Joint Wireless Resource and Computation Offloading Optimization for Energy Efficient Internet of Vehicles

The Internet of Vehicles (IoV) is an emerging paradigm, which expected to be integral component beyond-fifth-generation and sixth-generation mobile networks. However, the processing requirements strict delay constraints IoV applications pose a challenge vehicle units. To this end, multi-access edge computing (MEC) can leverage availability resources at network meet intensive computation demands. Nevertheless, optimal allocation challenging due various parameters, such as number vehicles, available resources, particular each task. In work, we consider consisting multiple vehicles connected MEC-enabled roadside units (RSUs) propose approach that minimizes total energy consumption system by jointly optimizing task offloading decision, power bandwidth, assignment tasks RSUs. Due original problem complexity, decouple it into subproblems block coordinate descent method iteratively optimize them. Finally, numerical results demonstrate proposed solution effectively minimize for numbers MEC nodes while maintaining low outage probability.