一种保持OpenFlow功能完整性的TCAM流表压缩模型

随着OpenFlow协议版本的不断更新,其在数据平面上细粒度的控制能力得到了很大提升。然而,由于表项匹配域支持的任意通配符依赖TCAM进行匹配处理,随着OpenFlow匹配域支持字段的增加,设备中的TCAM存储空间面临很大压力。为此,提出一种减小TCAM中流表存储空间的数学模型FICO(A Function-Integral TCAM-saving Compression model for flow table of OpenFlow)。FICO首先根据匹配域不同字段间的关系,将字段之间的冗余分为三种。然后基于冗余提出三种预压缩算法,分别为域间字段合并、字段映射、域内字段压缩,最终组合为更小位宽的表项被送往TCAM中进行流匹配。通过仿真表明在保持OpenFlow功能完整性的前提下,较未压缩流表,FICO可以节省60%TCAM存储空间。并且随着流表规模的增大,压缩性能保持稳定。

A Function-integral TCAM-saving compression model for flow table of OpenFlow

In recent years, the fine-grained control ability of OpenFlow in data forwarding plane has increased greatly due to the constant upgrade of protocol version. However, expansion of supported fields in OpenFlow brings additional pressure to the storage space of TCAM (ternary content addressable memory) in physical device, since the arbitrary wildcard support in match field relies heavily on TCAM for matching process. In this paper, a mathematical model aiming at storage space reduction of the flow table in TCAM is presented, which is named with FICO: A Function-Integral TCAM-saving Compression model for flow table of OpenFlow. FICO analyzes the relationships among all the fields and then categorize the redundancy among different fields into three types. Based on the three redundancy types, three compression algorithm named as inter-field merge, field mapping and intra-field compression are presented, which are mainly performed in RAM space. The outcomes of each compression algorithm are flow entries with smaller bit-width which is sent to TCAM for flow matching. In this way, the flexibility of OpenFlow is not harmed, thus maintaining the function integrity of the original flow table. Simulation at the end shows that FICO saves almost about 60% of TCAM space for a given flow table with no damage to the function integrity of OpenFlow, and the compression performance stands stable with the increase of flow table size.