Dynamic Pricing for Resource-Quota Sharing in Multi-Access Edge Computing

Abstract

In this paper, we analyze resource allocation in Multi-Access Edge Computing (MEC) from the perspective of revenue and profit management. Current coarse-grained pricing and resource plans have not made full use of the extreme heterogeneity of computing usage levels across users in the Internet of Everything (IoE), leading to wastage. Some users would have excess un-utilized resource quota while others might have reserved insufficient resources. Therefore, we introduce a novel sharing economy-inspired business model, following the trend towards the decentralized provision and sharing of digital resources. In our model, a platform facilitates the sharing of excess resource quota among users, leading to a more efficient usage of resources. Based on our model, we design and analyse two dynamic pricing mechanisms for resource quota sharing, which maximizes the social welfare or profit of the platform respectively. In our dynamic pricing mechanisms, the platform coordinates the sharing of compute resource quota in real-time, without knowledge of users' payoffs or control over users' decisions. We prove the optimality and convergence of the proposed mechanisms, and provide simulations to illustrate the convergence and robustness of our mechanisms to changes in demand and supply, as well as provide insights under changes in exogenous conditions.