55 resultados para Cloud Computing Modelli di Business


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Cloud computing has seen an impressive growth in recent years, with virtualization technologies being massively adopted to create IaaS (Infrastructure as a Service) public and private solutions. Today, the interest is shifting towards the PaaS (Platform as a Service) model, which allows developers to abstract from the execution platform and focus only on the functionality. There are several public PaaS offerings available, but currently no private PaaS solution is ready for production environments. To fill this gap a new solution must be developed. In this paper we present a key element for enabling this model: a cloud repository based on the OSGi component model. The repository stores, manages, provisions and resolves the dependencies of PaaS software components and services. This repository can federate with other repositories located in the same or different clouds, both private and public. This way, dependencies can be fulfilled collaboratively, and new business models can be implemented.

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New technologies such as, the new Information and Communication Technology ICT, break new paths and redefines the way we understand business, the Cloud Computing is one of them. The on demand resource gathering and the per usage payment scheme are now commonplace, and allows companies to save on their ICT investments. Despite the importance of this issue, we still lack methodologies that help companies, to develop applications oriented for its exploitation in the Cloud. In this study we aim to fill this gap and propose a methodology for the development of ICT applications, which are directed towards a business model, and further outsourcing in the Cloud. In the former the Development of SOA applications, we take, as a baseline scenario, a business model from which to obtain a business process model. To this end, we use software engineering tools; and in the latter The Outsourcing we propose a guide that would facilitate uploading business models into the Cloud; to this end we describe a SOA governance model, which controls the SOA. Additionally we propose a Cloud government that integrates Service Level Agreements SLAs, plus SOA governance, and Cloud architecture. Finally we apply our methodology in an example illustrating our proposal. We believe that our proposal can be used as a guide/pattern for the development of business applications.

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Real-world experimentation facilities accelerate the development of Future Internet technologies and services, advance the market for smart infrastructures, and increase the effectiveness of business processes through the Internet. The federation of facilities fosters the experimentation and innovation with larger and more powerful environment, increases the number and variety of the offered services and brings forth possibilities for new experimentation scenarios. This paper introduces a management solution for cloud federation that automates service provisioning to the largest possible extent, relieves the developers from time-consuming configuration settings, and caters for real-time information of all information related to the whole lifecycle of the provisioned services. This is achieved by proposing solutions to achieve the seamless deployment of services across the federation and ability of services to span across different infrastructures of the federation, as well as monitoring of the resources and data which can be aggregated with a common structure, offered as an open ecosystem for innovation at the developers' disposal. This solution consists of several federation management tools and components that are part of the work on Cloud Federation conducted within XIFI project to build the federation of cloud infrastructures for the Future Internet Lab (FIWARE Lab). We present the design and implementation of the solution-concerned FIWARE Lab management tools and components that are deployed within a federation of 17 cloud infrastructures distributed across Europe.

