A Location-Dependent Runs-and-Gaps Model for Predicting TCP Performance Over a UAV Wireless Channel
In this paper, the authors use a finite-state model to predict the performance of the Transmission Control Protocol (TCP) over a varying wireless channel between an Unmanned Aerial Vehicle (UAV) and ground nodes. As a UAV traverses its flight path, the wireless channel may experience periods of significant packet loss, successful packet delivery, and intermittent reception. By capturing packet run-length and gap-length statistics at various locations on the flight path, this location-dependent model can predict TCP throughput in spite of dynamically changing channel characteristics. They train the model by using packet traces from flight tests in the field and validate it by comparing TCP throughput distributions for model-generated traces against those for actual traces randomly sampled from field data.