Energy consumption assessment of a Virtual Reality Remote Rendering application over 5G networks

TL;DR

The paper tackles the energy costs of VR remote rendering over a real 5G testbed by deploying a dual energy monitoring framework that combines hardware-based power meters with software telemetry in a Kubernetes environment. It demonstrates a MoQ-based VR renderer running as a CNF on the edge, enabling end-to-end energy assessment across the 5G Core, RAN, and UE. Key findings show that hardware monitoring captures higher and more variable energy use than software methods, and that the edge component dominates energy consumption during remote rendering, with only minor variations caused by bitrate changes. These insights guide energy-aware deployment and highlight the need for improved software models and real-time orchestration to balance performance and energy efficiency in CNF-enabled XR 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.

Figures (8)

• Figure 1: Dual energy monitoring architecture.
• Figure 2: Hardware-based energy monitoring.
• Figure 3: Software-based energy monitoring
• Figure 4: Architecture of the 5G network testbed.
• Figure 5: Remote renderer with MoQ transmission to Web player.