Research On Computing Offloading And Resource Allocation Strategy Under 5G Heterogeneous Cellular Network

With the development of mobile Internet technology,mobile terminal equipment and data traffic grow rapidly,and a series of computation-intensive and delay sensitive applications are derived.However,due to the limited computing and storage capacity of mobile terminal devices,they cannot support computation-intensive and delay-sensitive applications.Therefore,mobile terminal devices need to offload complex computing tasks to cloud computing centers for execution to reduce service delays.However,offloading computing tasks to the cloud computing center will bring a lot of data transfer,cause congestion in the core network,and have a serious impact on the delay sensitive users.Mobile Edge Computing(MEC)technology,as a key technology in 5G,can alleviate network load,reduce transmission delay and improve user satisfaction by deploying MEC servers at the network Edge.In 5G heterogeneous cellular networks,users can offload compute-intensive and delaysensitive applications to MEC servers to solve their own computing power and battery capacity constraints.However,the introduction of computing and storage resources into the edge of the network by MEC technology will bring new problems,such as the complex situation of the edge of the network,the coexistence of multiple resources and different user demands.Therefore,it is necessary to formulate a reasonable resource management strategy according to the data size and delay demand of user tasks as well as energy consumption constraints,so that limited resources can provide services for more users while meeting user's needs.Many literatures have studied computing unloading and resource allocation under heterogeneous cellular networks,but they almost ignore the computing resources of idle devices in the network.By reasonably utilizing the computing resources of idle devices,we can provide better services for users.In this paper,computing unloading and resource allocation are studied in 5G heterogeneous cellular network,and computing resources of idle devices are fully considered.The specific research contents are as follows:(1)Resource allocation strategy based on Gale-Shapley algorithm in heterogeneous cellular networks.In heterogeneous cellular networks,considering the mobile user equipment limited battery capacity and computing resources,idle equipment,and deployed on a small base station of the difference of MEC server computing resources and the needs of different users are different,therefore,how to design the optimal resource allocation strategy,in order to achieve the purpose of make full use of resources and improve customer satisfaction,is a problem worthy of studying.In view of this,this paper proposes a three-tier resource allocation model under 5G heterogeneous cellular network.In order to make full use of the computing power of idle devices and obtain additional benefits for idle devices,the computing resources required by user devices can be provided by MEC servers deployed on small base stations or by idle devices.Considering the user task data size and latency requirements and user according to the task size and latency requirements for compensation,also considering the small base stations and idle equipment energy consumption and income,and then defines the system to maximize energy cost performance as the goal of multiuser resource allocation optimization,the final design a resource allocation algorithm based on matching game.Simulation results show that the proposed multi-MEC server multi-user resource allocation strategy can effectively reduce user service delay and improve system performance in heterogeneous cellular networks.(2)Research on joint computing offloading and resource allocation in heterogeneous cellular networks.In view of the limited computing resources of mobile user devices,which cannot support applications with delay sensitivity and complex computing requirements,and the problem of low transmission rate caused by limited communication resources at the edge of the network,this paper studies the computing unloading and resource allocation of multiple mobile terminal devices in heterogeneous cellular networks.In this paper,we consider users with poor quality of cell links at the edge of base stations and delay sensitive applications,who,in order to reduce transmission delay and energy consumption,offload computing tasks to idle user devices nearby for execution.Then considering the user's task execution delay and energy consumption,to minimize cost to customers as the goal,task execution will jointly calculate unloading and resource allocation problem formulation to mixed integer nonlinear programming problem,this problem is difficult to solve,thus presents a heuristic algorithm,the problem is decomposed into computing unload strategy and resource allocation problems.The subproblem of unloading strategy is solved by mathematical method.For the sub-problem of resource allocation,the preference of users and idle devices to each other is considered,and the matching game algorithm is used to solve the problem.Finally,MATLAB simulation experiments are used to verify the better performance of the proposed algorithm.