An Improved Multi-Pattern Matching Algorithm for Large-Scale Pattern Sets

Multi-pattern matching algorithms are broadly used in many fields of computer science. However, the performance of the existing algorithms seriously degrades with the increasing of the number of patterns. In this paper, an improved multi-pattern matching algorithm based on the framework of the Wu-Manber (WM) algorithm is proposed to effectively deal with the large pattern sets. The WM algorithm is improved in two aspects. Firstly, the lengths of lists in the HASH table are balanced to reduce the number of candidate patterns; Secondly, a data structure called the "INDEX table" based on binary search is designed to reduce the time for finding candidate patterns. Experimental results show that our algorithm is efficient for large-scale pattern sets.