SenShaMart: A Trusted Internet of Things Marketplace for Sensor Sharing. This project aims to devise a novel Internet of Things (IoT) sensor sharing marketplace that permits IoT applications to discover, integrate, and pay for any IoT sensor data that is made available by other parties. The project will devise highly-scalable sensor classification, query processing, and transactions solutions and incorporate them in a pair of novel blockchains that work in tandem to securely manage all the infor ....SenShaMart: A Trusted Internet of Things Marketplace for Sensor Sharing. This project aims to devise a novel Internet of Things (IoT) sensor sharing marketplace that permits IoT applications to discover, integrate, and pay for any IoT sensor data that is made available by other parties. The project will devise highly-scalable sensor classification, query processing, and transactions solutions and incorporate them in a pair of novel blockchains that work in tandem to securely manage all the information and contracts needed by IoT applications to discover, integrate, pay, and use sensors provided by another parties. These IoT advancements will provide significant economic, environmental, and social benefits via making low-cost and immediate sensing available across the world.Read moreRead less
Reliable and Seamless Service Provisioning in Mobile Edge Computing . This project aims to develop enabling technologies to provide reliable and seamless services in mobile edge computing environments. This project will develop advanced algorithms with performance guarantees and efficient mechanisms for such service provisioning. The project expects to lay theoretical foundations and generate new knowledge for the provisioning of reliability-aware and mobility-aware services in mobile edge compu ....Reliable and Seamless Service Provisioning in Mobile Edge Computing . This project aims to develop enabling technologies to provide reliable and seamless services in mobile edge computing environments. This project will develop advanced algorithms with performance guarantees and efficient mechanisms for such service provisioning. The project expects to lay theoretical foundations and generate new knowledge for the provisioning of reliability-aware and mobility-aware services in mobile edge computing. The expected outcome of the project is a set of solutions to the myriad of services relying on mobile edge computing including e-Health, autonomous vehicles, and Internet of Things. This project will develop key fundamental technologies to improve Australia’s standing in the international research community.
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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
A mmWave Sensor Network for Hand Gesture Monitoring. This project aims to realise a world-first mmWave radar-based sensor network for device-free ubiquitous hand gesture monitoring. By harnessing recent radar technology breakthrough in mmWave, hand gesture may be monitored in a non-privacy intrusive manner. Pilot studies show different handrub gestures can be sensed and recognised by analysing the radio signal variations in the receiver. Given the many social, economic and health advantages of ....A mmWave Sensor Network for Hand Gesture Monitoring. This project aims to realise a world-first mmWave radar-based sensor network for device-free ubiquitous hand gesture monitoring. By harnessing recent radar technology breakthrough in mmWave, hand gesture may be monitored in a non-privacy intrusive manner. Pilot studies show different handrub gestures can be sensed and recognised by analysing the radio signal variations in the receiver. Given the many social, economic and health advantages of low-cost and non-privacy intrusive hand gesture sensing --- including enabling interactions and communications with smart environments (e.g., homes and offices) in a natural way --- the proposed research promises multiple benefits while positioning Australia as smart buildings innovator.Read moreRead less
Blockchain-Enabled Federated Learning for Secure and Decentralised Learning. This project aims to develop novel blockchain-enabled federated learning techniques for secure and decentralised learning. It addresses an important and urgent machine learning problem, that is, the data useful for training machine learning models are often held by different owners who are not willing to share their data due to privacy concerns, resulting in isolated data islands. The project will result in a set of inn ....Blockchain-Enabled Federated Learning for Secure and Decentralised Learning. This project aims to develop novel blockchain-enabled federated learning techniques for secure and decentralised learning. It addresses an important and urgent machine learning problem, that is, the data useful for training machine learning models are often held by different owners who are not willing to share their data due to privacy concerns, resulting in isolated data islands. The project will result in a set of innovative algorithms that provide solutions to the key challenges in blockchain-enabled federated learning. The expected outcomes of the project will dramatically advance the frontier of machine learning and blockchain research, and have massive social and economic benefits for Australia and international communities.Read moreRead less
