Monitoring large-scale virtual environments with hundreds / thousands of nodes (participants) brings many interesting challenges. As this is often the case in large-scale distributed systems, the data collection process itself should not introduce bottlenecks in the system. Also, it might not make sense for interested viewers to observe each individual node in the system. Viewers might want to view collected information at different hierarchical levels; thus, aggregation might be needed.
We designed a monitoring framework tailored for large-scale virtual environments and games . Our framework can collect data about all observable nodes (participants), and perform aggregation depending on the level of details that the viewer wishes to observe.
Experiments were run in the context of a large-scale massive multiplayer online game, with up to 1000 players. Our monitoring framework was used to follow player positions in real time at different zoom levels. Results showed that our framework was properly able to monitor moving players with minimal overhead.