Main research findings
Mobile Broadband (MBB) networks underpin several essential operations of today’s society by regulating a huge portion of the modern communications system. The recent scientific advances in MBB technologies such as Fifth Generation (5G) and cellular Internet of Things (IoT) will further strengthen the MBB networks’ role, making them the norm in the global mobile telecommunications ecosystem. Given the increasing number of mobile devices and coupled with the high availability of data, it is therefore important to understand the underlying mechanisms that define the behaviour of the MBB network performance. In this thesis, we focus on the empirical characterization and modelling of mobile systems. In particular, we are interested in capturing the interplay between numerous network performance metrics, including bandwidth, latency, and signal strength. Toward this goal, we exploit experimental platforms to perform controlled, transparent, and replicable real-world measurements and collect a multitude of attributes from operational networks. For the analysis, we design, implement and propose supervised learning models using data-driven methods and Artificial Intelligence (AI) paradigms.
The work has been conducted at Simula Research Laboratory and UiO.
Prior to the defence, Konstantinos presented his trial lecture«The Evolution of Mobile broadband networks».
The PhD defence and trial lecture were fully digital.
- Professor Nur Zincir-Heywood,Faculty of Computer Science, Dalhousie University, Canada
- Professor Yong Liu,Electrical and Computer Engineering Department, Tandon School of Engineering, New York University, USA
- Professor Tor Skeie,Department of Informatics, University of Oslo, Norway
- Associate Professo rÖzgü Alay, Department of Informatics, University of Oslo
- Associate Professor Antonios Argyriou, University of Thessaly, Greece
- Professor Carsten Griwodz, Department of Informatics, University of Oslo
Chair of defence
- ProfessorStephan Oepen, Department of Informatics, UiO