Implementing Bioinformatics Algorithms using .NET-based Stored Procedures in a Database Cluster. We will create the technology for significantly improving the management, processing and sharing of biological data. Areas in which Australia has a large stake, including the development of new drugs, disease research, and agricultural genetic engineering, stand to benefit considerably from these advances. This contribution by Australian researchers to a global problem will have a positive impact on ....Implementing Bioinformatics Algorithms using .NET-based Stored Procedures in a Database Cluster. We will create the technology for significantly improving the management, processing and sharing of biological data. Areas in which Australia has a large stake, including the development of new drugs, disease research, and agricultural genetic engineering, stand to benefit considerably from these advances. This contribution by Australian researchers to a global problem will have a positive impact on our own health industry, and will provide the foundation for improvements in agriculture and financial services.Read moreRead less
Automating real-time feedback in virtual reality training through data mining. This project will use data mining techniques to develop a real-time feedback system that can be used in virtual reality training environments. This system will not only improve trainees' learning, it will also lead to more efficient use of virtual reality training in industries such as aviation, aerospace, mining, health and emergency services.
Improving provision of a document store as a service in a public cloud. Improving provision of a document store as a service in a public cloud. This project aims to develop a model of document-oriented database correctness and performance that can be applied to cloud-hosted clusters. Many modern web applications rely on document-oriented databases hosted on clusters of virtualised servers from commercial cloud providers. Developers make difficult deployment decisions, such as how to combine data ....Improving provision of a document store as a service in a public cloud. Improving provision of a document store as a service in a public cloud. This project aims to develop a model of document-oriented database correctness and performance that can be applied to cloud-hosted clusters. Many modern web applications rely on document-oriented databases hosted on clusters of virtualised servers from commercial cloud providers. Developers make difficult deployment decisions, such as how to combine data sharding and replication to meet service requirements without any guidance on the degree of precision. This research will allow developers and database administrators to predict how systems will behave in conditions difficult to simulate directly. Ultimately, this is expected to improve the quality and efficiency of services built using document databases.Read moreRead less
In-memory moving objects analytics for real-time business applications. This project aims to develop a novel computing foundation based on in-memory technologies to address significant challenges of big data and location-based business intelligence, building upon the well-recognised research excellence in spatiotemporal data management at the University of Queensland, and HANA, SAP's (Systems, Applications, Products in data processing) new in-memory analytics platform.
Cost efficient scheduling of big data application workflows on cloud through information correlation. Information correlation in and between big data application workflows scheduled on the cloud can help to significantly reduce overall scheduling costs by avoiding the execution of many correlated workflow activities. This project aims to systematically investigate such correlation for cost efficient scheduling. The expected outcomes are: establishing information correlation based scheduling rese ....Cost efficient scheduling of big data application workflows on cloud through information correlation. Information correlation in and between big data application workflows scheduled on the cloud can help to significantly reduce overall scheduling costs by avoiding the execution of many correlated workflow activities. This project aims to systematically investigate such correlation for cost efficient scheduling. The expected outcomes are: establishing information correlation based scheduling research and practical solutions for this important cloud and big data research area; benefiting key big data application areas on the cloud, such as hospitals, insurance companies and government information services; and helping to maintain Australia at the forefront of cloud and big data research with innovative industry applications.Read moreRead less