Abstract
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.
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Mahramian, M., Yazdani, N., Faez, K., Taheri, H. (2002). Neural Network Based Algorithms for IP Lookup and Packet Classification. In: Shafazand, H., Tjoa, A.M. (eds) EurAsia-ICT 2002: Information and Communication Technology. EurAsia-ICT 2002. Lecture Notes in Computer Science, vol 2510. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36087-5_24
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DOI: https://doi.org/10.1007/3-540-36087-5_24
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