Abstract
AbstractRecent years have witnessed Food-as-a-Service (FaaS) facing challenges in delivery pricing. FaaS platform collects orders from restaurants and distributes them to delivery man (DM). The fairness of the pricing and distribution have raised attention. To improve the fairness of FaaS delivery order pricing and allocation, it is critical to design a trading system with a better order distribution rule and pricing model. This paper proposes a trading system with a fair pricing model based on the edge computing system. The Stackelberg model, a second-order game model, is deployed on the edge computing system for pricing. And a smart agent algorithm based on Deep Reinforced Learning (DRL) is used for optimization. The system realizes a balance of utilities of both restaurant and DM, and it also helps the DM supply meets the spatiotemporally dynamic demands. The results indicate that the system will carry on a fair and win-win FaaS delivery trading. The verification result shows the stability of Nash equilibrium in practice and proves that our system helps build a balance between utilities of restaurant and DM. Moreover, the simulation result illustrates the system’s stability and real-time response performance, and the transaction result indicates that our system helps improve market fairness.KeywordsStackelberg gameDynamic pricingEdge computing
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