A rapidly emerging need within virtual environments is the ability to accommodate a large, distributed user-base. In particular, Internet-based distributed virtual environments represent a challenge in providing a heterogeneous environment accessible by many thousands of users. Interest Management represents the process of filtering network data based on relevance to users, in order to make the most efficient use possible of available network capacity. In this thesis, the potential for a visual-attention based refinement to interest management is explored, which utilises a spotlight-based model of human attention. By considering the relationship between attention and interest management, this thesis illustrates a tendency within existing systems to use a simplistic or object-based approach to measure relevance, typically based on proximity to the user or visibility. By considering the current state of the art alongside common theories of visual attention, it is hypothesised that a refinement aiming to accommodate a spotlight model may offer an approach capable of more efficient use of bandwidth when compared to existing techniques. In particular, it is suggested a spotlight model would be capable of accommodating key aspects of human visual attention in a processor-efficient and composable manner. Bandwidth conserved by the use of such an approach may be subsequently re-utilised to provide a higher degree of interactivity within a distributed virtual environment, or to support greater numbers of simultaneous users. In order to evaluate the effectiveness of a spotlight-based approach, a test environment is created which allows users to participate in a number of activities alongside a large volume of simulated clients. Throughout these activities, interest management is changed seamlessly between variations of a spotlight approach, extremes, and an approximation of the current state of the art. Results obtained from a total of 15 users indicate a preference for such an approach when compared to the current state of the art in 80% of subjects, and suggest the capacity to reduce available bandwidth by up to 60%, dependent on task, without perceivable impact.