Maximizing the Capacity of Edge-Caching Networks With User-Content Evolution Relationship

System capacity is an important metric for evaluating the performance of edge-caching networks. In most previous studies, the caching content was assumed to remain unchanged in a base station. Hence, the requested probability for each content was treated as stable; In fact, both the number of content and users can change overtime, which impacts the system performance. This article firstly constructs a new user-content evolution model to infer such performance changes, and analyzes the number of links between users and content (i.e., degree). Then, the requested probability of the content and the optimal copy number are calculated by using the content degree. Next, the minimum average transmission distance of the content and system capacity under the cache scheme are given. Finally, a user-content time-varying system is simulated. The results show that the proposed model can characterize the evolution relationship between users and content and achieve better performance in terms of system capacity.