Research On Joint Resource Allocation And Computation Offloading Strategy For Mobile Edge Computing Network

In recent years,with the popularization of smart devices and the development of mobile Internet,new computation-intensive and delay-sensitive applications have emerged one after another.These applications need to consume a large amount of computation resources and storage resources.However,the mobile terminal is limited by physical size,battery capacity,storage space and computation power are very limited and can not meet the needs of such applications in terms of energy consumption and time delay.Therefore,how to provide users with a good computing experience under the condition of limited resources is facing a huge challenge.Mobile edge computing relies on computation offloading technology to offload all or part of the computation tasks of mobile terminals to edge servers with relatively sufficient computation resources and storage resources for execution,effectively solving the contradiction between increased computation requirements and limited equipment resources.At the same time,because the MEC server is deployed at the edge of the network closer to the user,it has lower latency than traditional remote cloud computing.In addition,different choices of servers in the task of computation offloading will produce different benefits.Therefore,it is of great significance to study offloading strategies in mobile edge computing networks.However,considering the actual mobile network edge computing,the computation resources and radio resources,the edge server storage resources are limited.Therefore,in the development of computation offloading strategy,how to efficiently allocate these resources to achieve greater benefits,become the problem need to be resolved.In response to the above problems,this article has carried out the following two aspects of work:(1)In a multi-user edge computing network,this paper optimizes the resource allocation strategy and the computation task offloading decision jointly.First,in order to achieve the goal of minimizing energy consumption of the mobile terminal,the establishment of optimization model.Secondly,because the target problem is NP-hard problem,it is difficult to obtain analytical solutions in polynomial time.Therefore,this paper analyzes the relationship between variables,transforms the objective function into two convex optimization problems,and obtains the semi-closed solution of the variables by solving the KKT condition.Finally,based on the dichotomy solve the optimal resource allocation policies and computation offloading strategy.The simulation results show that based on this scheme,the energy consumption of mobile terminals in the system can be effectively reduced.(2)For the multi-user and multi-edge server scenario,considering the limited wireless resources,storage resources and computation resources of the edge server,an edge server resource allocation algorithm based on multi-round Double Auction is proposed.This article first models the many-to-many computation offloading scenario as an auction model.Secondly,in view of the user's task execution cost and priority,a quotation strategy based on an auction compensation mechanism is designed.At the same time,a dynamic quotation strategy is adopted based on the limited communication resources,computation resources,and storage resources of the edge server.Finally,a resource allocation scheme based on a multi-round double auction algorithm is proposed to realize the efficient allocation of communication resources,computation resources,and storage resources in the mobile edge computing network,and maximize the benefits of edge servers.The simulation results show that the proposed algorithm enables the server edge higher returns.