基于随机几何理论的流行度匹配边缘缓存策略

异构网络边缘缓存机制是解决传统回程传输链路负载过大的可靠技术之一，但已有的缓存策略往往不能与被请求数据的流行度相匹配。为了解决这一问题，该文提出一种流行度匹配边缘缓存策略(PMCP)，该策略能够根据流行度参数匹配对应的文件缓存概率以最大限度提升通信可靠性并降低回程带宽压力。基站的平面位置通过随机几何建模，文件的被请求概率则通过齐夫分布建模。蒙特卡罗仿真结果表明缓存机制能够有效降低回程带宽压力，且所提出缓存策略的可靠性优于对比策略。

Popularity Matching Edge Caching Policy Based on Stochastic Geometry Theory

Edge caching mechanism for heterogeneous network is one of the reliable technologies to solve the excessive link load of the traditional backhaul mechanism, but the existing caching policies often can not match the popularity of the required data. To solve this problem, a Popularity Matching Caching Policy (PMCP) is proposed in this paper, which can match the corresponding file cache probability according to the popularity parameters to maximize communication reliability and reduce backhaul bandwidth pressure. The plane position of the base station is modeled by stochastic geometry theory. The results of the Monte Carlo simulation show that the proposed caching policy can effectively reduce the backhaul bandwidth pressure, and the reliability of the proposed caching policy is better than the comparison policies.