A Bayesian game-enhanced auction model for federated cloud services using blockchain
Zeshun Shi, Huan Zhou, Cees de Laat, Zhiming Zhao
Abstract
Industrial applications often require federated cloud services from multiple providers to improve reliability and flexibility. Traditional selection methods through auctions usually involve a centralized auctioneer to coordinate the auction procedure. Blockchain and smart contracts provide a decentralized mechanism to automate the cloud auction process; however, existing solutions fail in the selection of the most suitable providers and the violation detection of the signed auction agreements, which are also known as service-level agreements (SLAs). To tackle these problems, we propose an integrated auction model using Bayesian game theory and blockchain techniques. The proposed model is enhanced with two Bayesian Nash Equilibriums (BNEs); the first BNE enables the selection of cost-effective providers to construct the federated cloud services, while the second BNE ensures consistent and trustworthy monitoring of federated SLAs. Moreover, a timed message submission (TMS) algorithm is proposed to protect the auction privacy during the message submission phase. This paper validates the equilibrium results of two BNEs and implements the proposed model on the Ethereum blockchain. The analytical and experimental results demonstrate the feasibility, trustworthiness, and cost-effectiveness of our model.