Efficient Fuzzy based UAV Positioning in IoT Environment Data Collection

Abstract

Wireless networks can be considered one of the key features of Internet of Things (IoT), and the rise of IoT, has helped wireless networks to be improved and developed immensely. This improvement has increased QoS, data rate, transmit range, etc. The use of Unmanned Aerial Vehicles (UAVs) as Flying Base Stations (FBS) are growing in wireless networks specially in IoT environments. FBSs are a cost-effective and rapid way that can be used in areas which are difficult to access or there are no chances to build a fixed BS. The inherent characteristics of drones such as high mobility and presence of Line of Sight (LoS) in their connection has increased their efficiency when used as FBS, but one of the main challenges is the optimal placement of drones as BS in such a way that full coverage of sensors and actuators is provided to guarantee the demanded service. In this paper, the efficient placement of drones as BSs is modeled in the form of an optimization placement (OP) problem. The objective of this approach is to minimize the number of required UAVs and the distance of the drones from the cluster points while the sensor positions are accessible, keeping in mind the limitations of backhaul. We are using fuzzy-based clustering to find the candidate cluster heads. Finally the results shows that a proper parameter of fuzzy-based clustering algorithm can significantly improve the results of the optimization problem.