Program Leader: Associate Professor Jinjun Chen
Our research in this stream positions us as a world-leading innovator in cloud computing and big data systems, delivering powerful enabling technologies with significant power to transform the increasingly data-intensive arenas of industry, research, and personal computing.
In this area of rapid development and change, our focus is on scalable and efficient solutions in the areas of privacy and security, big sensing data processing, public auditing and searchable encryption, workflow scheduling, and data link enabled efficient big document data processing.
Privacy and security in big data and cloud computing
Privacy and security are key challenges in this space, particularly in online user transactions data and records data analysis for personalised recommendation. This research area is focused on developing scalable and efficient solutions for effective and timely privacy preservation and security protection in the open big data and cloud environment.
Scalability, latency, availability for big data applications on cloud
With an estimated 40% of data globally being touched by cloud computing by 2020, there is strong demand for real solutions in storage, computation and distributed capability in support of big data processing. Our research in this area is identifying and addressing those challenges by developing innovative, scalable solutions to enable fast-response big data processing.
Big sensing data, data intensive applications, resource management and scheduling on cloud
Research in this area focuses on developing scalable and efficient solutions for on-demand resource management and scheduling, with applications in processing big sensing data and broad data intensive applications such as surveillance data, traffic data and meteorological data.
Large-scale workflow/scientific workflow/data intensive workflow/big data workflow management on cloud
There are endless everyday applications for large-scale data intensive or big data application workflows, in areas such as patient life-cycle medical records, insurance claims and taxation returns. This research area is focused on cost-efficient scheduling and management of these workflows within the cloud environment.