Scalable Interest Management based on Interest Groups for Large Networked Virtual Environments

As networked virtual environment (NVE) scales in terms of users and network latency, a key aspect to consider is scalability for interactive performance because a large number of objects likely impose heavy burden especially on the network and computational resources. To improve the scalability, various relevance-filtering mechanism have been proposed. However, the existing filtering mechanism do not scale well in terms of interactive performance as the number of users increase and crowds in a specific place. In this paper, we propose a new scalable filtering scheme which reduces the number of messages by dynamically grouping users based on their interests and distance. Within a group, members communicate with each other with high fidelity. However, a representative sends up-to-dated group information of members with low transmission frequency when they are not of immediate interest but are still within the interest area. The representative is elected from members of the group in distributed manner. The proposed scheme enhances the interactive performance scalability of large-scale NVE systems as much as 18% compared with the existing approach.