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A Networked Desktop Virtual Reality Setup for Decision Science and Navigation Experiments with Multiple Participants
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    Area of Science:

    • Computer Science
    • Virtual Reality

    Background:

    • Server-client communication bottlenecks hinder scalability in collocated multi-user virtual reality (VR).
    • Existing unicast approaches struggle to efficiently support large groups due to individual data streams.

    Purpose of the Study:

    • To present an efficient multicast-based communication strategy for collocated multi-user VR.
    • To improve the speed and completeness of environment reconstruction in large VR groups.

    Main Methods:

    • Implemented a system that multicasts identical packets to all clients, employing packetization, visibility-aware prioritization, and lightweight acknowledgments.
    • Partitioned the environment into independently decodable packets, with transmission order guided by precomputed visibility footprints.
    • Utilized repeated multicast and compact bitmap acknowledgments for scalability, ensuring communication cost is largely independent of client numbers.

    Main Results:

    • The multicast approach demonstrated significantly faster environment reconstruction compared to unicast TCP-based methods.
    • Fewer missing environment parts were observed with the multicast system in controlled studies.
    • The system successfully supported collocated VR groups of 7 and 16 participants.

    Conclusions:

    • Multicast transmission over commodity Wi-Fi is a viable solution for large collocated VR groups.
    • The proposed method effectively alleviates server-client communication bottlenecks in multi-user VR environments.
    • This approach enhances efficiency and fairness in VR data delivery.