Consensus Based Networking of Distributed Virtual Environments

Friston, Sebastian, Griffith, Elias ORCID: 0000-0001-9360-381X, Swapp, David, Julier, Simon, Irondi, Caleb, Jjunju, Fred ORCID: 0000-0001-6257-434X, Ward, Ryan ORCID: 0000-0002-9850-5191, Marshall, Alan ORCID: 0000-0002-8058-5242 and Steed, Anthony
(2022) Consensus Based Networking of Distributed Virtual Environments. IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS, 28 (9). pp. 3138-3153.

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Distributed virtual environments (DVEs) are challenging to create as the goals of consistency and responsiveness become contradictory under increasing latency. DVEs have been considered as both distributed transactional databases and force-reflection systems. Both are good approaches, but they do have drawbacks. Transactional systems do not support Level 3 (L3) collaboration: manipulating the same degree-of-freedom at the same time. Force-reflection requires a client-server architecture and stabilisation techniques. With Consensus Based Networking (CBN), we suggest DVEs be considered as a distributed data-fusion problem. Many simulations run in parallel and exchange their states, with remote states integrated with continous authority. Over time the exchanges average out local differences, performing a distribued-average of a consistent, shared state. CBN aims to build simulations that are highly responsive, but consistent enough for use cases such as the piano-movers problem. CBN's support for heterogeneous nodes can transparently couple different input methods, avoid the requirement of determinism, and provide more options for personal control over the shared experience. Our work is early, however we demonstrate many successes, including L3 collaboration in room-scale VR, 1000's of interacting objects, complex configurations such as stacking, and transparent coupling of haptic devices. These have been shown before, but each with a different technique; CBN supports them all within a single, unified system.

Item Type: Article
Uncontrolled Keywords: Synchronization, Collaboration, Servers, Kalman filters, Haptic interfaces, Task analysis, Solid modeling, C, 2, 4, b distributed applications, I, 6, 8, e distributed simulations, H, 5, 1, b artificial, augmented, and virtual realities
Depositing User: Symplectic Admin
Date Deposited: 19 Feb 2021 09:54
Last Modified: 20 Apr 2023 06:53
DOI: 10.1109/TVCG.2021.3052580
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