The number of IPv6 routes in todays backbone routers has grown rapidly,which has put tremendous pressure on route lookup and storage.Based on the analysis of IPv6 address prefix length and distribution characteristics...The number of IPv6 routes in todays backbone routers has grown rapidly,which has put tremendous pressure on route lookup and storage.Based on the analysis of IPv6 address prefix length and distribution characteristics,this paper proposes an IPv6 route lookup architecture called LPR-Trie.The core idea of the algorithm is to utilize more spaces and accelerate routing lookup.Moreover,we put forward the concept of virtual nodes,and leverage the link between virtual nodes and ordinary nodes to accelerate routing lookup.We provide the longest prefix routing entry(LPR)calculation algorithm to achieve the longest prefix match.The experimental results show that the virtual node mechanism increases the search speed up to 244%,and the virtual nodes have better stability by setting an appropriate keep-alive time according to the characteristics of actual traffic.This paper shows that our design improves the routing lookup speed and have better memory utilization.展开更多
A Scalable Multi-Hash( SMH) name lookup method is proposed,which is based on hierarchical name decomposition to aggregate names sharing common prefixes and multiple scalable hash tables to minimize collisions among pr...A Scalable Multi-Hash( SMH) name lookup method is proposed,which is based on hierarchical name decomposition to aggregate names sharing common prefixes and multiple scalable hash tables to minimize collisions among prefixes. We take the component instead of the entire name as a key in the hash functions. The SMH method achieves lookup speeds of 21. 45 and 20. 87 Mbps on prefix table with 2 million and 3. 6 million names,respectively. The proposed method is the fastest of the four methods considered and requires 61.63 and 89.17 Mb of memory on the prefix tables with 2 million and 3. 6 million names,respectively. The required memory is slightly larger than the best method. The scalability of SMH outperforms that of the other two methods.展开更多
基金support from the National Natural Science Foundation of China (61872252)National Key Research and Development Program of China (2018YFB1800403)+1 种基金the Beijing Natural Science Foundation (4202012)the Science and Technology Project of Beijing Municipal Commission of Education in China (KM201810028017)
文摘The number of IPv6 routes in todays backbone routers has grown rapidly,which has put tremendous pressure on route lookup and storage.Based on the analysis of IPv6 address prefix length and distribution characteristics,this paper proposes an IPv6 route lookup architecture called LPR-Trie.The core idea of the algorithm is to utilize more spaces and accelerate routing lookup.Moreover,we put forward the concept of virtual nodes,and leverage the link between virtual nodes and ordinary nodes to accelerate routing lookup.We provide the longest prefix routing entry(LPR)calculation algorithm to achieve the longest prefix match.The experimental results show that the virtual node mechanism increases the search speed up to 244%,and the virtual nodes have better stability by setting an appropriate keep-alive time according to the characteristics of actual traffic.This paper shows that our design improves the routing lookup speed and have better memory utilization.
基金sponsored by the National Basic Research Program of China(973 Program)(Grant No.2011CB302605)the National High Technology Research and Development Program of China(863 Program)(Grants No.2011AA010705+5 种基金2012AA0125022012AA012506)the National Key Technology R&D Program of China(Grant No.2012BAH37B01)the National Science Foundation of China(Grant No.6120245761402149)the CNNIC(Grant No.K201211043)
文摘A Scalable Multi-Hash( SMH) name lookup method is proposed,which is based on hierarchical name decomposition to aggregate names sharing common prefixes and multiple scalable hash tables to minimize collisions among prefixes. We take the component instead of the entire name as a key in the hash functions. The SMH method achieves lookup speeds of 21. 45 and 20. 87 Mbps on prefix table with 2 million and 3. 6 million names,respectively. The proposed method is the fastest of the four methods considered and requires 61.63 and 89.17 Mb of memory on the prefix tables with 2 million and 3. 6 million names,respectively. The required memory is slightly larger than the best method. The scalability of SMH outperforms that of the other two methods.
