An intelligent UAV based data aggregation strategy for IoT after disaster scenarios

Abstract

The study on data aggregation in Internet of Things (IoT) has drawn a great attention in recent years. Since a large-scale disaster could damage the entire communication network and cut off data aggregation completely, an Intelligent UAV based Data Aggregation Strategy, named (IDAS), is proposed for after disaster scenarios in IoT. Specifically, IDAS first employs an task distribution mechanism to achieve the trade-off between the aggregation ratio and the energy cost. Then, a deep reinforcement learning method is developed for UAV route design to perform corresponding task. Thus, all data are aggregated toward the rescue headquarter by UAV deployment. The simulation results indicate that IDAS has a higher aggregation ratio and a lower energy cost while compared with contemporary strategies.