  With the popularity of mobile devices and development of computationally
intensive applications, researchers are focusing on offloading computation to
Mobile Edge Computing (MEC) server due to its high computational efficiency and
low communication delay. As the computing resources of an MEC server are
limited, vehicles in the urban area who have abundant idle resources should be
fully utilized. However, offloading computing tasks to vehicles faces many
challenging issues. In this paper, we introduce a vehicular fog-edge computing
paradigm and formulate it as a multi-stage Stackelberg game to deal with these
issues. Specifically, vehicles are not obligated to share resources, let alone
disclose their private information (e.g., stay time and the amount of
resources). Therefore, in the first stage, we design a contract-based incentive
mechanism to motivate vehicles to contribute their idle resources. Next, due to
the complicated interactions among vehicles, road-side unit (RSU), MEC server
and mobile device users, it is challenging to coordinate the resources of all
parties and design a transaction mechanism to make all entities benefit. In the
second and third stages, based on Stackelberg game, we develop pricing
strategies that maximize the utilities of all parties. The analytical forms of
optimal strategies for each stage are given. Simulation results demonstrate the
effectiveness of our proposed incentive mechanism, reveal the trends of energy
consumption and offloading decisions of users with various parameters, and
present the performance comparison between our framework and existing MEC
offloading paradigm in vehicular networks.
