981 resultados para application deployment


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Cloud and service computing has started to change the way research in science, in particular biology and medicine, is being carried out. Researchers that have taken advantage of this technology (making use of public and private cloud compute resources) can process large amounts of data (big data) and speed up discovery. However, this requires researchers to acquire a solid knowledge and skills in the development of sequential and high performance computing (HPC), and cloud development and deployment background. In response a technology exposing HPC applications as services through the development and deployment of a SaaS cloud, and its proof of concept in the form of implementation of a cloud environment, Uncinus, has been developed and implemented to allow researchers easy access to cloud computing resources. The new technology offers and Uncinus supports the development of applications as services and the sharing of compute resources to speed up applications' execution. Users access these cloud resources and services through web interfaces. Using the Uncinus platform, a bio-informatics workflow was executed on a private (HPC) cloud, server and public cloud (Amazon EC2) resources, performance results showing a 3 fold improvement compared to local resources' performance. Biology and medicine specialists with no programming and application deployment on clouds background could run the case study applications with ease.

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Recent advances in hardware development coupled with the rapid adoption and broad applicability of cloud computing have introduced widespread heterogeneity in data centers, significantly complicating the management of cloud applications and data center resources. This paper presents the CACTOS approach to cloud infrastructure automation and optimization, which addresses heterogeneity through a combination of in-depth analysis of application behavior with insights from commercial cloud providers. The aim of the approach is threefold: to model applications and data center resources, to simulate applications and resources for planning and operation, and to optimize application deployment and resource use in an autonomic manner. The approach is based on case studies from the areas of business analytics, enterprise applications, and scientific computing.

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The cost and time of deploying HPC applications on clouds is a problem. Instead of conducting their research discipline specialists are forced to carry out activities for application deployment, publication and ease of access. In response, a new approach for HPC application deployment and access in clouds is proposed. The major innovations are a new approach to deploying and executing HPC applications on IaaS and PaaS clouds, and exposing HPC applications as services. Through three case studies this paper demonstrates the feasibility and effectiveness of the proposed approach that could lead to the building of a SaaS library of discipline-oriented services evocable through user friendly, discipline specific interfaces. The new approach will reduce the time and money needed to deploy and expose discipline HPC applications.

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Software-as-a-service (SaaS) multi-tenancy in cloud-based applications helps service providers to save cost, improve resource utilization, and reduce service customization and maintenance time. This is achieved by sharing of resources and service instances among multiple "tenants" of the cloud-hosted application. However, supporting multi-tenancy adds more complexity to SaaS applications required capabilities. Security is one of these key requirements that must be addressed when engineering multi-tenant SaaS applications. The sharing of resources among tenants - i.e. multi-tenancy - increases tenants' concerns about the security of their cloud-hosted assets. Compounding this, existing traditional security engineering approaches do not fit well with the multi-tenancy application model where tenants and their security requirements often emerge after the applications and services were first developed. The resultant applications do not usually support diverse security capabilities based on different tenants' needs, some of which may change at run-time i.e. after cloud application deployment. We introduce a novel model-driven security engineering approach for multi-tenant, cloud-hosted SaaS applications. Our approach is based on externalizing security from the underlying SaaS application, allowing both application/service and security to evolve at runtime. Multiple security sets can be enforced on the same application instance based on different tenants' security requirements. We use abstract models to capture service provider and multiple tenants' security requirements and then generate security integration and configurations at runtime. We use dependency injection and dynamic weaving via Aspect-Oriented Programming (AOP) to integrate security within critical application/service entities at runtime. We explain our approach, architecture and implementation details, discuss a usage example, and present an evaluation of our approach on a set of open source web applications.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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RESUMEN DEL PROYECTO Organizar actividades y proyectos entre varias personas o tomar decisiones conjuntas son cuestiones a las que se enfrenta cualquier individuo en su día a día. El simple hecho de coordinar o poner de acuerdo a un grupo reducido de personas puede llegar a suponer un gran problema ya que cada participante tiene sus propias preferencias y, en ocasiones, es difícil conseguir encajarlas con las demás del grupo. Este proyecto, llamado “DealtDay”, surge para facilitar esta labor. La idea nace ante la necesidad de organizar, de forma fácil e intuitiva, a un grupo de personas para, por ejemplo, concretar una reunión, quedar para ir a dar una vuelta, decidir qué película ver, etc. Este proyecto se ha desarrollado basándose en el sistema actual de relaciones con el que se han creado la mayoría de las redes sociales que hoy conocemos. Como medio para poder hacer uso del proyecto se ha construido una aplicación web que, gracias a las decisiones de diseño tomadas, se puede usar tanto en un ordenador, una tablet o un Smartphone. Este punto se considera fundamental ya que cada vez más personas están dejando de lado los ordenadores corrientes para dar paso al uso de las nuevas tecnologías. Además, se ha creado una API REST, lo que nos permite utilizar todas las funcionalidades de la aplicación desde cualquier sistema que pueda realizar peticiones http. En este proyecto en concreto se realizará la parte del desarrollo de la API, el cliente web y el despliegue de la aplicación en un servidor web para realizar las pruebas pertinentes. ABSTRACT To organize activities and projects between several people or make joint decisions are issues to which any person faces every day.The simple fact of coordinate or coming to an agreement with a group of persons could be a major problem, since each participant has their own preferences and often fails when tries to fit them with the group. This project, called “Dealt Day”, is born to facilitate this task. The idea arises of how to achieve organize a group of people in an easily and intuitively way in order to arrange a meeting, be able to go for a walk, decide what movie to see or simply vote a choice between a users group. This project has been developed based on the current relation system that has been created in the most social networks we know. As a means of making use of the project a web application has been built, that thanks to the design decisions taken it can be used in a computer, tablet or smartphone, This is an essential point because more and more people are abandoning the current computers to make way for the use of new technologies. Also, a REST API has been created, which allows us to use all the features of the application from any system able to make http requests. In this particular project, I have done the development of the API, web client and the application deployment on a web server in order to test it.

