面向5G/Beyond 5G的移动边缘缓存优化技术综述

随着移动设备和新兴移动应用的广泛使用，移动网络中流量的指数级增长所引发的网络拥塞、时延较大、用户体验质量差等问题无法满足移动用户的需求。边缘缓存技术通过对网络热点内容的复用，能极大缓解无线网络的传输压力；同时，该技术减少用户请求的网络时延，进而改善用户的网络体验，已经成为面向5G/Beyond 5G的移动边缘计算（MEC）中的关键性技术之一。围绕移动边缘缓存技术，首先介绍了移动边缘缓存的应用场景、主要特性、执行过程和评价指标；其次，对以低时延高能效、低时延高命中率及最大化收益为优化目标的边缘缓存策略进行了分析和对比，并总结出各自的关键研究点；然后，阐述了支持5G的MEC服务器的部署，并在此基础上分析了5G网络中的绿色移动感知缓存策略和5G异构蜂窝网络中的缓存策略；最后，从安全、移动感知缓存、基于强化学习的边缘缓存、基于联邦学习的边缘缓存以及Beyond 5G/6G网络的边缘缓存等几个方面讨论了边缘缓存策略的研究挑战和未来发展方向。

Review of mobile edge caching optimization technologies for 5G/Beyond 5G

With the widespread use of mobile devices and emerging mobile applications， the exponential growth of traffic in mobile networks has caused problems such as network congestion， large delay， and poor user experience that cannot satisfy the needs of mobile users. Edge caching technology can greatly relieve the transmission pressure of wireless networks through the reuse of hot contents in the network. At the same time， it has become one of the key technologies in 5G/Beyond 5G Mobile Edge Computing （MEC） to reduce the network delay of user requests and thus improve the network experience of users. Focusing on mobile edge caching technology， firstly， the application scenarios， main characteristics， execution process， and evaluation indicators of mobile edge caching were introduced. Secondly， the edge caching strategies with energy efficiency， delay， hit ratio， and revenue maximization as optimization goals were analyzed and compared， and their key research points were summarized. Thirdly， the deployment of the MEC servers supporting 5G was described， based on this， the green mobility-aware caching strategy in 5G network and the caching strategy in 5G heterogeneous cellular network were analyzed. Finally， the research challenges and future development directions of edge caching strategies were discussed from the aspects of security， mobility-aware caching， edge caching based on reinforcement learning and federated learning and edge caching for Beyond 5G/6G networks.