Truthful Mechanism for Computation Offloading and Resource-Sharing in Vehicle Computing

Rapid advances in technology have endowed intelligent vehicles with increasing computing power and rich perception abilities. In this paper, we address the problem of computation offloading and resource sharing in vehicle computing, where the vehicle provides computing and sensing resources to users. Since sensing devices capture the same data at any given moment, multiple users can simultaneously share the sensing resources of the same vehicle. Building on this, we propose a novel resource-sharing model that, while allocating computing resources only to users, allows users to monopolize or share sensing resources. By serving more users, this resource-sharing model results in savings on vehicle costs. The proposed mechanism comprises three types of auctions: one-to-many, many-to-one, and one-to-one. While the one-to-many auction allocates resources of one vehicle to multiple users, the many-to-one auction allocates resources of multiple vehicles to one user. The one-to-one auction, on the contrary, restricts allocation of resources of one vehicle to one user. While being truthful for both users and vehicles, this mechanism also contributes to individual rationality, budget balance, and consumer sovereignty. Finally, simulation results confirm the efficiency of the mechanism, which achieves high performance while facilitating additional utility.