With the popularization of mobile terminals and the rapid development of mobile communication technology, many PC-based services have placed high demands on data processing and storage functions. Cloud laptops that transfer data processing tasks to the cloud cannot meet the needs of users due to low latency and high-quality services. In view of this, some researchers have proposed the concept of mobile edge computing. Mobile edge computing (MEC) is based on the 5G evolution architecture. By deploying multiple service servers on the base station side near the edge of the user’s mobile core network, it provides nearby computing and processing services for user business. This article is aimed at studying the use of caching and MEC processing functions to design an effective caching and distribution mechanism across the network edge and apply it to civil aviation express marketing. This paper proposes to focus on mobile edge computing technology, combining it with data warehouse technology, clustering algorithm, and other methods to build an experimental model of MEC-based caching mechanism applied to civil aviation express marketing. The experimental results in this paper show that when the cache space and the number of service contents are constant, the LECC mechanism among the five cache mechanisms is more effective than LENC, LRU, and RR in cache hit rate, average content transmission delay, and transmission overhead. For example, with the same cache space, ATC under the LECC mechanism is about 4%~9%, 8%~13%, and 18%~22% lower than that of LENC, LRU, and RR, respectively.

中文翻译：

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移动边缘计算技术在民航快递营销中的应用

随着移动终端的普及和移动通信技术的飞速发展，许多基于PC的业务对数据处理和存储功能提出了很高的要求。将数据处理任务转移到云端的云笔记本由于低延迟和高质量的服务无法满足用户的需求。有鉴于此，一些研究人员提出了移动边缘计算的概念。移动边缘计算（MEC）基于5G演进架构。通过在靠近用户移动核心网边缘的基站侧部署多台业务服务器，为用户业务提供就近的计算和处理服务。本文旨在研究利用缓存和MEC处理功能设计有效的跨网络边缘缓存和分发机制，并将其应用于民航快递营销。本文提出以移动边缘计算技术为核心，结合数据仓库技术、聚类算法等方法，构建基于MEC的缓存机制应用于民航快递营销的实验模型。本文的实验结果表明，当缓存空间和服务内容数量不变时，五种缓存机制中的LECC机制在缓存命中率、平均内容传输延迟、传输开销。比如同样的缓存空间，LECC机制下的ATC大概是4%~9%，8%~13%，