Le Cloud Computing représente une des plus importantes avancées numériques de ces dix dernières années. Le modèle de service offert par le cloud computing est basé sur une allocation élastique et à la demande des ressources et une facturation au plus juste de leur utilisation. Plusieurs catégories d’application sont en train de migrer vers le cloud (par exemple : les NFV et les applications du Big Data). D’autres domaines applicatifs, soumis à une législation plus stricte, sont plus frileux. Leurs exigences sont souvent liées à des problématiques de sécurité et/ou à la non satisfaction par les ressources proposées par un cloud unique, peuvent trouver des réponses dans l’utilisation conjointe de plusieurs fournisseurs de cloud computing (CSPs). L’exploitation simultanée, flexible, efficace et simplifiée de plusieurs clouds requiert des propriétés qui assurent sa viabilité et son acceptation tout d’abord par les fournisseurs de clouds qui proposent des offres hétérogènes et non interopérables et qui souvent pour des raisons commerciales, ne sont pas disposés à coopérer pour faciliter le multi-cloud « à la carte » ; mais aussi du point de vue du consommateur de services cloud dont les contraintes sont le temps de mise en service et le besoin d’exprimer les besoins en services et leur configuration de manière simple et transparente et de permettre la définition de configurations de déploiement adaptées aux besoins de chaque consommateur, comparables à celles offertes par les clouds privés et optimisées pour tirer profit des spécificités de chaque fournisseur de cloud. Dans cette thèse, nous proposons un framework permettant d’exprimer indépendamment de toute solution sous-jacente les besoins en services et en fournisseurs de cloud et de générer efficacement des infrastructures de déploiement extensibles, adaptatives et contrôlables par le consommateur. Cette solution est composée de MANTUS, un outil permettant l’expression des besoins et la génération automatique d’instances, d’ORBITS, des infrastructures de déploiement multi-cloud adaptables dynamiquement grâce aux mécanismes autonomiques offerts par MANTUS.La solution proposée se décline en plusieurs contributions : tout d’abord l’extension d’un framework IaC (Infrastructure as a Code) existant, dédié à la construction de solutions multi-cloud par des mécanismes de tissage, caractéristiques de la programmation par aspects (AOP), permettant ainsi d’injecter et d’extraire des ressources à la demande. Cette extension, expérimentée sur le framework TOSCA a nécessité la proposition du langage TML (Tosca Manipulation Language) permettant de formaliser et de manipuler ces extensions. Les expérimentations effectuées montrent une surcharge acceptable induite par le mécanisme de tissage. La seconde contribution a été de doter le framework IaC TOSCA d’un outil d’expression des besoins et d’un algorithme de matching en terme, d’une part, de nombre et de caractéristiques de fournisseur de cloud -notamment la localisation- et d’autre part en terme de caractéristiques des services proposés par ceux-ci, permettant de trouver la configuration multi-cloud la plus adaptée. La troisième contribution est la définition d’une architecture « template » multi-couche, ORBITS, offrant des mécanismes d’interopérabilité inter-cloud et une vision haut niveau indépendante des clouds sous jacents. Enfin la dernière contribution proposée est la pile de virtualisation U-cloud et les protocoles liée à son déploiement qui permettent de délimiter les zones contrôlables par le consommateur des zones contrôlées par le provider. Cette proposition est basée sur l’utilisation conjointe de la virtualisation imbriquée (Nested Virtualization) et des micro-hyperviseurs réduisant la zone d’attaque (TCB). / Cloud Computing represents one of the most important changes in information and communications technology (ICT) of the latest ten years. However, after a decade since its commercial debut, there are still several applications that cloud computing is not able to fully serve. These are the applications that, due to their particularly stringent requirements, must rely simultaneously on multiple Cloud Service Providers (CSPs), rather than only one. Multiple CSPs can in fact offer a better availability, improve QoS, and break the business dependence w.r.t. a single CSP. A cloud infrastructure based on multiple CSPs is called multi-cloud.Despite the benefits of multi-clouds, organisations (i.e developers and operators of IT services) seldom accept the challenge of building applications and crossing multiple CSP domains. In fact, multi-CSP architectures come at the cost of more complex applications and the logic to in terms of architecture and performance optimization.Recently, Multi-cloud client-oriented architectures emerged as important approach to construct multi-cloud applications. It