AI-Enabled Energy-Efficient Fog Computing for Internet of Vehicles

Future autonomous electric vehicles (EVs) are equipped with several IoT sensors, smart devices, and wireless adapters, thus forming an Internet of Vehicles (IoVs). These intelligent EVs envisioned to be a promising solution for improving transportation efficiency, road safety, driving experience. Vehicular fog computing (VFC) is evolving technology that allows vehicular application-related tasks offloaded nearby nodes process them quickly. A major challenge in the VFC system design energy-efficient task offloading algorithms. In this paper, we propose optimal algorithm maximizes expected reward function which derived using total energy time delay computation task. We use parallel formulate optimization problem as semi-Markov decision (SMDP). Bellman equation used value iteration (VIA) get scheme by selecting best action current state energy-based function. Numerical results show proposed outperforms greedy terms consumption.