The Wireless Networking research track is a joint between the IDLab research group of Ghent University and University of Antwerp. The focus is on providing deterministic guarantees on end-to-end service delivery to/between heterogeneous networked devices in dynamic wireless environments through collaborative management approaches. Within this track, we focus on the following sub-domains:
- End-to-end management of heterogeneous wireless networks
- Heterogeneous sub 1GHz wide area networks for IoT
- Localization and tracking
- AI-driven network optimization
- Full stack design and prototyping of embedded systems
Core PI's: Jeroen Famaey (UAntwerp), Chris Blondia (UAntwerp), Johann Marquez-Barja (UAntwerp), Maarten Weyn (UAntwerp), Jeroen Hoebeke (UGent), Ingrid Moerman (UGent) and Eli Depoorter (UGent)
Within this research, we focus on new machine learning solutions and their deployment on distributed environments (e.g., embedded systems, cloud networks, etc.). More specifically, we focus on the challenges that arise from distributed systems such as heterogenous sensors, noise in the data quality, resource constrained environments and a limited availability of data. Within this track, we focus on the following sub-domains:
- Deep reinforcement learning: development of new reinforcement learning algorithms with a particular emphasis on distributed deployments and reduced convergence times.
- Semi-supervised learning and one shot learning: learning to deal with a limited amount of labeled data.
- Machine learning based on new neuroscience models.
- Efficient development of AI in simulation: agent-based hybrid testing of large-scale and complex environments.
Core PI's: Steven Latré, Peter Hellinckx and José Oramas
Modelling of Complex Systems
Mathematical Modeling of Complex Systems and Networks
The research activities in this research line involve the development and application of stochastic modeling techniques to evaluate complex systems and communication systems in particular. This encompasses aspects of modelling, information theory, and its application to inventory systems and networks.
Core PI: Benny Van Houdt