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Field of Research : Distributed Computing
Research Topic : Diagnositc algorithms
Australian State/Territory : VIC
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  • Funded Activity

    Linkage Projects - Grant ID: LP160100406

    Funder
    Australian Research Council
    Funding Amount
    $390,000.00
    Summary
    Cloud-data centres resource allocation under bursty conditions. Cloud-data centres resource allocation under bursty conditions. The project aims to design, implement, and integrate solutions to manage resources in cloud data centres (CDCs), especially when operating under bursty workload conditions. CDCs are expected to assure performance whilst optimising resource usage at a minimum cost, but efficiently providing resources with specific performance requirements can be difficult. This project i .... Cloud-data centres resource allocation under bursty conditions. Cloud-data centres resource allocation under bursty conditions. The project aims to design, implement, and integrate solutions to manage resources in cloud data centres (CDCs), especially when operating under bursty workload conditions. CDCs are expected to assure performance whilst optimising resource usage at a minimum cost, but efficiently providing resources with specific performance requirements can be difficult. This project intends to develop scalable solutions with industry approved software plug-ins. This is expected to affect both trustworthy information and communications technology (ICT) infrastructure (delivering more resilient CDCs) and economic sustainability (reducing CDC usage cost for both users and providers) of today’s computerised society.
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    Funded Activity

    Linkage Projects - Grant ID: LP150101213

    Funder
    Australian Research Council
    Funding Amount
    $574,932.00
    Summary
    Contention-Aware Scheduling in Cloud Data Centres. This project aims to design, implement, and integrate solutions to improve resource use of private cloud data centres (CDCs). CDCs are expected to guarantee performance while optimising resource usage at a minimum cost. This incurs technical challenges that must be tackled to efficiently provision on-demand resources with specific performance requirements. The project intends to push the applicability of both current techniques and the ones to b .... Contention-Aware Scheduling in Cloud Data Centres. This project aims to design, implement, and integrate solutions to improve resource use of private cloud data centres (CDCs). CDCs are expected to guarantee performance while optimising resource usage at a minimum cost. This incurs technical challenges that must be tackled to efficiently provision on-demand resources with specific performance requirements. The project intends to push the applicability of both current techniques and the ones to be designed in this project to industry-scale CDCs, and identify metrics and variables to holistically control service-level agreements of hosted applications. Scalable solutions with industry approved software plug-ins are the major outcomes of this project. The outcomes of this project will have a substantial impact on both environmental (lowering energy consumption to lead to greener infrastructure) and economic sustainability (reducing cloud usage cost for both users and providers) of today’s much computerised society.
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    Funded Activity

    Linkage Projects - Grant ID: LP140100980

    Funder
    Australian Research Council
    Funding Amount
    $315,000.00
    Summary
    Energy-Efficient Computing: Expanding the Role of Scheduling in Cloud Data Centres. Cloud data centres have become increasingly large-scale to meet ever increasing computing and storage capacity. The requirement of uninterrupted service availability has also contributed to such expansion. However, this relentless pursuit of high performance and high availability has led to serious resource over-provisioning and, in turn, low performance to energy consumption ratios. The impact of this poor resou .... Energy-Efficient Computing: Expanding the Role of Scheduling in Cloud Data Centres. Cloud data centres have become increasingly large-scale to meet ever increasing computing and storage capacity. The requirement of uninterrupted service availability has also contributed to such expansion. However, this relentless pursuit of high performance and high availability has led to serious resource over-provisioning and, in turn, low performance to energy consumption ratios. The impact of this poor resource management goes beyond the issue of cloud data centre efficiency, including excessive carbon footprint. This project aims to develop new energy-aware scheduling and resource allocation algorithms to provide energy-efficient solutions. These solutions exploit both workload and system diversity in cloud data centres.
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