Optimal investment and pricing under uncertain resource supply in mobile edge computing
To alleviate the bottleneck of energy performance and meet the resource demand of more users,Mobile Edge Computing(MEC)combined with Energy Harvesting(EH)technology has been considered,in which EH technology facilitates sustainable computing in devices by capturing green energy from environment.Thus,a stochastic EH-MEC system is proposed to study the investment and pricing problem with uncertain resource supply.Users can either rent the inherent resources of MEC system or use the resources harvested by EH.Due to the time-varying nature of wireless environment,the energy collected by EH has the feature of uncertainty.Therefore,how to find a balance between MEC servers and users in MEC systems is a problem worth studying.To address this problem,a sequential decision-making method is proposed,and the interaction between users'investment and MEC server's resource pricing is formulated as a four-stage Stackelberg game.Then,backward induction is used to obtain Nash equilibrium for the users and MEC server under profit maximization.The MEC server optimal energy collection time,optimal leasing resources and pricing decisions has been demonstrated to follow a good threshold structure.Experimental results show that green resource acquisition can significantly improve the expected revenue of MEC servers and users.
mobile edge computingstackelberg gameenergy harvestingresource allocationinvestment and pricing