Memory-efficient Internet Protocol (IP) lookup with high speed is essential to achieve link-speed packet forwarding in IP routers. The rapid growth of Internet traffic and the development of optical link technologies have made IP lookup a major performance bottleneck in core routers. In this paper, we propose a new IP route lookup architecture based on hardware called Prefix-Route Trie (PR-Trie), which supports both IPv4 and IPv6 addresses. In PR-Trie, we develop a novel structure called Overlapping Hybrid Trie (OHT) to perform fast longest-prefix-matching (LPM) based on Multibit-Trie (MT), and a hash-based level matching query used to achieve only one off-chip memory access per lookup. In addition, the proposed PR-Trie also supports fast incremental updates. Since the memory complexity in MT-based IP lookup schemes depends on the level-partitioning solution and the data structure used, we develop an optimization algorithm called Bitmap-based Prefix Partitioning Optimization (BP2O). The proposed BP2O is based on a heuristic search using Ant Colony Optimization (ACO) algorithms to optimize memory efficiency. Experimental results using real-life routing tables prove that our proposal has superior memory efficiency. Theoretical performance analyses show that PR-Trie outperforms the classical Trie-based IP lookup algorithms.

In the previous work, Lampson et al. proposed an IP lookup algorithm which performs binary search on prefixes (BSP). The algorithm is attractive, even for IPv6, because of its bounded worst-case memory requirement. To achieve fast forwarding, it may need to slow down the insertion speed. Although this can be justified, the routing-table reconstruction in BSP is too time-consuming to handle the frequent route updates. In this work, we propose a fast forwarding-table construction algorithm which can accomplish more than 4,000 route updates per second. Moreover, it is simple enough to fulfill the need of fast packet forwarding. With the enhanced multiway search tree, we further reduced the depth of the tree and eliminated the pointer storage; this reduces the forwarding table size and shortens the lookup time.