Efficient Hierarchical Hash-Based Multi-Field Packet Classification With Fast Update for Software Switches

Abstract

Packet classification that attracts wide interests in router designs is one of the most important functionalities to provide services such as QoS, packet forwarding, firewall, and VPN. With the expanding network and the rise of software-defined networks, software routers/switches are needed to enable a wide variety of network applications in physical or virtual networks. Existing packet classification schemes used in software switches had become difficult to support a fast classification process for large multi-field rulesets. In addition, it is necessary to have fast updates that are frequently performed. In this paper, we propose a hash-based partitioning scheme for a multi-field packet classification problem. The proposed design is a 4-level data structure based on hashing. It selects the suitable fields to construct the data structures so that we can quickly narrow down the search space to find matched rules. The hash table used in the proposed design is more effective than the existing search data structures. Our experimental results show that the proposed scheme performs best in all four-performance metrics of memory consumption, construction time, classification time, and update time compared with the six most recently proposed schemes, CutTSS, TabTree, TupleMerge, CutSplit, PartitionSort, and PSTSS. The average number of bytes required per rule is only 27-99% of that needed in these schemes. The construction time of our scheme is 2.06 to 327.82 times faster than these schemes. Most importantly, the proposed scheme is 1.92-16.65 and 2.22-4.54 times faster than these six schemes in throughput and update time, respectively.

Keywords

• Packet classification
• hash table
• tuple space search
• linear search
• OpenFlow