Research On Incentive Mechanism Based On Contract Theory In Edge Computing Networks

With the rapid development of 5G applications and the Internet of Things,the massive increase of demand for delay sensitive computing poses more and more attention from academia and the industry of edge computing to computation offloading.However,due to the limited computing capacity and energy storage,it is hard for edge computing service provider(SP)to provide qualified services to a large number of users during peak load periods.With the improvement of computing capacity and energy storage of edge nodes(ENs),offloading tasks to edge computation nodes(ECNs)and charging from energy feeding nodes(EFNs)have become an effective solution for meeting the demand of computing service,so as to further increase the capacity of SP,reduce its costs and promote quality of service(QoS)and quality of experience(QoE).To effectively implement the above scheme and,SP needs to address the incentive issue for ENs.In reality,ENs are selfish and do not voluntarily share their own resources without appropriate compensation.Moreover,while ENs hope to obtain more compensation from the SP with the least shared resources,the SP is committed to compressing the cost.Therefore,how to balance the interests of both parties in the game and design an incentive mechanism that effectively incentivizes ENs at the minimum cost has become an important problem.However,some existing studies on computation offloading incentive mechanisms is conducted under the information symmetry.Such assumptions are not realistic.Even with considering information asymmetry,most of the current related work mainly focuses on incentives for ECNs,neglecting the potential energy shortages faced by SP,and failing to balancing the costs of energy feeding and computation offloading.Moreover,as a widely used transaction mode,forward transaction has the advantages of reducing the latency on trading decision-making and alleviating potential trading failures,etc.,but most of the existing incentive mechanisms on computation offloading are field oriented onsite transactions,and pay no attention on the risks caused by resource uncertainty and the risk attitude of ECNs.Therefore,they cannot be applied to forward transactions.To address the above problems,this paper focuses on the design of incentive mechanism for ENs in edge computing network.Considering the asymmetric information in transaction,the paper applies contract theory to analyze and model the behavior of SP and ENs,and design the optimal onsite and forward incentive mechanism.Our purpose is to increase the revenue of SP,promote onsite and forward transactions between the SP and ENs,and achieve the sharing of resource and benefit in edge networks.The main research contents are as follows.(1)A onsite incentive mechanism integrating computational offloading and energy feeding.Considering that SP can solve its own resource shortage through computing offloading and energy feeding,we establish the contracting models for computing offloading and energy feeding based on contract theory.Then,the task scheduling is used to balance the offloading and local computing,and further adjusting the incentive costs of computing offloading and energy feeding to reduce the total cost.After modeling the joint incentive problem and task scheduling as a cost minimization problem,we decouple and solve the problem by assuming that the scheduling scheme is known.Specifically,after the constraint simplification,we derive the optimal contract expression for computing offloading and energy feeding.Then,based on the optimal contract expression,we use an improved sparrow search algorithm(ISSA)to obtain the optimal task scheduling scheme.The simulation results verify the feasibility of the contract and demonstrate that the incentive mechanism has better performance than the comparison schemes in reducing costs,increasing potential computing capacity,and alleviating the supply pressure of power grid.(2)A risk-aware forward incentive mechanism for computation offloading.Firstly,the risk of node in forward transaction is modeled based on the resource uncertainty of the ECNs.Then,considering the differences in risk preferences of nodes,we establish a forward contract optimization problem based on contract theory to maximize the expected utility of the SP while controlling risks of ECNs.Finally,we analyze and simplify individual rationality(IR)constraints and incentive compatibility(IC)constraints,and provide an expression of the optimal forward contract.The simulation experiments have confirmed the feasibility and rationality of the forward contract,and it can effectively increase the utility of SP.