Research On Data Acquisition Mechanism Of WSN Based On UAV Assisted

In the Wireless Sensor Network（WSN）,data is traditionally forwarded to the fusion center by multi-hop routing.Too much data redundancy results not only in more energy consumption,but also in a lower data transfer rate.In addition,in harsh or damaged surface conditions such as hills or disaster areas,infrastructure deployment is also difficult.In recent years,Unmanned Aerial Vehicle（UAV）has received extensive attention due to its flexible deployment,low cost,and high maneuverability.Using UAV as a mobile data collector can realize reliable and energy-saving data transmission,which can effectively solve the problem of lack of communication resources in the terrestrial network.In addition,considering that the limited battery capacity of UAV is also the main factor restricting the performance of WSN,and due to the high mobility of UAV,it will lead to dynamic changes in the channel between the UAV and the sensor,so the flight trajectory of UAV needs to be reasonably optimized to achieve more efficient data transmission.Based on the practical application requirements of WSN,this research proposes two data collection mechanisms based on single UAV and multi-UAV,and designs a trajectory planning algorithm to optimize the trajectory of UAV,so as to achieve efficient data collection in the target area.Firstly,an efficient and energy-saving data collection mechanism is designed for the needs of sensor data collection in the regional deployment scenario of a single UAV in this research.A distributed clustering algorithm based on center bias is proposed to select the Cluster Head（CH）,so that UAV can search the CH position according to the proposed algorithm and optimize the data collection position.According to the obtained data collection position,an improved genetic algorithm is designed to optimize the UAV data collection trajectory and minimize the UAV flight time,so as to meet the needs of low energy consumption.Experimental results show that the proposed data acquisition mechanism outperforms traditional single-UAV data acquisition schemes in terms of energy consumption,scalability,control overhead,latency,and load balancing.The research further extends the application scenario to the wide-area UAV cluster coverage area to achieve more efficient data collection,and proposes a multi-UAV-assisted WSN Data collection Time Minimization Scheme（DTMS）.DTMS considers multiple constraints such as UAV speed,energy threshold,and SN data volume and available energy,and minimizes the task completion time of all UAVs by jointly optimizing UAV trajectories,SN association mechanisms,and the acquisition time of each UAV.Since this problem is a non-convex optimization problem,it is difficult to solve.To this end,the research considers the two data acquisition modes of UAV hovering and flying,and transforms the non-convex problem into a convex optimization problem through model construction based on slack variables.Iterative algorithms based on alternating optimization and successive convex approximation are proposed to solve the problem of secondary convex optimization.The results show that the multi-UAV data acquisition scheme in this paper shortens the task completion time compared with the baseline scheme.