Abstract
Parallel Tree Search (PTS) is one of the best algorithms among the existing algorithms for rule matching. However,PTS needs to construct so many external nodes and only supports rules with prefixes. The authors proposed an algorithm named RMBRDM for rule matching based on rule decomposing. At first,RMBRDM employed heuristic methods to choose a standard dimension. And then rules could be decomposed according to rule decomposing mapping and the standard dimension. At last,a binary decision tree could be built. Algorithm analysis and simulation results show that RMBRDM can support rules with ranges and the performance of RMBRDM is better than that of PTS.
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