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Recientemente, el paradigma de la computación en la nube ha recibido mucho interés por parte tanto de la industria como del mundo académico. Las infraestructuras cloud públicas están posibilitando nuevos modelos de negocio y ayudando a reducir costes. Sin embargo, una compañía podría desear ubicar sus datos y servicios en sus propias instalaciones, o tener que atenerse a leyes de protección de datos. Estas circunstancias hacen a las infraestructuras cloud privadas ciertamente deseables, ya sea para complementar a las públicas o para sustituirlas por completo. Por desgracia, las carencias en materia de estándares han impedido que las soluciones para la gestión de infraestructuras privadas se hayan desarrollado adecuadamente. Además, la multitud de opciones disponibles ha creado en los clientes el miedo a depender de una tecnología concreta (technology lock-in). Una de las causas de este problema es la falta de alineación entre la investigación académica y los productos comerciales, ya que aquella está centrada en el estudio de escenarios idealizados sin correspondencia con el mundo real, mientras que éstos consisten en soluciones desarrolladas sin tener en cuenta cómo van a encajar con los estándares más comunes o sin preocuparse de hacer públicos sus resultados. Con objeto de resolver este problema, propongo un sistema de gestión modular para infraestructuras cloud privadas enfocado en tratar con las aplicaciones en lugar de centrarse únicamente en los recursos hardware. Este sistema de gestión sigue el paradigma de la computación autónoma y está diseñado en torno a un modelo de información sencillo, desarrollado para ser compatible con los estándares más comunes. Este modelo divide el entorno en dos vistas, que sirven para separar aquello que debe preocupar a cada actor involucrado del resto de información, pero al mismo tiempo permitiendo relacionar el entorno físico con las máquinas virtuales que se despliegan encima de él. En dicho modelo, las aplicaciones cloud están divididas en tres tipos genéricos (Servicios, Trabajos de Big Data y Reservas de Instancias), para que así el sistema de gestión pueda sacar partido de las características propias de cada tipo. El modelo de información está complementado por un conjunto de acciones de gestión atómicas, reversibles e independientes, que determinan las operaciones que se pueden llevar a cabo sobre el entorno y que es usado para hacer posible la escalabilidad en el entorno. También describo un motor de gestión encargado de, a partir del estado del entorno y usando el ya mencionado conjunto de acciones, la colocación de recursos. Está dividido en dos niveles: la capa de Gestores de Aplicación, encargada de tratar sólo con las aplicaciones; y la capa del Gestor de Infraestructura, responsable de los recursos físicos. Dicho motor de gestión obedece un ciclo de vida con dos fases, para así modelar mejor el comportamiento de una infraestructura real. El problema de la colocación de recursos es atacado durante una de las fases (la de consolidación) por un resolutor de programación entera, y durante la otra (la online) por un heurístico hecho ex-profeso. Varias pruebas han demostrado que este acercamiento combinado es superior a otras estrategias. Para terminar, el sistema de gestión está acoplado a arquitecturas de monitorización y de actuadores. Aquella estando encargada de recolectar información del entorno, y ésta siendo modular en su diseño y capaz de conectarse con varias tecnologías y ofrecer varios modos de acceso. ABSTRACT The cloud computing paradigm has raised in popularity within the industry and the academia. Public cloud infrastructures are enabling new business models and helping to reduce costs. However, the desire to host company’s data and services on premises, and the need to abide to data protection laws, make private cloud infrastructures desirable, either to complement or even fully substitute public oferings. Unfortunately, a lack of standardization has precluded private infrastructure management solutions to be developed to a certain level, and a myriad of diferent options have induced the fear of lock-in in customers. One of the causes of this problem is the misalignment between academic research and industry ofering, with the former focusing in studying idealized scenarios dissimilar from real-world situations, and the latter developing solutions without taking care about how they f t with common standards, or even not disseminating their results. With the aim to solve this problem I propose a modular management system for private cloud infrastructures that is focused on the applications instead of just the hardware resources. This management system follows the autonomic system paradigm, and is designed around a simple information model developed to be compatible with common standards. This model splits the environment in two views that serve to separate the concerns of the stakeholders while at the same time enabling the traceability between the physical environment and the virtual machines deployed onto it. In it, cloud applications are classifed in three broad types (Services, Big Data Jobs and Instance Reservations), in order for the management system to take advantage of each type’s features. The information model is paired with a set of atomic, reversible and independent management actions which determine the operations that can be performed over the environment and is used to realize the cloud environment’s scalability. From the environment’s state and using the aforementioned set of actions, I also describe a management engine tasked with the resource placement. It is divided in two tiers: the Application Managers layer, concerned just with applications; and the Infrastructure Manager layer, responsible of the actual physical resources. This management engine follows a lifecycle with two phases, to better model the behavior of a real infrastructure. The placement problem is tackled during one phase (consolidation) by using an integer programming solver, and during the other (online) with a custom heuristic. Tests have demonstrated that this combined approach is superior to other strategies. Finally, the management system is paired with monitoring and actuators architectures. The former able to collect the necessary information from the environment, and the later modular in design and capable of interfacing with several technologies and ofering several access interfaces.

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The number of online real-time streaming services deployed over network topologies like P2P or centralized ones has remarkably increased in the recent years. This has revealed the lack of networks that are well prepared to respond to this kind of traffic. A hybrid distribution network can be an efficient solution for real-time streaming services. This paper contains the experimental results of streaming distribution in a hybrid architecture that consist of mixed connections among P2P and Cloud nodes that can interoperate together. We have chosen to represent the P2P nodes as Planet Lab machines over the world and the cloud nodes using a Cloud provider's network. First we present an experimental validation of the Cloud infrastructure's ability to distribute streaming sessions with respect to some key streaming QoS parameters: jitter, throughput and packet losses. Next we show the results obtained from different test scenarios, when a hybrid distribution network is used. The scenarios measure the improvement of the multimedia QoS parameters, when nodes in the streaming distribution network (located in different continents) are gradually moved into the Cloud provider infrastructure. The overall conclusion is that the QoS of a streaming service can be efficiently improved, unlike in traditional P2P systems and CDN, by deploying a hybrid streaming architecture. This enhancement can be obtained by strategic placing of certain distribution network nodes into the Cloud provider infrastructure, taking advantage of the reduced packet loss and low latency that exists among its datacenters.

