A memory efficient hashing by multi predicate bloom filters for packet classification
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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. Outline. Related Works – Basic Bloom filter

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A memory efficient hashing by multi predicate bloom filters for packet classification

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


Outline
Outline for Packet Classification

  • 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


Related works basic bloom filter

0 for Packet Classification

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.

……

…………………


Related works basic bloom filter1
Related Works for Packet Classification – 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


Related works basic bloom filter2
Related Works for Packet Classification – Basic Bloom filter

  • Linear property

    • Given f, n is linearly proportionate to m.

  • Reverse Exponential Property

    • Given n, m is exponential effect on f.


Outline1
Outline for Packet Classification

  • 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


Mbht benefits
MBHT - Benefits for Packet Classification

  • 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.


Mbht architecture
MBHT - Architecture for Packet Classification

01


Mbht insert
MBHT - Insert for Packet Classification

  • Partition address space.

    • n elements

    • Base-b number system,

      → digits

    • Address with r digits of x bits :

      is covered by


Mbht insert1
MBHT - Insert for Packet Classification


Mbht insert2
MBHT - Insert for Packet Classification

  • Transform to base-4 number system

    • Fewer columns in each address space.

    • Not affect addressing off-chip memory.


Mbht insert3
MBHT - Insert for Packet Classification

  • Memory usage :

    • .


Mbht insert4
MBHT - Insert for Packet Classification

  • Memory change rate with f and n.

    →larger base- is advantageous because x times on-chip memory saving.

    (hard in real hardware.)


Mbht insert5
MBHT - Insert for Packet Classification

  • Algorithm :

→ Θ(1)

Execute each column

Set bloom filter

→Θ(1)


Mbht query
MBHT - Query for Packet Classification

  • Algorithm

    • Consider only on-chip operation.

    • Need to be called twice on l-MBHT and r-MBHT

    • Θ(1)


Mbht delete
MBHT - Delete for Packet Classification

  • Algorithm

    • Need to be called twice on l-MBHT and r-MBHT

    • Θ(1)


Outline2
Outline for Packet Classification

  • 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


On off chip memory usage
On/Off-chip memory usage for Packet Classification

  • Memory efficiency ratio :

R = # of layers

B = # of bits in one layer

(in FHT memory consumption, 4 is bits for counter.)


On off chip memory usage1

Better memory efficiency ratio begins at b = for Packet Classification

On/Off-chip memory usage


Average access of search
Average access of search for Packet Classification

The lower successful search rate,

the better access time performance


Url switching
URL switching for Packet Classification

on-chip memory reduction

1.7 times to LHT

2 times to FHT

AAS* = average access for a successful search


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