Collaborative Research Center 876
The collaborative research center SFB876 brings together data mining and embedded systems. On the one hand, embedded systems can be further improved using machine learning. On the other hand, data mining algorithms can be realized in hardware, e.g. FPGAs, or run on GPGPUs. The restrictions of ubiquitous systems in computing power, memory, and energy demand new algorithms for known learning tasks. These resource bounded learning algorithms may also be applied on extremely large data bases on servers.
Project duration: 01.01.2015 - 31.12.2022
Project Composition of the SFB 876
The collaborative research center is divided into multiple projects. An extensive overview of all projects and their main objective can be found on the homepage of the SFB 876.
The Communication Networks Institute attends projects A4 and B4
News
Excellent wireless localization technology - CNI team wins IPIN competition
The CNI team (Janis Tiemann, Fabian Eckermann and Christian Wietfeld) won first prize in the "Indoor Mobile Robot Localization" category within the…
ComNets-Awards for Graduates of the Institute
The coveted awards by the "Verein der Freunde und Förderer der ComNets-Einrichtungen", who dedicated themselves to the research on future…
Collaborative Research Center with CNI-Participation Approved for 4 More Years
In the Collaborative Research Center 876 (SFB 876), the combination of data analysis (Data Mining/Big Data) with networked, embedded systems…
Successful Completion of Björn Dusza's Doctoral Studies in the Collaborative Research Center 876
Due to strongly increasing data traffic in mobile communications, the influence of the intensive use of mobile services on the battery life of…
Publications
Client-Based Intelligence for Resource Efficient Vehicular Big Data Transfer in Future 6G Networks
B. Sliwa, R. Adam, C. Wietfeld
In IEEE Transactions on Vehicular Technology, February 2021
Reflecting Surfaces for Beyond Line-Of-Sight Coverage in Millimeter Wave Vehicular Networks
K. Heimann, A. Marsch, B. Sliwa, C. Wietfeld
In IEEE Vehicular Networking Conference (VNC), December 2020
Scalability Analysis of Context-Aware Multi-RAT Car-to-Cloud Communication
J. Güldenring, C. Wietfeld
In 2020 IEEE 92th Vehicular Technology Conference (VTC-Fall), Victoria, B.C., Canada, October 2020
Cooperative Validation of CAM Position Information Using C-V2X
F. Eckermann, P. Gorczak, C. Wietfeld
In 2020 IEEE 92th Vehicular Technology Conference (VTC-Fall), Victoria, B.C., Canada, October 2020
Deep Learning-based Signal Strength Prediction Using Geographical Images and Expert Knowledge
J. Thrane, B. Sliwa, C. Wietfeld, H. Christiansen
In 2020 IEEE Global Communications Conference (GLOBECOM), Taipei, Taiwan, December 2020
The Best of Both Worlds: Hybrid Data-Driven and Model-Based Vehicular Network Simulation
B. Sliwa, M. Patchou, C. Wietfeld
In 2020 IEEE Global Communications Conference (GLOBECOM), Taipei, Taiwan, December 2020
CELIDON: Supporting First Responders through 3D AOA-based UWB Ad-Hoc Localization
J. Tiemann, et al.
In 16th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob), October 2020
Acting Selfish for the Good of All: Contextual Bandits for Resource-Efficient Transmission of Vehicular Sensor Data
B. Sliwa, R. Adam, C. Wietfeld
In Proceedings of the ACM MobiHoc Workshop on Cooperative Data Dissemination in Future Vehicular Networks (D2VNet),…
Offloading safety- and mission-critical tasks via unreliable connections
L. Schönberger, et al.
In 32st Euromicro Conference on Real-Time Systems (ECRTS 2020), Modena, Italy, July 2020