CyberWalk is a distributed virtual walkthrough system that we have developed. It allows users at different geographical locations to share information and interact within a shared virtual environment (VE) via a local network or through the Internet. In this paper, we illustrate that as the number of users exploring the VE increases, the server will quickly become the bottleneck. To enable good performance, CyberWalk utilizes multiple servers and employs an adaptive region partitioning technique to dynamically partition the whole VE into regions. All objects within each region will be managed by one server. Under normal circumstances, when a viewer is exploring a region, the server of that region will be responsible for serving all requests from the viewer. When a viewer is crossing the boundary of two or more regions, the servers of all the regions involved will be serving requests from the viewer since the viewer might be able to view objects within all these regions. This is analogous to evaluating a database query using a parallel database server, which could improve the performance of serving a viewer's request tremendously. We evaluate the performance of this multiserver architecture of CyberWalk via a detail simulation model.

A distributed virtual environment (DVE) allows geographically separated users to participate in a shared virtual environment via connected networks. However, when the users are connected by the Internet, bandwidth limitation and network latency may seriously affect the performance and the interactivity of the system. This explains why there are very few DVE applications for the Internet. To address these shortcomings, caching and prefetching techniques are usually employed. Unfortunately, the effectiveness of these techniques depends largely on the accuracy of the prediction method used. Although there are a few methods proposed for predicting 3D motion, most of them are primarily designed for predicting the motion of specific objects by assuming certain object motion behaviors. We notice that in desktop DVE applications, such as virtual walkthrough and network gaming, the 2D mouse is still the most popular device used for navigation input. Through studying the motion behavior of a mouse during 3D navigation, we have developed a hybrid motion model for predicting the mouse motion during such navigation---a linear model for prediction at low-velocity motion and an elliptic model for prediction at high-velocity motion. The predicted mouse motion velocity is then mapped to the 3D environment for predicting the user's 3D motion. We describe how this prediction method can be integrated into the caching and prefetching mechanisms of our DVE prototype. We also demonstrate the effectiveness of the method and the resulting caching and prefetching mechanisms through extensive experiments.

A distributed virtual environment (DVE) allows users at different geographical locations to share information and interact within a common virtual environment (VE) via a local network or through the Internet. However, when the number of users exploring the VE increases, the server will quickly become the bottleneck. To enable good performance, we are currently developing a multi-server DVE prototype. In this paper, we describe an adaptive data partitioning technique to dynamically partition the whole VE into regions. All objects within each region will be managed by a single server. As the loading of the servers changes, we show how it can be redistributed while minimizing the communication cost. Our initial results show that the proposed adaptive partitioning technique significantly improves the performance of the overall system.

CyberWalk is a distributed virtual walkthrough system that we have developed. It allows users at different geographical locations to share information and interact within a common virtual environment (VE) via a local network or through the Internet. In this paper, we illustrate that when the number of users exploring the VE increases, the server will quickly become the bottleneck. To enable good performance, CyberWalk utilizes multiple servers and employs an adaptive data partitioning techniques to dynamically partition the whole VE into regions. All objects within each region will be managed by one server. Under normal circumstances, when a viewer is exploring a region, the server of that region will be responsible for serving all requests from the viewer. When a viewer is crossing the boundary of two or more regions, the servers of all the regions involved will be serving requests from the viewer since the viewer might be able to view objects within all those regions. We evaluate the performance of this multi-server architecture of CyberWalk via a detail simulation model.

Although there are a few methods proposed for predicting 3D motion, most of these methods are primarily designed for predicting the motion of specific objects, by assuming certain object motion behaviors. We notice that in desktop distributed 3D applications, such as virtual walkthrough and computer games, the 2D mouse is still the most popular device being used as navigation input. Through studying the motion behavior of a mouse during 3D navigation, we propose a hybrid motion model for predicting the mouse motion during a 3D walkthrough. At low motion velocity, we use a linear model for prediction and at high motion velocity, we use an elliptic model for prediction. We describe how this prediction method can be integrated into our distributed virtual environment for object model caching and prefetching. We also demonstrate the effectiveness of the prediction method and the resulting caching and prefetching mechanisms through extensive experiments.