Logo
ScienceStack
Table of Contents
Fetching ...
Sign In

Experimental Studies of Metaverse Streaming

Haopeng Wang, Roberto Martinez-Velazquez, Haiwei Dong, Abdulmotaleb El Saddik

TL;DR

This paper investigates Metaverse streaming across four platforms (Vircadia, Mozilla Hubs, VRChat, and MR Virtual City) through real-world network traces to characterize protocol use, throughput, and latency. It identifies two-stage transmission (TCP for setup and UDP for streaming) and highlights significant latency and bursty traffic, especially with avatar loading and multi-user arrivals. To address these challenges, it proposes a remote rendering architecture evaluated on a campus network with HoloLens 2, showing substantial gains: 60 fps remote rendering versus 12 fps local, and reduced client-side resource needs while maintaining interactive fidelity. The study argues that remote rendering offers a practical path to scalable, high-quality Metaverse experiences and discusses complementary strategies like bandwidth prediction, adaptive streaming, and viewport-based transmission.

Abstract

Metaverse aims to construct a large, unified, immersive, and shared digital realm by combining various technologies, namely XR (extended reality), blockchain, and digital twin, among others. This article explores the Metaverse from the perspective of multimedia communication by conducting and analyzing real-world experiments on four different Metaverse platforms: VR (virtual reality) Vircadia, VR Mozilla Hubs, VRChat, and MR (mixed reality) Virtual City. We first investigate the traffic patterns and network performance in the three VR platforms. After raising the challenges of the Metaverse streaming and investigating the potential methods to enhance Metaverse performance, we propose a remote rendering architecture and verify its advantages through a prototype involving the campus network and MR multimodal interaction by comparison with local rendering.

Experimental Studies of Metaverse Streaming

TL;DR

This paper investigates Metaverse streaming across four platforms (Vircadia, Mozilla Hubs, VRChat, and MR Virtual City) through real-world network traces to characterize protocol use, throughput, and latency. It identifies two-stage transmission (TCP for setup and UDP for streaming) and highlights significant latency and bursty traffic, especially with avatar loading and multi-user arrivals. To address these challenges, it proposes a remote rendering architecture evaluated on a campus network with HoloLens 2, showing substantial gains: 60 fps remote rendering versus 12 fps local, and reduced client-side resource needs while maintaining interactive fidelity. The study argues that remote rendering offers a practical path to scalable, high-quality Metaverse experiences and discusses complementary strategies like bandwidth prediction, adaptive streaming, and viewport-based transmission.

Abstract

Metaverse aims to construct a large, unified, immersive, and shared digital realm by combining various technologies, namely XR (extended reality), blockchain, and digital twin, among others. This article explores the Metaverse from the perspective of multimedia communication by conducting and analyzing real-world experiments on four different Metaverse platforms: VR (virtual reality) Vircadia, VR Mozilla Hubs, VRChat, and MR (mixed reality) Virtual City. We first investigate the traffic patterns and network performance in the three VR platforms. After raising the challenges of the Metaverse streaming and investigating the potential methods to enhance Metaverse performance, we propose a remote rendering architecture and verify its advantages through a prototype involving the campus network and MR multimodal interaction by comparison with local rendering.
Paper Structure (20 sections, 11 figures)

This paper contains 20 sections, 11 figures.

Table of Contents

  1. Introduction
  2. Network Trace Case Study I: VR Vircadia
  3. Vircadia
  4. Experiment Setup
  5. Network Trace Analysis
  6. Network Trace Case Study II: VR Mozilla Hubs
  7. Mozilla Hubs
  8. Experiment Setup
  9. Network Trace Analysis
  10. Network Trace Case Study III: VRChat
  11. VRChat
  12. Experiment Setup
  13. Network Trace Analysis
  14. Challenges in Current Metaverse Streaming
  15. Potential Solutions
  16. ...and 5 more sections

Figures (11)

  • Figure 1: Users in the Vircadia are having a conversation.
  • Figure 2: Packets captured after uses enter the Vircadia Metaverse. The data stream is divided into the UDP uplink stream and the UDP downlink stream.
  • Figure 3: DL and UL network throughput of Vircadia. U1 and U2 indicate the throughput of user1 and user2, respectively.
  • Figure 4: Users in the Mozilla Hubs are having a seminar.
  • Figure 5: Network throughput of three users in Mozilla Hubs. (a) UL throughput (b) DL throughput.
  • ...and 6 more figures