Routing Table Implementation Using Integer Data Structure

Abstract

Tremendous growth in traffic is witnessed over the Internet where backbone links of several gigabits per second are commonly deployed. In order to handle these gigabit-per-second traffic rates, backbone routers must forward millions of packets per second on each of their ports. Routing tables of the core routers consists of IP addresses of the order of 200,000-500,000 and changes dynamically. A major challenge is to determine the next-hop address with as low as possible number of accesses of the routing table. IP address lookup in the routers uses the packets destination address to determine the next hop for each packet and is therefore crucial to achieve the required packet forwarding rates. IP address lookup is difficult because it requires a longest common prefix (LCP) match search. In the last couple of years, various algorithms for high-performance IP address lookup have been proposed. The objective of this paper is to use a specific data structure and develop the lookup algorithm that is required to meet the demands like fast lookup, memory efficiency and fast incremental updates. We have used a novel data structure y-fast trie for the routing table in this work. We adapted the algorithm for predecessor/successor search in x-fast trie via dynamic perfect hashing technique to find the longest common prefix between the incoming packets destination address and the next-hop address. By looking at this longest common prefix, we identify the next-hop address. As an improvement over this method, we also have used indirection using balanced BSTs (y-fast trie). On average the routing table creation takes 51703 μsec for 100000 IP addresses in the method using indirection. Average lookup time using dynamic perfect table takes 0.83 μsec.KeywordsIP address lookuproutingnext hopdestination IP address and packetsy-fast trielongest common prefix