To introduce blockchain technology to the mobile internet and Internet of Things, offloading proof-of-work tasks to edge computing nodes is considered an effective solution. Among these solutions, pricing edge computing resources through auctions has been widely accepted as a simple and efficient method. However, in these auctions, it is difficult to identify bid-rigging behavior by users, and the lack of technical means to avoid such behavior can results in a loss of revenue for edge service providers (ESPs). In this study, we first model the optimal bid-rigging mechanism in a mobile blockchain edge computing resource auction. Then, we introduce an auction method that an ESP can use to prevent the bid-rigging strategy in resource auctions. Finally, we propose a solution for the optimal reserve price of the SA (simulated annealing) algorithm, which calculates the optimal reserve price according to bidders’ willingness to pay and the number of bid-rigging participants to improve the revenue of the ESP. Through experiments, it is verified that the proposed method meets the requirements of IR (individual rationality) and IC (incentive compatibility) in resource allocation, and effectively impacts of the number of bidders who adopt a bid-rigging strategy in auctions on ESP revenue. Furthermore, the efficiency and effectiveness of the algorithm are analyzed using data. When the cooling coefficient is less than 0.95, the time complexity of the algorithm is . Using this algorithm to conduct auctions can increase revenue by approximately 2%, requiring the ESP to pay only a small computational cost.