Distributed Edge System Orchestration for Web-Based Mobile Augmented Reality Services

The emergence of edge computing and 5G networks has fueled the growth of mobile Web AR. Although efforts have been made to improve the edge system efficiency for Web AR applications, efficient edge-assisted mobile Web AR services remain technically challenging. This paper presents EARNet, a distributed edge system orchestration approach for mobile Web AR in 5G networks. The design of EARNet makes three novel contributions. First, EARNet manages the edge network dynamics with respect to user mobility and their Web AR service requests by employing landmarks and grid index based edge node localization mechanisms. Second, EARNet takes into account both request serving performance and offloading cost in managing workload balance and quality of service and leverages dynamic hash and max heap mechanisms for efficient Web AR service lookup and AR computations. Third, EARNet designs the service migration schemes by optimizing several performance factors, such as message efficiency, scheduling latency, request density and locality of mobile users and edge nodes, and accuracy of Web AR services after migration. Experimental evaluations are conducted using the real base station deployment data in the Melbourne Central Business District (CBD) area. The results shows the effectiveness of the EARNet edge orchestration approach compared to several baseline approaches.

Automated summary

This paper proposes EARNet, a distributed edge system orchestration approach for mobile Web AR in 5G networks. EARNet manages the edge network dynamics using landmarks and grid index based edge node localization mechanisms, considers both request serving performance and offloading cost, and leverages dynamic hash and max heap mechanisms for efficient Web AR service lookup and AR computations. Additionally, EARNet designs service migration schemes by optimizing several performance factors. Experimental evaluations demonstrate the effectiveness of EARNet compared to several baseline approaches.