Joint Optimal Allocation of Wireless Resource and MEC Computation Capability in Vehicular Network

Numerous applications of vehicles are computation-intensive and delay-sensitive. In order to deal with the problem caused by limited wireless and computation capability in the Mobile Edge Computing (MEC) enabled vehicular network, a Joint Optimization of Wireless and Computation Allocation (JOWCA) algorithm is proposed to minimize global delay of MEC-enabled vehicular network. The JOWCA algorithm consists of vehicle-to-vehicle (V2X) matching and MEC computation capability allocation. In the V2X matching, a Graph-based Interference Cancellation (Graph-IC) scheme is proposed to allocate Resource Blocks (RBs) for vehicle-to-infrastructure (V2I) links and vehicle-to-vehicle (V2V) links to mitigate co-channel interference. The Graph-IC contains an adaptive interference threshold modified Heuristic Clustering (HC) algorithm and Hungarian algorithm. In the MEC computation capability allocation, the optimal solution of V2I link offloading ratio and MEC computation capability scheduling are obtained by applying Karush-Kuhn-Tucker (KKT) condition. Simulation shows that the proposed scheme can effectively reduce the global delay of the MEC-enabled vehicular network.