Research And Implementation Of Unmanned Aircraft Energy Consumption Optimization Mechanism For Wireless Sensor Network Data Collection

Data collection is an important research direction in the field of wireless sensor networks.The traditional collection methods based on fixed sink nodes and mobile sink nodes have obvious deficiencies.With the continuous maturity of UAV technology,data collection based on UAV has attracted extensive attention from academia.Limited to energy-carrying capacity of UAVs,most of the related research mainly focused on optimizing the energy consumption of UAVs by improving the network throughput or extending the network life cycle,but still faced the following challenges: on the one hand,distance-related energy consumption model is the mainstream in their research,which ignored the impact of flight speed and flight time on energy consumption.In the speed-related energy consumption model,the convex function relationship between flight power and flight speed is ignored;on the other hand,the existing work focuses on reducing the energy consumption of the sensor,lacking accurate flight control of the UAV,which can not effectively save UAV energy consumption.Therefore,it is necessary to model the UAV flight energy consumption to realize the UAV precise flight control,which has important theoretical significance for large-scale wireless sensor network data collection.For this reason,this paper first measured the UAV energy consumption and modeled through a lot of real-world flight tests.On this basis,different flight control strategies were designed for different sensor application deployment scenarios,so that the UAV can collect all the data in the wireless sensor network.Specific research results include:Firstly,for the simple application scenario of sensor deployment,this paper studied two modes of offline speed scheduling and online speed scheduling.In the offline scheduling mode,the "Slowest Segment First" algorithm is proposed and the optimality of the algorithm is proved;in the online scheduling mode,the online speed scheduling algorithm is proposed based on the offline algorithm.Experimental results show that the energy consumption of UAV flight based on this online algorithm does not exceed 110% of the minimum flight energy consumption;Secondly,For the complex application scenario of sensor deployment,this paper first designed a heuristic method to determine the collection order of the sensor,and then proposed a grid-based dynamic programming algorithm to determine the optimal flight of the UAV under this acquisition order.At the same time,a new method was designed to reduce the complexity of the dynamic programming algorithm,and proved the correctness of the pruning method.Experimental results show that the dynamic programming algorithm saves about 50% of flight energy consumption compared with hovering algorithm;Thirdly,A wireless sensor network data collection UAV energy consumption optimization system is designed and implemented,effectively validating the theoretical research work of this article.In short,this paper has conducted in-depth exploration of the optimization mechanism of UAV energy consumption for wireless sensor network data collection.The results of a series of simulation experiments and real-machine test of the UAV show that the relevant algorithms mentioned in this paper can precisely optimize the UAV’s flight energy consumption,which can provide a proven solution for collecting large-scale wireless sensor network data in practical applications,and can be further applied to industrial Internet,smart city construction,etc.field.