A Unified Framework for Resource Management in Edge-Cloud Data Centres. Edge Computing (EC) is an emerging paradigm with a great promise for advancing Information and Communications Technologies. This project aims to investigate and provide solutions for the realization of a seemingly integrated Edge Data Centres (EDCs) with cloud environments. Using theoretical and system development approaches, the project expects to generate new knowledge for managing the resources of an EDC ecosystem. Outcom ....A Unified Framework for Resource Management in Edge-Cloud Data Centres. Edge Computing (EC) is an emerging paradigm with a great promise for advancing Information and Communications Technologies. This project aims to investigate and provide solutions for the realization of a seemingly integrated Edge Data Centres (EDCs) with cloud environments. Using theoretical and system development approaches, the project expects to generate new knowledge for managing the resources of an EDC ecosystem. Outcome of this project includes practical solutions through building novel mathematical frameworks and resource management objectives accompanied by system implementations. These outcomes will benefit both scientific and industrial communities, and mark Australian scientists as pioneers in this emerging area of research.Read moreRead less
Cost-effective App Service Management in Edge Computing Environment. This project aims to deliver a framework and a suite of approaches for cost-effective app service management in the edge computing (EC) environment facilitated by the 5G mobile network. Edge computing offers great promises for rapidly advancing mobile and IoT apps in many active domains in Australia, e.g., self-driving cars, medical services, etc. Using a variety of optimization techniques and game theory, this project attacks ....Cost-effective App Service Management in Edge Computing Environment. This project aims to deliver a framework and a suite of approaches for cost-effective app service management in the edge computing (EC) environment facilitated by the 5G mobile network. Edge computing offers great promises for rapidly advancing mobile and IoT apps in many active domains in Australia, e.g., self-driving cars, medical services, etc. Using a variety of optimization techniques and game theory, this project attacks the new challenges in the deployment, delivery and adaptation of app services in the EC environment. The outcomes of this project will significantly promote new mobile and IoT apps over Australia's 5G mobile network by allowing app vendors to manage their services cost-effectively with ease in the EC environment.Read moreRead less
Adaptive context caching for fast concurrent access in Internet of Things. Context-awareness in Internet of Things (IoT) applications has profound impact on smartness, relevance, adaptability, dependability, performance and flexibility of such applications. This project will address the significant knowledge gap by investigating, proposing and validating a novel adaptive context caching scheme for fast near real-time access in multiple concurrent context queries coming from multiple and diverse ....Adaptive context caching for fast concurrent access in Internet of Things. Context-awareness in Internet of Things (IoT) applications has profound impact on smartness, relevance, adaptability, dependability, performance and flexibility of such applications. This project will address the significant knowledge gap by investigating, proposing and validating a novel adaptive context caching scheme for fast near real-time access in multiple concurrent context queries coming from multiple and diverse IoT applications. The outcome will be a critical component of the IoT context management platform called Context-as-a-Service which is currently under development. The expected benefits will be far ranging and applicable to many domains including intelligent transportation, industrial internet and smart cities..Read moreRead less
Multi-resolution situation recognition for urban-aware smart assistant. This project aims to develop a situation recognition framework to recognise and anticipate unforeseen emerging situations, such as schedule changes, incidents, and disruptions in an urban environment. The project will address a significant knowledge gap by capturing and modelling unpredictability in human mobility and work routines. The outcome will be a situation recognition framework that can be applied at the individual, ....Multi-resolution situation recognition for urban-aware smart assistant. This project aims to develop a situation recognition framework to recognise and anticipate unforeseen emerging situations, such as schedule changes, incidents, and disruptions in an urban environment. The project will address a significant knowledge gap by capturing and modelling unpredictability in human mobility and work routines. The outcome will be a situation recognition framework that can be applied at the individual, social group, and urban level, and at multiple locations and time scales. This should provide users with timely notifications and recommendations to resume their activities and routines. The expected benefits will be far-ranging and adaptable to many domains, from personal smart assistants to trip planning and emergency services.Read moreRead less
Edge-Accelerated Deep Learning. Implementing deep learning (DL) applications usually requires a large amount of collected data and powerful computing resources in the cloud. However, this centralised approach has issues of high latency, large bandwidth usage, and possible privacy violation for many practical applications. Without properly addressing these issues, the wider application of DL in practice will seriously be hindered. This project aims to solve several key challenging problems in eff ....Edge-Accelerated Deep Learning. Implementing deep learning (DL) applications usually requires a large amount of collected data and powerful computing resources in the cloud. However, this centralised approach has issues of high latency, large bandwidth usage, and possible privacy violation for many practical applications. Without properly addressing these issues, the wider application of DL in practice will seriously be hindered. This project aims to solve several key challenging problems in effective deployment and efficient execution of DL applications in a distributed edge-computing environment. Several innovative edge-computing methods will be developed for DL training, inference and implementation to achieve high performance with low latency and enhanced privacy.Read moreRead less