provides cloud consumers a mechanism to allocate resources over multiple CSPs without requiring any cooperation among the CSPs themselves.In particular, Infrastructure as Code-based (IaC-based) represent the reference paradigm when building multi-cloud applications.However, the adoption of IaC in the multi-cloud context us limited by the fact that the cloud consumer cannot easily reuse the infrastructure code across different applications. This is due to two major problems, which we investigate in this manuscript.First, infrastructure are composed of functional (e.g. resources for applications) and non-functional services (e.g. monitoring). Non-functional related code should be shared at most across different applications and cloud consumers. However, this separation between functional and non-functional code is often blurred and, therefore, non-functional code is hard to be shared across them. This enables the possibility of code re-using across different cloud consumers (e.g., their different multi-cloud infrastructures) and static analysis of infrastructure templates. Furthermore, we present a TML (TOSCA Manipulation Language) aspect specification language to dynamically inject “non-functional” services to the virtual multi-cloud infrastructure. Secondly, the multi-cloud paradigm is limited by the “least common denominator” barrier. The cloud consumer can hardly obtain an optimized usage of resources and services through existing IaC frameworks. Despite compatible with different CSPs, those frameworks do not specialize the output according to deployment context.To tackle the “under-specialization” of multi-cloud templates, we introduce a “context-based matching” scheduling algorithm to select the most compelling set of CSPs according to the cloud consumer needs.To validate such contributions, we defined an end-to-end workflow to optimize a multi-cloud infrastructure definition. More precisely, in our model, the cloud consumer initially models the IaC code as an high-level graph of services, leveraging the combination of TML and context-based matching adoption. The output of this workflow is the instantation of such optimized and fully-featured multi-cloud on most suitable CSPs. We implemented Mantus, a multi-cloud compiler, which encapsulates this workflow and we benchmarked this implementation according to different perspectives as scalability and performance.

In recent times, there’s been a trend towards setting up smaller clouds at the edge of the network and interconnecting them across multiple sites. In these scenarios, the software used for managing the resources should be flexible enough to scale. Considering OpenStack the most widely used cloud software, It is observed that the compute service has shown performance degradation when the deployment reaches fewer hundreds of nodes. Finding out solutions to address the scalability issue in OpenStack, Ericsson has developed a new architecture that supports massive scalability of OpenStack clouds. However, the challenges with multicloud networking in P2P OpenStack remained unsolved. This thesis work as an extension to Ericsson’s P2P OpenStack project investigates various multi-cloud networking techniques and proposes two decentralized designs for cross Neutron networking in P2P OpenStack. The design-1 is based on OpenStack Tricircle project and design-2 is based on VPNaaS. This thesis work implements VPNaaS design to support the automatic interconnection of Virtual machines that belong to the same user but deployed in different OpenStack clouds. We evaluate this thesis for control plane operation under two different scenarios namely single user case and multiple users cases. In both scenarios, request-response time is chosen as an evaluating parameter. Results show that there is an increase in request-response time when users in the system are increased.

Distributed Real-Time Media Processing refers to classes of highly distributed, delay no-tolerant applications that account for the majority of the data traffic generated in the world today. Real-Time audio/video conferencing and live content streaming are of particular research interests as technology forecasts predict video traffic surpassing every other type of data traffic in the world in the near future. Live streaming refers to applications in which audio/video streams from a source need to be delivered to a set of geo-distributed destinations while maintaining low latency of stream delivery. Real-time conferencing platforms are application platforms that implement many-to-many audio/video real-time communications. Both of these categories exhibit high sensitivity to both network state (latency, jitter, packet loss, bit rate) as well as stream processing backend load profiles (latency and jitter introduced as Cloud processing of media packets). This thesis