839 resultados para hybrid cloud computing


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Introducción: Los softwares dietoterapéuticos constituyen actualmente una herramienta básica en el tratamiento dietético de pacientes, ya sea desde un punto de vista fisiológico y/o patológico. Las nuevas tecnologías y la investigación en este sentido, han favorecido la aparición de nuevas aplicaciones de gestión dietético-nutricional que facilitan la gestión de la empresa dietoterapéutica. Objetivos: Estudiar comparativamente las principales aplicaciones dietoterapéuticas existentes en el mercado para dar criterio a los usuarios profesionales de la dietética y nutrición en la selección de una de las principales herramientas para éstos. Resultados: Desde nuestro punto de vista, dietopro. com resulta, junto con otras de las aplicaciones dietoterapéuticas analizadas, una de las más completas para la gestión de la clínica nutricional. Conclusión: En función de la necesidad del usuario, éste dispone de diferentes softwares dietéticos donde elegir. Se concluye que la selección de una u otra, depende de las necesidades del profesional.

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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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Wireless Body Area Networks (WBANs) have emerged as a promising technology for medical and non-medical applications. WBANs consist of a number of miniaturized, portable, and autonomous sensor nodes that are used for long-term health monitoring of patients. These sensor nodes continuously collect information of patients, which are used for ubiquitous health monitoring. In addition, WBANs may be used for managing catastrophic events and increasing the effectiveness and performance of rescue forces. The huge amount of data collected by WBAN nodes demands scalable, on-demand, powerful, and secure storage and processing infrastructure. Cloud computing is expected to play a significant role in achieving the aforementioned objectives. The cloud computing environment links different devices ranging from miniaturized sensor nodes to high-performance supercomputers for delivering people-centric and context-centric services to the individuals and industries. The possible integration of WBANs with cloud computing (WBAN-cloud) will introduce viable and hybrid platform that must be able to process the huge amount of data collected from multiple WBANs. This WBAN-cloud will enable users (including physicians and nurses) to globally access the processing and storage infrastructure at competitive costs. Because WBANs forward useful and life-critical information to the cloud – which may operate in distributed and hostile environments, novel security mechanisms are required to prevent malicious interactions to the storage infrastructure. Both the cloud providers and the users must take strong security measures to protect the storage infrastructure.

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Nowadays, data handling and data analysis in High Energy Physics requires a vast amount of computational power and storage. In particular, the world-wide LHC Com- puting Grid (LCG), an infrastructure and pool of services developed and deployed by a ample community of physicists and computer scientists, has demonstrated to be a game changer in the efficiency of data analyses during Run-I at the LHC, playing a crucial role in the Higgs boson discovery. Recently, the Cloud computing paradigm is emerging and reaching a considerable adoption level by many different scientific organizations and not only. Cloud allows to access and utilize not-owned large computing resources shared among many scientific communities. Considering the challenging requirements of LHC physics in Run-II and beyond, the LHC computing community is interested in exploring Clouds and see whether they can provide a complementary approach - or even a valid alternative - to the existing technological solutions based on Grid. In the LHC community, several experiments have been adopting Cloud approaches, and in particular the experience of the CMS experiment is of relevance to this thesis. The LHC Run-II has just started, and Cloud-based solutions are already in production for CMS. However, other approaches of Cloud usage are being thought of and are at the prototype level, as the work done in this thesis. This effort is of paramount importance to be able to equip CMS with the capability to elastically and flexibly access and utilize the computing resources needed to face the challenges of Run-III and Run-IV. The main purpose of this thesis is to present forefront Cloud approaches that allow the CMS experiment to extend to on-demand resources dynamically allocated as needed. Moreover, a direct access to Cloud resources is presented as suitable use case to face up with the CMS experiment needs. Chapter 1 presents an overview of High Energy Physics at the LHC and of the CMS experience in Run-I, as well as preparation for Run-II. Chapter 2 describes the current CMS Computing Model, and Chapter 3 provides Cloud approaches pursued and used within the CMS Collaboration. Chapter 4 and Chapter 5 discuss the original and forefront work done in this thesis to develop and test working prototypes of elastic extensions of CMS computing resources on Clouds, and HEP Computing “as a Service”. The impact of such work on a benchmark CMS physics use-cases is also demonstrated.

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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

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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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Il serverless é un paradigma del cloud computing al giorno d’oggi sempre più diffuso; si basa sulla scrittura di funzioni stateless in quanto le attività relative alla loro manutenzione e scalabilità fanno capo al provider dei servizi cloud. Lo sviluppatore deve quindi solamente concentrarsi sulla creazione del prodotto. Questo lavoro si apre con un’analisi del cloud computing introducendo i principali modelli di applicazione, passando dal parlare di servizi cloud, con le varie sottocategorie e i relativi utilizzi per poi arrivare a parlare di serverless. Si é scelto di focalizzarsi sulla piattaforma Google con la suite: Google Cloud Platform. In particolare, si parlerà di Google Cloud Functions, una nuova offerta serverless della compagnia, di recente sviluppo e in continuo aggiornamento. Partiremo dalle prime release, analizzeremo l’ambiente di sviluppo, i casi d’uso, vantaggi, svantaggi, parleremo poi di portabilità e verranno mostrati alcuni esempi del loro utilizzo.

