■ Resource-efficient Transmission of Vehicular Sensor Data Using Context-aware Communication

Abstract.

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 conclusion, public cellular networks will be confronted with massive increases in Machine-Type Communication (MTC) and will require efficient communication schemes to minimize the interference of Internet of Things (IoT) data traffic with human communication. In this demonstration, we present an Open Source framework for context-aware transmission of vehicular sensor data that exploits knowledge about the characteristics of the transmission channel for leveraging connectivity hotspots, where data transmissions can be performed with a high grade if resource efficiency. At the conference, we will present the measurement application for acquisition and live-visualization of the required network quality indicators and show how the transmission scheme performs in real-world vehicular scenarios based on measurement data obtained from field experiments.

Bibtex Entry.

@inproceedings{DBLP:conf/mdm/SliwaLFPW18,
  author    = {Benjamin Sliwa and
               Thomas Liebig and
               Robert Falkenberg and
               Johannes Pillmann and
               Christian Wietfeld},
  title     = {Resource-Efficient Transmission of Vehicular Sensor Data Using Context-Aware
               Communication},
  booktitle = {19th {IEEE} International Conference on Mobile Data Management, {MDM}
               2018, Aalborg, Denmark, June 25-28, 2018},
  pages     = {282--283},
  year      = {2018},
  crossref  = {DBLP:conf/mdm/2018},
  url       = {https://doi.org/10.1109/MDM.2018.00051},
  doi       = {10.1109/MDM.2018.00051},
  timestamp = {Tue, 31 Jul 2018 12:20:29 +0200},
  biburl    = {https://dblp.org/rec/bib/conf/mdm/SliwaLFPW18},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}