abstract
- © 1999-2012 IEEE.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.