Research For Strategy Of Wireless Powered Mobile Edge Computing Offloading

In response to the explosive growth in the demand for applications from a large number of Io T devices,cloud computing allows mobile devices to offload computationally intensive tasks to resource-rich remote cloud data centers,because most mobile devices are computationally and energy limited.However,the inherent disadvantage of cloud computing is the long distance transfer from mobile devices to remote cloud centers,which results in high latency and energy consumption of mobile devices.In order to solve this problem,edge computing has been proposed as a promising example,where the computing function is implemented at the network edge(such as base stations and access points),thereby greatly reducing the transfer distance.As a result,edge computing guarantees low latency and low energy consumption to facilitate real-time applications.Recently,mobile edge computing has been regarded as a key technology to realize the Internet of Things and the fifth generation(5G)mobile communication system.On the other hand,how to provide a sustainable and cost-effective energy supply for large computing-intensive devices is another challenge facing the Internet of Things.Wireless power transfer(WPT)based on radio frequency(RF)signals provides a viable solution by deploying dedicated energy transmitters to transmit energy wirelessly.Therefore,the combined design of mobile edge computing(MEC)and wireless energy transfer(WPT)has been recognized as a promising technology in the era of the Internet of Things,which can provide enhanced computing power and sustainable energy supply for large low-power wireless devices.The first research object of this paper is the optimization of mobile edge computing offloading based on wireless power supply.The multi-antenna access point of the integrated mobile edge computing server has computing resources and communication resources.Several local devices search for an available access point with a mobile edge computing server in the surroundings.After receiving energy from the access point,it first divides the calculation The task is divided into two parts,one part is completed by local calculation,and the other part is completed by offloading the calculation to the access point.A mathematical model for jointly optimizing the energy transfer power and transfer time of the access point,user task offload time,calculation task division,and minimizing the total energy consumption of the system is established and solved with a unique alternating optimization algorithm.Finally,combined with the actual selection of parameters for numerical simulation experiments,and compared with the three basic schemes to verify the effectiveness of the scheme.The second research object of this paper is the wireless power supply cooperative computing system based on mobile edge computing.The design uses nearby idle wireless devices as auxiliary devices,uses these auxiliary devices to obtain wireless energy,and collaborates to perform computing tasks for active users.Specifically,this chapter develops an effective design framework that maximizes the user's computing rate within a given time block under the energy constraints of the user and collaborators.After establishing the corresponding convex optimization problem,the CVX toolbox is used to solve the problem,and the numerical simulation experiments under different experimental conditions are carried out.The numerical simulation results show that the proposed wireless edge cooperative computing scheme based on mobile edge computing has a significant performance gain compared to the benchmark scheme without such cooperation.