Fundamentals of neural networks: architectures, algorithms, and applications
Fundamentals of neural networks: architectures, algorithms, and applications
Routing on longest-matching prefixes
IEEE/ACM Transactions on Networking (TON)
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
Scalable high speed IP routing lookups
SIGCOMM '97 Proceedings of the ACM SIGCOMM '97 conference on Applications, technologies, architectures, and protocols for computer communication
IP lookups using multiway and multicolumn search
IEEE/ACM Transactions on Networking (TON)
Packet classification on multiple fields
Proceedings of the conference on Applications, technologies, architectures, and protocols for computer communication
Router plugins: a software architecture for next-generation routers
IEEE/ACM Transactions on Networking (TON)
Introduction to Switching Theory and Logical Design
Introduction to Switching Theory and Logical Design
An Empirical Study of Today's Internet Traffic for Differentiated Services IP QoS
ISCC '00 Proceedings of the Fifth IEEE Symposium on Computers and Communications (ISCC 2000)
Algorithms for routing lookups and packet classification
Algorithms for routing lookups and packet classification
IP-address lookup using LC-tries
IEEE Journal on Selected Areas in Communications
You can get there from here: routing in the internet
CAAN'04 Proceedings of the First international conference on Combinatorial and Algorithmic Aspects of Networking
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IP routers need lookup tables to forward packets. They also classify packets to determine which flow they belong to and to decide what quality of service they should receive. Increasing rate of communication links is in contrast with practical processing power of routers and switches. We propose a few neural network algorithms to solve the IP lookup problem. Some of these algorithms, gives promising results, however, they have problems in training time. Parallel processing of neural networks provide a huge processing power to do IP lookup. The algorithm can be implemented in hardware on a single chip. Our method can perform an IP lookup in 4.5 nanoseconds, which implies supporting 60 Gbps link rate. Pipelining and parallel processing can be used to increase the link rate up to 400 Gbps and decrease the learning time.