Repeatable and Realistic Experimentation in Mobile Wireless Networks

Experimenting with mobile and wireless networks is challenging because testbeds lack repeatability and existing simulation models are unrealistic for real-world settings. We present practical models for the physical and MAC layer behavior in mobile wireless networks in order to address this challenge. Our models use measurements of a real network rather than abstract radio propagation and mobility models as the basis for accuracy in complex environments. We develop an adaptive measurement technique in order to maximize the accuracy of our models in dynamic environments. The models then predict the packet delivery, deferring, and collision probability in the same network for an arbitrary set of transmitters. This allows to explore the performance of different network and higher layer protocols in simulation or emulation under identical and realistic conditions. We evaluate the accuracy of our models empirically by comparing them to benchmark measurements. We find that our models are effective at reproducing mobile scenarios in various environments. Across many experiments in realistic environments, we are able to reproduce link delivery probabilities with RMS error below 12 percent, and the simulated throughput of data flows in the presence of interfering transmitters with an error that is below 10 percent.