  Roadside units (RSUs), which have strong computing capability and are close
to vehicle nodes, have been widely used to process delay- and
computation-intensive tasks of vehicle nodes. However, due to their high
mobility, vehicles may drive out of the coverage of RSUs before receiving the
task processing results. In this paper, we propose a mobile edge
computing-assisted vehicular network, where vehicles can offload their tasks to
a nearby vehicle via a vehicle-to-vehicle (V2V) link or a nearby RSU via a
vehicle-to-infrastructure link. These tasks are also migrated by a V2V link or
an infrastructure-to-infrastructure (I2I) link to avoid the scenario where the
vehicles cannot receive the processed task from the RSUs. Considering mutual
interference from the same link of offloading tasks and migrating tasks, we
construct a vehicle offloading decision-based game to minimize the computation
overhead. We prove that the game can always achieve Nash equilibrium and
convergence by exploiting the finite improvement property. We then propose a
task migration (TM) algorithm that includes three task-processing methods and
two task-migration methods. Based on the TM algorithm, computation overhead
minimization offloading (COMO) algorithm is presented. Extensive simulation
results show that the proposed TM and COMO algorithms reduce the computation
overhead and increase the success rate of task processing.
