Small forwarding tables for fast routing lookups
SIGCOMM '97 Proceedings of the ACM SIGCOMM '97 conference on Applications, technologies, architectures, and protocols for computer communication
Fast and scalable layer four switching
Proceedings of the ACM SIGCOMM '98 conference on Applications, technologies, architectures, and protocols for computer communication
High-speed policy-based packet forwarding using efficient multi-dimensional range matching
Proceedings of the ACM SIGCOMM '98 conference on Applications, technologies, architectures, and protocols for computer communication
Packet classification using tuple space search
Proceedings of the conference on Applications, technologies, architectures, and protocols for computer communication
Packet classification on multiple fields
Proceedings of the conference on Applications, technologies, architectures, and protocols for computer communication
Scalable packet classification
Proceedings of the 2001 conference on Applications, technologies, architectures, and protocols for computer communications
Space Decomposition Techniques for Fast Layer-4 Switching
PfHSN '99 Proceedings of the IFIP TC6 WG6.1 & WG6.4 / IEEE ComSoc TC on on Gigabit Networking Sixth International Workshop on Protocols for High Speed Networks VI
Packet classification using multidimensional cutting
Proceedings of the 2003 conference on Applications, technologies, architectures, and protocols for computer communications
Algorithms for packet classification
IEEE Network: The Magazine of Global Internetworking
Large-scale wire-speed packet classification on FPGAs
Proceedings of the ACM/SIGDA international symposium on Field programmable gate arrays
Scalable packet classification on FPGA
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
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In this paper we introduce two new concepts to the design of packet classification systems. First, we propose most specific filter matching (MSFM), an improvement over the well known Cross Producting algorithm [V. Srinivasan, S. Suri, G. Varghese, M. Waldvogel, Fast and scalable layer four switching, in: Proceedings of ACM SIGCOMM, 1998] that significantly reduces the memory requirement of the earlier scheme. Second, we suggest that rules specifying the same source-destination IP prefix pair can be grouped together forming shared sets of transport level fields. This property of Transport Level Sharing (TLS), which characterizes real world classification databases is exploited for reducing a classifier's memory requirement and for hardware acceleration. We split the classification process into two stages. First, we perform classification on source-destination IP prefix pairs using the MSFM algorithm. Second, we perform classification on transport level fields exploiting transport level sharing. It is the combination of most specific filter matching and transport level sharing which results in a scheme that requires no more than 11 dependent memory accesses in the critical path independent of the size of the classification database. The memory access bandwidth of our scheme is also bounded when our scheme is accelerated in hardware. Compared to other schemes which involve a small and predictable number of steps in the critical path (e.g., Cross Producting [V. Srinivasan, S. Suri, G. Varghese, M. Waldvogel, Fast and scalable layer four switching, in: Proceedings of ACM SIGCOMM, 1998] or Recursive Flow Classification [P. Gupta, N. McKeown, Packet classification on multiple fields, in: Proceedings of ACM SIGCOMM, 1999]) the combination of most specific filter matching and transport level sharing is associated with the least memory requirement.