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Cloud computing is one the most relevant computing paradigms available nowadays. Its adoption has increased during last years due to the large investment and research from business enterprises and academia institutions. Among all the services cloud providers usually offer, Infrastructure as a Service has reached its momentum for solving HPC problems in a more dynamic way without the need of expensive investments. The integration of a large number of providers is a major goal as it enables the improvement of the quality of the selected resources in terms of pricing, speed, redundancy, etc. In this paper, we propose a system architecture, based on semantic solutions, to build an interoperable scheduler for federated clouds that works with several IaaS (Infrastructure as a Service) providers in a uniform way. Based on this architecture we implement a proof-of-concept prototype and test it with two different cloud solutions to provide some experimental results about the viability of our approach.

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Over the last decade, Grid computing paved the way for a new level of large scale distributed systems. This infrastructure made it possible to securely and reliably take advantage of widely separated computational resources that are part of several different organizations. Resources can be incorporated to the Grid, building a theoretical virtual supercomputer. In time, cloud computing emerged as a new type of large scale distributed system, inheriting and expanding the expertise and knowledge that have been obtained so far. Some of the main characteristics of Grids naturally evolved into clouds, others were modified and adapted and others were simply discarded or postponed. Regardless of these technical specifics, both Grids and clouds together can be considered as one of the most important advances in large scale distributed computing of the past ten years; however, this step in distributed computing has came along with a completely new level of complexity. Grid and cloud management mechanisms play a key role, and correct analysis and understanding of the system behavior are needed. Large scale distributed systems must be able to self-manage, incorporating autonomic features capable of controlling and optimizing all resources and services. Traditional distributed computing management mechanisms analyze each resource separately and adjust specific parameters of each one of them. When trying to adapt the same procedures to Grid and cloud computing, the vast complexity of these systems can make this task extremely complicated. But large scale distributed systems complexity could only be a matter of perspective. It could be possible to understand the Grid or cloud behavior as a single entity, instead of a set of resources. This abstraction could provide a different understanding of the system, describing large scale behavior and global events that probably would not be detected analyzing each resource separately. In this work we define a theoretical framework that combines both ideas, multiple resources and single entity, to develop large scale distributed systems management techniques aimed at system performance optimization, increased dependability and Quality of Service (QoS). The resulting synergy could be the key 350 J. Montes et al. to address the most important difficulties of Grid and cloud management.

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El mundo tecnológico está cambiando hacia la optimización en la gestión de recursos gracias a la poderosa influencia de tecnologías como la virtualización y la computación en la nube (Cloud Computing). En esta memoria se realiza un acercamiento a las mismas, desde las causas que las motivaron hasta sus últimas tendencias, pasando por la identificación de sus principales características, ventajas e inconvenientes. Por otro lado, el Hogar Digital es ya una realidad para la mayoría de los seres humanos. En él se dispone de acceso a múltiples tipos de redes de telecomunicaciones (3G, 4G, WI-FI, ADSL…) con más o menos capacidad pero que permiten conexiones a internet desde cualquier parte, en todo momento, y con prácticamente cualquier dispositivo (ordenadores personales, smartphones, tabletas, televisores…). Esto es aprovechado por las empresas para ofrecer todo tipo de servicios. Algunos de estos servicios están basados en el cloud computing sobre todo ofreciendo almacenamiento en la nube a aquellos dispositivos con capacidad reducida, como son los smarthphones y las tabletas. Ese espacio de almacenamiento normalmente está en los servidores bajo el control de grandes compañías. Guardar documentos, videos, fotos privadas sin tener la certeza de que estos no son consultados por alguien sin consentimiento, puede despertar en el usuario cierto recelo. Para estos usuarios que desean control sobre su intimidad, se ofrece la posibilidad de que sea el propio usuario el que monte sus propios servidores y su propio servicio cloud para compartir su información privada sólo con sus familiares y amigos o con cualquiera al que le dé permiso. Durante el proyecto se han comparado diversas soluciones, la mayoría de código abierto y de libre distribución, que permiten desplegar como mínimo un servicio de almacenamiento accesible a través de Internet. Algunas de ellas lo complementan con servicios de streaming tanto de música como de videos, compartición y sincronización de documentos entre múltiples dispositivos, calendarios, copias de respaldo (backups), virtualización de escritorios, versionado de ficheros, chats, etc. El proyecto finaliza con una demostración de cómo utilizar dispositivos de un hogar digital interactuando con un servidor Cloud, en el que previamente se ha instalado y configurado una de las soluciones comparadas. Este servidor quedará empaquetado en una máquina virtual para que sea fácilmente transportable e utilizable. ABSTRACT. The technological world is changing towards optimizing resource management thanks to the powerful influence of technologies such as Virtualization and Cloud Computing. This document presents a closer approach to them, from the causes that have motivated to their last trends, as well as showing their main features, advantages and disadvantages. In addition, the Digital Home is a reality for most humans. It provides access to multiple types of telecommunication networks (3G, 4G, WI-FI, ADSL...) with more or less capacity, allowing Internet connections from anywhere, at any time, and with virtually any device (computer personal smartphones, tablets, televisions...).This is used by companies to provide all kinds of services. Some of these services offer storage on the cloud to devices with limited capacity, such as smartphones and tablets. That is normally storage space on servers under the control of important companies. Saving private documents, videos, photos, without being sure that they are not viewed by anyone without consent, can wake up suspicions in some users. For those users who want control over their privacy, it offers the possibility that it is the user himself to mount his own server and its own cloud service to share private information only with family and friends or with anyone with consent. During the project I have compared different solutions, most open source and with GNU licenses, for deploying one storage facility accessible via the Internet. Some supplement include streaming services of music , videos or photos, sharing and syncing documents across multiple devices, calendars, backups, desktop virtualization, file versioning, chats... The project ends with a demonstration of how to use our digital home devices interacting with a cloud server where one of the solutions compared is installed and configured. This server will be packaged in a virtual machine to be easily transportable and usable.

