移动边缘计算缓存策略的挑战

Tanusha Bhuruth, A. Mungur, Sheeba Armoogum, S. Pudaruth
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引用次数: 1

摘要

随着智能设备和新应用程序的出现,无线网络流量正在经历指数级增长,因此,由于更高的延迟,应用程序需要更多的时间来响应。因此,最终用户的体验质量(QoE)会受到影响。为了缓解这一问题,需要将网络内容传送到网络边缘的新思路。为此,引入了移动边缘计算和缓存技术。然而,边缘节点的分散式设计、覆盖范围小、计算和存储容量有限,对移动边缘缓存的发展提出了挑战。本研究的目的是探讨移动边缘计算最新进展的意义,重点是数据缓存技术。我们强调边缘计算的缓存技术,它提供的不同优势以及随之而来的一些挑战。已经存在的一些最佳实践被认为可以解决5G网络中缓存的挑战。文献中提出的一个框架包括使用边缘节点对用户进行身份验证,同时实时预测和更新用户的内容需求。根据预测,通过使用高级优化技术确定要存储的最佳内容,可以减少用户的平均延迟。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Challenges in Caching Strategies for Mobile Edge Computing
With the advent of smart devices and new applications, wireless network traffic is experiencing exponential growth and, as a result, applications take more time to respond due to higher latencies. The Quality of Experience (QoE) for the end-users is, therefore, affected. To alleviate this problem, new ideas that carry network contents to the edge of the network are required. For this purpose, mobile edge computing and caching was introduced. However, the decentralized design of edge nodes, their small coverage, limited computing, and storage capacity pose challenges to the advancement of mobile edge caching. The purpose of this study is to explore the significance of recent advances in Mobile Edge Computing with focus on data caching techniques. We emphasize on the caching techniques of edge computing, the different advantages that it provides and also some of the challenges that come along with it. Some best practices that already exist have been considered to address the challenges of caching in 5G networks. One of the proposed frameworks in the literature consists of using an edge node to authenticate users while predicting and updating their content demands in real time. Based on the predictions, the users' average latency can be reduced by determining the optimal content that is to be stored through the use of advanced optimization techniques.
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