Packet classification has become increasingly complex and important to network equipment intended for future use. A recent trend to achieve complex packet classification is to use software-based methods, which tend to be slower than hardware-based methods. For search, this typically means using ternary content-addressable memory (TCAM) to make classification feasible. However, TCAM is not well-suited to the long (in bits) and sparse rules used for running advanced applications that require complicated classification. We propose a multi-dimension search engine (MDSE) that is optimized for use with long, sparse rules, and we propose a multi-dimensional TCAM scheme, which is an MDSE constructed to operate on TCAM. Through fine-grained simulations with real traffic, we show that our proposed search engine can reduce the power consumed by network equipment by about 85%.
['Masami Nawa', 'Kenzo Okuda', 'Shingo Ata', 'Yasuto Kuroda', 'Yuji Yano', 'Hisashi Iwamoto', 'Kazunari Inoue', 'Ikuo Oka']
Energy-efficient high-speed search engine using a multi-dimensional TCAM architecture with parallel pipelined subdivided structure