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With the advent of cloud computing model, distributed caches have become the cornerstone for building scalable applications. Popular systems like Facebook [1] or Twitter use Memcached [5], a highly scalable distributed object cache, to speed up applications by avoiding database accesses. Distributed object caches assign objects to cache instances based on a hashing function, and objects are not moved from a cache instance to another unless more instances are added to the cache and objects are redistributed. This may lead to situations where some cache instances are overloaded when some of the objects they store are frequently accessed, while other cache instances are less frequently used. In this paper we propose a multi-resource load balancing algorithm for distributed cache systems. The algorithm aims at balancing both CPU and Memory resources among cache instances by redistributing stored data. Considering the possible conflict of balancing multiple resources at the same time, we give CPU and Memory resources weighted priorities based on the runtime load distributions. A scarcer resource is given a higher weight than a less scarce resource when load balancing. The system imbalance degree is evaluated based on monitoring information, and the utility load of a node, a unit for resource consumption. Besides, since continuous rebalance of the system may affect the QoS of applications utilizing the cache system, our data selection policy ensures that each data migration minimizes the system imbalance degree and hence, the total reconfiguration cost can be minimized. An extensive simulation is conducted to compare our policy with other policies. Our policy shows a significant improvement in time efficiency and decrease in reconfiguration cost.

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One of the key factors for a given application to take advantage of cloud computing is the ability to scale in an efficient, fast and reliable way. In centralized multi-party video conferencing, dynamically scaling a running conversation is a complex problem. In this paper we propose a methodology to divide the Multipoint Control Unit (the video conferencing server) into more simple units, broadcasters. Each broadcaster receives the media from a participant, processes it and forwards it to the rest. These broadcasters can be distributed among a group of CPUs. By using this methodology, video conferencing systems can scale in a more granular way, improving the deployment.

