1 / 16

A Heuristic and Hybrid Hash-based Approach to Fast Lookup

A Heuristic and Hybrid Hash-based Approach to Fast Lookup. Author : Gianni Antichi, Andrea Di Pietro, Domenico Ficara, Stefano Giordano, Gregorio Procissi, Fabio Vitucci Publisher: 15th IEEE Workshop on High Performance Switching and Routing (HPSR), 2009 Presenter: Hsin-Mao Chen

abbott
Download Presentation

A Heuristic and Hybrid Hash-based Approach to Fast Lookup

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. A Heuristic and Hybrid Hash-based Approach to Fast Lookup Author: Gianni Antichi, Andrea Di Pietro, Domenico Ficara, Stefano Giordano, Gregorio Procissi, Fabio Vitucci Publisher: 15th IEEE Workshop on High Performance Switching and Routing (HPSR), 2009 Presenter: Hsin-Mao Chen Date:2009/9/16

  2. Outline • Introduction • Background • H-cube Idea • H-cube Data Structures • H-cube Search • Performance

  3. Introduction • From lookup tables, there is a large prefix disparity of density within each lookup table. • The IP lookup problem can be the adoption of a Heuristic and Hybrid Hash-based technique.

  4. Introduction • Heuristic and Hybrid Hash-based (H-cube), where different data structures store different prefix ranges according to their density.

  5. Background • Perfect Hash Function (PHF) A perfect hash function maps a static set of n keys into a set of m integers without collisions, where m is greater than or equal to n.

  6. Background • Minimal Perfect Hash Function (MPHF) A minimal perfect hash function is the same as perfect hash function. If m is equal to n, the function is called minimal perfect hash function.

  7. H-cube Idea

  8. H-cube Data Structures • 23-24(MPHF24) (1)For the range, we use a MPHF realized by means of Blooming Trees. Avoiding collision, each entry of such a table stores also the first 24 bits of the relative IP destination address. (2)To be able to use such a binary search, the range 25-32 we insert in the MPHF24 a 24 bit-long rule and a bit b which signals whether more specified rules are in the range 25-32.

  9. H-cube Data Structures • 17-22,25-32(PHF22,PHF32) For the range, we use a PHF obtained by double hashing. Each entry stores the first 22(32) bits of the relative IP address to solve potential collisions.

  10. H-cube Data Structures • 1-16(DA16) In this range, the number of possible rules is limited(216), a direct addressing table can be used.

  11. H-cube Data Structures

  12. H-cube Search

  13. Performance • Constructing time and memory

  14. Performance • Average number of accesses in SRAM and scratchpad for lookup

  15. Performance • Memory consumption

  16. Performance • Memory accesses

More Related