Research On UAV-assisted Mobile Edge Computing Resource Allocation Model

In the new era of the Internet of Everything,terminal devices and latency-sensitive applications have exploded.In order to solve the problem of high transmission delay caused by the long data transmission distance of traditional cloud computing,mobile edge computing was born.By migrating the cloud computing platform（including computing,storage and network resources）to the edge of the network,it reduces the end-to-end delay of service delivery,explores the inherent capabilities of the network,and improves user experience.However,some Io T devices deployed in remote areas are inconvenient to communicate and obtain energy.In addition,there are a lot of idle computing resources in Io T that are not utilized,and Io T devices have unequal access to data offloading services.In this thesis,the research on the system model and algorithm of UAV-assisted mobile edge computing resource allocation is carried out as follows:（1）In order to solve the problem of inconvenient energy supply for Io T devices,a UAV-assisted communication relay and wireless energy transmission system model is designed.Most existing models only consider drones as communication relays to help mobile users forward data to base stations.The model designed in this thesis adds a wireless energy transmission module on the basis of the existing model to wirelessly charge mobile users.This improvement is of great significance in communication in disaster areas and remote areas.Based on this model,by optimizing the energy of different devices,data transmission time and UAV trajectory,the total upload data volume of the entire network in a limited time can be maximized.Since this problem is a non-convex optimization problem,it is difficult to solve.In this thesis,some methods are adopted to transform the problem into a convex problem,and the continuous convex approximation method is used to iterate.Numerical simulation verifies the performance of the algorithm,and has obvious advantages compared with the equal time allocation algorithm and the square trajectory algorithm.Through the results,we can analyze the conclusion that the UAV trajectory approaches the Io T device to obtain better channel conditions,the task execution time increases,and the total uploaded data volume increases accordingly.（2）The previous model only considers the UAV as a communication relay to transmit data to the mobile edge computing server for calculation.There are many idle Io T nodes in the network,and each Io T device has unequal opportunities to obtain offloading services.In response to these problems,we A UAV-assisted energy transmission load balancing mobile edge computing system model is designed.This model not only considers the unmanned aerial vehicle to assist busy Io T nodes to perform data unloading,but also adds idle nodes to assist in computing,which realizes the load balancing of wireless sensor networks and utilizes resources more fully.By optimizing the CPU frequency,data transmission time and UAV trajectory of different devices,the minimum upload data rate of all devices in a limited period of time is maximized,so as to ensure the fairness of each user’s access to UAV services.The problem is equivalently transformed,and the continuous convex approximation method is used to approximate it as a convex optimization problem to solve.The simulation results of the previous model are still valid.In addition,when the number of auxiliary nodes is insufficient,the fairness of Io T nodes to obtain data offloading services will be guaranteed.