Virtual Forces based UAV Fleet Mobility Models for Air Pollution Monitoring

One of the main issues in UAVs networks design is how nodes are relocated in order to meet the desired performance objectives. In this work, we propose two UAVs fleet mobility models based on the Virtual Forces Algorithm (VFA). The application context we are interested in is the air pollution surveillance over wide areas. The first model is a centralized variant where all computations are performed in a central ground base station. While the second model is a distributed version where each node takes its own decision in collaboration with its neighbors. We evaluate our models performances and we compare them with state of the art solutions using a real data set of air pollution concentrations and according to three main metrics: the maximal estimation error, execution time and communication cost.