Computation Offloading and Resource Allocation for Vehicle-Assisted Edge Computing Networks With Joint Access and Backhaul

The edge computing utilizes vehicles as resources to assist in computational offloading can shorten the distance between users and computing servers, thereby improving the reliability of communication between them. In this paper, we investigate a Vehicle-assisted Edge Computing (VEC) model by jointly considering wireless access and backhaul links, and formulate an optimization problem that combines computational offloading and resource allocation, aiming at minimizing system delay. Further, the formulated problem is decomposed into two subproblems, e.g., computation offloading and resource allocation. In particular, we propose a new computational offloading approach that models the offloading decision for joint wireless access and backhaul as a potential game. The Nash equilibrium is guaranteed by the rational design of potential function, and the corresponding solution is solved by a backward induction method. On the other hand, the resource allocation subproblem is transformed from a nonconvex to a convex optimization problem based on equivalent transformation with successive convex approximation methods and finally derives the optimal solution satisfying Karush-Kuhn-Tucker (KKT) conditions. Simulation results show that the proposed algorithm have near-optimal performance and is superior to the state-of-the-art over a wide range of parameter settings.