Advertisement

The CPBT: A Method for Searching the Prefixes Using Coded Prefixes in B-Tree

  • Mohammad Behdadfar
  • Hossein Saidi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4982)

Abstract

Due to the increasing size of IP routing table and the growing rate of their lookups, many algorithms are introduced to achieve the required speed in table search and update or optimizing the required memory size. Many of these algorithms are suitable for IPv4 but cannot be used for IPv6. Nevertheless new efforts are going on to fit the available algorithms and techniques to the IPv6 128 bits addresses and prefixes. The challenging issues in the design of these prefix search structures are minimizing the worst case memory access, processing and pre-processing time for search and update procedures, e.g. Binary Tries have a worst case performance of O(32) memory accesses for IPv4 and O(128) for IPv6. Other compressed Tries have better worst case lookup performance however their update performance is degraded. One of the proposed schemes to make the lookup algorithm independent of IP address length is to use a binary search tree and keep the prefix endpoints within its nodes. Some new methods are introduced based on this idea such as ”Prefixes in B-Tree”, PIBT. But, they need up to 2n nodes for n prefixes. This paper proposes ”Coded Prefixes in B-Tree”, the CPBT. In which, prefixes are coded to make them scalar and therefore suitable as ordinary B-tree keys, without the need for additional node complexity which PIBT requires. We will finally compare the CPBT method with the recent PIBT method and show that although both of them have the same search complexity; this scheme has much better storage requirements and about half of the memory accesses during the update procedures.

Keywords

lookup insert delete LMP LPM SMV 

References

  1. 1.
    Morrison, D.R.: PATRICIA Practical algorithm to retrieve information coded in alphanumeric. Journal of the ACM 15(14), 514–534 (1968)CrossRefGoogle Scholar
  2. 2.
    Sirinivasan, V., Varghes, G.: Faster IP lookup using controlled prefix expansion. ACM Transactions on computer systems 17(1), 1–40 (1999)CrossRefGoogle Scholar
  3. 3.
    Nilson, S., Karlsson, G.: IP address lookup using LC-tries. IEEE Journal of selected Areas in communications 17(6), 1083–1092 (1999)CrossRefGoogle Scholar
  4. 4.
    Gupta, P., lin, S., McKeown, N.: Routing lookups in Hardware at Memory Access Speeds. In: Proceedings of IEEE Infocom, vol. 3, pp. 1240–1247 (1998)Google Scholar
  5. 5.
    Shad, D., Gupta, P.: Fast Incremental updates on ternary-CAMs for routing lookups and Packet classification. In: Proceedings of Hot Interconnects VIII. (2000), IEEE Micro. (2001)Google Scholar
  6. 6.
    Lampson, B., Srinivasan, V., Varghese, G.: IP lookups using multiway and multicolumn search. In: Proceedings of IEEE Infocom, vol. 3, pp. 1248–1256 (1998)Google Scholar
  7. 7.
    Yazdani, N., Min, P.: Prefix Trees: new Efficient Data Structures for Matching Strings of Different length. In: Ideas 2001, pp. 76–85 (2001)Google Scholar
  8. 8.
    Behdadfar, M.: Review and Improvement of Longest Matching Prefix Problem in IP Network, MSC thesis, Isfahan University of Technology (2002)Google Scholar
  9. 9.
    Lu, H., Sahni, S.: A B-Tree Dynamic Router-Table Design. IEEE transactions on computers 54(7), 813–824 (2005)CrossRefGoogle Scholar
  10. 10.
    Sun, Q., Zhaho, X., Huang, X., Jiang, W., Ma, Y.: A Scalable Exact Matching in Balance Tree Scheme for IPv6 Lookup. In: ACM SIGCOMM 2007 data communication festival, IPv6 2007 (2007)Google Scholar
  11. 11.
    Cormen, T., Leiserson, C., Rivest, R.: Introduction to Algorithms. Hill Book Company. McGraw-Hill, New York (1999)zbMATHGoogle Scholar

Copyright information

© IFIP International Federation for Information Processing 2008

Authors and Affiliations

  • Mohammad Behdadfar
    • 1
  • Hossein Saidi
    • 1
  1. 1.Department of Electrical and Computer EngineeringIsfahan University of TechnologyIran

Personalised recommendations