Discovery Early Career Researcher Award - Grant ID: DE240100006
Funder
Australian Research Council
Funding Amount
$444,847.00
Summary
Robust Derivative-Free Algorithms for Complex Optimisation Problems. Mathematical optimisation gives a systematic way for optimal decision-making. This project aims to develop new mathematical tools for complex optimisation problems where limited problem information is available. It will generate new foundational theories for alternative optimisation tools, introducing substantial new capability and rigour to the discipline. The project will create significant new mathematical optimisation techn ....Robust Derivative-Free Algorithms for Complex Optimisation Problems. Mathematical optimisation gives a systematic way for optimal decision-making. This project aims to develop new mathematical tools for complex optimisation problems where limited problem information is available. It will generate new foundational theories for alternative optimisation tools, introducing substantial new capability and rigour to the discipline. The project will create significant new mathematical optimisation techniques and create world-leading and publicly available software. These new techniques and software may ultimately be able to solve some of the most complex optimisation problems in research and industry, such as improving long-term climate predictions and designing 3D-printed medical implants.Read moreRead less
Resilience Oriented Multicast for Real-time Multimedia. The current communication infrastructure market is one of the largest market segments in the world. However, it is evident that the current Internet provides limited support for a multitude of current, emerging and future services that require multicasting support (worldwide, enhanced IP service revenues are forecast to grow to $104.4 billion in 2005). The introduction of enhanced multicasting services will result in lowered input costs to ....Resilience Oriented Multicast for Real-time Multimedia. The current communication infrastructure market is one of the largest market segments in the world. However, it is evident that the current Internet provides limited support for a multitude of current, emerging and future services that require multicasting support (worldwide, enhanced IP service revenues are forecast to grow to $104.4 billion in 2005). The introduction of enhanced multicasting services will result in lowered input costs to industries and consumers with a wider choice of enhanced services. The mechanisms developed in this project will allow service providers to raise additional revenue and differentiate themselves by offering a wide range of enhanced services.Read moreRead less
Efficient Distribution of Content in Multi-Rate Multi-channel Wireless Mesh Networks. The current wireless broadband access is one of the fastest growing markets in communications area. A study by market research firms such as BWCS (England) and SFC (US) estimates the US market itself to be over $3.7 billion by year 2009.
The current Wireless Mesh Network has limited capability to support for a multitude of current, emerging and future services . The mechanisms developed in this project will ....Efficient Distribution of Content in Multi-Rate Multi-channel Wireless Mesh Networks. The current wireless broadband access is one of the fastest growing markets in communications area. A study by market research firms such as BWCS (England) and SFC (US) estimates the US market itself to be over $3.7 billion by year 2009.
The current Wireless Mesh Network has limited capability to support for a multitude of current, emerging and future services . The mechanisms developed in this project will allow service providers to raise additional revenue and differentiate themselves by offering a wide range of enhanced services. Our research will help efficient sharing of network resources (such as bandwidth) between multiple users of multimedia communications using broadcasting and multicasting protocols. Read moreRead less
Unifying Modern Approaches in Machine Learning. The proposed research will lead to better algorithms for some important machine learning problems that could lead to better tools for extracting useful knowledge from data such as in bioinformatics and sensor networks; it will strengthen an international collaboration with one of the world's top centres of machine learning research; it will contribute to an open source toolkit of machine learning algorithms which will put Australia on the map as a ....Unifying Modern Approaches in Machine Learning. The proposed research will lead to better algorithms for some important machine learning problems that could lead to better tools for extracting useful knowledge from data such as in bioinformatics and sensor networks; it will strengthen an international collaboration with one of the world's top centres of machine learning research; it will contribute to an open source toolkit of machine learning algorithms which will put Australia on the map as a provider of sophisticated machine learning software; it will provide training opportunities for several PhD students and a postdoc to work with some of the best machine learning researchers in the world.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE150100240
Funder
Australian Research Council
Funding Amount
$315,000.00
Summary
Geometry and Conditioning in Structured Conic Problems. Conic programming allows one to model and solve large industrial problems via modern optimisation methods, such as interior-point algorithms. These methods are efficient and reliable in solving a vast number of problems, however, they fail on a relatively small but significant set of ill-posed instances, thus affecting the overall reliability of the technique. The reason for such behaviour is profound and constitutes one of the major unsolv ....Geometry and Conditioning in Structured Conic Problems. Conic programming allows one to model and solve large industrial problems via modern optimisation methods, such as interior-point algorithms. These methods are efficient and reliable in solving a vast number of problems, however, they fail on a relatively small but significant set of ill-posed instances, thus affecting the overall reliability of the technique. The reason for such behaviour is profound and constitutes one of the major unsolved problems in real complexity: there is no known algorithm that solves conic problems with real data in polynomial time. The project aims to develop a deep understanding of the geometry of conic problems, aiming for the resolution of this fundamental problem in computational theory.Read moreRead less