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El extraordinario auge de las nuevas tecnologías de la información, el desarrollo de la Internet de las Cosas, el comercio electrónico, las redes sociales, la telefonía móvil y la computación y almacenamiento en la nube, han proporcionado grandes beneficios en todos los ámbitos de la sociedad. Junto a éstos, se presentan nuevos retos para la protección y privacidad de la información y su contenido, como la suplantación de personalidad y la pérdida de la confidencialidad e integridad de los documentos o las comunicaciones electrónicas. Este hecho puede verse agravado por la falta de una frontera clara que delimite el mundo personal del mundo laboral en cuanto al acceso de la información. En todos estos campos de la actividad personal y laboral, la Criptografía ha jugado un papel fundamental aportando las herramientas necesarias para garantizar la confidencialidad, integridad y disponibilidad tanto de la privacidad de los datos personales como de la información. Por otro lado, la Biometría ha propuesto y ofrecido diferentes técnicas con el fin de garantizar la autentificación de individuos a través del uso de determinadas características personales como las huellas dáctilares, el iris, la geometría de la mano, la voz, la forma de caminar, etc. Cada una de estas dos ciencias, Criptografía y Biometría, aportan soluciones a campos específicos de la protección de datos y autentificación de usuarios, que se verían enormemente potenciados si determinadas características de ambas ciencias se unieran con vistas a objetivos comunes. Por ello es imperativo intensificar la investigación en estos ámbitos combinando los algoritmos y primitivas matemáticas de la Criptografía con la Biometría para dar respuesta a la demanda creciente de nuevas soluciones más técnicas, seguras y fáciles de usar que potencien de modo simultáneo la protección de datos y la identificacíón de usuarios. En esta combinación el concepto de biometría cancelable ha supuesto una piedra angular en el proceso de autentificación e identificación de usuarios al proporcionar propiedades de revocación y cancelación a los ragos biométricos. La contribución de esta tesis se basa en el principal aspecto de la Biometría, es decir, la autentificación segura y eficiente de usuarios a través de sus rasgos biométricos, utilizando tres aproximaciones distintas: 1. Diseño de un esquema criptobiométrico borroso que implemente los principios de la biometría cancelable para identificar usuarios lidiando con los problemas acaecidos de la variabilidad intra e inter-usuarios. 2. Diseño de una nueva función hash que preserva la similitud (SPHF por sus siglas en inglés). Actualmente estas funciones se usan en el campo del análisis forense digital con el objetivo de buscar similitudes en el contenido de archivos distintos pero similares de modo que se pueda precisar hasta qué punto estos archivos pudieran ser considerados iguales. La función definida en este trabajo de investigación, además de mejorar los resultados de las principales funciones desarrolladas hasta el momento, intenta extender su uso a la comparación entre patrones de iris. 3. Desarrollando un nuevo mecanismo de comparación de patrones de iris que considera tales patrones como si fueran señales para compararlos posteriormente utilizando la transformada de Walsh-Hadarmard. Los resultados obtenidos son excelentes teniendo en cuenta los requerimientos de seguridad y privacidad mencionados anteriormente. Cada uno de los tres esquemas diseñados han sido implementados para poder realizar experimentos y probar su eficacia operativa en escenarios que simulan situaciones reales: El esquema criptobiométrico borroso y la función SPHF han sido implementados en lenguaje Java mientras que el proceso basado en la transformada de Walsh-Hadamard en Matlab. En los experimentos se ha utilizado una base de datos de imágenes de iris (CASIA) para simular una población de usuarios del sistema. En el caso particular de la función de SPHF, además se han realizado experimentos para comprobar su utilidad en el campo de análisis forense comparando archivos e imágenes con contenido similar y distinto. En este sentido, para cada uno de los esquemas se han calculado los ratios de falso negativo y falso positivo. ABSTRACT The extraordinary increase of new information technologies, the development of Internet of Things, the electronic commerce, the social networks, mobile or smart telephony and cloud computing and storage, have provided great benefits in all areas of society. Besides this fact, there are new challenges for the protection and privacy of information and its content, such as the loss of confidentiality and integrity of electronic documents and communications. This is exarcebated by the lack of a clear boundary between the personal world and the business world as their differences are becoming narrower. In both worlds, i.e the personal and the business one, Cryptography has played a key role by providing the necessary tools to ensure the confidentiality, integrity and availability both of the privacy of the personal data and information. On the other hand, Biometrics has offered and proposed different techniques with the aim to assure the authentication of individuals through their biometric traits, such as fingerprints, iris, hand geometry, voice, gait, etc. Each of these sciences, Cryptography and Biometrics, provides tools to specific problems of the data protection and user authentication, which would be widely strengthen if determined characteristics of both sciences would be combined in order to achieve common objectives. Therefore, it is imperative to intensify the research in this area by combining the basics mathematical algorithms and primitives of Cryptography with Biometrics to meet the growing demand for more secure and usability techniques which would improve the data protection and the user authentication. In this combination, the use of cancelable biometrics makes a cornerstone in the user authentication and identification process since it provides revocable or cancelation properties to the biometric traits. The contributions in this thesis involve the main aspect of Biometrics, i.e. the secure and efficient authentication of users through their biometric templates, considered from three different approaches. The first one is designing a fuzzy crypto-biometric scheme using the cancelable biometric principles to take advantage of the fuzziness of the biometric templates at the same time that it deals with the intra- and inter-user variability among users without compromising the biometric templates extracted from the legitimate users. The second one is designing a new Similarity Preserving Hash Function (SPHF), currently widely used in the Digital Forensics field to find similarities among different files to calculate their similarity level. The function designed in this research work, besides the fact of improving the results of the two main functions of this field currently in place, it tries to expand its use to the iris template comparison. Finally, the last approach of this thesis is developing a new mechanism of handling the iris templates, considering them as signals, to use the Walsh-Hadamard transform (complemented with three other algorithms) to compare them. The results obtained are excellent taking into account the security and privacy requirements mentioned previously. Every one of the three schemes designed have been implemented to test their operational efficacy in situations that simulate real scenarios: The fuzzy crypto-biometric scheme and the SPHF have been implemented in Java language, while the process based on the Walsh-Hadamard transform in Matlab. The experiments have been performed using a database of iris templates (CASIA-IrisV2) to simulate a user population. The case of the new SPHF designed is special since previous to be applied i to the Biometrics field, it has been also tested to determine its applicability in the Digital Forensic field comparing similar and dissimilar files and images. The ratios of efficiency and effectiveness regarding user authentication, i.e. False Non Match and False Match Rate, for the schemes designed have been calculated with different parameters and cases to analyse their behaviour.

