905 resultados para Grid Web Service


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Este trabajo descriptivo exploratorio se propone analizar la arquitectura de información (AI) de sitios Web de bibliotecas de la Universidad Nacional de La Plata (UNLP), Argentina. Se analizaron 17 bibliotecas y se aplicó una grilla para recabar 10 aspectos relevantes. Los resultados fueron: 1. Ubicación del sitio Web de la biblioteca: 9 sitios incluidos en la página principal de la facultad. 2. Etiquetado de contenidos: terminología simple, sin jergas; no hay homogeneidad entre las bibliotecas. 3. Capacidad de búsqueda: 62 por ciento positiva, 38 por ciento negativa. 4. Sistema de búsqueda: simple 43 por ciento, compleja 10 por ciento, con ayudas 10 por ciento, ninguno 38 por ciento. 5. Sistemas de navegación: globales 5 por ciento, jerárquicos 79 por ciento, locales 5 por ciento, ninguno 11 por ciento. 6. Herramientas de navegación: barras 16 por ciento, frames o marcos 30 por ciento, índices 2 por ciento, mapas de sitio 7 por ciento, menús horizontales 9 por ciento, menús verticales 35 por ciento. 7. Sindicación de contenidos RSS: 3 sitios. 8. Otros servicios: chat 7 por ciento, descarga de documentos 16 por ciento, envío de formularios 14 por ciento, instructivos 21 por ciento, links a otras páginas 23 por ciento, tutoriales 5 por ciento, otros 14 por ciento. 9. Accesibilidad Web: 1 sitio. 10. Otras observaciones: ninguna. Se concluye que el desarrollo de los sitios es dispar y se recomienda considerar pautas de AI como parte de la cooperación en la red de bibliotecas de la UNLP

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Este trabajo descriptivo exploratorio se propone analizar la arquitectura de información (AI) de sitios Web de bibliotecas de la Universidad Nacional de La Plata (UNLP), Argentina. Se analizaron 17 bibliotecas y se aplicó una grilla para recabar 10 aspectos relevantes. Los resultados fueron: 1. Ubicación del sitio Web de la biblioteca: 9 sitios incluidos en la página principal de la facultad. 2. Etiquetado de contenidos: terminología simple, sin jergas; no hay homogeneidad entre las bibliotecas. 3. Capacidad de búsqueda: 62 por ciento positiva, 38 por ciento negativa. 4. Sistema de búsqueda: simple 43 por ciento, compleja 10 por ciento, con ayudas 10 por ciento, ninguno 38 por ciento. 5. Sistemas de navegación: globales 5 por ciento, jerárquicos 79 por ciento, locales 5 por ciento, ninguno 11 por ciento. 6. Herramientas de navegación: barras 16 por ciento, frames o marcos 30 por ciento, índices 2 por ciento, mapas de sitio 7 por ciento, menús horizontales 9 por ciento, menús verticales 35 por ciento. 7. Sindicación de contenidos RSS: 3 sitios. 8. Otros servicios: chat 7 por ciento, descarga de documentos 16 por ciento, envío de formularios 14 por ciento, instructivos 21 por ciento, links a otras páginas 23 por ciento, tutoriales 5 por ciento, otros 14 por ciento. 9. Accesibilidad Web: 1 sitio. 10. Otras observaciones: ninguna. Se concluye que el desarrollo de los sitios es dispar y se recomienda considerar pautas de AI como parte de la cooperación en la red de bibliotecas de la UNLP

