IP-address lookup using LC-tries

Abstract

There has recently been a notable interest in the organization of routing information to enable fast lookup of IP addresses. The interest is primarily motivated by the goal of building multigigabit routers for the Internet, without having to rely on multilayer switching techniques. We address this problem by using an LC-trie, a trie structure with combined path and level compression. This data structure enables us to build efficient, compact, and easily searchable implementations of an IP-routing table. The structure can store both unicast and multicast addresses with the same average search times. The search depth increases as 2(log log n) (log log n) (log log n) with the number of entries in the table for a large class of distributions, and it is independent of the length of the addresses. A node in the trie can be coded with four bytes. Only the size of the base vector, which contains the search strings, grows linearly with the length of the addresses when extended from 4 to 16 bytes, as mandated by the shift from IP version 4 to IP version 6. We present the basic structure as well as an adaptive version that roughly doubles the number of lookups/s. More general classifications of packets that are needed for link sharing, qualityof-service provisioning, and multicast and multipath routing are also discussed. Our experimental results compare favorably with those reported previously in the research literature.

Tree-Combined Trie: A Compressed Data Structure for Fast IP Address Lookup

“…Some of them compress the trie for decreasing the memory consumption and improving the speed [1][2], [19][20][21]. Since a binary trie needs lots of comparisons and memory accesses, many solutions use multibit trie concept to accelerate the lookup search [3][4][5][6][7][8][9][10][11][12][13]; however, using a multi-bit trie instead of binary trie normally increases the memory consumption. Some papers have proposed compression methods for solving this problem [8]- [13].Compression methods usually suffer from update overhead.…”

The Ubiquitous Digital Tree

“…Level compressed tries. Nilsson and Karlsson [48] made a sensation when they discovered the "LC trie" (in full: Level Compressed trie): they demonstrated that their data structure could handle address lookup in routing tables with a standard PC in a way that can compete favorably with dedicated hardware embedded into routers. One of their beautifully simple ideas consists in compressing the perfect tree contained in a trie (starting from the root) into a single node of high degreethis principle is then used recursively.…”

“…It is evocative of a partial realization of extendible hashing. The decisive advantage in terms of execution time stems from the fact that chains of pointers are replaced by a single array access, while the search depth decreases to O(log log n) for a large class of distributions [12,13,48] …”

IP Lookup Using the Novel Idea of Scalar Prefix Search with Fast Table Updates

“…For w bits IP addresses, the main drawback of this structure is its worst case O(w) node access complexity for search and update procedures. Some improvements of Trie [2]- [4], were also introduced to solve this problem. However, most of them suffer from the above disadvantage or time consuming update procedures.…”