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Volker Turau

Picture of Volker Turau
Prof. Dr. rer. nat. Volker Turau
Room 4.088, building E
Am Schwarzenberg-Campus 3
21073 Hamburg
phone+49 40 42878 - 3530

I am professor at Hamburg Universtity of Technology since October 2002.

Program Committee Activities | Editorial Activities | CV | Ph.D. students


Algorithmische Graphentheorie - 4., extended and revised edition
De Gruyter Studium, 2015, ISBN 978-3-110-41727-2 (Solutions)

Erdős number

My Erdős number is 3.



Nisal Manikku Badu, Marcus Venzke, Volker Turau and Yanqiu Huang. Machine Learning-based Positioning using Multivariate Time Series Classification for Factory Environments. Technical Report Report arXiv:2308.11670, e-Print Archive - Computing Research Repository (CoRR), Cornell University, August 2023.
@TechReport{Telematik_arxiv_2023, author = {Nisal Manikku Badu and Marcus Venzke and Volker Turau and Yanqiu Huang}, title = {Machine Learning-based Positioning using Multivariate Time Series Classification for Factory Environments}, number = {Report arXiv:2308.11670}, institution = { e-Print Archive - Computing Research Repository (CoRR)}, address = {Cornell University}, month = aug, year = 2023, }
Abstract: Indoor Positioning Systems (IPS) gained importance in many industrial applications. State-of-the-art solutions heavily rely on external infrastructures and are subject to potential privacy compromises, external information requirements, and assumptions, that make it unfavorable for environments demanding privacy and prolonged functionality. In certain environments deploying supplementary infrastructures for indoor positioning could be infeasible and expensive. Recent developments in machine learning (ML) offer solutions to address these limitations relying only on the data from onboard sensors of IoT devices. However, it is unclear which model fits best considering the resource constraints of IoT devices. This paper presents a machine learning-based indoor positioning system, using motion and ambient sensors, to localize a moving entity in privacy concerned factory environments. The problem is formulated as a multivariate time series classification (MTSC) and a comparative analysis of different machine learning models is conducted in order to address it. We introduce a novel time series dataset emulating the assembly lines of a factory. This dataset is utilized to assess and compare the selected models in terms of accuracy, memory footprint and inference speed. The results illustrate that all evaluated models can achieve accuracies above 80 %. CNN-1D shows the most balanced performance, followed by MLP. DT was found to have the lowest memory footprint and inference latency, indicating its potential for a deployment in real-world scenarios.
Marcus Venzke, Yevhenii Shudrenko, Amine Youssfi, Tom Steffen, Volker Turau and Christian Becker. Co-Simulation of a Cellular Energy System. Energies, 16(17), August 2023.
@Article{Energies_2023, author = {Marcus Venzke and Yevhenii Shudrenko and Amine Youssfi and Tom Steffen and Volker Turau and Christian Becker}, title = {Co-Simulation of a Cellular Energy System}, pages = , journal = {Energies}, volume = {16}, number = {17}, publisher = {MDPI}, month = aug, year = 2023, }
Abstract: The concept of cellular energy systems of the German Association for Electrical, Electronic and Information Technologies (VDE) proposes sector coupled energy networks for energy transition based on cellular structures. Its decentralized control approach radically differs from that of existing networks. Deeply integrated information and communications technologies (ICT) open opportunities for increased resilience and optimizations. The exploration of this concept requires a comprehensive simulation tool. In this paper, we investigate simulation techniques for cellular energy systems and present a concept based on co-simulation. We combine simulation tools developed for different domains. A classical tool for studying physical aspects of energy systems (Modelica, TransiEnt library) is fused with a state-of-the-art communication networks simulator (OMNeT++) via the standardized functional mock-up interface (FMI). New components, such as cell managers, aggregators, and markets, are integrated via remote procedure calls. A special feature of our concept is that the communication simulator coordinates the co-simulation as a master and integrates other components via a proxy concept. Model consistency across different domains is achieved by a common description of the energy system. Evaluation proves the feasibility of the concept and shows simulation speeds about 20 times faster than real time for a cell with 111 households.
Shashini Thamarasie Wanniarachchi and Volker Turau. A Study on the Influence of 5G Network planning on communication in Urban Air Mobility. In Proceedings of 24th {IEEE} International Symposium on a World of Wireless, Mobile and Multimedia Networks, WoWMoM 2023, IEEE, June 2023, pp. 394–399. Boston, USA.
@InProceedings{Telematik_wowmom_2023, author = {Shashini Thamarasie Wanniarachchi and Volker Turau}, title = {A Study on the Influence of 5G Network planning on communication in Urban Air Mobility}, booktitle = {Proceedings of 24th {IEEE} International Symposium on a World of Wireless, Mobile and Multimedia Networks, WoWMoM 2023}, pages = {394-399}, publisher = {IEEE}, day = {12-15}, month = jun, year = 2023, location = {Boston, USA}, }
Abstract: The emerging implementation of urban air mobility (UAM) is in need of a robust low latency communication system. The key priority is to cope with the required high level of safety assurance. 5G communication standards lay the foundation for a promising communication infrastructure, yet there exists the challenge of connectivity and coverage through the base station network. In this paper, we address this aspect and study the realization of a reliable and efficient 5G base station plan and evaluate its influence on the performance of the UAM communication system through simulations. Our findings can assist in real UAM deployment scenarios to search for the most cost effective radio network planning solution. We focus on the 3d-channel model and on the number and placement of base stations. As a use case we consider the Hamburg metropolitan region.

The complete list of publications is available separately.

Supervised Theses

Open Theses

Completed Theses