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
Fast Updating Algorithms for TCAMs
IEEE Micro
Packet classification using multidimensional cutting
Proceedings of the 2003 conference on Applications, technologies, architectures, and protocols for computer communications
Packet Classification Using Extended TCAMs
ICNP '03 Proceedings of the 11th IEEE International Conference on Network Protocols
CoPTUA: Consistent Policy Table Update Algorithm for TCAM without Locking
IEEE Transactions on Computers
Algorithms for advanced packet classification with ternary CAMs
Proceedings of the 2005 conference on Applications, technologies, architectures, and protocols for computer communications
Survey and taxonomy of packet classification techniques
ACM Computing Surveys (CSUR)
ClassBench: a packet classification benchmark
IEEE/ACM Transactions on Networking (TON)
OpenFlow: enabling innovation in campus networks
ACM SIGCOMM Computer Communication Review
EffiCuts: optimizing packet classification for memory and throughput
Proceedings of the ACM SIGCOMM 2010 conference
Towards TCAM-based scalable virtual routers
Proceedings of the 8th international conference on Emerging networking experiments and technologies
High-performance architecture for dynamically updatable packet classification on FPGA
ANCS '13 Proceedings of the ninth ACM/IEEE symposium on Architectures for networking and communications systems
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Packet Classification is a key functionality provided by modern routers. Previous approaches --- TCAM and algorithmic --- perform well in either lookup efficiency (power and number of accesses) or update effort but not both. To perform well in both, we propose TreeCAM, which employs three novel ideas. (1) Dual versions of TreeCAM's decision tree to decouple lookups and updates: A coarse version with a few thousand rules per leaf achieves efficient lookups and a fine version with a few tens of rules per leaf reduces update effort. (2) Interleaved layout of the rules in the TCAM: Combined with the fine version's few rules per leaf, the layout enables us to bound our worst-case update effort. (3) Path-by-path updates to enable update work to be interspersed with packet lookups (i.e., non-atomic updates), eliminating packet buffering or packet drops during update. Using simulations of 100,000-rule classifiers, we show that TreeCAM performs well in both lookups and updates: (1) 6--8 TCAM subarray accesses per packet, matching modern TCAMs. (2) close to an idealized TCAM in worst-case update effort while requiring little buffering of packets.