Scalable Packet Classification Using Condensate Bit Vector

Packet classification is important in fulfilling the requirements of differentiated services in next generation networks. One of interesting hardware solutions proposed to solve the packet classification problem is bit vector algorithm. Different from other hardware solutions such as ternary CAM, it efficiently utilizes the memories to achieve an excellent performance in medium size policy database; however, it exhibits poor worst-case performance with a potentially large number of policies. In this paper, we proposed an improved bit-vector algorithm named Condensate Bit Vector which can be adapted to large policy databases in the backbone network. Experiments showed that our proposed algorithm drastically improves in the storage requirements and search speed as compared to the original algorithm.

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