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Heuristic and Hybrid Hash-based Approach for Efficient IP Lookup

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abbott
16 diapositives · 331 Views · Aug 21, 2014

This paper presents a novel Heuristic and Hybrid Hash-based approach, termed H-cube, to optimize IP address lookup. By utilizing varying data structures that correspond to different prefix density ranges, the H-cube improves efficiency in memory consumption and access time. Key techniques include the implementation of Perfect and Minimal Perfect Hash Functions, alongside Blooming Trees for collision avoidance and direct addressing for limited rule ranges. Performance evaluations demonstrate significant enhancements in lookup speed and memory efficiency, addressing the critical challenges in high-performance networking.

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Heuristic and Hybrid Hash-based Approach for Efficient IP Lookup
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  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