A Truthful FPTAS Auction for the Edge-Cloud Pricing Problem

Abstract

Edge computing, as a new promising paradigm of cloud computing, has gained widespread attention from both academia and industry. Tremendous progress in many aspects of edge computing has been achieved. However, the further development of edge computing also needs to be promoted by economic benefits, while few studies focus on the pricing in the edge-cloud scenario. In this paper, we propose and study the Edge-Cloud Pricing Problem, where a service provider provides both the edge and the cloud platform for executing computational tasks. In order to achieve the optimal social welfare, we design a truthful auction mechanism for the service provider, which is an FPTAS. Theoretical analysis shows that our auction mechanism yields the optimal allocation that maximizes the social welfare while violating the supply constraint by at most a factor of 1+ε. Extensive simulations validate our analysis and show that the auction mechanism performs better than the heuristic algorithms, i.e., with ε=1, the auction mechanism outperforms the greedy algorithm by 30.2% in average.