Wireless sensor network data collection by connected cooperative UAVs

Peng Wei, Quanquan Gu, Dengfeng Sun

Abstract: Wireless sensor network is a prevailing research topic in recent years. It is adopted in the scenario of monitoring environmental parameters, which is normally expensive or even impossible to monitor by human labor or other technologies. At the same time, another popular topic is Unmanned Aerial Vehicle (UAV), which is widely used in military, commercial and civilian activities. In this paper cooperative UAVs form a team to accomplish the data collection task on wireless sensor network, where the technologies in wireless sensor network and UAV are integrated together. We study the novel wireless sensor network data collection with UAVs by considering the cluster load balancing and the connectivity of UAVs. We implement an Iterative Balanced Assignment with Integer Programming (IBA-IP) algorithm for efficient UAV deployment and sensor assignment. The authors analyze the advantages of IBA-IP compared to the Iterative and Adaptive (ITA) algorithm developed in [1]. In order to approximate the performance bound, we solve the problem by applying the Genetic Algorithm (GA). Finally, simulation results are presented under different parameter settings and the performances of the IBA-IP algorithm and the Genetic Algorithm are evaluated.