Research On Distributed Renewable Energy Allocation And Price Decision For Data Collection In Mobile Edge Computing

Mobile Edge Computing(MEC)effectively alleviates the burden of the core network,deploying servers at the edge of the network to perform computing near the data source,resulting in greatly reduced latency for end-user service requests,which brings a better user experience.In the case of limited wireless spectrum resources,how to reduce the energy consumption and optimize the allocation of resources is an urgent problem to be solved.In this paper,a MEC green data collection model is studied,in which the MEC operator provides the radio access spectrum,then the edge node collects data and forwards to the edge processing node though the multi-level relay nodes powered by Renewable Power Supplier(RPS).The MEC operator decides the service price,then the RPS determines the initial energy storage and price strategy according to the service price.This thesis firstly uses the game theory method to model the game relationship between leaders and followers between the MEC operator and RPS as a dynamic Stackelberg non-cooperative game model.The operator's strategy is set the service price according to user's requirements.The energy supplier's strategy is to determine the green energy storage and price strategy at the relay node after the given service price.In order to solve the equilibrium solution,this thesis proposes a two-stage algorithm and divides the game into two phases.The first stage is that MEC operator provides spectrum access and make service price strategy.The second stage is deciding the energy storage and pricing based on service price.In this thesis,the energy storage and price equilibrium strategy of RPS at the relay node is firstly obtained.Then,the first stage equilibrium strategy is obtained according to the conclusion of the second stage.Meanwhile,this thesis further considers the simultaneous and sequential decision making scenes.Finally,the effects of two different strategies on the equilibrium strategy set are compared by theoretical analysis and numerical simulation.The proposed scheme makes a stable game equilibrium between the MEC operator and the RPSs.The storage allocation and energy price strategy acquired optimal and the MEC operator gain the biggest profit.The solution optimizes the allocation of energy in the green data collection network and improves energy efficiency(EE)and spectrum utilization(SE).