Towards a Packet Classification Benchmark

Packet classification is the enabling technology for next generation network services and often the primary bottleneck in high-performance routers. Due to the importance and complexity of the problem, a myriad of algorithms and resulting implementations exist. The performance and capacity of many algorithms and classification devices, including TCAMs, depend upon properties of the filter set and query patterns. Unlike microprocessors in the field of computer architecture, there are no standard performance evaluation tools or techniques available to evaluate packet classification algorithms and products. Network service providers are reluctant to distribute copies of real filter databases for security and confidentiality reasons, hence realistic test vectors are a scarce commodity. The small subset of the research community who obtain real databases either limit performance evaluation to the small sample space or employ ad hoc methods of modifying those databases. We present a tool for creating synthetic filter databases that retain characteristics of a seed database and provide systematic mechanisms for varying the number and composition of the filters. We propose a benchmarking methodology based on this tool that provides a mechanism for evaluating packet classification performance on a uniform scale. We seek to initiate a broader discussion within the community that will result in a standard packet classification benchmark