Research on Content-aware Classification Offloading Algorithm Based on Mobile Edge Calculation in the Internet of Vehicles

With the rapid development of intelligent transportation, vehicle terminals generate a large number of data messages that need to be processed in real time. Competition on limited resources will increase the delay of message processing and energy consumption for terminal equipment. For the equilibrium relationship between delay and energy loss, this paper proposes a content-aware classification offloading algorithm based on Mobile Edge Computing (MEC). Firstly, the security message is prioritized according to the analytic hierarchy process, and then the optimal task unloading model of delay and energy loss is established. The relational model is established by assigning different weight coefficients to delay and energy loss. The Lagrangian relaxation method is used to transform the non-convex problem into a convex problem, which combines the subgradient projection method and the greedy algorithm to obtain the feasible solution. The performance evaluation results show that the algorithm improves the message processing delay and energy loss to some extent.