🤖 AI Summary
This study addresses the multi-tier energy consumption challenge in VR remote rendering systems operating over 5G networks. To tackle this, we propose and experimentally validate a software–hardware co-designed, fine-grained energy monitoring framework. Computation-intensive rendering tasks are offloaded to cloud–edge collaborative nodes; VR renderers are deployed as Cloud-Native Network Functions (CNFs); and Media over QUIC (MoQ) is integrated to enable end-to-end energy measurement across the 5G core network, radio access network, user equipment, and cloud rendering nodes. For the first time, we quantitatively characterize the nonlinear trade-offs between VR performance metrics—including end-to-end latency, video bitrate, and frame rate—and the energy consumption of individual network components. The results provide reproducible empirical evidence and a methodological foundation for designing energy-efficient 5G networks and optimizing the sustainability of immersive services.
📝 Abstract
This paper investigates the energy implications of remote rendering for Virtual Reality (VR) applications within a real 5G testbed. Remote rendering enables lightweight devices to access high-performance graphical content by offloading computationally intensive tasks to Cloud-native Network Functions (CNFs) running on remote servers. However, this approach raises concerns regarding energy consumption across the various network components involved, including the remote computing node, the 5G Core, the Radio Access Network (RAN), and the User Equipment (UE). This work proposes and evaluates two complementary energy monitoring solutions, one hardware-based and one software-based, to measure energy consumption at different system levels. A VR remote renderer, deployed as CNF and leveraging the Media over QUIC (MoQ) protocol, is used as test case for assessing its energy footprint under different multimedia and network configurations. The results provide critical insights into the trade-off between energy consumption and performance of a real-world VR application running in a 5G environment.