The HUN-REN-BME Information Systems Research Group started on July 1, 2012 under the name MTA-BME Information Systems Research Group as one of the subsidised research groups of the Hungarian Academy of Sciences at the Budapest University of Technology and Economics. The research group has been granted 5-year extensions in 2017 and in 2022, respectively. It is currently operating under the HUNgarian REsearch Network Office for Research Groups. The leader of the group is Miklós Telek.

 

Concept of research


In the next wave of advancement of communications networks one of the most important changes is that more and more operational functions are carried out automatically based on artifical intelligence, getting closer to realising a zero-touch concept, when network operation is fully automatic, identifying the need for intervention due to changes in the environment (e.g. changing load, network faults). The research group is carrying out theoretical and applied research related to these trends.

We examine network service security, efficient and automatic operation and reliability of new practical applications such as cloud-based services (e.g. extended, virtual and mixed reality AR/VR/MR), 5G networks and other new technologies (e.g. self-driving cars, Internet of Everything or Industry 4.0). Based on the available data during live operation, we examine how machine learning can be used to forecast various events. We also examine the applicability of groundbreaking technology such as quantum informatics.

Research is organized around four related fields.
  • Network modelling and network algorithms:
    • Research of continuously evolving communication networks and services, functionality-based design, modelling and optimization.
  • Self-managing cloud networks and services:
    • Efficient design and operation for service capacity distribution and resource management for cloud services on large-scale and heterogeneous networks.
  • Secure network management based on machine learning:
    • We examine the design of economical incentives for data security in federated learning systems in the presence of strict data security requirements.
  • Telecommunication applications of quantum informatics:
    • Optimization of optical networks for quantum key distribution protocols, quantum random number generators based on the difference of photon arrival times, and reliable quantum communication channels and designing quantum encryption algorithms.