| 英文标题 | Decision tree based pre-classifier for energy-efficient TCAM based packet classification |
| 作者英文名 | Li Wenjun, Liu Xinwei, Xing Kaixuan, Le Wenxia, Li Hui |
| 机构英文名 | 1.Peking University Shenzhen Graduate School,Shenzhen Guangdong 518055,China;2.Peng Cheng Laboratory,Shenzhen Guangdong 518055,China;3.School of Electronic Engineering & Computer Science,Peking University,Beijing 100871,China |
| 英文摘要 | Due to the high-speed requirement of high-end network devices, hardware using TCAMs has been the dominant implementation of packet classification in industry. Despite its capability for line-speed queries, TCAM is not only power hungry but also capacity inefficient. By making use of a pre-classifier to activate TCAM blocks selectively, many research efforts significantly reduce the power consumption of TCAM. However, these bottom-up based pre-classifiers achieve power savings at the expense of poor utilization of TCAM capacity, and the potential of power reduction is not fully exploited in many cases. This paper proposed a power-saving pre-classifier for TCAM based packet classification, which constructed based on decision trees. By grouping rules with respect to their small fields, rules could be recursively mapped into decision trees without the trouble of rule replications, so that a top-down traversal algorithm could be well applied for obtaining index items. Experimental results show that for rule sets up to one hundred thousand entries, the proposed design achieves 98.2% power reduction with a TCAM storage overhead of 1.3% on average. |
| 英文关键词 | SDN; OpenFlow; packet classification; TCAM(ternary content addressable memory); energy-efficient |