Research On Resource Scheduling Mechanism Of Mobile Edge Computing Based On Multi-UAV

With the development of information and communication technology(ICT),smart homes,wearable devices,and smart farms are becoming more and more popular in our daily life.An increasing number of computationally-expensive and delay-sensitive mobile applications,such as virtual reality,augmented reality,object detection,etc.,make them difficult to be executed by the mobile user equipment(UEs)due to their limited computing and energy resources.Fortunately,mobile edge computing(MEC)provides an effective solution to the above problem by deploying computing resources into network edge(e.g.,cellular base stations or BSs).In this case,UEs can offload their computing tasks to the edge servers for execution.However,in some special scenarios such as earthquakes,fires,and tsunamis,the network infrastructure could be damaged by natural disasters,or the computing and communication resources at the edge servers may not be adequate due to rush hours.Recently,the application of UAV has become increasingly widespread,the UAV-enabled system providing the solution to the problem mentioned above.Particularly,UAVs can serve as base stations to provide the computing services on demand.Although the computing resources carried by UAVs are limited compared with ground edge servers,multiple UAVs can be applied to add both flexibility and capacity.A Multi-UAV enabled MEC system is established in this background,a group of UAVs can carry micro MEC servers and micro base stations to help ground user equipment offload their computing tasks to the UAVs for execution.This paper aims to minimize the total time required for the UAVs to complete the UE generated computing tasks by jointly optimizing the 3D deployment and resource scheduling of UAVs.This paper first adopts a Line of Sight(Lo S)channel model.The UAV can improve the possibility of establishing Lo S to the ground UEs by taking advantage of the mobility of the UAVs.Although the formulated optimization problem is a mixedinteger nonlinear programming problem(MINLP),we can convert it to a second-order cone programming problem(SOCP)and develop a successive convex approximationbased algorithm to effectively solve it.The simulation results show that the joint optimization of the horizontal position and the vertical position of a group of UAVs can achieve a better performance than the traditional algorithms.This paper applies the Rician fading channel model to the Multi-UAV-enabled MEC system,and explores the problem of Multi-UAV deployment and its computational resource allocation under this condition.The formulated optimization problem is a mixed-integer non-convex programming problem(MINCP).This paper adopts the Block Coordinate Descent method and decomposes the problem into three subproblems.Then,the approximate solution of the optimization problem can be obtained by solving the three subproblems iteratively.The simulation results demonstrate the effectiveness of the proposed algorithm.