addresses enhancing real-time media processing both at the network level parameters as well as Cloud optimisations. We provide a novel, bandwidth management algorithm, for cloud services sharing the same network infrastructure, which provides a 2x improvement in system stability. Further examining network impact on cloud services, we provide a novel hybrid Cloud-Network distributed Cloud architecture to enable locality aware, application enhancements. This architecture led to a multi-cloud management overlay algorithm that maintains low management overhead on large scale cloud deployments. On the application level we provide a study of Media Quality parameters for a WebRTC enabled Media Cloud back-end, and provide patterns of quality metrics with respect to back-end stream load and network parameters. Additionally we empirically show that a "minimal load" algorithm for stream allocation, outperforms other Rotational, or Static Threshold based algorithms. / El procesamiento de medios en tiempo real distribuido se refiere a clases de aplicaciones altamente distribuidas,no tolerantes al retardo, que representan la mayoría del tráfico de datos generado en el mundo actual. Las conferenciasde audio y video en tiempo real y la transmisión de contenido en vivo tienen especial interés en investigación, ya quela prospectiva tecnológica estima que el tráfico de video supere a cualquier otro tipo de tráfico de datos en el futurocercano. La transmisión envivo se refiere a aplicaciones en las que flujos de audio/vídeo de una fuente se han de entregara un conjunto de destinos en lugares geográficos diferentes mientras se mantiene baja la latencia de entrega del flujo(como por ejemplo la cobertura de eventos en vivo). Las plataformas de conferencia en tiempo real son plataformasde  aplicación  que  implementan  comunicaciones  de  audio/video  en  tiempo  real  entre  muchos  participantes.  Ambascategorías presentan una alta sensibilidad tanto al estado de la red (latencia, jitter, pérdida de paquetes, velocidad debits) como a los perfiles de carga de la infraestructura de procesamiento de flujo (latencia y jitter introducidos duranteel procesamiento en la nube de paquetes de datos multimedia). Esta tesis trata de mejorar el procesamiento de datosmultimedia en tiempo real tanto en los parámetros de nivel de red como en las optimizaciones en la nube.En este contexto, investigamos si los recursos de la red se podían controlar a nivel de servicio para aumentar laeficiencia y el rendimiento de la red, así como cuantificar el impacto del recurso compartido de la red en la calidad delservicio. Los recursos de red compartidos afectan el rendimiento del servicio en la nube y, por lo tanto, optimizandoo intercambiando recursos de red pueden mejorar el rendimiento del servicio en la nube. Esta posible degradación delrendimiento se debe a la infraestructura de red compartida no regulada (la asignación de recursos de ancho de banda noes consciente de los objetivos del acuerdo de nivel de servicio (SLO) y de comportamiento). Gestionando el ancho debanda de la red a través de control predictivo, permitimos un mejor uso de los recursos de red disponibles y menoresviolaciones de SLO, logrando una mayor estabilidad del sistema por al menos un factor de 2.Las redes de acceso (AN) (extremo, red principal) de los ISP, transportistas y redes comunitarias no tienen unainfraestructura de nube de propósito general, mientras que los proveedores de recursos de Internet proporcionan bajodemanda recursos de la nube. Encontramos una oportunidad para la unificación de los recursos dentro de un AN y fueracon el fin de proporcionar una oferta de nube unificada a través de una federación de nubes y proporcionar movilidad delservicio hacia los usuarios para optimizar la localidad. Este trabajo de investigación proporciona una nueva arquitecturade red híbrida y nube federada que proporciona una infraestructura de red extendida con un despliegue en nube a granescala, incorporándolo directamente a la infraestructura de red. La nueva arquitectura multi-nube permite a los serviciosllegar a un compromiso entre localidad respecto al usuario o el rendimiento en tiempo de ejecución optimizando asípara latencia para conseguir la asignación óptima de recursos de aplicaciones en tiempo real. Para  optimizar  la  latencia  en  las  aplicaciones  de  transmisión  en  vivo  se  propuso  un  nuevo  algoritmo  desuperposición  de  multi-nube  autogestionado  basado  en  una  topología  de  gradiente  en  la  que  cada  nube  de  unaaplicación de transmisión de flujos optimiza la proximidad del cliente a la fuente. El modelo de aplicación se separa enun  diseño  de  dos  capas,  el  back-end  de  entrega  multi-nube  y  los  clientes  de  flujo.  El  backend  de  gradienteautorregulado minimiza la carga de tráfico creando un árbol de expansión mínimo a través de las nubes que se utilizapara  el  enrutamiento  de  cada  flujo.  