Research Of Computation Offloading And Resource Allocation Based On Game Theory For Mobile Edge Computing

With the development of the Internet of Things(IoT),mobile edge computing has rapidly become the focus of current research.It can process data closer to where it is produced,which meets more the delay-sensitive applications.However,due to the limited computing capacity of the edge server,an excellent offload and resource allocation scheme is needed.In this paper,the joint optimization of computation offloading and resource allocation for mobile edge computing is studied.In this paper,it is divided into two problems,the computation offloading problem based on the result of resource allocation and resource allocation problem.Aiming at computation offloading problem based on the resource allocation scheme.The traditional computation offloading scheme only considers the computation offloading problem in the Cloud,Edge and Terminal structure,but does not consider the attributes of the public and private clouds.In this paper,a novel computation offloading scheme is proposed,which considers the relationship between public cloud and private cloud,and uses public cloud as a supplement to private cloud resources.In this scheme,the insufficient computing power caused by the limitation of private cloud resources can be alleviated,and a two-layer Stackelberg game is established to solve the computation offloading problem.Moreover,the optimal strategies of each player are obtained,and the existence and uniqueness of the Nash equilibrium solution of the two-layer game are proved.The simulation results show that the feasibility of the computation offloading scheme based on the two-layer Stackelberg game is proved,and the computation offloading scheme based on the two-layer Stackelberg game is more efficient than the computation offloading scheme based on the single-layer Stackelberg game.Aiming at resource allocation problem.In order to solve the problem of solution space explosion of centralized resource allocation model and the problem of fast change of Mobile edge computing environment.This paper proposes an algorithm called AGGA(Adaptive Group Game Allocation Algorithm).In this algorithm,a large number of homogeneous tasks are solved by relatively simple mathematical programming,while the rest tasks are allocated by non-cooperative group game.In addition,this paper uses Long Short-Term Memory(LSTM)to predict the CPU usage,and adaptively adjusts the parameters according to the current CPU usage and predicted values.Finally,this paper carries out comparative experiments to prove that the algorithm AGGA is more fit the current environment,and proves that the algorithm AGGA is feasible and efficient.