Modern mobile networks face a dynamic environment with massive devices and heterogeneous service expectations that will need to significantly scale for 5G. Edge computing approaches aim at enhancing scalability through strategies like computation offloading and local storage services, which will be fundamental to deploying large-scale distributed applications. Unlike the cloud, edge resources are limited, which call for novel techniques to handle large volumes of up- and downstream data under a changing environment. Being closer to data consumers and producers, a compelling view is to adopt context-aware techniques for enabling the edge to work with patterns from mobile traffic at different spatiotemporal scales. In this article, we overview the challenges and opportunities of edge storage from the perspective of context-awareness. We introduce a conceptual architecture to learn and exploit context information for enhancing uplink and downlink scenarios. Finally, we outline future directions for edge applications.

中文翻译：

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在边缘计算中为存储服务使用上下文感知

现代移动网络面临着一个动态环境，该环境具有庞大的设备和不同的服务期望，需要针对5G进行大规模扩展。边缘计算方法旨在通过诸如计算卸载和本地存储服务之类的策略来增强可伸缩性，这对于部署大规模分布式应用程序至关重要。与云不同，边缘资源是有限的，这就要求采用新颖的技术来在不断变化的环境中处理大量的上下行数据。与数据消费者和生产者之间的距离更近，一种引人注目的观点是采用上下文感知技术，以使边缘能够处理来自不同时空范围的移动流量的模式。在本文中，我们从上下文感知的角度概述了边缘存储的挑战和机遇。我们介绍了一种概念体系结构，用于学习和利用上下文信息来增强上行链路和下行链路方案。最后，我们概述了边缘应用程序的未来方向。