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La tesis está focalizada en la resolución de problemas de optimización combinatoria, haciendo uso de las opciones tecnológicas actuales que ofrecen las tecnologías de la información y las comunicaciones, y la investigación operativa. Los problemas de optimización combinatoria se resuelven en general mediante programación lineal y metaheurísticas. La aplicación de las técnicas de resolución de los problemas de optimización combinatoria requiere de una elevada carga computacional, y los algoritmos deben diseñarse, por un lado pensando en la efectividad para encontrar buenas soluciones del problema, y por otro lado, pensando en un uso adecuado de los recursos informáticos disponibles. La programación lineal y las metaheurísticas son técnicas de resolución genéricas, que se pueden aplicar a diferentes problemas, partiendo de una base común que se particulariza para cada problema concreto. En el campo del desarrollo de software, los frameworks cumplen esa función de comenzar un proyecto con el trabajo general ya disponible, con la opción de cambiar o extender ese comportamiento base o genérico, para construir el sistema concreto, lo que permite reducir el tiempo de desarrollo, y amplía las posibilidades de éxito del proyecto. En esta tesis se han desarrollado dos frameworks de desarrollo. El framework ILP permite modelar y resolver problemas de programación lineal, de forma independiente al software de resolución de programación lineal que se utilice. El framework LME permite resolver problemas de optimización combinatoria mediante metaheurísticas. Tradicionalmente, las aplicaciones de resolución de problemas de optimización combinatoria son aplicaciones de escritorio que permiten gestionar toda la información de entrada del problema y resuelven el problema en local, con los recursos hardware disponibles. Recientemente ha aparecido un nuevo paradigma de despliegue y uso de aplicaciones que permite compartir recursos informáticos especializados por Internet. Esta nueva forma de uso de recursos informáticos es la computación en la nube, que presenta el modelo de software como servicio (SaaS). En esta tesis se ha construido una plataforma SaaS, para la resolución de problemas de optimización combinatoria, que se despliega sobre arquitecturas compuestas por procesadores multi-núcleo y tarjetas gráficas, y dispone de algoritmos de resolución basados en frameworks de programación lineal y metaheurísticas. Toda la infraestructura es independiente del problema de optimización combinatoria a resolver, y se han desarrollado tres problemas que están totalmente integrados en la plataforma SaaS. Estos problemas se han seleccionado por su importancia práctica. Uno de los problemas tratados en la tesis, es el problema de rutas de vehículos (VRP), que consiste en calcular las rutas de menor coste de una flota de vehículos, que reparte mercancías a todos los clientes. Se ha partido de la versión más clásica del problema y se han hecho estudios en dos direcciones. Por un lado se ha cuantificado el aumento en la velocidad de ejecución de la resolución del problema en tarjetas gráficas. Por otro lado, se ha estudiado el impacto en la velocidad de ejecución y en la calidad de soluciones, en la resolución por la metaheurística de colonias de hormigas (ACO), cuando se introduce la programación lineal para optimizar las rutas individuales de cada vehículo. Este problema se ha desarrollado con los frameworks ILP y LME, y está disponible en la plataforma SaaS. Otro de los problemas tratados en la tesis, es el problema de asignación de flotas (FAP), que consiste en crear las rutas de menor coste para la flota de vehículos de una empresa de transporte de viajeros. Se ha definido un nuevo modelo de problema, que engloba características de problemas presentados en la literatura, y añade nuevas características, lo que permite modelar los requerimientos de las empresas de transporte de viajeros actuales. Este nuevo modelo resuelve de forma integrada el problema de definir los horarios de los trayectos, el problema de asignación del tipo de vehículo, y el problema de crear las rotaciones de los vehículos. Se ha creado un modelo de programación lineal para el problema, y se ha resuelto por programación lineal y por colonias de hormigas (ACO). Este problema se ha desarrollado con los frameworks ILP y LME, y está disponible en la plataforma SaaS. El último problema tratado en la tesis es el problema de planificación táctica de personal (TWFP), que consiste en definir la configuración de una plantilla de trabajadores de menor coste, para cubrir una demanda de carga de trabajo variable. Se ha definido un modelo de problema muy flexible en la definición de contratos, que permite el uso del modelo en diversos sectores productivos. Se ha definido un modelo matemático de programación lineal para representar el problema. Se han definido una serie de casos de uso, que muestran la versatilidad del modelo de problema, y permiten simular el proceso de toma de decisiones de la configuración de una plantilla de trabajadores, cuantificando económicamente cada decisión que se toma. Este problema se ha desarrollado con el framework ILP, y está disponible en la plataforma SaaS. ABSTRACT The thesis is focused on solving combinatorial optimization problems, using current technology options offered by information technology and communications, and operations research. Combinatorial optimization problems are solved in general by linear programming and metaheuristics. The application of these techniques for solving combinatorial optimization problems requires a high computational load, and algorithms are designed, on the one hand thinking to find good solutions to the problem, and on the other hand, thinking about proper use of the available computing resources. Linear programming and metaheuristic are generic resolution techniques, which can be applied to different problems, beginning with a common base that is particularized for each specific problem. In the field of software development, frameworks fulfill this function that allows you to start a project with the overall work already available, with the option to change or extend the behavior or generic basis, to build the concrete system, thus reducing the time development, and expanding the possibilities of success of the project. In this thesis, two development frameworks have been designed and developed. The ILP framework allows to modeling and solving linear programming problems, regardless of the linear programming solver used. The LME framework is designed for solving combinatorial optimization problems using metaheuristics. Traditionally, applications for solving combinatorial optimization problems are desktop applications that allow the user to manage all the information input of the problem and solve the problem locally, using the available hardware resources. Recently, a new deployment paradigm has appeared, that lets to share hardware and software resources by the Internet. This new use of computer resources is cloud computing, which presents the model of software as a service (SaaS). In this thesis, a SaaS platform has been built for solving combinatorial optimization problems, which is deployed on architectures, composed of multi-core processors and graphics cards, and has algorithms based on metaheuristics and linear programming frameworks. The SaaS infrastructure is independent of the combinatorial optimization problem to solve, and three problems are fully integrated into the SaaS platform. These problems have been selected for their practical importance. One of the problems discussed in the thesis, is the vehicle routing problem (VRP), which goal is to calculate the least cost of a fleet of vehicles, which distributes goods to all customers. The VRP has been studied in two directions. On one hand, it has been quantified the increase in execution speed when the problem is solved on graphics cards. On the other hand, it has been studied the impact on execution speed and quality of solutions, when the problem is solved by ant colony optimization (ACO) metaheuristic, and linear programming is introduced to optimize the individual routes of each vehicle. This problem has been developed with the ILP and LME frameworks, and is available in the SaaS platform. Another problem addressed in the thesis, is the fleet assignment problem (FAP), which goal is to create lower cost routes for a fleet of a passenger transport company. It has been defined a new model of problem, which includes features of problems presented in the literature, and adds new features, allowing modeling the business requirements of today's transport companies. This new integrated model solves the problem of defining the flights timetable, the problem of assigning the type of vehicle, and the problem of creating aircraft rotations. The problem has been solved by linear programming and ACO. This problem has been developed with the ILP and LME frameworks, and is available in the SaaS platform. The last problem discussed in the thesis is the tactical planning staff problem (TWFP), which is to define the staff of lower cost, to cover a given work load. It has been defined a very rich problem model in the definition of contracts, allowing the use of the model in various productive sectors. It has been defined a linear programming mathematical model to represent the problem. Some use cases has been defined, to show the versatility of the model problem, and to simulate the decision making process of setting up a staff, economically quantifying every decision that is made. This problem has been developed with the ILP framework, and is available in the SaaS platform.