El  algoritmo  propuesto  tiene  una  tasa  de  convergencia  muy  rápida  en  losdespliegues de nube a gran escala, y no resulta afectado por la rotación de recursos de la nube, así como proporcionauna mayor estabilidad de la transmisión en vivo.En este trabajo ofrecemos un análisis de calidad de los medios de comunicación y mejoras de los emisores deflujo en la nube en tiempo real, así como estrategias de asignación para mejorar el rendimiento de nivel de serviciode las plataformas de comunicación de Web en tiempo real. Los patrones de calidad de los medios están fuertementeinfluenciados por el rendimiento del procesamiento en la nube, y por lo tanto, al ajustar este aspecto, podemos controlarla calidad de los medios. En particular, demostramos empíricamente que a medida que los tamaños de sesión aumentan,la difusión simultánea supera la codificación de capa única. Además, introducimos un algoritmo de asignación de flujopara minimizar los picos de carga en los retransmisores de flujos en la nube y comparamos el comportamiento devarias políticas de asignación de flujos. Con la mínima información y el requisito de asignación de sesión de un únicoservidor, la política de asignación de carga mínima se comporta bastante mejor que otros algoritmos basados en unumbral rotativo o estático. / Distribuerad realtidshantering av mediadata syftar på klasser av starkt distribuerade tillämpningar som inte tolererar fördröjningar, och som utgör majoriteten av datatrafiken som genereras i världen idag. Audio/video-konferenser i realtid och överföring av innehåll "live" är av speciellt intresse för forskningen eftersom teknikprognoser förutser att videotrafiken kommer att kraftigt dominera över all annan datatrafik i den nära framtiden. "Live streaming" syftar på tillämpningar i vilka audio/video strömmar från en källa och behöver distribueras till en mängd av geografisk distribuerade destinationer medan överföringen bibehåller låg latens i leveransen av det strömmade datat (som ett exempel kan nämnas "live"-täckning av händelser). Konferensplattformar för realtidsdata är tillämpningsplattformar som implementerar realtidskommunikation av audio/video-data av typen "många-till-många". Båda dessa kategorier uppvisar hög känslighet för såväl nätverkets tillstånd (latens, jitter, paketförluster, bithastighet) och lastprofiler av ström bearbetning "back-end" (latens och jitter introducerat som Cloud-hantering av mediadatapaket). Denna avhandling adresserar förbättringar inom realtidshantering av mediainnehåll både med avseende på nätverksnivåns parametrar och optimeraringar för molninfrastrukturen. I detta sammanhang har vi undersökt huruvida nätverksresurserna kan kontrolleras på servicenivån i syfte att öka nätverkets effektivitet och prestanda, och även att kvantifiera påverkan av den delade nätverksresursen på servicekvaliteten. Delade nätverksresurser påverkar molntjänstens prestanda och dessa kan genom en optimering eller handel med nätverksresurser förbättra molntjänstens prestanda. Denna potentiella prestandadegradering beror på en oreglerad delad nätverksinfrastruktur (allokeringen av bandbredd är inte medveten om prestanda och mål för servicenivån). Genom att mediera nätverkets bandbredd genom prediktiv kontroll, möjliggör vi ett bättre utnyttjande av de tillgängliga nätverksresurserna och en lägre grad av avvikelser mot SLO, vilket leder till en ökad stabilitet med åtminstone en faktor 2. Accessnätverken (AN) (edge, kärnnätverk) hos ISP, bärare och lokala nätverk har ingen generell molninfrastruktur, medan s.k. "Internet Resource Providers" erbjuder resurser för molntjänster "on demand". Vi ser en möjlighet till ensande av resurserna inuti ett AN och utanför i syfte att erbjuda ett samlat molntjänsterbjudande genom s.k. "Cloud Federation" och erbjuder tjänstemobilitet för användarna för att optimera lokaliteten. Denna forskningansats erbjuder ett nytt hybrid nätverk med Federated Cloud arkitektur vilken ger en utvidgad nätverksinfrastruktur med en storskalig användning av molntjänster, som direkt inkorporerar denna i nätverksinfrastrukturen. Den nyskapande "Multi-Cloud"-arkitekturen möjliggör för tjänster att balansera lokalitet för användaren mot run-time-prestanda och därigenom optimera för latens mot optimal resursallokering för realtidstillämpningar. För att optimera latensen i "live streaming"-tillämpningar föreslås en nyskapande självstyrd "multi-Cloud-overlay"-algorithm baserad på gradienttopologi i vilken varje moln för en tillämpning inom "stream broadcasting" optimerar klientens närhet till källan. Tillämpningsmodellen separeras i en tvålagersdesign, "multi-cloud delivery back-end" och "stream clients". Denna självreglerande gradientbaserade "back-end" minimerar trafiklasten genom att skapa ett minimalt