软件定义网络中一种两步式多级流表构建算法

针对软件定义网络中流表规模的扩张以及流表存储资源利用率低效的问题，提出一种两步式多级流表构建算法．第1步基于流表中不同的流类别对匹配域进行拆分，简化不同流类别之间的通配表项；第2步根据匹配域的重复率对流表进行正交分解，进一步压缩了流表中的冗余表项．仿真实验表明，该方法能够节省60%以上的流表存储空间，相对于现有方法，流表压缩率提高了21.4%到51.5%．使用现场可编程门阵列的验证结果表明，该方法能够在优化存储空间的同时保证硬件可实现性和流水线的处理速度，数据吞吐量可达197MPacket/s，支持100Gbit/s的线速处理．

Two-step multiple flow table construction algorithm in the software-defined network

Aimed at the problem of the rapid growth of the flow table size and the inefficient utilization of the flow table storage resources, this paper proposes a two-step multiple flow table construction algorithm. First, the match fields in the single flow table are split into multiple flow tables according to the flow classification vectors, so the wildcards in the flow table are eliminated. Second, the orthogonal decomposition is performed for each sub-tables, and the redundant entries are compressed. Experimental results indicate that the method can save more than 60% storage space for a given flow table. Compared with existing works, the flow table compression ratio is improved by 21.4% to 51.5%. FPGA verification shows that this method can be implemented in practical hardware and the pipeline processing speed is guaranteed. The data throughput can achieve 197 Million Packets Per Second (MPPS), which supports the 100 Gbit/s line-rate packet processing.