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
Ultra-wideband Aided Precision Parking for Wireless Power Transfer to Electric Vehicles in Real Life Scenarios
J. Tiemann, J. Pillmann, S. Böcker, C. Wietfeld,
In IEEE Vehicular Technology Conference (VTC-Fall), Montréal, Canada, September 2016.
BaLAnce: Battery Lifetime-Aware LTE Switching-Off Strategy in Green Network Infrastructures
C. Ide, O. Belov, D. Kaulbars, C. Wietfeld,
In IEEE Vehicular Technology Conference (VTC-Fall), Montréal, Canada, September 2016.
Improving Vehicular Traffic Simulations Using Real-Time Information on Environmental Conditions
L. Habel, C. Ide, C. Wietfeld, M. Schreckenberg,
In IEEE Vehicular Technology Conference (VTC-Fall), Montréal, Canada, September 2016.
Client-Based Control Channel Analysis for Connectivity Estimation in LTE Networks
R. Falkenberg, C. Ide, C. Wietfeld,
In IEEE Vehicular Technology Conference (VTC-Fall), Montréal, Canada, September 2016.
An OMNeT++ based Framework for Mobility-aware Routing in Mobile Robotic Networks
B. Sliwa, C. Ide, C. Wietfeld,
In OMNeT++ Community Summit 2016, Brno, Czech Republic, September 2016.
Local interference compensation (LOCATe) for GNSS-based Lane-Specific Positioning of Vehicles
B. Niehöfer, F. Schweikowski, C. Wietfeld,
In IEEE Vehicular Technology Conference (VTC-Spring), Nanjing, China, May 2016.
Empirical Analysis of the Impact of LTE Downlink Channel Indicators on the Uplink Connectivity
C. Ide, R. Falkenberg, D. Kaulbars, C. Wietfeld,
In IEEE Vehicular Technology Conference (VTC-Spring), Nanjing, China, May 2016.
Forecasting Cellular Connectivity for Cyber-Physical Systems: A Machine Learning Approach
C. Ide, M. Nick, D. Kaulbars, C. Wietfeld,
In Machine Learning for Cyber Physical Systems (O. Niggemann, J. Beyerer, eds.), Springer Vieweg
Spatially Distributed Traffic Generation for Stress Testing the Robustness of Mission-Critical Smart Grid Communication
D. Kaulbars, F. Schweikowski, C. Wietfeld,
In IEEE GLOBECOM 2015 Workshop on SmartGrid Resilience, San Diego, USA, December 2015.