Location Planning of UAVs for WSNs Data Collection Based on Adaptive Search Algorithm

Abstract

Unmanned Aerial Vehicles (UAVs) have been widely used in data collection, tracking and monitoring in wireless sensor networks (WSNs). By considering the three factors of sensor coverage, energy consumption and Quality of Service (QoS), the WSNs data collection problem is transformed into a location planning model for optimizing K-location of UAVs. Besides, an adaptive search algorithm contains two crucial methods are proposed to address this issue, form which one is the optimal matching method between sensors and UAVs, and the other is automatic location generation strategy of UAVs. Finally, analytical and simulation-based results show that the proposed algorithm has obvious advantages over the KMeans algorithm in location planning option of UAVs.