A Memory-Efficient Hashing by Multi-Predicate Bloom Filters for Packet Classification

1. A Memory-Efficient Hashing by Multi-Predicate Bloom Filters for Packet Classification Author: Heeyeol Yu; Mahapatra, R.; Publisher: IEEE INFOCOM 2008 Presenter: Yu-Ping Chiang Date: 2008/12/17

2. Outline • Related Works – Basic Bloom filter • Multi-predicate Bloom-filter Hash Table (MBHT) • Benefits • Architecture • Insert • Query • Delete • Analysis and Simulation • On/Off-chip memory usage • Average access of search • URL switching

3. 0 1 2 3 m-1 …… …… …… 1 1 1 Related Works – Basic Bloom filter • set S = • n elements. • represented in m bits array, initially set to 0. • using k independent hash functions mapping. …… …………………

4. Related Works – Basic Bloom filter • The probability that a bit is 0 • Probability of false-positive • In requirement of by [17] A. Broder and M. Mitzenmacher, “Network Applications of Bloom Filters: A Survey,” pp. 485–509, 2002. [Online]. Available:citeseer.ist.psu.edu/broder02network.html

5. Related Works – Basic Bloom filter • Linear property • Given f, n is linearly proportionate to m. • Reverse Exponential Property • Given n, m is exponential effect on f.

6. Outline • Related Works – Basic Bloom filter • Multi-predicate Bloom-filter Hash Table (MBHT) • Benefits • Architecture • Insert • Query • Delete • Analysis and Simulation • On/Off-chip memory usage • Average access of search • URL switching

7. MBHT - Benefits • On-chip • Reduce memory size in base- number system by x times compares to that of base- number system. • Insert and delete operations are done in constant time in parallel. • Off-chip • Saves memory by removing linked list mechanism. • Does not save the duplicate items.

8. MBHT - Architecture 01

9. MBHT - Insert • Partition address space. • n elements • Base-b number system, → digits • Address with r digits of x bits : is covered by

10. MBHT - Insert

11. MBHT - Insert • Transform to base-4 number system • Fewer columns in each address space. • Not affect addressing off-chip memory.

12. MBHT - Insert • Memory usage : • .

13. MBHT - Insert • Memory change rate with f and n. →larger base- is advantageous because x times on-chip memory saving. (hard in real hardware.)

14. MBHT - Insert • Algorithm : → Θ(1) Execute each column Set bloom filter →Θ(1)

15. MBHT - Query • Algorithm • Consider only on-chip operation. • Need to be called twice on l-MBHT and r-MBHT • Θ(1)

16. MBHT - Delete • Algorithm • Need to be called twice on l-MBHT and r-MBHT • Θ(1)

17. Outline • Related Works – Basic Bloom filter • Multi-predicate Bloom-filter Hash Table (MBHT) • Benefits • Architecture • Insert • Query • Delete • Analysis and Simulation • On/Off-chip memory usage • Average access of search • URL switching

18. On/Off-chip memory usage • Memory efficiency ratio : R = # of layers B = # of bits in one layer (in FHT memory consumption, 4 is bits for counter.)

19. Better memory efficiency ratio begins at b = On/Off-chip memory usage

20. Average access of search The lower successful search rate, the better access time performance

21. URL switching on-chip memory reduction 1.7 times to LHT 2 times to FHT AAS* = average access for a successful search