Energy Efficient AR/VR Edge Processing: Architecture and Optimization - Azza E. A. Eltraify; Randa A. Thabit; Opeyemi O. Ajibola; Wafaa B. M. Fadlelmula; Ahmed A. M. Hassan; Ahrar N. S. Hamad; Abdelrahman S. Elgamal; Walter Z. Ncube; Harith S. Ibrahim; Mariam Elmirghani; Sanaa Hamid Mohamed; Louise Krug; et al. (IEEE Access)
This article introduces a server-centric cellular Passive Optical Network (C-PON) architecture to support the deployment of Augmented Reality (AR)/ Virtual Reality (VR) event viewing applications in edge data centers. The proposed architecture is compared with the state-of-the-art Spine-and-Leaf architecture. For fair comparison, we model production style environments based on both C-PON and Spine-and-leaf data center architectures. We developed a Mixed Integer Linear Programming (MILP) model with multi-objective function to optimize routing of AR/VR traffic on both C-PON and Spine-and-Leaf architectures. The multi-objective function considers minimizing power consumption and minimizing end-to-end delay within the network architectures. We compare hosting the AR/VR applications in C-PON and in Spine-and-Leaf in terms of the power consumption, the average delay in links, and the end-to-end delay per user. We also developed a heuristic algorithm to enhance the scalability enabling the optimization of complex and larger systems. The results show that C-PON can enable substantial savings in terms of power consumption compared to the state-of-the-art Spine-and-Leaf architecture.