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Field of Research : Distributed and Grid Systems
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  • Funded Activity

    Linkage Projects - Grant ID: LP130100324

    Funder
    Australian Research Council
    Funding Amount
    $360,000.00
    Summary
    Enabling small businesses to more cost-effectively use big data on cloud computing platforms. This project will invent a new generic cost model for managing big data in cloud computing. This model will enable agent-based, innovative data management technologies to reduce the cost of storage, computation and bandwidth consumption in the cloud. Outcomes will enable small businesses to use big data in cloud computing more cost effectively.
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    Funded Activity

    Discovery Projects - Grant ID: DP120102653

    Funder
    Australian Research Council
    Funding Amount
    $320,000.00
    Summary
    Model-driven engineering of scientific software for graphical processing units. Novel visual models, model-driven engineering techniques and software engineering tools will be invented to synthesize and optimise graphical processing unit software for scientific applications. These will be validated using large data-centric applications from molecular simulation and astrophysics domains.
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    Funded Activity

    Discovery Projects - Grant ID: DP150101775

    Funder
    Australian Research Council
    Funding Amount
    $295,900.00
    Summary
    Smart quality management for service-based systems in cloud environment. Cloud computing is a rapidly growing paradigm for Software-as-a-Service (SaaS). For enabling broad applications of a huge number of services available in the cloud, quality management for service-based systems is critical. This project aims to cover smart quality management for the whole lifetime of SaaS from service composition to service delivery. The project is expected to offer a novel solution for managing both build-t .... Smart quality management for service-based systems in cloud environment. Cloud computing is a rapidly growing paradigm for Software-as-a-Service (SaaS). For enabling broad applications of a huge number of services available in the cloud, quality management for service-based systems is critical. This project aims to cover smart quality management for the whole lifetime of SaaS from service composition to service delivery. The project is expected to offer a novel solution for managing both build-time service selection and runtime service monitoring and adaptation by inventing corresponding innovative efficient and effective strategies for quality management. Given the prediction that the SaaS market will grow from $13.5 billion in 2011 to $32.8 billion in 2016, the success of this project is anticipated to translate into scientific and economic value.
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    Funded Activity

    Linkage Projects - Grant ID: LP100100588

    Funder
    Australian Research Council
    Funding Amount
    $805,000.00
    Summary
    Advancing Medical Image Analysis through High Performance Heterogeneous Computing, Numerical Simulation, and Novel Human Computer Interfaces. This project will link Australian researchers with a major multi-national IT company. The engagement of world-class personnel from Microsoft will provide unprecedented opportunities for graduate students to experience research in both an academic and an industrial setting. The participation of Microsoft product division offers the potential to transform th .... Advancing Medical Image Analysis through High Performance Heterogeneous Computing, Numerical Simulation, and Novel Human Computer Interfaces. This project will link Australian researchers with a major multi-national IT company. The engagement of world-class personnel from Microsoft will provide unprecedented opportunities for graduate students to experience research in both an academic and an industrial setting. The participation of Microsoft product division offers the potential to transform the outcomes of this project into widely-used software solutions. The project will pave the way for more widespread and reliable evidenced-based computer-aided diagnosis and image-guided treatment. It will produce well-trained and sought-after graduates and research associates with extensive inter-disciplinary knowledge of medical image analysis and high-performance computing.
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    Showing 1-4 of 4 Funded Activites

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