spännande träd genom molnen som används för routing av strömmarna. Den föreslagna algoritmen har en mycket snabb konvergenshastighet vid större moln, och påverkas inte av "churn" hos molnresursen liksom att den erbjuder ökad motståndskraft hos "live"-strömmen. I detta arbete erbjuder vi mediakvalitetsanalys och förstärkning av realtidsmolnets "forwarders", liksom även allokeringsstrategier för att förstärka servicenivåprestanda hos "Web Real-Time Communication"-plattformar. Mediakvalitetsmönster påverkas kraftigt av molnets bearbetsningsprestanda, och således kan vi genom att påverka denna aspekt kontrollera mediakvaliteten. Specifikt demonstrerar vi empiriskt att efterhand som sessionsstorlekarna ökar, så utklassar simulcast enlagersinkodning. Dessutom introducerar vi en strömallokeringsalgoritm för att minimera "load spikes" hos "Cloud stream forwarders" och jämför beteendet hos olika strömallokeringspolicys. Med enbart minimal information och allokeringsbehoven hos en enskild serversession beter sig den minimala lastbalansallokeringspolicyn tydligt bättre än andra "rotational"- eller "static threshold"-baserade algoritmer. / <p>QC 20170425</p>

No contexto da Engenharia de Software para a Computação em Nuvem as pesquisas relacionadas ao tema são cada vez mais crescentes e investiga-se como a Computação em Nuvem influenciará no desenvolvimento de sistemas de uma maneira geral. A atividade de construir sistemas para nuvem é uma tarefa complexa, criar aplicações de múltiplas nuvens, sobretudo, no contexto do modelo de serviço Plataforma-como-um-Serviço(PaaS), é ainda mais agravada devido especificidades de plataformas de nuvem que podem tornar a tarefa de desenvolvimento repetitiva, custosa e dependente de um provedor específico. As abordagens dirigidas por modelos(MDE) resolvem alguns desses problemas, elas propõem que a modelagem e mecanismos de transformação utilizados para gerar código a partir de modelos são uma melhor maneira de desenvolver sistemas de software, ao invés da codificação pura. Portanto, visando investigar como combinar os benefícios da Computação em Nuvem alinhados ao MDE, foi desenvolvida uma abordagem dirigida por modelos para desenvolvimento de aplicações multi-PaaS. Em direção a este objetivo foi realizado um Estudo de Caso em colaboração com uma empresa da indústria. Essa colaboração permitiu a criação de implementações de referencia que possibilitaram o desenvolvimento de uma Linguagem Específica de Domínio (DSL) e metaprogramas que compõem a abordagem. Para avaliar a abordagem desenvolvida foi realizado um Estudo de Caso. Os resultados mostram que MDE pode não só resolver o problema, mas trazer benefícios adicionais em relação a abordagens tradicionais de desenvolvimento de sistemas. Este trabalho explora esses benefícios, apresenta uma maneira de unir recursos heterogêneos de nuvem por meio de uma abordagem dirigida por modelos e aplicações orientadas a serviço. / Cloud computing is a computational paradigm that has increasingly been used in various sectors of industry and academia. Researchers have been studying how cloud technologies can influence several areas of science and research. In the context of Software Engineering, the researches related to cloud are increasingly increasing. Researchers are studying how to develop better cloud services offerings and how to find a strategy for combining existing resources to build improved services and solve problems. Building cloud systems is a complex task, in the context of the Platform-as-a-Service(PaaS) cloud service model; this activity is further aggravated by cloud platform specificities that can make the task of development repetitive, costly,and platform-specific. Model-driven approaches (MDE) solve some of these issues; they propose that the modeling and transformation mechanisms used to generate code from models are a better way to develop software systems, rather than pure coding. Development with MDE is a comprehensive and relevant research area and needs to be better explored in a wide range of contexts. Therefore, in order to investigate how to combine the benefits of multi-cloud appications aligned to the MDE, we developed a model-driven approach to build multi-PaaS applications.Toward this objective, we performed a case study in collaboration with an industry company.This collaboration allowed the creation of reference implementations that enabled the development of a Domain Specific Language (DSL) and metaprograms that constitute the approach. To evaluate the approach, we performed a case study. The results show that MDE cannot only solve the problem, but also bring additional benefits over traditional systems development approaches. This work explores these benefits, presents a way to combine heterogeneous cloud resources through a service-driven model and application-driven approach.

