Performance Analysis And Optimization Of Mobile Edge Computing System Assisted By Device To Device Communication

With the rapid development of 5G technology,we have entered the era of the Internet of Everything.At the same time,the number of Internet of Things(Io T)devices is increasing exponentially,and they continue to work as functional nodes.Some common Io T devices,such as human body wearable devices,road condition monitoring modules,etc.,are limited by their own size,resulting in limited energy storage.How to achieve sustainable and low-energy communication and computing is one of the current research problems.At the same time,Due to the functional requirements of some Io T devices,some latency-sensitive and computation-intensive computing tasks need to be processed,and achieving low-latency computing is also a huge challenge at present.To this end,this paper adopts Device to Device(D2D)communication technology to assist Mobile Edge Computing(MEC)to make full use of the computing resources of idle user equipment in the Mobile Edge Computing system to transfer and reduce computing pressure.This paper focuses on the energy consumption and latency issues in different mobile edge computing scenarios.The specific research content of this thesis is as follows:(1)Aiming at the energy consumption problem of D2D-assisted WPT-MEC system,a joint optimization scheme of energy transmitter(ET)transmission power allocation and user computing task allocation is proposed.In the mobile edge computing system that uses ET to transmit energy to task users(TU)and resourcee users(RU),the computing tasks dynamically arrived by TU are divided into three parts,which are respectively passed through local and offloaded Go to the RU and MEC server for calculation.Under the causal constraints of user energy consumption and computing tasks,construct the energy consumption minimization problem of ET,deduce the closed expression of the optimal transmission power of ET,and transform the original optimization problem into a convex optimization problem of user weighted energy consumption and minimization,using KKT(KarushKuhn-Tucker)optimality condition and forward search algorithm to obtain the optimal user task allocation scheme for the transformed problem.The simulation results show that the introduction of D2 D communication and cache offloading strategies in the WPT-MEC system can effectively reduce system energy consumption.(2)Aiming at the time delay problem of the D2D-MEC system assisted by the Intelligent Reflecting Surface(IRS),the optimization of the user’s computing task allocation,transmission power allocation,system bandwidth ratio allocation and IRS phase shift matrix is proposed.Design.In the multi-user mobile edge computing system that introduces IRS,TU offloads computing tasks to MEC servers and multiple RUs for computing through direct links and reflective cascade links constructed by IRS.Under the constraints of user task allocation,maximum transmission power,system bandwidth allocation,and IRS phase shift matrix,the delay expressions of each part of the user are derived,and the system delay minimization problem is constructed,and the non-convex problem is divided into multiple sub-problems alternately Optimize,and deduce the closed expression of the user’s optimal task assignment and the optimal phase shift matrix of IRS.The simulation results show that the introduction of D2 D communication and IRS technology in the MEC system can effectively reduce the system delay.