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Research on Digital Agricultural Information Resources Sharing Plan Based on Cloud Computing
"... Abstract: In order to provide the agricultural works with customized, visual, multi-perspective and multi-level active service, we conduct a research of digital agricultural information resources sharing plan based on cloud computing to integrate and publish the digital agricultural information reso ..."
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Abstract: In order to provide the agricultural works with customized, visual, multi-perspective and multi-level active service, we conduct a research of digital agricultural information resources sharing plan based on cloud computing to integrate and publish the digital agricultural information resources efficiently and timely. Based on cloud computing and virtualization technology, we establish a cloud computing server storage architecture, design deployment of server virtualization service, and present information resource sharing plan, so the users on different network environment could access to digital agricultural information resources at any time. Application examples demonstrate the use of cloud computing technology can provide heterogeneous resource sharing services for all agriculture-related facilities.
en vue d'obtenir le grade de
, 2013
"... an Scheduling and deployment of large-scale applications on Cloud platforms Directeurs de thèse: Après avis de: ..."
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an Scheduling and deployment of large-scale applications on Cloud platforms Directeurs de thèse: Après avis de:
5 Resource Allocation in Clouds: Concepts, Tools and Research Challenges
"... Cloud computing is an attractive computing model since it allows for the provision of resources on-demand. Such a process of allocation and reallocation of resources is the key to accommodating unpredictable demands and improving the return on investment from the infrastructure supporting the Cloud. ..."
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Cloud computing is an attractive computing model since it allows for the provision of resources on-demand. Such a process of allocation and reallocation of resources is the key to accommodating unpredictable demands and improving the return on investment from the infrastructure supporting the Cloud. However, despite the recent growth of the Cloud Computing market, several problems with the process of resource allocation remain unaddressed. This short course introduces essential concepts and technologies regarding Cloud Computing and presents some research questions on the topic, focusing on the challenges and the state-of-the-art solutions in resource allocation. Resumo Computação na Nuvem é um modelo de computação atrativo, uma vez que permite que recursos sejam provisionados sob demanda. Tal processo de alocação e realocação de recursos é a chave para acomodar demandas imprevistas e para melhorar o retorno de investimento na infraestrutura que suporta a Nuvem. Entretanto, a despeito da recente expansão do mercado de Computação na Nuvem, diversos problemas relativos à alocação de recursos permanecem abertos. Este minicurso introduz os conceitos e tecnologias essenciais da Computação em Nuvem e apresenta algumas questões de pesquisa na área, focando nos desafios e soluções para alocação de recursos.
Running User-provided Virtual Machines in Batch-oriented Computing Clusters
"... The use of virtualization in HPC clusters can provide rich software environments, application isolation and efficient workload management mechanisms, but system-level virtualization introduces a software layer on the computing nodes that reduces performance and inhibits the direct use of hardware de ..."
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The use of virtualization in HPC clusters can provide rich software environments, application isolation and efficient workload management mechanisms, but system-level virtualization introduces a software layer on the computing nodes that reduces performance and inhibits the direct use of hardware devices. We present an unobtrusive user-level platform to execute virtual machines inside batch jobs that does not handicap the computing cluster’s ability to execute the most demanding applications. A per-user platform uses a static mode in which the VMs run entirely within the resources of a single batch job and a dynamic mode in which the VMs navigate at runtime between the continuously allocated jobs node time-slots. In the dynamic mode fault-tolerant system agents are integrated using group communication to control the system, to execute user commands and to implement user-defined scheduling policies. In our tests compute intensive applications suffered negligible performance overhead compared to the native configuration, but the user-mode network overlay introduced a significant penalty on the more taxing networked applications.
doi:10.1155/2012/212343 Research Article An SOA-Based Model for the Integrated Provisioning of Cloud and Grid Resources
"... which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. In the last years, the availability andmodels of use of networked computing resources within reach of e-Science are rapidly changing and see the coexistence of many disparate p ..."
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which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. In the last years, the availability andmodels of use of networked computing resources within reach of e-Science are rapidly changing and see the coexistence of many disparate paradigms: high-performance computing, grid, and recently cloud. Unfortunately, none of these paradigms is recognized as the ultimate solution, and a convergence of them all should be pursued. At the same time, recent works have proposed a number of models and tools to address the growing needs and expectations in the field of e-Science. In particular, they have shown the advantages and the feasibility of modeling e-Science environments and infrastructures according to the service-oriented architecture. In this paper, we suggest a model to promote the convergence and the integration of the different computing paradigms and infrastructures for the dynamic on-demand provisioning of resources from multiple providers as a cohesive aggregate, leveraging the service-oriented architecture. In addition, we propose a design aimed at endorsing a flexible, modular, workflow-based computing model for e-Science. The model is supplemented by a working prototype implementation together with a case study in the applicative domain of bioinformatics, which is used to validate the presented approach and to carry out some performance and scalability measurements. 1.