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as tecnologías emergentes como el cloud computing y los dispositivos móviles están creando una oportunidad sin precedentes para mejorar el sistema educativo, permitiendo tanto a los educadores personalizar y mejorar la experiencia de aprendizaje, como facilitar a los estudiantes que adquieran conocimientos sin importar dónde estén. Por otra parte, a través de técnicas de gamificacion será posible promover y motivar a los estudiantes a que aprendan materias arduas haciendo que la experiencia sea más motivadora. Los juegos móviles pueden ser el camino correcto para dar soporte a esta experiencia de aprendizaje mejorada. Este proyecto integra el diseño y desarrollo de una arquitectura en la nube altamente escalable y con alto rendimiento, así como el propio cliente de iOS, para dar soporte a una nueva version de Temporis, un juego móvil multijugador orientado a reordenar eventos históricos en una línea temporal (e.j. historia, arte, deportes, entretenimiento y literatura). Temporis actualmente está disponible en Google Play. Esta memoria describe el desarrollo de la nueva versión de Temporis (Temporis v.2.0) proporcionando detalles acerca de la mejora y adaptación basados en el Temporis original. En particular se describe el nuevo backend hecho en Go sobre Google App Engine creado para soportar miles de usuarios, asó como otras características por ejemplo como conseguir enviar noticaciones push desde la propia plataforma. Por último, el cliente de iOS en Temporis v.2.0 se ha desarrollado utilizando las últimas y más relevantes tecnologías, prestando especial atención a Swift (el lenguaje de programación nuevo de Apple, que es seguro y rápido), el Paradigma Funcional Reactivo (que ayuda a construir aplicaciones altamente interactivas además de a minimizar errores) y la arquitectura VIPER (una arquitectura que sigue los principios SOLID, se centra en la separación de asuntos y favorece la reutilización de código en otras plataformas). ABSTRACT Emerging technologies such as cloud computing and mobile devices are creating an unprecedented opportunity for enhancing the educational system, letting both educators customize and improve the learning experience, and students acquire knowledge regardless of where they are. Moreover, through gamification techniques it would be possible to encourage and motivate students to learn arduous subjects by making the experience more motivating. Mobile games can be a perfect vehicle to support this enhanced learning experience. This project integrates the design and development of a highly scalable and performant cloud architecture, as well as the iOS client that uses it, in order to provide support to a new version of Temporis, a mobile multiplayer game focused on ordering time-based (e.g. history, art, sports, entertainment and literature) in a timeline that currently is available on Google Play. This work describes the development of the new Temporis version (Temporis v.2.0), providing details about improvements and details on the adaptation of the original Temporis. In particular, the new Google App Engine backend is described, which was created to support thousand of users developed in Go language are provided, in addition to other features like how to achieve push notications in this platform. Finally, the mobile iOS client developed using the latest and more relevant technologies is explained paying special attention to Swift (Apple's new programming language, that is safe and fast), the Functional Reactive Paradigm (that helps building highly interactive apps while minimizing bugs) and the VIPER architecture (a SOLID architecture that enforces separation of concerns and makes it easy to reuse code for other platforms).