No contexto da Engenharia de Software para a Computação em Nuvem as pesquisas relacionadas ao tema são cada vez mais crescentes e investiga-se como a Computação em Nuvem influenciará no desenvolvimento de sistemas de uma maneira geral. A atividade de construir sistemas para nuvem é uma tarefa complexa, criar aplicações de múltiplas nuvens, sobretudo, no contexto do modelo de serviço Plataforma-como-um-Serviço(PaaS), é ainda mais agravada devido especificidades de plataformas de nuvem que podem tornar a tarefa de desenvolvimento repetitiva, custosa e dependente de um provedor específico. As abordagens dirigidas por modelos(MDE) resolvem alguns desses problemas, elas propõem que a modelagem e mecanismos de transformação utilizados para gerar código a partir de modelos são uma melhor maneira de desenvolver sistemas de software, ao invés da codificação pura. Portanto, visando investigar como combinar os benefícios da Computação em Nuvem alinhados ao MDE, foi desenvolvida uma abordagem dirigida por modelos para desenvolvimento de aplicações multi-PaaS. Em direção a este objetivo foi realizado um Estudo de Caso em colaboração com uma empresa da indústria. Essa colaboração permitiu a criação de implementações de referencia que possibilitaram o desenvolvimento de uma Linguagem Específica de Domínio (DSL) e metaprogramas que compõem a abordagem. Para avaliar a abordagem desenvolvida foi realizado um Estudo de Caso. Os resultados mostram que MDE pode não só resolver o problema, mas trazer benefícios adicionais em relação a abordagens tradicionais de desenvolvimento de sistemas. Este trabalho explora esses benefícios, apresenta uma maneira de unir recursos heterogêneos de nuvem por meio de uma abordagem dirigida por modelos e aplicações orientadas a serviço. / Cloud computing is a computational paradigm that has increasingly been used in various sectors of industry and academia. Researchers have been studying how cloud technologies can influence several areas of science and research. In the context of Software Engineering, the researches related to cloud are increasingly increasing. Researchers are studying how to develop better cloud services offerings and how to find a strategy for combining existing resources to build improved services and solve problems. Building cloud systems is a complex task, in the context of the Platform-as-a-Service(PaaS) cloud service model; this activity is further aggravated by cloud platform specificities that can make the task of development repetitive, costly,and platform-specific. Model-driven approaches (MDE) solve some of these issues; they propose that the modeling and transformation mechanisms used to generate code from models are a better way to develop software systems, rather than pure coding. Development with MDE is a comprehensive and relevant research area and needs to be better explored in a wide range of contexts. Therefore, in order to investigate how to combine the benefits of multi-cloud appications aligned to the MDE, we developed a model-driven approach to build multi-PaaS applications.Toward this objective, we performed a case study in collaboration with an industry company.This collaboration allowed the creation of reference implementations that enabled the development of a Domain Specific Language (DSL) and metaprograms that constitute the approach. To evaluate the approach, we performed a case study. The results show that MDE cannot only solve the problem, but also bring additional benefits over traditional systems development approaches. This work explores these benefits, presents a way to combine heterogeneous cloud resources through a service-driven model and application-driven approach.

Real-time streaming is becoming popular nowadays on the internet. WebRTC is a promising web technology that enables media stream transmission between two browsers without other third-party plugins. However, traditional WebRTC applications can only establish peer-to-peer (P2P) communications, which cannot be directly used in one-to-more streaming scenarios such as a multi-party video conference. This thesis project presents a development of a multi-cloud simulation framework to implement software multicast of WebRTC streams to enable oneto-more real-time streaming. The framework can generate a cloud network topology with a simple script, and provides flexible ways to model the network links with parameters such as bandwidth, packet loss, and link latency. By using selective forwarding units (SFUs), a stream publisher only needs to send a single copy of the data to the cloud, the data packets are duplicated and forwarded to multiple subscribers. In addition, three resource allocation algorithms are included in the framework to determine the data center for a task. To evaluate the performance, this framework enables people to monitor the throughputs and running streams on the data centers during the experiments. We develop benchmark applications as substitutes for real WebRTC traffic. These applications can generate UDP stream packets with the same dimension of WebRTC packets and provide the customization of stream parameters. In this report, we present a comparison of the stream performances under different allocation algorithms. Finally, as an outcome of this project, we design an integrated functional test to simulate a real-world scenario. The result shows that the framework is able to work well on complex real cases and simulate most of the multi-cloud networks.

