to their consumption of resources, our focus is not only on query performance from an execution time perspective, but also on the monetary costs associated to this processing. In particular, we study the applicability of several content indexing strategies, and show that they lead not only to reducing query evaluation time, but also, importantly, to reducing the monetary costs associated with the exploitation of the cloud-based warehouse.Second, we consider the efficient parallelization of the execution of complex queries over XML documents, implemented within our system PAXQuery. We provide novel algorithms showing how to translate such queries into plans expressed in the PArallelization ConTracts (PACT) programming model. These plans are then optimized and executed in parallel by the Stratosphere system. We demonstrate the efficiency and scalability of our approach through experiments on hundreds of GB of XML data.Finally, we present a novel approach for identifying and reusing common subexpressions occurring in Pig Latin scripts. In particular, we lay the foundation of our reuse-based algorithms by formalizing the semantics of the Pig Latin query language with extended nested relational algebra for bags. Our algorithm, named PigReuse, operates on the algebraic representations of Pig Latin scripts, identifies subexpression merging opportunities, selects the best ones to execute based on a cost function, and merges other equivalent expressions to share its result. We bring several extensions to the algorithm to improve its performance. Our experiment results demonstrate the efficiency and effectiveness of our reuse-based algorithms and optimization strategies.

Made available in DSpace on 2014-12-17T15:48:05Z (GMT). No. of bitstreams: 1 EvertonRSC_DISSERT.pdf: 4653595 bytes, checksum: 83e897be68464555082a55505fd406ea (MD5) Previous issue date: 2013-01-31 / Conselho Nacional de Desenvolvimento Cient?fico e Tecnol?gico / With the advance of the Cloud Computing paradigm, a single service offered by a cloud platform may not be enough to meet all the application requirements. To fulfill such requirements, it may be necessary, instead of a single service, a composition of services that aggregates services provided by different cloud platforms. In order to generate aggregated value for the user, this composition of services provided by several Cloud Computing platforms requires a solution in terms of platforms integration, which encompasses the manipulation of a wide number of noninteroperable APIs and protocols from different platform vendors. In this scenario, this work presents Cloud Integrator, a middleware platform for composing services provided by different Cloud Computing platforms. Besides providing an environment that facilitates the development and execution of applications that use such services, Cloud Integrator works as a mediator by providing mechanisms for building applications through composition and selection of semantic Web services that take into account metadata about the services, such as QoS (Quality of Service), prices, etc. Moreover, the proposed middleware platform provides an adaptation mechanism that can be triggered in case of failure or quality degradation of one or more services used by the running application in order to ensure its quality and availability. In this work, through a case study that consists of an application that use services provided by different cloud platforms, Cloud Integrator is evaluated in terms of the efficiency of the performed service composition, selection and adaptation processes, as well as the potential of using this middleware in heterogeneous computational clouds scenarios / Com o avan?o do paradigma de Computa??o em Nuvem, um ?nico servi?o oferecido por uma plataforma de nuvem pode n?o ser suficiente para satisfazer todos os requisitos da aplica??o. Para satisfazer tais requisitos, ao inv?s de um ?nico servi?o, pode ser necess?ria uma composi??o que agrega servi?os providos por diferentes plataformas de nuvem. A fim de gerar valor agregado para o usu?rio, essa composi??o de servi?os providos por diferentes plataformas de Computa??o em Nuvem requer uma solu??o em termos de integra??o de plataformas, envolvendo a manipula??o de um vasto n?mero de APIs e protocolos n?o interoper?veis de diferentes provedores. Nesse cen?rio, este trabalho apresenta o Cloud Integrator, uma plataforma de middleware para composi??o de servi?os providos por diferentes plataformas de Computa??o em Nuvem. Al?m de prover um ambiente que facilita o desenvolvimento e a execu??o de aplica??es que utilizam tais servi?os, o Cloud Integrator funciona como um mediador provendo mecanismos para a constru??o de aplica??es atrav?s da composi??o e sele??o de servi?os Web sem?nticos que consideram metadados acerca dos servi?os, como QoS (Quality of Service), pre?os etc. Adicionalmente, a plataforma de middleware proposta prov? um mecanismo de adapta??o que pode ser disparado em caso de falha ou degrada??o da qualidade de um ou mais servi?os utilizados pela aplica??o em quest?o, a fim de garantir sua a qualidade e disponibilidade. Neste trabalho, atrav?s de um estudo de caso que consiste de uma aplica??o que utiliza servi?os providos por diferentes plataformas de nuvem, o Cloud Integrator ? avaliado em termos da efici?ncia dos processos de composi??o de servi?os, sele??o e adapta??o realizados, bem como da potencialidade do seu uso em cen?rios de nuvens computacionais heterog?neas

