Efficient IP table lookup via adaptive stratified trees with selective reconstructions (Articolo in rivista)

Type
Label
  • Efficient IP table lookup via adaptive stratified trees with selective reconstructions (Articolo in rivista) (literal)
Anno
  • 2008-01-01T00:00:00+01:00 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
  • 10.1145/1227161 (literal)
Alternative label
  • [1] Pellegrini M., [1] Fusco G. (2008)
    Efficient IP table lookup via adaptive stratified trees with selective reconstructions
    in ACM journal of experimental algorithmics; ACM Press, New York (Stati Uniti d'America)
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • [1] Pellegrini M., [1] Fusco G. (literal)
Pagina inizio
  • 1 (literal)
Pagina fine
  • 28 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
  • 12 (literal)
Rivista
Note
  • Scopu (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • [1] CNR-IIT, Pisa, Italy (literal)
Titolo
  • Efficient IP table lookup via adaptive stratified trees with selective reconstructions (literal)
Abstract
  • IP address lookup is a critical operation for high-bandwidth routers in packet-switching networks, such as Internet. The lookup is a nontrivial operation, since it requires searching for the longest prefix, among those stored in a (large) given table, matching the IP address. Ever increasing routing table size, traffic volume, and links speed demand new and more efficient algorithms. Moreover, the imminent move to IPv6 128-bit addresses will soon require a rethinking of previous technical choices. This article describes a the new data structure for solving the IP table lookup problem christened the adaptive stratified tree (AST). The proposed solution is based on casting the problem in geometric terms and on repeated application of efficient local geometric optimization routines. Experiments with this approach have shown that in terms of storage, query time, and update time the AST is at a par with state of the art algorithms based on data compression or string manipulations (and often it is better on some of the measured quantities). (literal)
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