Study On Energy-efficient Resource Allocation In Wireless Powered Mobile Edge Computing

With the rapid increasing of Internet service scenarios,how to solve the problem of high complexity and high energy consumption of mobile devices with limited computing,storage and battery resources remains a challenge.Mobile cloud computing(MCC)can leverage the vast amount of resources available in the cloud to provide elastic computing and storage capabilities to support resource-constrained mobile devices.However,the migration of tasks to the cloud will result in a number of data transmission and the corresponding transmission delay.It will affect the quality of service of the application,especially for some delay-sensitive industrial control applications.Therefore,mobile edge computing(MEC)has widely drawn attention to academia and industry.MEC enables the applications,services and content deployed locally with shorten distance through migrating the computing,storage and service capability to the edge of the network.Because the edge cloud server is close to the user,the MEC network can provide a service environment with ultra-low latency,high bandwidth and direct access to real-time network information.The main research content of this paper is how to achieve energy-efficient network resource allocation in multi-user MEC networks and wireless rechargeable communication networks both based on wireless power transfer.Firstly,we propose MEC network framework based on harvesting-then-offloading protocol,which adopts the time division multiple access(TDMA)mechanism to complete the computationally intensive tasks offloading of two typical users.From an overall perspective,we pay attention to maximize the total energy efficiency of all mobile users.From the perspective of user fairness,we aim to maximize the minimum energy efficiency of all users.Secondly,we proposed a wireless communication network based on wireless power transfer to achieve energyefficient communication of the transmitter/receiver.The main research contents and results of this article are summarized as follows:1.We consider the issue of user fairness with non-cooperative mechanisms and the energy efficiency of system with the cooperative communication mechanism.First,we characterize the user benefit function using energy efficiency and propose the minimum user energy efficiency problem(MMUEE)for user fairness.Secondly,in order to solve the ”double near-far” problem in the wireless power transfer network,we adopt a user collaboration scheme,which uses the near user as a relay to help the far user forward its tasks or applications.Then,we propose two time allocation optimization algorithms to achieve energy efficiency maximization for individual user and systems respectively.The simulation results show that our user collaboration scheme effectively solves the ”double near-far” problem and greatly improves the energy efficiency of the MEC system compared with the non-cooperative mechanism.2.We consider the energy efficiency optimization problem of transmitters in proposed wireless powered communication networks.Then,we give models describing to two phases,charging and information transmission,with the TDMA mechanism.We construct an energy efficiency optimization problem subject to maximum transmission power,minimum harvested energy and minimum Qos constraint.In particular,we propose an power/time allocation algorithm to maximize energy efficiency of the communication link.The simulation results show that the proposed optimization algorithm can converge quickly with different experimental parameters,which is expected for the practical system.In addition,we verify the effects of minimum Qo S and minimum harvested energy on energy efficiency of the communication link.