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Este trabajo descriptivo exploratorio se propone analizar la arquitectura de información (AI) de sitios Web de bibliotecas de la Universidad Nacional de La Plata (UNLP), Argentina. Se analizaron 17 bibliotecas y se aplicó una grilla para recabar 10 aspectos relevantes. Los resultados fueron: 1. Ubicación del sitio Web de la biblioteca: 9 sitios incluidos en la página principal de la facultad. 2. Etiquetado de contenidos: terminología simple, sin jergas; no hay homogeneidad entre las bibliotecas. 3. Capacidad de búsqueda: 62 por ciento positiva, 38 por ciento negativa. 4. Sistema de búsqueda: simple 43 por ciento, compleja 10 por ciento, con ayudas 10 por ciento, ninguno 38 por ciento. 5. Sistemas de navegación: globales 5 por ciento, jerárquicos 79 por ciento, locales 5 por ciento, ninguno 11 por ciento. 6. Herramientas de navegación: barras 16 por ciento, frames o marcos 30 por ciento, índices 2 por ciento, mapas de sitio 7 por ciento, menús horizontales 9 por ciento, menús verticales 35 por ciento. 7. Sindicación de contenidos RSS: 3 sitios. 8. Otros servicios: chat 7 por ciento, descarga de documentos 16 por ciento, envío de formularios 14 por ciento, instructivos 21 por ciento, links a otras páginas 23 por ciento, tutoriales 5 por ciento, otros 14 por ciento. 9. Accesibilidad Web: 1 sitio. 10. Otras observaciones: ninguna. Se concluye que el desarrollo de los sitios es dispar y se recomienda considerar pautas de AI como parte de la cooperación en la red de bibliotecas de la UNLP

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Infrastructure as a Service clouds are a flexible and fast way to obtain (virtual) resources as demand varies. Grids, on the other hand, are middleware platforms able to combine resources from different administrative domains for task execution. Clouds can be used by grids as providers of devices such as virtual machines, so they only use the resources they need. But this requires grids to be able to decide when to allocate and release those resources. Here we introduce and analyze by simulations an economic mechanism (a) to set resource prices and (b) resolve when to scale resources depending on the users’ demand. This system has a strong emphasis on fairness, so no user hinders the execution of other users’ tasks by getting too many resources. Our simulator is based on the well-known GridSim software for grid simulation, which we expand to simulate infrastructure clouds. The results show how the proposed system can successfully adapt the amount of allocated resources to the demand, while at the same time ensuring that resources are fairly shared among users.

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Next Generation Networks (NGN) provide Telecommunications operators with the possibility to share their resources and infrastructure, facilitate the interoperability with other networks, and simplify and unify the management, operation and maintenance of service offerings, thus enabling the fast and cost-effective creation of new personal, broadband ubiquitous services. Unfortunately, service creation over NGN is far from the success of service creation in the Web, especially when it comes to Web 2.0. This paper presents a novel approach to service creation and delivery, with a platform that opens to non-technically skilled users the possibility to create, manage and share their own convergent (NGN-based and Web-based) services. To this end, the business approach to user-generated services is analyzed and the technological bases supporting the proposal are explained.

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As a common reference for many in-development standards and execution frameworks, special attention is being paid to Service-Oriented Architectures. SOAs modeling, however, is an area in which a consensus has not being achieved. Currently, standardization organizations are defining proposals to offer a solution to this problem. Nevertheless, until very recently, non-functional aspects of services have not been considered for standardization processes. In particular, there exists a lack of a design solution that permits an independent development of the functional and non-functional concerns of SOAs, allowing that each concern be addressed in a convenient manner in early stages of the development, in a way that could guarantee the quality of this type of systems. This paper, leveraging on previous work, presents an approach to integrate security-related non-functional aspects (such as confidentiality, integrity, and access control) in the development of services.

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Service-Oriented Architectures (SOA), and Web Services (WS), the technology generally used to implement them, achieve the integration of heterogeneous technologies, providing interoperability, and yielding the reutilization of pre-existent systems. Model-driven development methodologies provide inherent benefits such as increased productivity, greater reuse, and better maintainability, to name a few. Efforts on achieving model-driven development of SOAs already exist, but there is currently no standard solution that addresses non-functional aspects of these services as well. This paper presents an approach to integrate these non-functional aspects in the development of web services, with an emphasis on security.

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The Future Internet is expected to be composed of a mesh of interoperable Web services accessed from all over the Web. This approach has not yet caught on since global user-service interaction is still an open issue. Successful composite applications rely on heavyweight service orchestration technologies that raise the bar far above end-user skills. The weakness lies in the abstraction of the underlying service front-end architecture rather than the infrastructure technologies themselves. In our opinion, the best approach is to offer end-to-end composition from user interface to service invocation, as well as an understandable abstraction of both building blocks and a visual composition technique. In this paper we formalize our vision with regard to the next-generation front-end Web technology that will enable integrated access to services, contents and things in the Future Internet. We present a novel reference architecture designed to empower non-technical end users to create and share their own self-service composite applications. A tool implementing this architecture has been developed as part of the European FP7 FAST Project and EzWeb Project, allowing us to validate the rationale behind our approach.

