An Approach for Parallel Interest Matching in Distributed Virtual Environments

Interest management is essential for real-time large-scale distributed virtual environments (DVEs) which seeks to filter irrelevant messages on the network. Many existing interest management schemes such as HLA DDM focus on providing precise message filtering mechanisms. However, this leads to a second problem: the computational overhead of the interest matching process. If the CPU cost of interest matching is too high, it would be unsuitable for real-time applications such as multiplayer online games for which runtime performance is important. This paper evaluates the performance of existing interest matching algorithms and proposes a new algorithm based on parallel processing. The new algorithm is expected to have better computational efficiency than existing algorithms and maintain the same accuracy of message filtering as them. Experimental evidence shows that our approach works well in practice.