Research On Mobile Edge Computing Offloading Assisted By Multiple UAVs In 3D Scene

The Internet of things(IoT)is expanding and driving the growing number of connected devices.To access the Internet of things on a large scale,edge computing servers are installed on cellular ground base stations(GBSs)with fixed geographical locations,which easily suffer from traffic overload of the end-user(EU)with high density and mobility.In recent years,unmanned aerial vehicle(UAV)is widely used to assist the mobile edge computing of the IoT.On one hand,due to the high mobility of UAV,it can establish an emergency communication network for places where the GBS cannot serve and provide reliable and flexible offloading services.On the other hand,due to the three-dimensional deployment characteristics of UAVs,high-quality communication channel can be established.However,most existing UAV researches focus on trajectory design to reduce offloading delay,which ignoring the variability of user distribution and the energy limitation of UAV and the impact of wall occlusion on the channel.Therefore,this thesis considers two realistic scenarios:1)scenic spots with slow movement and strong time-varying distribution of end-users,and 2)urban overpasses with fast movement of end-users and covered by bridges.Specifically,the main contents of this study are as follows:1.For the first scenario,we propose a novel UAV-assisted edge computing framework,named as HOTSPOT,which locates the UAV in 3D space according to the time-varying hot spot of user distribution and provides the corresponding edge computing offloading assistance to reduce the average delay in the target area.HOTSPOT is divided into two parts:in the first part,by formulating the UAV positioning problem into a maximum clique problem,a lightweighted deterministic algorithm is proposed based on stochastic gradient descent to search the optimal location of UAV.The second part,with the elaborate UAV position,HOTSPOT further gives an opportunistic offloading balanced scheme to reach low latency.Simulation results show that when the GBS load is 75%,HOTSPOT reduces the average offloading delay by 33%.When the GBS load reaches 90%,the average delay reduction is up to 80%.2.For the second scenario,we propose an energy-aware 3D-deployment of UAVs,named 3D-UAV for IoV with highway interchange to improve the average uplink rate with minimized UAVs.The basic idea is firstly to determine UAVs’ position on the horizontal plane and then adjust their flight altitude.Considering the channel gain over bridges,3D-UAV firstly uses a kmeans algorithm to divide vehicles into several clusters whose positions determine the plane position of UAVs.Then a stochastic gradient ascent algorithm is designed to optimize the flight altitude of the UAV aiming at maximizing the average uplink rate of transmission.Numerical results show that the proposed 3D-UAV can cover all vehicles on the highway interchange with the number of UAVs close to the theoretical lower bound.Meanwhile,it outperforms other methods in terms of the uplink rate and energy.