Projects
Collaborations
Current Projects
Green and Energy Monitoring for Future Network Infrastructures enabling also Large Deployments (GREENFIELD)
(Januar 2024 – Dezember 2026)
Das Ziel von GREENFIELD ist es, Energieeffizienz und ökologische Nachhaltigkeit in Kommunikationsnetzen zu definieren und zu erfassen (Green Monitoring), um darauf aufbauend Optimierungs- und Einsparpotential in bestehenden Netzen und Anwendungsfällen zu erforschen und Mechanismen zur Umsetzung (Green Management) zu entwickeln und zu demonstrieren.
SimDNA-SatNet: Simulation of DNA Infrastructure in Satellite Networks
(seit Juli 2023)
Ziel dieses Projekts ist die Simulation und Modellierung dezentraler, datenzentrierter Netzwerkarchitekturen mit besonderem Blick auf die Anwendbarkeit in Satellitennetzwerken.
Modellierung und Monitoring von Virtual Private Cloud Netzen für automatisierte Anomalieerkennung für Unternehmensanwendungen in heterogenen Netzen (VIPNANO)
(Oktober 2023 - September 2026)
In vielen Unternehmen steigt der Bedarf nach flexiblen und zuverlässigen Virtual Private Clouds (VPCs), wobei häufig mehrere große Cloud-Anbieter, private Clouds und eigene Netze in einer heterogenen Infrastruktur kombiniert werden. Diese Komplexität stellt neue Herausforderungen an das Netzmonitoring für einen zuverlässigen Anwendungsbetrieb. In diesem Vorhaben werden Verfahren entwickelt, um automatisiert den Normalzustand bzgl. Verkehrsmustern zu modellieren und darauf eine automatisierte Anomalieerkennung aufzubauen. Diese ermöglicht es, aus Netz- und Anwendungsbetrieb frühzeitig kritische Situationen zu erkennen, um mit passenden Gegenmaßnahmen Probleme und Ausfälle zu vermeiden. Die Projektpartner vereinen dabei die dafür notwendige Expertise: Isarnet mit der Datenanalyse von Netzmonitoring-Daten, JMU im Bereich Modellierung und Simulation sowie die Enterprise Kunden als assoziierte Partner mit einer großen Netz-Infrastruktur und mehrjähriger Erfahrung beim Anwendungsbetrieb in VPCs.
Optimierung und Modellierung eines IoT-zentrischen Mobilfunkkernnetzes (OMI)
(Oktober 2022 - September 2025)
Im Rahmen dieses Projekts sollen Arbeiten zur Optimierung einer vollständig virtualisierten Mobilfunkkernnetzumgebung in dem Bereich des Internets der Dinge durchgeführt werden. Der Fokus sollte unter anderem auf der Qualitätssicherung, Untersuchung von Netzwerkanomalien, Identifizierung gerätespezifischer Traffic-Eigenschaften, Entwicklung von Metriken zur Bewertung der Quality of Experience (QoE) auf User-Plane-Ebene und Systemoptimierung für ressourcenbegrenzte Geräte liegen.
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
(Oktober 2021 - September 2024)
Ziel dieses Projektes ist es, robuste, skalierbare Industrienetzwerke für die intelligente Fabrik zu entwickeln und deren Leistungsfähigkeit zu evaluieren. An das industrielle Netzwerk werden Echtzeitanforderungen gestellt und Garantien für die Kommunikationsnetze der Fabrik der Zukunft gefordert.
5GQMON - Crowdsourcing-based measurement methodology of user-oriented quality of service and network quality in 5G mobile networks
(May 2021 - April 2024)
The aim of the project is to investigate and define reliable crowdsourcing and agent-based methods to measure the performance of the new 5G mobile networks and their new applications, such as industrial applications, smart city, and the Internet of Things (IoT), according to end user's quality of experience.
DFG Group-based Communication
(Since January 2021)
The goal of this research project is analyzing the novel communication paradigm of group-based communication. The findings are used to design edge caching mechanism, which can reduce the network load imposed by user-generated contents, and increase the Quality of Experience of end users.
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.
WebQKAI
(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.
KIKDIN
(July 2019 - September 2020)
This project examines the usage of AI methods for the parametrization of convergent, deterministic, industrial networks.
QoE-Care
(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.
5MART
(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.
IOT4WUE
(March 2019 - December 2020)
We develop, roll out, and evaluate a LORAWAN network in the city of Würzburg.
EduQoE
(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.
ATS-Performance
(June 2018 - September 2020)
This project examines the performance characteristics of IEEE 802.1Q Transmission Selection Algorithms for time-critical traffic.
What's Up?
(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.
SDN App-Aware
(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.
Crowdsourcing DFG
(April 2014 - December 2021)
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.