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Complexity has always been one of the most important issues in distributed computing. From the first clusters to grid and now cloud computing, dealing correctly and efficiently with system complexity is the key to taking technology a step further. In this sense, global behavior modeling is an innovative methodology aimed at understanding the grid behavior. The main objective of this methodology is to synthesize the grid's vast, heterogeneous nature into a simple but powerful behavior model, represented in the form of a single, abstract entity, with a global state. Global behavior modeling has proved to be very useful in effectively managing grid complexity but, in many cases, deeper knowledge is needed. It generates a descriptive model that could be greatly improved if extended not only to explain behavior, but also to predict it. In this paper we present a prediction methodology whose objective is to define the techniques needed to create global behavior prediction models for grid systems. This global behavior prediction can benefit grid management, specially in areas such as fault tolerance or job scheduling. The paper presents experimental results obtained in real scenarios in order to validate this approach.

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This paper proposes a new methodology focused on implementing cost effective architectures on Cloud Computing systems. With this methodology the paper presents some disadvantages of systems that are based on single Cloud architectures and gives some advices for taking into account in the development of hybrid systems. The work also includes a validation of these ideas implemented in a complete videoconference service developed with our research group. This service allows a great number of users per conference, multiple simultaneous conferences, different client software (requiring transcodification of audio and video flows) and provides a service like automatic recording. Furthermore it offers different kinds of connectivity including SIP clients and a client based on Web 2.0. The ideas proposed in this article are intended to be a useful resource for any researcher or developer who wants to implement cost effective systems on several Clouds