Edge Caching Placement Optimization for Improving User Experience

In recent years, the rapid expansion of short video services has led to a surge in internet traffic from mobile devices. Transferring a large volume of popular videos from centralized cloud servers to edge data centers or edge servers can incur significant expenses for these providers, highlighting the importance of a well-defined edge cache placement strategy. This paper explores into the cache placement problem of popular videos on short video platforms within edge environments, aiming to optimize user experience while minimizing cache deployment costs. Initially, we assess user experience holistically, considering both user preferences for popular videos and the latency involved in fetching requested content. Subsequently, we quantify cache placement expenses, accounting for both video transmission and storage costs. Ultimately, we formulate the placement problem as a single objective optimization problem maximizing overall user experience. A genetic algorithm is proposed to solve the problem. Simulation results indicate that, compared to traditional edge caching placement algorithms, our proposed strategy can reduce the average response time by 17% and improve the cache hit rate by 21%.