Research On A Three-dimensional Load-balancing Routing Algorithm For Business-driven UAV Group

Nowadays UAV has been not only widely used in military fields but in civilian area.On account of the high maneuverability,topological property and deployment,UAV is playing a more and more important role in disaster districts where the environment conditions change quickly and the base stations tend to be heavily destroyed.Consequently,how to achieve the communication transmission with low delay and high reliability is of great significance.At present,lots of researches on routing algorithms of UAV concentrate on two-dimension routing of traditional single business or some early popular intelligent algorithms.But these algorithms focus on optimizing the single indicator and their models tend to be 2D systems,so that they can hardly meet the requirements in disaster areas where the business is complicated.Moreover,only focusing on the single indicator tends to cause the congestion of nodes.In terms of these disadvantages,this article is aimed at designing a method which can choose the specific routing algorithm according to the information type to meet the requirements of the business and achieve the load-balancing.This article firstly put forward a double-layer UAV structure.By analyzing the location of the upper-layer UAV,we propose a UAV coverage model based on maximum probability of communication success to solve the communication problem of UAV in the covering blind area.The lower task level UAV group is divided into cubes.Based on the analysis of the maximum effective communication distance between unmanned aerial vehicles from point to point,the size of the cube is obtained.Labeling can help study the UAV network whose topology changes rapidly.Then we introduce the basic knowledge of traditional two-dimensional routing and swarm intelligence algorithm,and analyzes the advantages and disadvantages of different routing methods in terms of performance s such as time delay and link success rate.According to the Qo S indicators required by different business,this paper chooses to use fuzzy logic and ant colony algorithm to transmit the data of different services respectively,so as to realize the business-driven routing.In this paper,weight parameters are set to realize the selection of specific routes under different business through reinforcement learning nonlinear weighting,to balance the traffic load in the network and reduce the probability of network congestion.The simulation results show that the business-driven load balancing algorithm is suitable for the three-dimensional scene of multi-UAVs under multi-business state,and has remarkable effect on reducing network delay and link success rate.