This paper presents an approach to alleviating the server-client communication bottleneck in collocated multi-user virtual reality (VR). Instead of transmitting unique packets to each client, the system multicasts the same packets to all users, combining packetization, visibility-aware prioritization, and lightweight acknowledgments to ensure efficiency and fairness. To enable rapid scene completion, the environment is partitioned into independent fixed-size packets that can be decoded immediately upon arrival, and transmission order is guided by precomputed visibility footprints. Scalability is achieved through repeated multicast until compact bitmap acknowledgments confirm reception, keeping communication cost mostly independent of the number of clients. A controlled study with 23 participants in groups of 7 and 16 showed that this method reconstructs environments several times faster and with fewer missing parts than a conventional unicast TCP-based approach. These findings demonstrate that multicast transmission over commodity Wi-Fi can support large collocated VR groups.

Immersive virtual reality (VR) experiences require transmission and rendering of large-scale 3D content, often represented as point clouds or polygon meshes. Unfortunately, existing networked VR systems often fail to fully exploit the flexibility of VR data representations. To address this problem, we propose a cross-layer design that elevates a network data unit to a usable rendering unit for VR applications. Our aim is to bridge the gap between networks and applications in order to enhance visual quality, especially over constrained and variable networks. Our approach, Rendering Unit that is Network-aware (RUN), with two variants, RUN-Packet and RUN-Hybrid, includes mechanisms to effectively utilize network data units when encoding, transmitting, decoding, and rendering. Specifically, we develop additive detail refinement mechanisms and address streaming challenges such as head-of-line (HoL) blocking. We prototype our system in Unity 3D and evaluate it using synthetic network environments and real network traces. Our results with both static and dynamic point clouds demonstrate that RUN significantly reduces stalls and delivers smoother frame updates, enhancing visual quality.

The increasing popularity of video streaming and conferencing services have altered the nature of Internet traffic. In this paper, we take a first step toward quantifying the impact of this changing nature of traffic on the Quality of Experience (QoE) of popular video streaming and conferencing applications. We first analyze the traffic characteristics of these applications and of backbone links, and show how simple multipath routing may adversely impact application QoE. To mitigate this problem, we propose a new routing path selection approach, inspired by the TCP timeout computation algorithm, that uses both the average and variation of path load. Preliminary results show that this approach improves application QoE by on average 14% and packet latency by 11% for video streaming and conferencing applications, respectively.1