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This paper presents our approach in testing the scalability of large-scale multi-user networked virtual environments. Emphasis is laid on both the number of users that are supported by the architecture and the resulting network traffic, both at client and server side. Instead of using a limited number of actual human users and extrapolating the results to larger user bases, we have opted for a system in which autonomous avatars are employed. These autonomous avatars are programmed with a limited number of fast algorithms that determine their behavior. These algorithms result in awareness of the structure of the world and reactions to events that happen in the world. By using these autonomous avatars as actual users of our Networked Virtual Environment, they also generate traffic that is representative for their human counterparts. This testing methodology is applied to our custom developed networked virtual environment framework 'ALVIC' (Architecture for Large Scale Virtual Interactive Communities). This enables us to prove scalability of the system to at least 1000 clients using results acquired by actually capturing network traffic. This method for scalability testing eliminates the need for large numbers of human users and is furthermore able to provide accurate results by only using a limited number of computers.