DFG Emmy Noether Junior Research Group UserNet
(Since October 2022)
In order to allow QoE monitoring for arbitrary Internet applications, the interplays between QoE and user interactions is investigated and modelled based on measurements and subjective studies. In addition, ML methods are adapted to the domain in order to apply them to encrypted network traffic. This allows to quantify the QoE by monitoring interactions and the resulting changes in the encrypted application traffic. Based on this, a data-driven improvement of QoE and QoE fairness is enabled by using reinforcement learning to find optimal network configurations by interacting with the dynamic network environment. By means of powerful, software-defined networking (SDN) technologies like P4, together with available computing resources in the network, such fine-granular models can now be implemented in the network for the first time, such that network management becomes more dynamic. Thus, the implementation of the required ML-based algorithms and components and their integration into network operation is researched.
KOSINU5 - Konvergierte deterministische Industrienetze in heterogenen Umgebungen mit Campus-5G
(October 2021 - September 2024)
The aim of this project is to develop robust, scalable industrial networks for intelligent factories and to evaluate their performance. Real-time requirements are placed on the industrial network and guarantees are required for the communication networks of the factory of the future.
WINTERMUTE (funded by BMBF)
(April 2020 - March 2023)
This project focuses on AI-based network assessment, policy definition, and enforcement of security in complex networks.
(October 2019 - July 2020)
The objective of the “WebQKAI” project is to infer web QoE key performance indicators (KPIs) from data collected by network devices, which provide insights for operators with respect to network operations and maintenance.
(July 2019 - September 2020)
This project examines the usage of AI methods for the parametrization of convergent, deterministic, industrial networks.
(May 2019 - April 2021)
This project focusses on the relationship between the perceived quality of the performance of business applications by the employees and the technical performance data of such applications.
Performance Evaluation and Network Planning for Automotive TSN
(May 2019 -June 2020)
This project evaluates how techniques and variants of Time Sensitive Networking (TSN), including IEEE 802.1Qbv and 802.1Qcr, can best be realized in a future, realistic car network with the intention to support autonomous driving. For this we aim to develop a reference architecture and reference packet schedule.
(March 2019 - February 2022)
On the example of the city of Würzburg the project 5MART develops and evaluates communication technologies and architectures (5G and LPWAN) and open data platforms for smart cities.
(March 2019 - December 2020)
We develop, roll out, and evaluate a LORAWAN network in the city of Würzburg.
(since March 2019)
The goal is to monitor and analyze the QoE in the networks of an education service provider, with the eventual goal of improving their services.
5CALE - Massive scaling of fully virtualized 5G mobile core networks in the context of IoT
(Februray 2019 - January 2022)
Within the project, new scaling methods and resource management approaches are being developed for the next generation 5G mobile communication network with IoT traffic. It is funded within the 5G call "Digitale Offensive" of the Bavarian Ministry of Economic Affairs with a total budget of one million euros and a term of 3 years.
(June 2018 - September 2020)
This project examines the performance characteristics of IEEE 802.1Q Transmission Selection Algorithms for time-critical traffic.
(since December 2017 )
What's Up is an interdisciplinary project together with psychologists of the University of Tübingen to analyze the communication of depressive children and adolescents in WhatsApp. With the help of WhatsAnalyzer, an early-warning system for depressive phases will be developed, which can effectively be used in the treatment of depression.
(January 2017 - December 2019)
The project targets the development of fundamental control mechanisms for network-aware application control and application-aware network control for Software Defined Networks (SDN) in order to enhance the user perceived quality (QoE). The idea is to leverage the QoE from multiple applications as control input parameter for application control and network control mechanisms.
(since April 2014)
This project focuses on designing and evaluating new mechanisms in micro tasking platforms to improve the basic concepts with respect to the interests of provider, employer and worker.