A Neural-Network Based Technology of Data Distribution Management in Distributed Virtual Environment

In distributed virtual environment many methods of data distribution management (DDM) are presented to efficiently improve network traffic situation and save system resources, these technologies are based on virtual environment partition. The grid size of the partition affects the data distribution results. This paper aims to present a neural-network based study mechanism, which adjusts the grid size dynamically in the virtual environment. The simulation results indicate that by using this technique, better experimental results and practicability were achieved regardless the DDM used. And there is a significant improvement in system scalability.