Large-scale wire-speed packet classification on FPGAs
Proceedings of the ACM/SIGDA international symposium on Field programmable gate arrays
Field-split parallel architecture for high performance multi-match packet classification using FPGAs
Proceedings of the twenty-first annual symposium on Parallelism in algorithms and architectures
Energy-efficient multi-pipeline architecture for terabit packet classification
GLOBECOM'09 Proceedings of the 28th IEEE conference on Global telecommunications
Speedy FPGA-based packet classifiers with low on-chip memory requirements
Proceedings of the ACM/SIGDA international symposium on Field Programmable Gate Arrays
International Journal of Reconfigurable Computing
Scalable packet classification on FPGA
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Hardware accelerators targeting a novel group based packet classification algorithm
International Journal of Reconfigurable Computing
An impulse-c hardware accelerator for packet classification based on fine/coarse grain optimization
International Journal of Reconfigurable Computing
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Packet classification is one of the most important enabling technologies for next generation network services. Even though many multi-dimensional classification algorithms have been proposed, most of them are precluded from commercial equipments due to their high memory requirements. In this paper, we present an efficient packet classification scheme, implemented in reconfigurable hardware, called Dual Stage Bloom Filter Classification Engine (2sBFCE). 2sBFC comprises of an innovative 5-field search scheme that decomposes multi-field classification rules into internal single-field rules which are combined using multi-level Bloom filters. The design of 2sBFCE is optimized for the common case based on analysis of real world classification databases. The FPGA implementation of the proposed scheme handles 4K rules, with very small memory requirements, while supporting network streams at a rate of 2Gbps in the worst case, and more than 6Gbps in the average case.