Optimization of Caching Update and Pricing Algorithm Based on Stochastic Geometry Theory in Video Service

In order to meet the growing needs of vehicle users for high-quality video experience, it can be used caching technology and transcoding technology to meet the needs of vehicle users. However, due to the complexity of the practical scene, when improving the service quality of vehicle users, it is necessary to consider the mobility of vehicle users and the utilization of network resources (caching, base station computing resources, backhaul links, etc.). In order to deal with the impact of vehicle mobility and network resource usage on the acquisition of video segments by vehicle users, this paper not only takes vehicle mobility into full account in mathematical modeling, but also proposes caching update algorithm and pricing algorithm. Firstly, considering the transcoding between different versions of video, the base station takes into account the value of energy consumption when caching video segments. Then, according to the different use of caching, base station computing resources and backhaul links by vehicle users, a pricing algorithm of network resources is proposed to improve the flexibility of network resource utilization. Finally, the mathematical model is optimized by convex optimization theory, and the influence of caching update algorithm on caching gain and the impact of pricing algorithm on network resource utilization are shown through simulation. The simulation results show that the total gain, caching gain, transcoding gain and flexibility of network resource utilization are improved significantly.