3 citations · 3 across the 1 of their papers we have counts for
8 papers
Exploiting Map Topology Knowledge for Context-predictive Multi-interface Car-to-cloud Communication
Benjamin Sliwa, Johannes Pillmann, Maximilian Klaß +1
While the automotive industry is currently facing a contest among different communication technologies and paradigms about predominance in the connected vehicles sector, the divers…
Machine learning based context-predictive car-to-cloud communication using multi-layer connectivity maps for upcoming 5G networks
Benjamin Sliwa, Thomas Liebig, Robert Falkenberg +2
While cars were only considered as means of personal transportation for a long time, they are currently transcending to mobile sensor nodes that gather highly up-to-date informatio…
The AutoMat CVIM - A Scalable Data Model for Automotive Big Data Marketplaces
Johannes Pillmann, Benjamin Sliwa, Christian Wietfeld
In the past years, connectivity has been introduced in automotive production series, enabling vehicles as highly mobile Internet of Things sensors and participants. The Horizon 202…
Resource-efficient Transmission of Vehicular Sensor Data Using Context-aware Communication
Benjamin Sliwa, Thomas Liebig, Robert Falkenberg +2
Upcoming Intelligent Traffic Control Systems (ITSCs) will base their optimization processes on crowdsensing data obtained for cars that are used as mobile sensor nodes. In conclusi…
Novel Common Vehicle Information Model (CVIM) for Future Automotive Vehicle Big Data Marketplaces
Johannes Pillmann, Christian Wietfeld, Adrian Zarcula +2
Even though connectivity services have been introduced in many of the most recent car models, access to vehicle data is currently limited due to its proprietary nature. The Europea…
Empirical evaluation of predictive channel-aware transmission for resource efficient car-to-cloud communication
Johannes Pillmann, Benjamin Sliwa, Christian Kastin +1
Nowadays vehicles are by default equipped with communication hardware. This enables new possibilities of connected services, like vehicles serving as highly mobile sensor platforms…