Passive monitoring and geo-based prediction of mobile network vehicle-to-server communication

Predicting mobile network parameters while driving is a challenge. The high dynamics and the mobility of the clients lead to spontaneous changes in the communication quality. There are different known approaches to predict the throughput of such mobile network connections. The paper presents a novel overview for the performance of different geographical prediction methods based on the same dataset. To generate the dataset, a tool for monitoring a vehicle-to-server communication in a passive way is presented, too. It does not only capture high level parameters like TCP throughput and round trip times, but also mobile network parameters, like RSSI or RSRQ. In addition, the data is recorded in real-time and augmented with GPS coordinates to analyze them location-dependent.