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Modern network security devices employ packet classification and pattern matching algorithms to inspect packets. Due to the complexity and heterogeneity of different search data structures, it is difficult for existing algorithms to leverage modern hardware platforms to achieve high performance. This paper presents a Structural Compression(SC) method that optimizes the data structures of both algorithms. It reviews both algorithms under the model of search space decomposition, and homogenizes their search data structures. This approach not only guarantees deterministic lookup speed but also optimizes the data structure for efficient implementation on many-core platforms. The performance evaluation reveals that the homogeneous data structure achieves 10 Gbps line-rate 64 byte packet classification throughput and multi-Gbps deep inspection speed.
Modern network security devices employ packet classification and pattern matching algorithms to inspect packets. Due to the complexity and heterogeneity of different search data structures, it is difficult for existing algorithms to leverage modern hardware platforms to achieve high performance. This paper presents a Structural Compression ( SC) method that optimizes the data structures of both algorithms. It reviews both algorithms under the model of search space decomposition, and homogenizes their search data structures. This approach not only deterministically lookup speed but also optimizes the data structure for efficient implementation on many -core platforms. The performance evaluation reveals that the homogeneous data structure achieves 10 Gbps line-rate 64 byte packet classification throughput and multi-Gbps deep inspection speed.