Double-Sided Auction based Data-Energy Trading Architecture in Internet of Vehicles

In the era of big data, the unprecedented growth of data has spawned the commercial application of data trading markets in the Internet of Vehicles (IoV), while also posing challenges to their economic feasibility. In this paper, we propose a data-energy trading architecture in IoV consisting of a market operator, electric vehicles (EVs), and roadside units (RSUs), where RSUs exchange energy for data collected by EVs, and the market operator solves the data/energy allocation problem to maximize social welfare. However, due to the information asymmetry and fragmentation in the market, it is difficult to determine the optimal data and energy trading amount. To this end, we design an iterative double-sided auction (IDA) mechanism to regulate the interactive behaviors among the trading entities, where the market operator gathers local information from RSUs and EVs, and gradually adjusts the submitted bids of two sides to reach the desired payment and reward rules. The proposed IDA-based data-energy trading algorithm is convergent and satisfies the economic properties of efficiency, incentive compatibility, individual rationality, and budget balance. Numerical results demonstrate the performance of the proposed IDA-based data-energy trading architecture in IoV.