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Myriad: scalable VR via peer-to-peer connectivity, PC clustering, and transient inconsistency
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Source Virtual Reality Software and Technology archive
Proceedings of the ACM symposium on Virtual reality software and technology table of contents
Monterey, CA, USA
SESSION: Collaboration and cooperation -- II table of contents
Pages: 68 - 77  
Year of Publication: 2005
ISBN:1-59593-098-1
Authors
Benjamin Schaeffer  University of Illinois at Urbana-Champaign, Urbana IL
Peter Brinkmann  TU Berlin, Inst. für Mathematik, Berlin, Germany
George Francis  University of Illinois at Urbana-Champaign, Urbana IL
Camille Goudeseune  University of Illinois at Urbana-Champaign, Urbana IL
Jim Crowell  University of Illinois at Urbana-Champaign, Urbana IL
Hank Kaczmarski  University of Illinois at Urbana-Champaign, Urbana IL
Sponsors
SIGCHI: ACM Special Interest Group on Computer-Human Interaction
SIGGRAPH: ACM Special Interest Group on Computer Graphics and Interactive Techniques
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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ABSTRACT

Distributed scene graphs are important in virtual reality, both in collaborative virtual environments and in cluster rendering. In Myriad, individual scene graphs form a peer-to-peer network whose connections filter scene graph updates and create flexible relationships between scene graph nodes in the various peers. Modern scalable visualization systems often feature high intracluster throughput, but collaborative virtual environments (VEs) over a WAN share data at much lower rates, complicating the use of one scene graph system across the whole application. To avoid these difficulties, Myriad uses fine-grained sharing, whereby sharing properties of individual scene graph nodes can be dynamically changed from C++ and Python, and transient inconsistency, which relaxes resource requirements in collaborative VEs. A test application, WorldWideCrowd, implements these methods to demonstrate collaborative prototyping of a 300-avatar crowd animation viewed on two PC-cluster displays and edited on low-powered laptops, desktops, and even over a WAN.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Benjamin Schaeffer: colleagues
Peter Brinkmann: colleagues
George Francis: colleagues
Camille Goudeseune: colleagues
Jim Crowell: colleagues
Hank Kaczmarski: colleagues