Unified Management of Applications on Heterogeneous Clouds

La diversidad con la que los proveedores cloud ofrecen sus servicios, definiendo sus propias interfaces y acuerdos de calidad y de uso, dificulta la portabilidad y la interoperabilidad entre proveedores, lo que incurre en el problema conocido como el bloqueo del vendedor. Dada la heterogeneidad que existe entre los distintos niveles de abstracción del cloud, como IaaS y PaaS, hace que desarrollar aplicaciones agnósticas que sean independientes de los proveedores y los servicios en los que se van a desplegar sea aún un desafío. Esto también limita la posibilidad de migrar los componentes de aplicaciones cloud en ejecución a nuevos proveedores. Esta falta de homogeneidad también dificulta el desarrollo de procesos para operar las aplicaciones que sean robustos ante los errores que pueden ocurrir en los distintos proveedores y niveles de abstracción. Como resultado, las aplicaciones pueden quedar ligadas a los proveedores para las que fueron diseñadas, limitando la capacidad de los desarrolladores para reaccionar ante cambios en los proveedores o en las propias aplicaciones. En esta tesis se define trans-cloud como una nueva dimensión que unifica la gestión de distintos proveedores y niveles de servicios, IaaS y PaaS, bajo una misma API y hace uso del estándar TOSCA para describir aplicaciones agnósticas y portables, teniendo procesos automatizados, por ejemplo para el despliegue. Por otro lado, haciendo uso de las topologías estructuradas de TOSCA, trans-cloud propone un algoritmo genérico para la migración de componentes de aplicaciones en ejecución. Además, trans-cloud unifica la gestión de los errores, permitiendo tener procesos robustos y agnósticos para gestionar el ciclo de vida de las aplicaciones, independientemente de los proveedores y niveles de servicio donde se estén ejecutando. Por último, se presentan los casos de uso y los resultados de los experimentos usados para validar cada una de estas propuestas

Exploring traffic and QoS management mechanisms to support mobile cloud computing using service localisation in heterogeneous environments

In recent years, mobile devices have evolved to support an amalgam of multimedia applications and content. However, the small size of these devices poses a limit the amount of local computing resources. The emergence of Cloud technology has set the ground for an era of task offloading for mobile devices and we are now seeing the deployment of applications that make more extensive use of Cloud processing as a means of augmenting the capabilities of mobiles. Mobile Cloud Computing is the term used to describe the convergence of these technologies towards applications and mechanisms that offload tasks from mobile devices to the Cloud. In order for mobile devices to access Cloud resources and successfully offload tasks there, a solution for constant and reliable connectivity is required. The proliferation of wireless technology ensures that networks are available almost everywhere in an urban environment and mobile devices can stay connected to a network at all times. However, user mobility is often the cause of intermittent connectivity that affects the performance of applications and ultimately degrades the user experience. 5th Generation Networks are introducing mechanisms that enable constant and reliable connectivity through seamless handovers between networks and provide the foundation for a tighter coupling between Cloud resources and mobiles. This convergence of technologies creates new challenges in the areas of traffic management and QoS provisioning. The constant connectivity to and reliance of mobile devices on Cloud resources have the potential of creating large traffic flows between networks. Furthermore, depending on the type of application generating the traffic flow, very strict QoS may be required from the networks as suboptimal performance may severely degrade an application’s functionality. In this thesis, I propose a new service delivery framework, centred on the convergence of Mobile Cloud Computing and 5G networks for the purpose of optimising service delivery in a mobile environment. The framework is used as a guideline for identifying different aspects of service delivery in a mobile environment and for providing a path for future research in this field. The focus of the thesis is placed on the service delivery mechanisms that are responsible for optimising the QoS and managing network traffic. I present a solution for managing traffic through dynamic service localisation according to user mobility and device connectivity. I implement a prototype of the solution in a virtualised environment as a proof of concept and demonstrate the functionality and results gathered from experimentation. Finally, I present a new approach to modelling network performance by taking into account user mobility. The model considers the overall performance of a persistent connection as the mobile node switches between different networks. Results from the model can be used to determine which networks will negatively affect application performance and what impact they will have for the duration of the user's movement. The proposed model is evaluated using an analytical approac

Emerging approaches for data-driven innovation in Europe: Sandbox experiments on the governance of data and technology

Europe’s digital transformation of the economy and society is one of the priorities of the current Commission and is framed by the European strategy for data. This strategy aims at creating a single market for data through the establishment of a common European data space, based in turn on domain-specific data spaces in strategic sectors such as environment, agriculture, industry, health and transportation. Acknowledging the key role that emerging technologies and innovative approaches for data sharing and use can play to make European data spaces a reality, this document presents a set of experiments that explore emerging technologies and tools for data-driven innovation, and also deepen in the socio-technical factors and forces that occur in data-driven innovation. Experimental results shed some light in terms of lessons learned and practical recommendations towards the establishment of European data spaces