yes / A large number of cloud middleware platforms and tools are deployed to support a variety of Internet of Things (IoT) data analytics tasks. It is a common practice that such cloud platforms are only used by its owners to achieve their primary and predefined objectives, where raw and processed data are only consumed by them. However, allowing third parties to access processed data to achieve their own objectives significantly increases intergation, cooperation, and can also lead to innovative use of the data. Multicloud, privacy-aware environments facilitate such data access, allowing different parties to share processed data to reduce computation resource consumption collectively. However, there are interoperability issues in such environments that involve heterogeneous data and analytics-as-a-service providers. There is a lack of both - architectural blueprints that can support such diverse, multi-cloud environments, and corresponding empirical studies that show feasibility of such architectures. In this paper, we have outlined an innovative hierarchical data processing architecture that utilises semantics at all the levels of IoT stack in multicloud environments. We demonstrate the feasibility of such architecture by building a system based on this architecture using OpenIoT as a middleware, and Google Cloud and Microsoft Azure as cloud environments. The evaluation shows that the system is scalable and has no significant limitations or overheads.

Submitted by SBI Biblioteca Digital (sbi.bibliotecadigital@puc-campinas.edu.br) on 2017-02-01T13:15:39Z No. of bitstreams: 1 LUIS PAULO GONCALVES PIRES.pdf: 3166033 bytes, checksum: 043d546bf3a8212c07798369bfcc2f7f (MD5) / Made available in DSpace on 2017-02-01T13:15:39Z (GMT). No. of bitstreams: 1 LUIS PAULO GONCALVES PIRES.pdf: 3166033 bytes, checksum: 043d546bf3a8212c07798369bfcc2f7f (MD5) Previous issue date: 2016-12-15 / Pontif?cia Universidade Cat?lica de Campinas ? PUC Campinas / While there is considerable enthusiasm for the migration of on-premise data centers to cloud computing services, there is still some concern about the availability of these same services. This is due, for example, to historical incidents such as that in 2011, when a crash on Amazon's servers caused sites of several of its customers to go down for almost 36 hours. In view of this, it becomes necessary to develop strategies to guarantee the availability offered by the providers. In the present work, a solution is proposed, which implements high availability in Multi-Cloud environments, through the distribution of DNS access and the use of reverse proxy. A financial analysis was also carried out, taking into account market values in Cloud Computing services, which showed that the proposed solution may even be advantageous with respect to the traditional one. Specifically, a Multi-Cloud system, consisting of two Clouds with 99.90% availability each, provides total availability of 99.999%, and it costs 34% less than a single Cloud with 99.95% availability. The simulation results, obtained in a virtualized environment, using two Clouds, with availability of 99.49% and 99.43%, showed a system availability of 99.9971%. In this way, using Multi-Cloud systems it is possible to obtain high availability systems, from lower availability Clouds, according to user?s needs, besides saving with provider services costs. / A despeito de haver consider?vel entusiasmo quanto ? migra??o de data-centers on-primese para servi?os de Cloud Computing, ainda existe certo receio no que se refere ? disponibilidade destes mesmos servi?os. Isso se deve, por exemplo, a incidentes hist?ricos como o ocorrido em 2011, quando uma falha nos servidores da Amazon fez com que sites de v?rios de seus clientes ficassem fora do ar por quase 36 horas. Em vista disso, torna-se necess?rio desenvolver estrat?gias para garantir a disponibilidade oferecida pelos provedores. No presente trabalho, descreve-se uma solu??o que implementa alta disponibilidade em ambientes Multi-Cloud, mediante a distribui??o de acesso por DNS e a utiliza??o de proxy reverso. Realizou-se tamb?m uma an?lise financeira, levando-se em conta valores de mercado em servi?os de Cloud Computing, o que mostrou que a solu??o proposta pode ser mesmo vantajosa com a rela??o ? solu??o tradicional. Especificamente, um sistema Multi-Cloud, composto por duas Clouds com disponibilidade de 99,90%, que prov? disponibilidade total de 99,999%, custa 34% menos do que uma ?nica Cloud com disponibilidade de 99,95%. Os resultados de simula??o, obtidos em ambiente virtualizado, utilizando-se duas Clouds, com disponibilidades de 99,49% e 99,43%, alcan?aram disponibilidade 99,9971%. Desta forma, utilizando-se sistemas Multi-Cloud ? poss?vel se obter sistemas de alta disponibilidade, de acordo necessidade do usu?rio, a partir de Clouds de mais baixa disponibilidade, al?m de ser poss?vel economizar com os custos dos servi?os do provedor.

