A Data-Centric Mobile Edge Platform for Resilient Logistics & Supply Chain. This project aims to develop a secure mobile edge computing platform for resilient logistic and supply chain management. It consists of easy-used functions that help businesses realise low latency, high reliability, low cost, and high security in their logistics and supply chain system. To cope with the vast generated application data, we invent new data replication, placement, and deduplication techniques to optimise th ....A Data-Centric Mobile Edge Platform for Resilient Logistics & Supply Chain. This project aims to develop a secure mobile edge computing platform for resilient logistic and supply chain management. It consists of easy-used functions that help businesses realise low latency, high reliability, low cost, and high security in their logistics and supply chain system. To cope with the vast generated application data, we invent new data replication, placement, and deduplication techniques to optimise the mobile edge computing platform from the computation, storage, and network aspects. The invented mobile edge computing platform will enable more intelligent business applications for various industries, e.g., IT, manufacturing, and media, to appear, thus benefiting both the economy of Australia.Read moreRead less
Cost-effective and Reliable Edge Caching for Software Vendors. This project aims to deliver a suite of models and techniques for cost-effective and reliable data caching in the multi-access edge computing (MEC) environment facilitated by 5G mobile network. MEC offers great promises for rapidly advancing mobile and IoT applications in various domains in Australia, e.g., smart cities, remote medical services, advanced manufacturing, etc. Combining graph analytics, optimisation techniques and game ....Cost-effective and Reliable Edge Caching for Software Vendors. This project aims to deliver a suite of models and techniques for cost-effective and reliable data caching in the multi-access edge computing (MEC) environment facilitated by 5G mobile network. MEC offers great promises for rapidly advancing mobile and IoT applications in various domains in Australia, e.g., smart cities, remote medical services, advanced manufacturing, etc. Combining graph analytics, optimisation techniques and game theory, this project tackles the new challenges in the placement, update and adaptation of edge data faced by software vendors embracing 5G. The outcomes can ease software vendors' cost and security concerns during the transition from 4G to 5G, and significantly promote the wave of 5G innovation in Australia.Read moreRead less
Driving Towards Greener and Safer Roads using Big Spatiotemporal Data. This project aims to design novel techniques for using big spatiotemporal data to reduce the impact of road transport on the environment and improve road safety. This project expects to address key challenges and lay scientific foundations of using the big data for developing a next-generation eco-friendly navigation system and increasing situational awareness for road transport safety. Expected outcomes of this project inclu ....Driving Towards Greener and Safer Roads using Big Spatiotemporal Data. This project aims to design novel techniques for using big spatiotemporal data to reduce the impact of road transport on the environment and improve road safety. This project expects to address key challenges and lay scientific foundations of using the big data for developing a next-generation eco-friendly navigation system and increasing situational awareness for road transport safety. Expected outcomes of this project include novel big data management and analytics techniques, and new edge computing models for vehicular networks. The success of this project should bring several key benefits including reducing greenhouse gas emissions on roads, facilitating urban planning, and improving road safety.Read moreRead less
Knowledge Graph-driven Software Vulnerability Risk Discovery and Assessment. This project aims to alleviate cyberattacks which are increasingly being crafted to attack software vulnerabilities and weaknesses by utilising advanced knowledge graphs and deep learning techniques. This project expects to construct an innovative software vulnerability knowledge graph and develop advanced graph-based algorithms and models. Expected outcomes of this project include the enhanced capacity to defend agains ....Knowledge Graph-driven Software Vulnerability Risk Discovery and Assessment. This project aims to alleviate cyberattacks which are increasingly being crafted to attack software vulnerabilities and weaknesses by utilising advanced knowledge graphs and deep learning techniques. This project expects to construct an innovative software vulnerability knowledge graph and develop advanced graph-based algorithms and models. Expected outcomes of this project include the enhanced capacity to defend against cyberattacks for both organisations and individuals in Australia and beyond, theory development in graph theory, refined graph neural network models and improved graph transfer learning algorithms.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE240100165
Funder
Australian Research Council
Funding Amount
$443,847.00
Summary
Evolving privacy and utility in data storage and publishing. This project aims to develop a distributed evolutionary computation-based framework to optimize data privacy and utility in distributed database systems. It intends to synchronously solve the conflicting challenges of privacy preservation and utility maintenance in multi-objective, dynamic, and multitasking scenarios. Expected outcomes include a new computation framework as a service and freely available distributed computation models, ....Evolving privacy and utility in data storage and publishing. This project aims to develop a distributed evolutionary computation-based framework to optimize data privacy and utility in distributed database systems. It intends to synchronously solve the conflicting challenges of privacy preservation and utility maintenance in multi-objective, dynamic, and multitasking scenarios. Expected outcomes include a new computation framework as a service and freely available distributed computation models, evolutionary algorithms, and knowledge-transfer strategies. Anticipated benefits include theoretical contributions to artificial intelligence, cyber security, distributed computation, and a service to eliminate data owners’ privacy concerns while guaranteeing the value of data in further utilization.Read moreRead less
Differential Evolution Framework for Intelligent Charging Scheduling. Smart charging scheduling is a vital challenge as dynamic environment with traffic networks and various unexpected issues. This project aims to develop a differential evolution framework for intelligent charging scheduling. The framework consists of a comprehensive charging scheduling model with various road networks and factors. The project outcomes include a distributed evolutionary computation framework, differential evolut ....Differential Evolution Framework for Intelligent Charging Scheduling. Smart charging scheduling is a vital challenge as dynamic environment with traffic networks and various unexpected issues. This project aims to develop a differential evolution framework for intelligent charging scheduling. The framework consists of a comprehensive charging scheduling model with various road networks and factors. The project outcomes include a distributed evolutionary computation framework, differential evolution algorithms, and cooperative co-evolutionary strategies. The outcome results will be demonstrated by practical evaluations over public datasets and comparisons to related works. The project is beneficial to the nation in both theory of artificial intelligence techniques and applications of real transport systems.Read moreRead less