Research On Resource Allocation Technology Of Shared Services Based On MEC

With the rapid development of mobile Internet,mobile network traffic is growing explosively.Users’ service requests bring the problems of insufficient edge service resources and users’ inability to obtain corresponding services in time.At the same time,the existing edge service resource allocation technology cannot meet the needs of users in mobile networks.In order to solve these problems,a feasible solution is to improve the ability of edge service resources in the network.Generally,the number of operators that can provide edge services can be increased.Based on this idea,the ability of edge service resources has been improved to a certain extent.However,the existing edge service resource pricing strategy and allocation strategy of operators still have some defects.The edge service price set by operators will be affected by other operators,which will lead to the reduction of operators’ income and users’ income.Based on the above observations,this paper proposes a new edge service resource model,which considers the resource allocation from the income of operators.Firstly,this paper studies the pricing process between two operators.Each server node deployed in the operator’s network can provide edge services to users through edge service provider(ESP),and the price of edge services provided by ESP is determined by its operator.Every device in the network that needs to obtain edge services is regarded as a user,such as smart phones,robots,drones and driverless cars.Users can obtain edge services by selecting an operator to access the network.Two operators in the network compete for users by setting the price of edge services,which can be regarded as a pricing game.The benefits of both sides of the game in this process are closely related to the edge service price,the degree of network congestion,the quality of service and the congestion sensitivity of users,which is specified as the utility function.In the process of game,the pricing strategy of each operator will be affected by the established price of the other party,and finally the game between operators will reach equilibrium.Then,according to the price in the equilibrium state,the edge service resource allocation strategy of the operator in the equilibrium state is obtained.Secondly,this paper studies the impact of service demand,service quality and users’ network congestion sensitivity on the equilibrium price.According to the performance of equilibrium price,the strategy of adjusting price to equilibrium state under different network conditions is given.In addition,the price adjustment strategy of the network in peak hours is solved.By selecting different time length frames to analyze the income changes of each role in the system,the price adjustment strategy is given to solve the pricing problem in peak hours.In this paper,the former can be referred to as "one or more operators",and the latter can only be referred to as "one or more operators" in the whole process of analysis.This paper analyzes the equilibrium results of the demand for edge service resources and the ability of edge service resources in the equilibrium of single-homing and multi-homing environments,and obtains the better choice between single-homing and multi-homing in different situations.