摘要
Addressing edge computing's economic issues is critical as we need to motivate edge devices as resource providers to devote their computing resources to the service. There are multiple users and resource providers in most edge computing service scenarios. The communication delays between users and providers are not the same since their physical distances are different. However, most existing works on edge computing regarding network economics adopt single market models that do not consider the influence of communication delay. Moreover, due to the high cost of deploying 5G ultra-dense small cells, barely a network operator can reach full network coverage. Users cannot rely on a single network, but existing multi-market models do not allow resource trading between different groups. Thus, in this paper, we propose a novel multi-market trading (MMT) framework to address these shortcomings. The framework combines the double auction at each group and a market selection game to enable the resource providers to participle in multiple auctions and analyze their behavior of choosing markets. Through extensive simulations using real-world datasets of vehicular networks, we show that the proposed framework can improve the social welfare by 14.45% and 36.74%, respectively, compared with classic multi-market and single market models.