By Topic

Greedy Prefix Cache for IP Routing Lookups

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Zhuo Huang ; Dept. of Comput. & Inf. Sci. & Eng., Univ. of Florida, Gainesville, FL, USA ; Gang Liu ; Jih-Kwon Peir

As the rapid growth of Internet and the communication link speed, it becomes increasingly challenging for network processors to timely route the incoming traffic to the destination ports. The traditional approach must look up the routing table based on the destination IP address to determine the output port. The ternary CAM approach provides fast associative look up, but is very costly for large routing tables. The trie-based algorithm allows inexpensive searching, but may not satisfy the growing speed requirement. Previous studies showed that the overall routing time can be shortened by adding a small prefix cache for the general trie-based routing algorithms. In caching the prefix, however, the nested prefixes are difficult to cache due to the constraint of the longest prefix matching requirement. This paper presents a greedy prefix caching technique to improve the prefix cache performance that allows caching the largest sub-tree of each prefix including the parent prefixes. Our experiment results show that the prefix cache using the proposed upgrade scheme can reduce the miss ratio by about 6-8% comparing to the best existing prefix caching mechanism.

Published in:

2009 10th International Symposium on Pervasive Systems, Algorithms, and Networks

Date of Conference:

14-16 Dec. 2009