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Performance Improvement of Two-Dimensional Packet

Classification by Filter Rephrasing

Department of Computer Science and Information Engineering National Cheng Kung University, Taiwan R.O.C.

Authors: Pi-Chung Wang, Chun-Liang Lee, Chia-Tai Chan, and Hung-Yi Chang

Publisher: IEEE/ACM TRANSACTIONS ON NETWORKING, VOL. 15, NO. 4, AUGUST 2007

Present: Yu-Tso Chen

Date: February, 12, 2008

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Outline

1. Introduction 2. Definitions and problem description 3. Tuple Reorganization by Filter Rephr

asing 4. Performance Evaluation

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Introduction

Our idea is inspired from the observation that the performance of the tuple-based schemes ties to the length distribution of the prefixes.

Hence, we exploit the property of prefix nesting by encoding the prefixes as well as the filters to revise the length distributions.

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Outline

1. Introduction 2. Definitions and problem descriptio

n 3. Tuple Reorganization by Filter Rephr

asing 4. Performance Evaluation

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Algorithms for Tuple Space Search

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Rectangle search algorithm

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Relationship Between filters and markers

The size explosion is caused by an unbalanced distribution of filter lengths

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Length Distribution of Original Filters

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Prefix nesting distribution of the routing table

The number of nested prefixes for each routing prefix in the existing routing tables from some major network access points

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Outline

1. Introduction 2. Definitions and problem description 3. Tuple Reorganization by Filter Rep

hrasing 4. Performance Evaluation

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Basic Prefix Encoding maximal 7 (=2+3+2) bits are required to

represent the original prefixes, but the number of distinct lengths is reduced from 7 to 3.

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Exclusive Prefix Encoding

“Level II” IDs could be reduced to 2 bits and the maximal length is reduced to 6.

separate the bitstreams based on their concatenated prefixes at each level

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Compare the lengths of the encoded prefixes

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Length Distribution of Encoded Filters

The encoded filters only occupy seven tuples The markers are inserted into only four tuples

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Search Procedure and Implement

Heuristic methods Select the field with more distinct prefix l

engths as the horizontal axis in the tuple space and perform prefix encoding only on this field.• Only one field is encoded, only one BMP look

up is required.

Choose the field of destination prefix as the horizontal axis

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Handling Dynamic Filters

Propose a hybrid approach by maintain two tuple spaces• 1) For encoded filters

• 2) For original filters

New filters is only inserted into the data structure of the tuple pruning search.• Two location lists, one for all filters and one fo

r the new filters.

• New filter inserted into both location lists.

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Insertion of Updates

Rectangle search and tuple pruning search are performed simultaneously.

Once the lookup performance of tuple pruning search degrades to threshold, the new filters are merged into a rect-angle search and trigger reconstruction.

During the period, the tuple pruning search looks up all filters by referring to the location list of all filters.

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Filter Updates

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Deletion of Updates

The pre-computation of the least-cost matching filter is modified to “pre-compute and record all matching filters.”• Listed according to their cost in ascending order.

Once B is deleted, B and best matching filter A are inserted into the tuple pruning search.

And B is recognized as deleted.

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Example of Filter Deletion

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Outline

1. Introduction 2. Definitions and problem description 3. Tuple Reorganization by Filter Rephr

asing 4. Performance Evaluation

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Comparison with Rectangle Search

Hash table and hash entry present the required storage for 1-D BMP lookups.

NLANR routing table

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Performance Comparisons

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Filter Length Distribution of synthetic Filter Databases

Original filters

Encoded filters, marker, and 1-D hash entries

Filters and markers

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Comparison with Rectangle Search(cont.)

Synthetic filter databases

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Performance Comparisons

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Performance Comparison with Existing Schemes