An analysis of parallel interest matching algorithms in distributed virtual environments

Interest management is a filtering technique which is designed to reduce bandwidth consumption in Distributed Virtual Environments. This technique usually involves a process called “interest matching”, which determines what data should be filtered. Existing interest matching algorithms, however, are mainly designed for serial processing which is supposed to be run on a single processor. As the problem size grows, these algorithms may not be scalable since the single processor may eventually become a bottleneck. In this paper, a parallel approach for interest matching is presented which is suitable to deploy on both shared-memory and distributed-memory multiprocessors. We also provide an analysis of speed-up and efficiency for the simulation results of the parallel algorithms.