Afin de construire des systèmes intelligents, où les machines sont capables de raisonner exactement comme les humains, les données avec sémantique sont une exigence majeure. Ce besoin a conduit à l’apparition du Web sémantique, qui propose des technologies standards pour représenter et interroger les données avec sémantique. RDF est le modèle répandu destiné à décrire de façon formelle les ressources Web, et SPARQL est le langage de requête qui permet de rechercher, d’ajouter, de modifier ou de supprimer des données RDF. Être capable de stocker et de rechercher des données avec sémantique a engendré le développement des nombreux systèmes de gestion des données RDF.L’évolution rapide du Web sémantique a provoqué le passage de systèmes de gestion des données centralisées à ceux distribués. Les premiers systèmes étaient fondés sur les architectures pair-à-pair et client-serveur, alors que récemment l’attention se porte sur le cloud computing.Les environnements de cloud computing ont fortement impacté la recherche et développement dans les systèmes distribués. Les fournisseurs de cloud offrent des infrastructures distribuées autonomes pouvant être utilisées pour le stockage et le traitement des données. Les principales caractéristiques du cloud computing impliquent l’évolutivité́, la tolérance aux pannes et l’allocation élastique des ressources informatiques et de stockage en fonction des besoins des utilisateurs.Cette thèse étudie la conception et la mise en œuvre d’algorithmes et de systèmes passant à l’échelle pour la gestion des données du Web sémantique sur des platformes cloud. Plus particulièrement, nous étudions la performance et le coût d’exploitation des services de cloud computing pour construire des entrepôts de données du Web sémantique, ainsi que l’optimisation de requêtes SPARQL pour les cadres massivement parallèles.Tout d’abord, nous introduisons les concepts de base concernant le Web sémantique et les principaux composants des systèmes fondés sur le cloud. En outre, nous présentons un aperçu des systèmes de gestion des données RDF (centralisés et distribués), en mettant l’accent sur les concepts critiques de stockage, d’indexation, d’optimisation des requêtes et d’infrastructure.Ensuite, nous présentons AMADA, une architecture de gestion de données RDF utilisant les infrastructures de cloud public. Nous adoptons le modèle de logiciel en tant que service (software as a service - SaaS), où la plateforme réside dans le cloud et des APIs appropriées sont mises à disposition des utilisateurs, afin qu’ils soient capables de stocker et de récupérer des données RDF. Nous explorons diverses stratégies de stockage et d’interrogation, et nous étudions leurs avantages et inconvénients au regard de la performance et du coût monétaire, qui est une nouvelle dimension importante à considérer dans les services de cloud public.Enfin, nous présentons CliqueSquare, un système distribué de gestion des données RDF basé sur Hadoop. CliqueSquare intègre un nouvel algorithme d’optimisation qui est capable de produire des plans massivement parallèles pour des requêtes SPARQL. Nous présentons une famille d’algorithmes d’optimisation, s’appuyant sur les équijointures n- aires pour générer des plans plats, et nous comparons leur capacité à trouver les plans les plus plats possibles. Inspirés par des techniques de partitionnement et d’indexation existantes, nous présentons une stratégie de stockage générique appropriée au stockage de données RDF dans HDFS (Hadoop Distributed File System). Nos résultats expérimentaux valident l’effectivité et l’efficacité de l’algorithme d’optimisation démontrant également la performance globale du système. / In order to build smart systems, where machines are able to reason exactly like humans, data with semantics is a major requirement. This need led to the advent of the Semantic Web, proposing standard ways for representing and querying data with semantics. RDF is the prevalent data model used to describe web resources, and SPARQL is the query language that allows expressing queries over RDF data. Being able to store and query data with semantics triggered the development of many RDF data management systems. The rapid evolution of the Semantic Web provoked the shift from centralized data management systems to distributed ones. The first systems to appear relied on P2P and client-server architectures, while recently the focus moved to cloud computing.Cloud computing environments have strongly impacted research and development in distributed software platforms. Cloud providers offer distributed, shared-nothing infrastructures that may be used for data storage and processing. The main features of cloud computing involve scalability, fault-tolerance, and elastic allocation of computing and storage resources following the needs of the users.This thesis investigates the design and implementation of scalable algorithms and systems for cloud-based Semantic Web data management. In particular, we study the performance and cost of exploiting commercial cloud infrastructures to build Semantic Web data repositories, and the optimization of SPARQL queries for massively parallel frameworks.First, we introduce the basic concepts around Semantic Web and the main components and frameworks interacting in massively parallel cloud-based systems. In addition, we provide an extended overview of existing RDF data management systems in the centralized and distributed settings, emphasizing on the critical concepts of storage, indexing, query optimization, and infrastructure. Second, we present AMADA, an architecture for RDF data management using public cloud infrastructures. We follow the Software as a Service (SaaS) model, where the complete platform is running in the cloud and appropriate APIs are provided to the end-users for storing and retrieving RDF data. We explore various storage and querying strategies revealing pros and cons with respect to performance and also to monetary cost, which is a important new dimension to consider in public cloud services. Finally, we present CliqueSquare, a distributed RDF data management system built on top of Hadoop, incorporating a novel optimization algorithm that is able to produce massively parallel plans for SPARQL queries. We present a family of optimization algorithms, relying on n-ary (star) equality joins to build flat plans, and compare their ability to find the flattest possibles. Inspired by existing partitioning and indexing techniques we present a generic storage strategy suitable for storing RDF data in HDFS (Hadoop’s Distributed File System). Our experimental results validate the efficiency and effectiveness of the optimization algorithm demonstrating also the overall performance of the system.