Online Resource Auction for EAVN with Non-Price Attributes

Through offloading tasks to surrounding edge nodes, the edge-assistant vehicular network (EAVN) could provide faster and more efficient services. To promote the deployment of EAVN, we need a reasonable resource allocation scheme. Nowadays, there are few auction mechanisms in EAVN scenario. Moreover, the auction mechanism in other edge computing scenario has following limitations. Firstly, current works only focus on the static/offline auction and do not consider that users will join and leave the auction system at any time in EAVN. Secondly, current works that determine the winning buyers/sellers only based on the price do not consider the unique attributes of EAVN, such as poor communication quality and various task demands. We design an online auction scheme for EAVN, which could satisfy the dynamics of users in the auction system. Moreover, the proposed auction mechanism also considers the non-price attributes, such as location, reputation, and computing ability, when constructing the matching between buyers and sellers. To verify our work, we simulate EAVN using a vehicular network simulator. Experimental results show that the proposed mechanism could meet the properties of computational efficiency, individual rationality, budget balance, and truthfulness.