Computing Resource Trading for Edge-Cloud-Assisted Internet of Things

Abstract

Optimal computing resource allocation for edge-cloud-assisted Internet of things (IoT) in blockchain network is attracting increasing attention. Auction is a classical algorithm which guarantees that the computing resources are allocated to the buyers of the computing resource. However, the traditional auction algorithm only guarantees the revenue gains for the sellers of the computing resource. How to guarantee the seller and the buyer of the computing resource when both are willing to trade and moreover, bid truthfully, is still an open problem in computing resource trading for edge-cloud-assisted IoT. In this paper, we introduce a broker with sparse information to manage and adjust the trading market. We then propose an iterative double-sided auction scheme for computing resource trading, where the broker solves an allocation problem to determine how much computing resource is traded and designs a specific price rule to induce the buyers and sellers of the computing resource to submit bids in a truthful way. Thus, hidden information can be extracted gradually to obtain optimal computing resource allocation and trading prices. Hence, the proposed algorithm can achieve the maximum social welfare meanwhile protecting the privacies of the buyers and the sellers. Our theoretical analysis and simulations demonstrate that the proposed algorithm is efficient, i.e., it achieves the maximum social welfare. In addition, the proposed algorithm can provide effective trading strategies for the buyers and sellers of the computing resource, leading to the proposed algorithm satisfying incentive compatibility, individual rationality, and budget balance.