Pervasive Grids with Autonomic Capabilities. A grid computing system that brings together a multitude of heterogonous resources able should be able to function continuously without much intervention by a human operator. This work aims at developing techniques and tools for the monitoring and prediction of the behaviour of the core structure of a grid. In this case, the ?core? structure is a large- or a wide-area network, or a collection of such networks. The monitoring process will feed into the ....Pervasive Grids with Autonomic Capabilities. A grid computing system that brings together a multitude of heterogonous resources able should be able to function continuously without much intervention by a human operator. This work aims at developing techniques and tools for the monitoring and prediction of the behaviour of the core structure of a grid. In this case, the ?core? structure is a large- or a wide-area network, or a collection of such networks. The monitoring process will feed into the other layers in the grid fabric important information (traffic, current and possible future congestions, failures, topological variations, etc) to enable the efficient and consistent operation of the grid. This is an important research problem in grid computing
since traditional assumptions that are more or less valid in conventional high-performance computing settings break down on the Grid.Read moreRead less
A Grid-Enabled Meta-Server for Protein Threading. Grid Computing is a driver for many e-Science research projects around the world today. The project investigates the use of grid technology in building a meta-server architecture for protein threading. Protein technology problems are important for the field of bioinformatics and they also influence many industries, such as, agriculture, drug design, food science, and many more. The proposed framework can be extended to other problems in the life ....A Grid-Enabled Meta-Server for Protein Threading. Grid Computing is a driver for many e-Science research projects around the world today. The project investigates the use of grid technology in building a meta-server architecture for protein threading. Protein technology problems are important for the field of bioinformatics and they also influence many industries, such as, agriculture, drug design, food science, and many more. The proposed framework can be extended to other problems in the life sciences such as bio- and health-informatics. Projects of this nature are significant and will enable Australia to maintain its pioneering position and international reputation among other nations as leaders in Information Technology.Read moreRead less
Algorithms for hard graph problems based on auxiliary data. When solving computational problems, algorithms usually access only the data that is absolutely necessary to define the problem. However, much more data is often readily available. Especially for important or slowly evolving data, such as road networks, social graphs, company rankings, or molecules, more and more auxiliary data becomes available through computational processes, sensors, and simple user entries. This auxiliary data can g ....Algorithms for hard graph problems based on auxiliary data. When solving computational problems, algorithms usually access only the data that is absolutely necessary to define the problem. However, much more data is often readily available. Especially for important or slowly evolving data, such as road networks, social graphs, company rankings, or molecules, more and more auxiliary data becomes available through computational processes, sensors, and simple user entries. This auxiliary data can greatly speed up an algorithm and improve its accuracy. This project aims to design improved algorithms that harness auxiliary data to solve selected high-impact NP-hard graph problems, and will build a new empowering theory to discern when auxiliary data can be used to improve algorithms.Read moreRead less
Holistic Energy-Aware Scheduling for Distributed Computing Systems. Distributed computing systems are the platform of choice for many applications. In these systems, applications are submitted by a large number of users that compete for the shared heterogeneous resources (computers, storage communication links, etc). Concerns of power (or energy) consumption have become increasingly significant in the context of the design as well as the use of distributed computing systems. Therefore, there is ....Holistic Energy-Aware Scheduling for Distributed Computing Systems. Distributed computing systems are the platform of choice for many applications. In these systems, applications are submitted by a large number of users that compete for the shared heterogeneous resources (computers, storage communication links, etc). Concerns of power (or energy) consumption have become increasingly significant in the context of the design as well as the use of distributed computing systems. Therefore, there is a need to develop new generation of algorithms and software tools that enable the creation of environmentally friendly 'green' distributed systems. This project is a major step in this direction.Read moreRead less
Data and Job Scheduling in Large-Scale Distributed Systems. Distributed computing systems are the platform of choice for many applications. In these systems, applications are submitted by a large number of users that compete for the shared heterogeneous resources (computers, storage communication links, etc.). Thus, a distributed system can be viewed as a collection of computing and communication resources shared by active users. Towards this end, a new generation of algorithms and software tool ....Data and Job Scheduling in Large-Scale Distributed Systems. Distributed computing systems are the platform of choice for many applications. In these systems, applications are submitted by a large number of users that compete for the shared heterogeneous resources (computers, storage communication links, etc.). Thus, a distributed system can be viewed as a collection of computing and communication resources shared by active users. Towards this end, a new generation of algorithms and software tools need to be developed for the efficient utilisation of these systems through an appropriate allocation of the available resources to competing applications and users. This project is a major step in this direction.Read moreRead less