VENUS: A virtual environment network using satellites

Sanjay K Udani, University of Pennsylvania

Abstract

Network access has evolved from basic text-only terminals to color graphical browsers with full-motion video capability. The next logical step of this evolution is to have fully immersive access to the network where users are no longer merely looking at a screen; instead, they will be immersed in a virtual environment and will be able to move around and interact with thousands of users. In addition to having suitable user interfaces such as head mounted displays and electronic gloves, the network has to be able to handle the traffic of all these users and deliver it reliably. Scalability, flexibility, and security are essential, as is quality of service. To achieve this level of immersion on a large scale, a new network/protocol architecture is necessary. The VENUS architecture addresses each of these problems by creating a network architecture which is scalable and flexible. We define a new hybrid architecture consisting of a server, a high bandwidth broadcast-only link and lower bandwidth bi-directional links. In our design, user attribute/control information is separated from user data and the two are sent over different network paths. Each user is able to obtain a complete, generic view of the virtual world. VENUS is highly scalable in both the number of users it can handle as well as in its geographical reach. Our architecture offers several other advantages over the previous designs, including privacy, ease of searching, variable field of view and user-defined access control. Using our experimental setup, we show that the VENUS model is feasible and scales well for tens of thousands of users. We present analysis that backs up our key claims. We also identify the key bottlenecks in the system and suggest methods to reduce them.

Subject Area

Computer science

Recommended Citation

Udani, Sanjay K, "VENUS: A virtual environment network using satellites" (1999). Dissertations available from ProQuest. AAI9953607.
https://repository.upenn.edu/dissertations/AAI9953607

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