Context: Cloud Computing is a very fascinating concept these days, it is attracting so many organiza-tions to move their utilities and applications into a dedicated data centers, and so it can be accessed from the Internet. This allows the users to focus solely on their businesses while Cloud Computing providers handle the technology. Choosing a best provider is a challenge for organizations that are willing to step into the Cloud Computing world. A single cloud center generally could not deliver large scale of resources for the cloud tenants; therefore, multiple cloud centers need to collaborate to achieve some business goals and to provide the best possible services at lowest possible costs. How-ever a number of aspects, legal issues, challenges, and policies should be taken into consideration when moving our service into the Cloud environment. Objectives: The aim of this research is to identify and elaborate the major technical and strategy differences between the cloud-computing providers in order to enable the organizations managements, system designers and decision makers to have better insight into the strategies of the different Cloud Computing providers. It is also to understand the risks and challenges due to implementing Cloud Computing, and “how” those issues can be moderated. This study will try to define Multi-Cloud Computing by studying the pros and cons of this new domain. It is also aiming to study the concept of load balancing in the cloud in order to examine the performance over multiple cloud environments. Methods: In this master thesis a number of research methods are used, including the systematic litera-ture review, contacting experts from the relevant field (Interviews) and performing a quantitative methodology (Experiment). Results: Based on the findings of the Literature Review, Interviews and Experiment, we got out the results for the research questions as, 1) A comprehensive study for identifying and comparing the major Cloud Computing providers, 2) Addressing a list of impacts of Cloud Computing (legal aspects, trust and privacy). 3) Creating a definition for Multi-Cloud Computing and identifying the benefits and drawbacks, 4) Finding the performance results on the cloud environment by performing an expe-riment on a load balancing solution. Conclusions: Cloud Computing becomes a central interest for many organizations nowadays. More and more companies start to step into the Cloud Computing service technologies, Amazon, Google, Microsoft, SalesForce, and Rackspace are the top five major providers in the market today. However, there is no Cloud that is perfect for all services. The legal framework is very important for the protection of the user’s private data; it is an important key factor for the safety of the user’s personal and sensitive information. The privacy threats vary according to the nature of the cloud scenario, since some clouds and services might face a very low privacy threats compare to the others, the public cloud that is accessed through the Internet is one of the most means when it comes the increasing threats of the privacy concerns. Lack of visibility of the provider supply chain will lead to suspicion and ultimately distrust. The evolution of Cloud Computing shows that it is likely, in a near future, the so-called Cloud will be in fact a Multi-cloud environment composed of a mixture of private and public Clouds to form an adaptive environment. Load balancing in the Cloud Computing environment is different from the typical load balancing. The architecture of cloud load balancing is using a number of commodity servers to perform the load balancing. The performance of the cloud differs depending on the cloud’s location even for the same provider. HAProxy load balancer is showing positive effect on the cloud’s performance at high amount of load, the effect is unnoticed at lower amounts of load. These effects can vary depending on the location of the cloud.

Storing personal information in a secure and reliable manner may be crucial for organizational as well as private users. Encryption protects the confidentiality of data against adversaries but if the cryptographic key is lost, the information will not be obtainable for authorized individuals either. Redundancy may protect information against availability issues or data loss, but also comes with greater storage overhead and cost. Cloud storage serves as an attractive alternative to traditional storage as one is released from maintenance responsibilities and does not have to invest in in-house IT-resources. However, cloud adoption is commonly hindered due to privacy concerns. Instead of relying on the security of a single cloud, this study aims to investigate the applicability of a multi-cloud solution based on Secret Sharing, and to identify suitable options and guidelines in a configuration user interface (UI). Interviews were conducted with technically skilled people representing prospective users, followed by walkthroughs of a UI prototype. Although the solution would (theoretically) allow for employment of less “trustworthy” clouds without compromising the data confidentiality, the research results indicate that trust factors such as compliance with EU laws may still be a crucial prerequisite in order for users to utilize cloud services. Users may worry about cloud storage providers colluding, and the solution may not be perceived as adequately secure without the use of encryption. The configuration of the Secret Sharing parameters are difficult to comprehend even for technically skilled individuals and default values could/should be recommended to the user. / PRISMACLOUD