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Because of the growing availability of third-party APIs, services, widgets and any other reusable web component, mashup developers now face a vast amount of candidate components for their developments. Moreover, these components quite often are scattered in many different repositories and web sites, which makes difficult their selection or discovery. In this paper, we discuss the problem of component selection in Service-Oriented Architectures (SOA) and Mashup-Driven Development, and introduce the Linked Mashups Ontology (LiMOn), a model that allows describing mashups and their components for integrating and sharing mashup information such as categorization or dependencies. The model has allowed the building of an integrated, centralized metadirectory of web components for query and selection, which has served to evaluate the model. The metadirectory allows accessing various heterogeneous repositories of mashups and web components while using external information from the Linked Data cloud, helping mashup development.

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One of the main challenges facing next generation Cloud platform services is the need to simultaneously achieve ease of programming, consistency, and high scalability. Big Data applications have so far focused on batch processing. The next step for Big Data is to move to the online world. This shift will raise the requirements for transactional guarantees. CumuloNimbo is a new EC-funded project led by Universidad Politécnica de Madrid (UPM) that addresses these issues via a highly scalable multi-tier transactional platform as a service (PaaS) that bridges the gap between OLTP and Big Data applications.

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Data grid services have been used to deal with the increasing needs of applications in terms of data volume and throughput. The large scale, heterogeneity and dynamism of grid environments often make management and tuning of these data services very complex. Furthermore, current high-performance I/O approaches are characterized by their high complexity and specific features that usually require specialized administrator skills. Autonomic computing can help manage this complexity. The present paper describes an autonomic subsystem intended to provide self-management features aimed at efficiently reducing the I/O problem in a grid environment, thereby enhancing the quality of service (QoS) of data access and storage services in the grid. Our proposal takes into account that data produced in an I/O system is not usually immediately required. Therefore, performance improvements are related not only to current but also to any future I/O access, as the actual data access usually occurs later on. Nevertheless, the exact time of the next I/O operations is unknown. Thus, our approach proposes a long-term prediction designed to forecast the future workload of grid components. This enables the autonomic subsystem to determine the optimal data placement to improve both current and future I/O operations.

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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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Aiming to address requirements concerning integration of services in the context of ?big data?, this paper presents an innovative approach that (i) ensures a flexible, adaptable and scalable information and computation infrastructure, and (ii) exploits the competences of stakeholders and information workers to meaningfully confront information management issues such as information characterization, classification and interpretation, thus incorporating the underlying collective intelligence. Our approach pays much attention to the issues of usability and ease-of-use, not requiring any particular programming expertise from the end users. We report on a series of technical issues concerning the desired flexibility of the proposed integration framework and we provide related recommendations to developers of such solutions. Evaluation results are also discussed.

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n this paper, we present the design and implementation of a prototype system of Smart Parking Services based on Wireless Sensor Networks (WSNs) that allows vehicle drivers to effectively find the free parking places. The proposed scheme consists of wireless sensor networks, embedded web-server, central web-server and mobile phone application. In the system, low-cost wireless sensors networks modules are deployed into each parking slot equipped with one sensor node. The state of the parking slot is detected by sensor node and is reported periodically to embedded web-server via the deployed wireless sensor networks. This information is sent to central web-server using Wi-Fi networks in real-time, and also the vehicle driver can find vacant parking lots using standard mobile devices.

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The uptake of Linked Data (LD) has promoted the proliferation of datasets and their associated ontologies bringing their semantic to the data being published. These ontologies should be evaluated at different stages, both during their development and their publication. As important as correctly modelling the intended part of the world to be captured in an ontology, is publishing, sharing and facilitating the (re)use of the obtained model. In this paper, 11 evaluation characteristics, with respect to publish, share and facilitate the reuse, are proposed. In particular, 6 good practices and 5 pitfalls are presented, together with their associated detection methods. In addition, a grid-based rating system is generated. Both contributions, the set of evaluation characteristics and the grid system, could be useful for ontologists in order to reuse existing LD vocabularies or to check the one being built.