Research On UAV Relay Control Forwarding Strategy Based On Mobile Edge Computing

Mobile edge computing technology and UAV communication technology are the key technologies in the fifth generation of communication.UAV communication based on mobile edge computing has become one of the current research hotspots.The UAV has task forwarding and calculation functions.The UAV relay control forwarding strategy can selectively forward or compute the UAV task,thereby reducing the transmission delay of the task,balancing the network load,and extending the life of the network.Therefore,the research of UAV relay control and forwarding strategy is of great significance,so this thesis proposes a UAV relay and forwarding strategy and a load balancing mechanism based on multi-attribute decision-making.The existing UAV communication network only forwards or calculates tasks uniformly,and does not make full use of the UAV’s own computing advantages,which results in large task transmission delays and high energy consumption.To solve this problem,this thesis proposes a UAV relay control forwarding strategy.This mechanism first builds a network lifetime model and transforms it into a problem of minimizing energy consumption,which jointly optimizes the location of the UAV,the user’s task transmission power,and the task transmission path to maximize the user’s network life.Secondly,in view of the high complexity of the solution caused by the non-convexity of the minimum energy consumption problem,this thesis divides it into three sub-problems and uses the block coordinate iterative algorithm to solve them to obtain the optimal UAV position,mission transmission mode and task transmission power.The simulation results show that this mechanism can effectively reduce the energy consumption of task transmission and effectively extend the life of the network.In view of the existing load balancing methods in the UAV communication network only use the load as the task unloading index,which leads to the low timeliness of task unloading and the problem that the UAV task processing type does not match the receiving task during the task unloading process.A load balancing mechanism based on multiple attribute decision making is proposed.The mechanism first builds a task offloading model,which combines the task transmission type and delay,UAV load and power and other factors to transform the load balancing problem into a multi-attribute decision-making problem.Secondly,use the deviation maximization algorithm to solve the multi-attribute decision-making problem and obtain the weights of influencing factors.Finally,a load balancing method based on multi-attribute decision-making is proposed,and the optimal UAV node is selected for task offloading.Simulation results prove that this mechanism can effectively balance network load and improve network stability.