基于匹配动作表模型的可编程数据平面流表归并

与传统网络技术相比，SDN技术将网络的控制平面与数据平面分离，使网络具有一定的可编程能力。以OpenFlow、POF、P4等为代表，领域内常见的SDN交换机大多基于匹配动作表模型实现。与协议相关的OpenFlow等技术不同，协议无感知的SDN技术使用{偏移，长度}等结构表示协议字段，从而实现对任意协议字段的解析和处理。然而，待处理的数据包可能带有不同长度的数据包头，所以这些数据包中特定协议字段的偏移也会不同，需要多个匹配域偏移不同的流表去完成数据流的解析，从而造成流表和流水线结构复杂。针对上述问题，本文提出一种基于MAT模型的可编程数据平面流表归并方案，扩展MAT模型中的动作集，在数据包查询流表时使用特定的动作动态地调整数据包的起始偏移，使不同数据包同一协议字段的偏移保持一致，实现匹配域相同的流表的归并。本文方案在兼容VLAN、QinQ的POF Switch实验场景下，以跳转流表时多执行一条动作为代价，缩减了约69%的流表内存消耗。

Flow Table Merging on Programmable Data Planes Based on MAT Model

Compared with traditional networking technologies, SDN technologies separate the control plane of the networking from the data plane, making the networking programmable. Most of the SDN switches, like OpenFlow, POF, P4, are implemented based on the match-action table model. Different from protocol-aware SDNs, such as OpenFlow, protocol-oblivious SDNs define protocol fields by {offset, length} structures, so as to realize the parsing and processing of any protocol fields. However, packets to be processed may have packet headers with different lengths. In order to match the fields in packet header protocols, the control plane needs to install more flow tables to parse packets, which results in complex flow tables and pipelines. To address the above problems, this paper proposes a flow table merging scheme on programmable data planes based on the MAT model, which extends the action set in the MAT model. The starting offset of packets can be adjusted dynamically with specific actions when a packet queries the flow table, making the offset of the same matching fields in different packets consistently, so that flow tables with the same matching fields are merged. The scheme reduces the flow table memory consumption by about 69% at the cost of executing one more action when jumping the flow table in the POF Switch experimental scenario compatible with VLAN and QinQ.