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Cloud computing is increasingly being adopted in different scenarios, like social networking, business applications, scientific experiments, etc. Relying in virtualization technology, the construction of these computing environments targets improvements in the infrastructure, such as power-efficiency and fulfillment of users’ SLA specifications. The methodology usually applied is packing all the virtual machines on the proper physical servers. However, failure occurrences in these networked computing systems can induce substantial negative impact on system performance, deviating the system from ours initial objectives. In this work, we propose adapted algorithms to dynamically map virtual machines to physical hosts, in order to improve cloud infrastructure power-efficiency, with low impact on users’ required performance. Our decision making algorithms leverage proactive fault-tolerance techniques to deal with systems failures, allied with virtual machine technology to share nodes resources in an accurately and controlled manner. The results indicate that our algorithms perform better targeting power-efficiency and SLA fulfillment, in face of cloud infrastructure failures.

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Trabalho Final de Mestrado para a obtenção do grau de Mestre em Engenharia Informática e de Computadores

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Projeto para obtenção do grau de Mestre em Engenharia Informática e de Computadores

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Data analytic applications are characterized by large data sets that are subject to a series of processing phases. Some of these phases are executed sequentially but others can be executed concurrently or in parallel on clusters, grids or clouds. The MapReduce programming model has been applied to process large data sets in cluster and cloud environments. For developing an application using MapReduce there is a need to install/configure/access specific frameworks such as Apache Hadoop or Elastic MapReduce in Amazon Cloud. It would be desirable to provide more flexibility in adjusting such configurations according to the application characteristics. Furthermore the composition of the multiple phases of a data analytic application requires the specification of all the phases and their orchestration. The original MapReduce model and environment lacks flexible support for such configuration and composition. Recognizing that scientific workflows have been successfully applied to modeling complex applications, this paper describes our experiments on implementing MapReduce as subworkflows in the AWARD framework (Autonomic Workflow Activities Reconfigurable and Dynamic). A text mining data analytic application is modeled as a complex workflow with multiple phases, where individual workflow nodes support MapReduce computations. As in typical MapReduce environments, the end user only needs to define the application algorithms for input data processing and for the map and reduce functions. In the paper we present experimental results when using the AWARD framework to execute MapReduce workflows deployed over multiple Amazon EC2 (Elastic Compute Cloud) instances.

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Neste trabalho foi considerada a possibilidade de incorporar serviços remotos, normalmente associados a serviços web e cloud computing, numa solução local que centralizasse os vários serviços num único sistema e permitisse aos seus utilizadores consumir e configurar os mesmos, quer a partir da rede local, quer remotamente a partir da Internet. Desta forma seria possível conciliar o acesso a partir de qualquer local com internet, característico nas clouds, com a simplicidade de concentrar num só sistema vários serviços que são por norma oferecidos por entidades distintas e ainda permitir aos seus utilizadores o controlo e configuração sobre os mesmos. De forma a validar que este conceito é viável, prático e funcional, foram implementadas duas componentes. Um cliente que corre nos dispositivos dos utilizadores e que proporciona a interface para consumir os serviços disponíveis e um servidor que irá conter e prestar esses serviços aos clientes. Estes serviços incluem lista de contactos, mensagens instantâneas, salas de conversação, transferência de ficheiros, chamadas e conferências de voz e vídeo, pastas remotas, pastas sincronizadas, backups, pastas partilhadas, VoD (Video-on Demand) e AoD (Audio-on Demand). Para o desenvolvimento do cliente e do servidor foi utilizada a framework Qt que recorre à linguagem de programação C++ e ao conjunto de bibliotecas que possui, para o desenvolvimento de aplicações multiplataforma. Para as comunicações entre clientes e servidor, foi utilizado o protocolo XMPP (Extensible Messaging and Presence Protocol), pela forma da biblioteca qxmpp e do servidor XMPP ejabberd. Pelo facto de conter um conjunto de centenas de extensões atualmente ativas que auferem funcionalidades como salas de conversação, transferências de ficheiros e até estabelecer sessões multimédia, graças à sua flexibilidade permitiu ainda a criação de extensões personalizada necessárias para algumas funcionalidades que se pretendeu implementar. Foi ainda utilizado no servidor a framework ffmpeg para suportar algumas funcionalidades multimédia. Após a implementação do cliente para Windows e Linux, e de implementar o servidor em Linux foi realizado um conjunto de testes funcionais para perceber se as funcionalidades e seus mecanismos funcionam corretamente. No caso onde a análise da performance e do consumo de recursos era importante, foram realizados testes de performance e testes de carga.

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Dissertação para obtenção do Grau de Mestre em Engenharia Informática

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Dissertação para obtenção do Grau de Mestre em Engenharia Informática

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Dissertação de mestrado integrado em Engenharia de Telecomunicações e Informática