Identifying syntactic differences between two programs
Software—Practice & Experience
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
Faster IP lookups using controlled prefix expansion
SIGMETRICS '98/PERFORMANCE '98 Proceedings of the 1998 ACM SIGMETRICS joint international conference on Measurement and modeling of computer systems
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 on multiple fields
Proceedings of the conference on Applications, technologies, architectures, and protocols for computer communication
The Design and Analysis of Computer Algorithms
The Design and Analysis of Computer Algorithms
Algorithms on Trees and Graphs
Algorithms on Trees and Graphs
Packet classification using multidimensional cutting
Proceedings of the 2003 conference on Applications, technologies, architectures, and protocols for computer communications
Tree bitmap: hardware/software IP lookups with incremental updates
ACM SIGCOMM Computer Communication Review
Dynamic pipelining: making IP-lookup truly scalable
Proceedings of the 2005 conference on Applications, technologies, architectures, and protocols for computer communications
Shape Shifting Tries for Faster IP Route Lookup
ICNP '05 Proceedings of the 13TH IEEE International Conference on Network Protocols
In VINI veritas: realistic and controlled network experimentation
Proceedings of the 2006 conference on Applications, technologies, architectures, and protocols for computer communications
A proposed architecture for the GENI backbone platform
Proceedings of the 2006 ACM/IEEE symposium on Architecture for networking and communications systems
CAMP: fast and efficient IP lookup architecture
Proceedings of the 2006 ACM/IEEE symposium on Architecture for networking and communications systems
How to lease the internet in your spare time
ACM SIGCOMM Computer Communication Review
Non-random generator for IPv6 tables
HOTI '04 Proceedings of the High Performance Interconnects, 2004. on Proceedings. 12th Annual IEEE Symposium
Scalable VPN routing via relaying
SIGMETRICS '08 Proceedings of the 2008 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Efficient IP-address lookup with a shared forwarding table for multiple virtual routers
CoNEXT '08 Proceedings of the 2008 ACM CoNEXT Conference
IP-address lookup using LC-tries
IEEE Journal on Selected Areas in Communications
Algorithms for packet classification
IEEE Network: The Magazine of Global Internetworking
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Many popular algorithms for fast packet forwarding and filtering rely on the tree data structure. Examples are the trie-based IP lookup and packet classification algorithms. With the recent interest in network virtualization, the ability to run multiple virtual router instances on a common physical router platform is essential. An important scaling issue is the number of virtual router instances that can run on the platform. One limiting factor is the amount of high-speed memory and caches available for storing the packet forwarding and filtering data structures. An ideal goal is to achieve good scaling while maintaining total isolation among the virtual routers. However, total isolation requires maintaining separate data structures in high-speed memory for each virtual router. In this paper, we study the case where some sharing of the forwarding and filtering data structures is permissible and develop algorithms for combining tries used for IP lookup and packet classification. Specifically, we develop a mechanism called trie braiding that allows us to combine tries from the data structures of different virtual routers into just one compact trie. Two optimal braiding algorithms and a faster heuristic algorithm are presented, and the effectiveness is demonstrated using the real-world data sets.