Escaping the concurrency trade-off: a new approach to enterprise software. Enterprise software manages the operations of all business and government organisations. Designers of this often rely on their intuition or luck, by using high-performance database facilities whose correctness is not guaranteed. This project will show designers how to use these facilities while still having the assurance that the data will not be corrupted. This will improve the quality of the data used by Australian ent ....Escaping the concurrency trade-off: a new approach to enterprise software. Enterprise software manages the operations of all business and government organisations. Designers of this often rely on their intuition or luck, by using high-performance database facilities whose correctness is not guaranteed. This project will show designers how to use these facilities while still having the assurance that the data will not be corrupted. This will improve the quality of the data used by Australian enterprises, and thus improve their operations. Australian software designers will also benefit, as they will be able to produce software that combines high performance with assurance that concurrency errors will not occur.Read moreRead less
Effective and Efficient Keyword Search in Relational Databases. Effective and efficient management of information, including textual information, is at the heard of ICT objectives and requirements global wide. The project aims to be of unique value to vitually all Australian industries by providing easier and better information access to their business data. The research conducted in this project will position Australia as one of the leaders in the database and information retrieval research. Th ....Effective and Efficient Keyword Search in Relational Databases. Effective and efficient management of information, including textual information, is at the heard of ICT objectives and requirements global wide. The project aims to be of unique value to vitually all Australian industries by providing easier and better information access to their business data. The research conducted in this project will position Australia as one of the leaders in the database and information retrieval research. The project outcomes in the form of algorithms and systems will provide powerful solutions that are applicable to many Australian and international organisations. It will will also encourage more ICT within Australia and worldwide.Read moreRead less
Computing with nearly-consistent data. This project will help programmers correctly use data that originates at various times and places, and spreads unevenly through a system. Computation will combine data that comes from different situations, and is not exactly consistent. Capability to develop high quality software on platforms with this feature will enhance the value of the Australian IT industry. As well, the industries which use the software benefit from correctly working with their data. ....Computing with nearly-consistent data. This project will help programmers correctly use data that originates at various times and places, and spreads unevenly through a system. Computation will combine data that comes from different situations, and is not exactly consistent. Capability to develop high quality software on platforms with this feature will enhance the value of the Australian IT industry. As well, the industries which use the software benefit from correctly working with their data. Sensor networks have data like this, and they play a vital role in environmental monitoring. Cloud computing platforms also have this type of data, and these allow smaller enterprises to grow smoothly, without needing large up-front investments in computing infrastructure.Read moreRead less
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
Towards High-Order Structure Search on Large-Scale Graphs. High-order structure search over large-scale graphs has many applications including cybersecurity, crime detection, social media, marketing recommendation, and public health. The project aims to lay the scientific foundations and develop novel computing techniques for efficiently conducting structure search. The outcomes include novel computing paradigms, algorithms, indexing, incremental computation, and distributed solutions. The succe ....Towards High-Order Structure Search on Large-Scale Graphs. High-order structure search over large-scale graphs has many applications including cybersecurity, crime detection, social media, marketing recommendation, and public health. The project aims to lay the scientific foundations and develop novel computing techniques for efficiently conducting structure search. The outcomes include novel computing paradigms, algorithms, indexing, incremental computation, and distributed solutions. The success of the project will directly contribute to the scientific foundation of Big Data computation. It will also contribute to the development of local industry involving cybersecurity, social media based recommendation, network management, and E-business.Read moreRead less
Efficient processing of distance-based spatial queries on multi-valued objects. This project aims to develop effective and efficient algorithms to analyse large scale multi-valued objects. The success of this project will not only be an important complement to the current spatial database systems but also bring considerable economic and social benefits to Australia.
Discovery Early Career Researcher Award - Grant ID: DE130101002
Funder
Australian Research Council
Funding Amount
$375,000.00
Summary
Efficiently querying uncertain spatial space. Location-based services are becoming increasingly popular due to exponentially increased usage of smartphones and cheap wireless network. This project aims to provide efficient solutions for various location-based queries applicable to different travelling domains such as road networks, Euclidean space with obstacles and indoor space.
Efficient and Scalable Similarity Query Processing on Big Streaming Graphs . This project aims to develop novel approaches for efficient and scalable similarity queries on big streaming graphs which are large-scale graphs where graph nodes and edges may arrive or expire at high speed. Three key challenges are expected to be addressed including high speed, large variety, and big volume of streaming graphs. Expected outcomes include new theories, novel indexing and query processing techniques, an ....Efficient and Scalable Similarity Query Processing on Big Streaming Graphs . This project aims to develop novel approaches for efficient and scalable similarity queries on big streaming graphs which are large-scale graphs where graph nodes and edges may arrive or expire at high speed. Three key challenges are expected to be addressed including high speed, large variety, and big volume of streaming graphs. Expected outcomes include new theories, novel indexing and query processing techniques, and advanced distributed algorithms as well as a system prototype for evaluation and to demonstrate the practical value. Success in this project should see significant benefits for many important applications, such as e-commerce, cybersecurity, health, social networks, and bio-informatics.
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Taming Large-Volume Dynamic Graphs in the Cloud. This project aims to develop efficient and scalable algorithms to process large-volume dynamic graphs in the cloud. The project expects to address key challenges and lay theoretical foundations in large-volume dynamic graph processing, which plays an important role in developing general-purpose, real-time structural search engines. Expected outcomes of this project include theoretical foundations and scalable algorithms to process big graphs that ....Taming Large-Volume Dynamic Graphs in the Cloud. This project aims to develop efficient and scalable algorithms to process large-volume dynamic graphs in the cloud. The project expects to address key challenges and lay theoretical foundations in large-volume dynamic graph processing, which plays an important role in developing general-purpose, real-time structural search engines. Expected outcomes of this project include theoretical foundations and scalable algorithms to process big graphs that evolve rapidly over time. These enable users to monitor and analyse structural information in large dynamic networks in real time. The project expects to open up a new research direction for graph processing to enrich frontier technologies and benefit many key applications in Australia.Read moreRead less
Next-generation search on social networks. This project aims to design effective and intelligent search techniques for large scale social network data. The project expects to advance existing social network search systems in utilizing the geographical locations of queries and social network data to provide more relevant results, acknowledging and handling inherent uncertainties in the data, and exploiting knowledge graphs to produce intelligent search results. Expected outcomes of this project i ....Next-generation search on social networks. This project aims to design effective and intelligent search techniques for large scale social network data. The project expects to advance existing social network search systems in utilizing the geographical locations of queries and social network data to provide more relevant results, acknowledging and handling inherent uncertainties in the data, and exploiting knowledge graphs to produce intelligent search results. Expected outcomes of this project include a next-generation social network search system. The success of this project will support and enhance a wide range of applications such as law enforcement, health, national security, marketing, and advertisement.Read moreRead less