Research On Secure Communication Strategy For UAV-Assisted Mobile Edge Computing Systems

With the popularization of smart devices,more and more computing resources are used to handle application tasks,and the limitation of computing power of devices has gradually become an unavoidable problem in communication systems.Mobile edge computing(MEC)technology can help Io T devices offload computationally-intensive tasks to the edge of the mobile network,reducing the computational stress on the device.However,in practical scenarios,static edge computing servers cannot be dynamically deployed according to the needs of mobile users.With the low cost and mobility of unmanned aerial vehicles(UAV),UAV equipped with edge computing servers can move to Io T devices.Nearby and establish a line of sight(Lo S)link to achieve efficient uplink and downlink offloading.Due to the broadcast characteristics of wireless communication,the tasks unloaded by users are likely to be acquired by nearby eavesdroppers,which may lead to potential eavesdropping risks.In order to ensure information security in edge computing networks,this thesis conducts research on physical layer secure communication.Since the on-board energy of UAV is limited,the efficient use of energy under the premise of completing tasks,that is,minimizing the energy consumption of UAV,is a problem worthy of study.In addition,if the UAV is used for malicious eavesdropping,its mobility makes the risk of information leakage greater.How to enhance the confidentiality of the system in the presence of aerial eavesdropping users is also a problem worthy of study.Aiming at these two problems,the main contents of this thesis are as follows.1.This thesis studies the energy strategy of UAV-MEC safety communication system.There are many users with limited resources in the system,and there are ground eavesdroppers near the users.In order to ensure safe task offloading for users,the MEC server is used to provide users with computing offloading resources.While the UAV helps the user to complete the target task,it is also necessary to ensure the security of the user’s communication link.Form a joint optimization problem about computational offloading,resource scheduling,and UAV trajectory.Under the constraints of task offloading,energy limitation,and information causality,the total energy consumption of the UAV is minimized.Since multiple optimization variables of the objective problem are coupled together,they cannot be solved directly by convex optimization algorithms.In this thesis,path discretization(PD)is adopted,and an algorithm based on successive convex approximation(SCA)and two-step alternating optimization is designed.The numerical simulation results show that the energy saving effect of this optimization scheme is better than other benchmarks.2.The thesis studies the secure communication of the UAV-MEC system for aerial eavesdropping.The UAV in the system is equipped with a MEC server to assist multiple users in completing the computing offloading task.It is assumed that there is an eavesdropping drone in the air to steal the user’s offloading information,and a jammer is introduced to jam two drones at the same time.Under this system,a joint optimization problem of user transmit power,resource scheduling and UAV trajectory is studied,which maximizes the user’s minimum security rate under the constraints of the user’s minimum security calculation and energy constraints.Since the multiple optimization variables of this problem are coupled together,it cannot be solved directly by a convex optimization algorithm.In this thesis,time discretization(TD)is adopted,and SCA technology and block coordinate descent(BCD)iterative optimization algorithm are used.The numerical simulation results show that the safety performance of this optimization scheme is better than other benchmark schemes.