Revisiting Multiple Pattern Matching Algorithms for Multi-Core Architecture

Due to the huge size of patterns to be searched, multiple pattern searching remains a challenge to several newly-arising applications like network intrusion detection. In this paper, we present an attempt to design efficient multiple pattern searching algorithms on multi-core architectures. We observe an important feature which indicates that the multiple pattern matching time mainly depends on the number and minimal length of patterns. The multi-core algorithm proposed in this paper leverages this feature to decompose pattern set so that the parallel execution time is minimized. We formulate the problem as an optimal decomposition and scheduling of a pattern set, then propose a heuristic algorithm, which takes advantage of dynamic programming and greedy algorithmic techniques, to solve the optimization problem. Experimental results suggest that our decomposition approach can increase the searching speed by more than 200% on a 4-core AMD Barcelona system.