In Detail: Our Research
The overall goal of our research is to make computer networks and networked systems “smarter” in order to better accommodate diversified vertical services, e.g., autonomous vehicles, next-generation healthcare, smart city, AR/VR, etc.
In particular, we make use of artificial intelligence (AI) in network operation and multi-access edge computing (MEC), to improve the user experience of these emerging services. Intelligence, Efficiency, and Trust (IET) are the three key objectives of our research. Our main research interests include:
- Intelligent Resource Allocation, Scheduling and Optimisation: Self-Driving Networks, Zero-Touch Networks, Network Slicing and Softwarisation, Software Defined Networking (SDN), Network Functions Virtualisation (NFV), clean-slate post-IP network technologies (e.g., Information Centric Networking), Cloud Computing, Edge Computing, 5G and beyond 5G, Wireless Networks, Green Networking.
- Large-scale System Modelling: Network Digital Twin, Analytical Modelling.
- Online and Robust Anomaly Detection and its applications in various systems and fields.
- Network Security, Privacy and Safety: Privacy Preserving, Accountability, Blockchain, Responsible Intelligent Networks
The methodologies we usually used to carry out our research include:
- Stochastic Combinatorial Optimisation
- Game Theory
- Machine Learning, Deep Learning
- Graph Neural Networks
- Queuing Theory, Network Calculus
We’re also working with the Exeter Science Centre to help make our research more accessible to the public – have a read of our latest research summaries to find out more.