ClassBench: a packet classification benchmark

Packet classification is an enabling technology for next generation network services and often the primary bottleneck in high-performance routers. The performance and capacity of many algorithms and classification devices, including TCAMs, depend upon properties of the filter set and query patterns. Despite the pressing need, no standard filter sets or performance evaluation tools are publicly available. In response to this problem, we present ClassBench, a suite of tools for benchmarking packet classification algorithms and devices. ClassBench includes a filter set generator that produces synthetic filter sets that accurately model the characteristics of real filter sets. Along with varying the size of the filter sets, we provide high-level control over the composition of the filters in the resulting filter set. The tool suite also includes a trace generator that produces a sequence of packet headers to exercise packet classification algorithms with respect to a given filter set. Along with specifying the relative size of the trace, we provide a simple mechanism for controlling locality of reference. While we have already found ClassBench to be very useful in our own research, we seek to eliminate the significant access barriers to realistic test vectors for researchers und initiate a broader discussion to guide the refinement of the tools and codification of a formal benchmarking methodology.