Mobile AR applications can thus augment the physical world with complex context-relevant virtual layers. Such applications are strongly dependent on solid network architectures to provide situational awareness (by connecting Mobile AR to the IoT world) as well as offloading the most computation-intensive operations to distant machines. Mobile AR traffic is much more constrained than tradition audiovisual flows, as it aims to provide a seamless experience through highly unstable wireless networks. 5GEAR aims at providing a reliable framework to meet Mobile AR constraints for 5G networks.
5GEAR project proposes a novel edge computing architecture to reduce latency, provide more stable network connectivity, and serve situational-awareness data to the application. This architecture will be divided in two layers, namely edge and cloud, in which autonomous edge nodes collect, pre-process and contextualize the data, while the cloud handles the most computation and storage intensive operations. A set of network and transmission layer protocol will complement this edge infrastructure to fully exploit the capabilities of 5G. In particular, we study how one can exploit multiple paths using predictive modelling to meet MobileAR constraints. These protocols will in turn interact directly with the application to determine the traffic priorities and ensure seamless service. We also design a robust and efficient security architecture for Mobile AR systems at the edge level, focusing on authentication and access control. In order to avoid overhead at the device level and reduce additional congestion at the central cloud, the security algorithms will be performed at the edge nodes, providing security as a service at the edge using 5G.
For the validation of the concepts developed within this project, 5GEAR will use the 5GTN deployed at University of Oulu campus. This network provides a carrier grade test network, with the necessary measurement and monitoring tools.