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Cloud Computing is a paradigm that enables the access, in a simple and pervasive way, through the network, to shared and configurable computing resources. Such resources can be offered on demand to users in a pay-per-use model. With the advance of this paradigm, a single service offered by a cloud platform might not be enough to meet all the requirements of clients. Ergo, it is needed to compose services provided by different cloud platforms. However, current cloud platforms are not implemented using common standards, each one has its own APIs and development tools, which is a barrier for composing different services. In this context, the Cloud Integrator, a service-oriented middleware platform, provides an environment to facilitate the development and execution of multi-cloud applications. The applications are compositions of services, from different cloud platforms and, represented by abstract workflows. However, Cloud Integrator has some limitations, such as: (i) applications are locally executed; (ii) users cannot specify the application in terms of its inputs and outputs, and; (iii) experienced users cannot directly determine the concrete Web services that will perform the workflow. In order to deal with such limitations, this work proposes Cloud Stratus, a middleware platform that extends Cloud Integrator and offers different ways to specify an application: as an abstract workflow or a complete/partial execution flow. The platform enables the application deployment in cloud virtual machines, so that several users can access it through the Internet. It also supports the access and management of virtual machines in different cloud platforms and provides services monitoring mechanisms and assessment of QoS parameters. Cloud Stratus was validated through a case study that consists of an application that uses different services provided by different cloud platforms. Cloud Stratus was also evaluated through computing experiments that analyze the performance of its processes.

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In cloud environments, IT solutions are delivered to users via shared infrastructure, enabling cloud service providers to deploy applications as services according to user QoS (Quality of Service) requirements. One consequence of this cloud model is the huge amount of energy consumption and significant carbon footprints caused by large cloud infrastructures. A key and common objective of cloud service providers is thus to develop cloud application deployment and management solutions with minimum energy consumption while guaranteeing performance and other QoS specified in Service Level Agreements (SLAs). However, finding the best deployment configuration that maximises energy efficiency while guaranteeing system performance is an extremely challenging task, which requires the evaluation of system performance and energy consumption under various workloads and deployment configurations. In order to simplify this process we have developed Stress Cloud, an automatic performance and energy consumption analysis tool for cloud applications in real-world cloud environments. Stress Cloud supports the modelling of realistic cloud application workloads, the automatic generation of load tests, and the profiling of system performance and energy consumption. We demonstrate the utility of Stress Cloud by analysing the performance and energy consumption of a cloud application under a broad range of different deployment configurations.

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Owing to the increased customer demands for make-to-order products and smaller product life-cycles, today assembly lines are designed to ensure a quick switch-over from one product model to another for companies' survival in market place. The complexity associated with the decisions pertaining to the type of training and number of workers and their exposition to the different tasks especially in the current era of customized production is a serious problem that the managers and the HRD gurus are facing in industry. This paper aims to determine the amount of cross-training and dynamic deployment policy caused by workforce flexibility for a make-to-order assembly. The aforementioned issues have been dealt with by adopting the concept of evolutionary fuzzy system because of the linguistic nature of the attributes associated with product variety and task complexity. A fuzzy system-based methodology is proposed to determine the amount of cross-training and dynamic deployment policy. The proposed methodology is tested on 10 sample products of varying complexities and the results obtained are in line with the conclusions drawn by previous researchers.

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The anticipated rewards of adaptive approaches will only be fully realised when autonomic algorithms can take configuration and deployment decisions that match and exceed those of human engineers. Such decisions are typically characterised as being based on a foundation of experience and knowledge. In humans, these underpinnings are themselves founded on the ashes of failure, the exuberance of courage and (sometimes) the outrageousness of fortune. In this paper we describe an application framework that will allow the incorporation of similarly risky, error prone and downright dangerous software artefacts into live systems – without undermining the certainty of correctness at application level. We achieve this by introducing the notion of application dreaming.

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This paper describes the deployment on GPUs of PROP, a program of the 2DRMP suite which models electron collisions with H-like atoms and ions. Because performance on GPUs is better in single precision than in double precision, the numerical stability of the PROP program in single precision has been studied. The numerical quality of PROP results computed in single precision and their impact on the next program of the 2DRMP suite has been analyzed. Successive versions of the PROP program on GPUs have been developed in order to improve its performance. Particular attention has been paid to the optimization of data transfers and of linear algebra operations. Performance obtained on several architectures (including NVIDIA Fermi) are presented.

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This paper presents the work in progress of an on-demand software deployment system based on application virtualization concepts which eliminates the need of software installation and configuration on each computer. Some mechanisms were created, such as mapping of utilization of resources by the application to improve the software distribution and startup; a virtualization middleware which give all resources needed for the software execution; an asynchronous P2P transport used to optimizing distribution on the network; and off-line support where the user can execute the application even when the server is not available or when is out of the network. © Springer-Verlag Berlin Heidelberg 2010.

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