Industrial Transformation Research Hubs - Grant ID: IH230100013
Funder
Australian Research Council
Funding Amount
$5,000,000.00
Summary
ARC Research Hub for Future Digital Manufacturing. This Hub aims to grow and accelerate Australian digital manufacturing (DM) transformation by devising novel DM technology and commercialisation/adoption pathways. The Hub expects to transform industry by developing novel AI and IoT-powered DM technology that provides for dramatic improvement in manufacturing productivity, resilience and competitiveness. Expected outcomes include novel DM technology for digitally representing, predicting, and imp ....ARC Research Hub for Future Digital Manufacturing. This Hub aims to grow and accelerate Australian digital manufacturing (DM) transformation by devising novel DM technology and commercialisation/adoption pathways. The Hub expects to transform industry by developing novel AI and IoT-powered DM technology that provides for dramatic improvement in manufacturing productivity, resilience and competitiveness. Expected outcomes include novel DM technology for digitally representing, predicting, and improving production and its outcomes via an open platform that supports reusing industry co-created DM solutions. Through supporting advanced manufacturing priorities and Industry 4.0, the Hub should provide significant benefits by increasing Australian manufacturing productivity and resilience by 30%.Read moreRead less
Internet Timing for the Ages: Establishing the New Timekeeping System. All computers incorporate a software clock, essential to myriad software applications. An economic way to synchronize such clocks is over a network, however the approach the Internet currently depends upon is unreliable and vulnerable. This project aims to establish a new architecture for networked timekeeping, built on future-proofed fundamentals, that will for the first time address each of accuracy, reliability, and trust. ....Internet Timing for the Ages: Establishing the New Timekeeping System. All computers incorporate a software clock, essential to myriad software applications. An economic way to synchronize such clocks is over a network, however the approach the Internet currently depends upon is unreliable and vulnerable. This project aims to establish a new architecture for networked timekeeping, built on future-proofed fundamentals, that will for the first time address each of accuracy, reliability, and trust. The expected outcome is a national prototype, serving the public with accurate and trusted time, that will form the basis of the next generation timekeeping system for the Internet and the Internet of Things. Expected benefits include enhanced productivity across the digital economy, and resilience to GPS failures.Read moreRead less
Attribution of Machine-generated Code for Accountability. Machine-generated (or neural) code is usually produced by AI tools to speed up software development. However, such codes have recently raised serious security and privacy concerns. This project aims to attribute these codes to their generative models for accountability purposes. In the process, a series of new techniques are developed to differentiate between the codes generated by different models. The outcomes include analysis of neural ....Attribution of Machine-generated Code for Accountability. Machine-generated (or neural) code is usually produced by AI tools to speed up software development. However, such codes have recently raised serious security and privacy concerns. This project aims to attribute these codes to their generative models for accountability purposes. In the process, a series of new techniques are developed to differentiate between the codes generated by different models. The outcomes include analysis of neural code fingerprints, classification of neural codes, and theories to verify the correctness of code attribution. These will provide significant benefits, ranging from copyright protection to privacy preservation. This project is timely since currently the software community is pervasively using neural codes.Read moreRead less
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.Read moreRead less
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.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE140101628
Funder
Australian Research Council
Funding Amount
$301,970.00
Summary
Non-Intrusive Resource Sharing for Cloud Data Centre Efficiency. Resource sharing using hardware virtualisation has become increasingly common for cloud data centre efficiency. Such virtualisation allows multiple workloads to share a common set of resources in a single physical machine. In practice, however, these co-located workloads often compete for resources, leading to their resource usage being non-isolable and intrusive. This intrusive resource sharing is a major source of cloud data cent ....Non-Intrusive Resource Sharing for Cloud Data Centre Efficiency. Resource sharing using hardware virtualisation has become increasingly common for cloud data centre efficiency. Such virtualisation allows multiple workloads to share a common set of resources in a single physical machine. In practice, however, these co-located workloads often compete for resources, leading to their resource usage being non-isolable and intrusive. This intrusive resource sharing is a major source of cloud data centre inefficiency. This project will develop non-intrusive resource allocation and scheduling solutions that enable co-located workloads to organically use resources. These solutions exploit the heterogeneity and dynamicity of cloud data centres that are often perceived as the main hurdles of resource management.Read moreRead less
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.Read moreRead less
Optimising service level agreements for performance and energy efficiency in cloud computing systems. In cloud platforms a large number of applications compete for shared resources. Concerns of power consumption have become increasingly significant in the context of the design and use of cloud systems. In this project new algorithms and software tools will be developed to enable a better utilisation of clouds whilst minimising energy usage.
The red belly blockchain: a scalable blockchain for internet of things. This project aims to offer a blockchain that scales with the number of participants. There have been major investments in blockchain technologies during the last year as blockchains promise to disrupt industries like supply chains. Unfortunately, blockchains cannot solve this problem in their current form, because they cannot scale. They require resources that grow with the number of participants and yet fail at providing in ....The red belly blockchain: a scalable blockchain for internet of things. This project aims to offer a blockchain that scales with the number of participants. There have been major investments in blockchain technologies during the last year as blockchains promise to disrupt industries like supply chains. Unfortunately, blockchains cannot solve this problem in their current form, because they cannot scale. They require resources that grow with the number of participants and yet fail at providing increasing performance. The project will leverage many devices of limited resources to offer higher performance and will impact the distributed computing field by establishing a new connection between energy efficient systems and highly scalable distributed algorithms.Read moreRead less
Resource Allocation for High-Volume Streaming Data in Data Centers. Almost all chip vendors are producing new hardware accelerators by combining several units into a single main-board, and therefore making the execution of parallel and distributed run-time primitives not efficient/scalable. This project aims to develop innovative ways to building incremental and iterative computations over massive data sets in a cluster of heterogeneous systems. This will provide a significant reduction of perfo ....Resource Allocation for High-Volume Streaming Data in Data Centers. Almost all chip vendors are producing new hardware accelerators by combining several units into a single main-board, and therefore making the execution of parallel and distributed run-time primitives not efficient/scalable. This project aims to develop innovative ways to building incremental and iterative computations over massive data sets in a cluster of heterogeneous systems. This will provide a significant reduction of performance bottlenecks when running heavily distributed data-driven applications. Expected outcomes will include resource management algorithms that optimise performance at large scale. The project will benefit many areas, including running stateful iterative stream-based data-analysis applications in data centres. Read moreRead less