Abstract Distributed scene graphs are important in virtual reality, both in collaborative virtual environments and in cluster rendering. Modern scalable visualization systems have high local throughput, but collaborative virtual environments (VEs) over a wide‐area network (WAN) share data at much lower rates. This complicates the use of one scene graph across the whole application. Myriad is an extension of the Syzygy VR toolkit in which individual scene graphs form a peer‐to‐peer network. Myriad connections filter scene graph updates and create flexible relationships between nodes of the scene graph. Myriad's sharing is fine‐grained: the properties of individual scene graph nodes to share are dynamically specified (in C++ or Python). Myriad permits transient inconsistency, relaxing resource requirements in collaborative VEs. A test application, WorldWideCrowd, demonstrates collaborative prototyping of a 300‐avatar crowd animation viewed on two PC‐cluster displays and edited on low‐powered laptops, desktops, and over a WAN. We have further used our framework to facilitate collaborative educational experiences and as a vehicle for undergraduates to experiment with shared virtual worlds. Copyright © 2006 John Wiley & Sons, Ltd.

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.

The Syzygy software library consists of tools for programming VR applications on PC clusters. Since the PC cluster environment presents application development constraints, it is impossible to simultaneously optimize for efficiency, flexibility, and portability between the single-computer and cluster cases. Consequently Syzygy includes two application frameworks: a distributed scene graph framework for rendering a single application's graphics database on multiple rendering clients, and a master/slave framework for applications with multiple synchronized instances. Syzygy includes a simple distributed OS and supports networked input devices, sound renderers, and graphics renderers, all built on a robust networking layer.

Researchers have had great success using motion capture tools for controlling avatars in virtual worlds. Another current of virtual reality research has focused on building collaborative environments connected by networks. The present paper combines these tendencies to describe an open source software system that uses motion capture tools as input devices for realtime collaborative virtual environments. Important applications of our system lie in the realm of simulating interactive, multiparticipant physical activities like sport and dance. Several challenges and their respective solutions are outlined. First, we describe the infrastructure necessary to handle full-body articulated avatars as driven by motion capture equipment, including calibration and avatar creation. Next, we outline the PC cluster solution chosen to render our worlds, exploring methods of data sharing and synchronization, both within the PC cluster nodes and between different sites in the distributed system. Finally, virtual sports require physics, and we describe the simulation algorithms used.

Complex, distributed applications pose new challenges for performance analysis and optimization. This paper outlines an online approach to performance analysis where developers are active participants, using integrated measurement and immersive performance visualization to tune parallel and distributed applications.