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Using sigcomp to compress SIP/SDP Messages Haipeng Jin and AC Mahendran Qualcomm Inc. San Diego, California, 92121, USA IEEE International Conference on Communication (ICC 2005). Speaker: 邱翰銓 Date:2010/10/4. Outline:. Introduction Signaling compression

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Speaker: 邱翰銓 Date:2010/10/4

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Speaker date 2010 10 4

Using sigcomp to compress SIP/SDP MessagesHaipeng Jin and AC Mahendran Qualcomm Inc.San Diego, California, 92121, USAIEEE International Conference on Communication (ICC 2005).

Speaker:邱翰銓

Date:2010/10/4


Outline

Outline:

  • Introduction

  • Signaling compression

  • Overview of Text Compression Algorithms

  • Performance Results

  • Conclusion


Introduction

Introduction

SIP and SDP are used in 3G cellular IP Multimedia

Subsystems (IMS) to perform multimedia session setup and maintenance.

However, both protocols are text-based and have large messages with sizes frequently exceeding several hundred bytes.

SigComp can be used to compress these messages and greatly reduce the call setup and feature invocation delays.


Signaling compression sigcomp

Signaling Compression(sigcomp)

SigComp is offered to applications such as SIP as a layer between the application and an underlying transport. The service provided is that of the underlying transport plus compression.

  • Basic SigComp

  • Dictionaries for SIP/SDP compression

  • Extended operations


Basic sigcomp

Basic SigComp

  • The core feature of SigComp is Universal Decompressor Virtual Machine (UDVM).

  • The UDVM provides decompression functionalities.

  • The UDVM is used to decompress SigComp messages.


Dictionaries for sip sdp compression

Dictionaries for SIP/SDP compression

  • In order to reduce the session setup time as much as

    possible, the SIPPING Working Group in IETF

    introduced a static dictionary for SIP and SDP. The

    dictionary is to be used in conjunction with SIP, SDP

    and SigComp.

  • The static SIP/SDP dictionary is a collection of well known strings that appear in most of the SIP and SDP

    messages.


Extended operations

Extended operations

Extended operations make use of UDVM instructions and the feedback mechanisms offered by SigComp to significantly improve the compression efficiency .

  • Dynamic compression

  • Shared compression


Dynamic compression

Dynamic compression

  • During dynamic compression, a compressor performs

    compression relative to messages that are sent to the

    remote end-point prior to the current message.

  • Shared compression involves compressing the current outgoing message relative to messages received from the remote end-point.

Shared compression


Speaker date 2010 10 4

2

Sigcomp message

Requesting

feedback

1

9

1

3

8

4

Sigcomp message

Returning

feedback

1

6

7

5


Overview of text compression algorithms

Overview of Text Compression Algorithms

  • LZ family of algorithms

    J.Ziv and A.Lempel

  • BWT

    Burrow-Wheeler Transform

  • PPM

    Prediction by Partial Math


Dictionary based

Dictionary-based

  • LZ family of algorithms

  • LZ77

  • LZW

  • BWT(Burrow-Wheeler Transform)

  • RLE(Run-Length Encoding )

Transform-based


Speaker date 2010 10 4

Static Dictionary codiog

A B B B A B A A B

1 0 1 1 1 0 00 1 0


Model based

Model-based

  • PPM (Prediction by Partial Math)

  • Prediction by partial matching (PPM) is an

    adaptive statistical data compression technique

    based on context modeling and prediction.

  • Huffman Coding

  • Arithmetic Coding


Speaker date 2010 10 4

A B C D E

15 7 6 6 5

Huffman coding

A 15

B 7

C 6

D 6

E 5

0

0

39

13

0

1

1

24

0

0

1

A

B

C

D

E

11

1

1

0

0

0

1

1

1

1

1

1

0

1


Arithmetic code

Arithmetic code

這個編碼的方法是將訊息全部壓縮成一個,範圍在[0﹐1)中由裡面的某一個數來代表這整段訊息

說例﹕假設符號 {00﹑01﹑10﹑11}機率分別為{0.1﹑0.2﹑0.3﹑0.4},依據這些機率分成個子隔﹕[0﹐0.1) ﹑[0.1﹐0.3) ﹑[0.3 ﹐0.6)﹑[0.6 ﹐1)

 如果二進位訊息輸入為﹕10 01 11 00


Speaker date 2010 10 4

1

0.33

0.33

0.3192

從[0.318,0.3192〉中選擇一個數代表輸出:0.3185,所以可以知道0.3185就是代表的編碼過後的訊息。

0.6

0.3

0.1

0.318

0.318

0

0.3


Performance results

Performance Results


Compression performance for concatenated sip messages size 7161bytes

Compression Performance for ConcatenatedSIP Messages, size = 7161Bytes


The following notations are used to indicate what states are used in the compression

The following notations are used to indicate what states are used in the compression:

  • SD: static dictionary

  • SUD: both static and user dictionary

  • DC: dynamic compression

  • SC: shared compression

  • SDC: both dynamic and shared compression


We use the following notations to indicate what messages are used

We use the following notations toindicate what messages are used:

  • M: message with the maximum size

  • L: latest sent or received message

  • ML: both the message with the maximum size and

    the latest message


Effects of user defined dictionary on individual messages deflate with dc

Effects of User Defined Dictionary onIndividual Messages (Deflate with DC)


Sigcomp for ims call setup messages

SigComp for IMS Call Setup Messages


Conclusion

Conclusion

  • It is shown that dictionary-based compression schemes are the ones best suited for SigComp because of their low complexity, fast speed and low memory requirement.

  • Static and user-defined dictionaries are very useful for compressing the first several messages in a SIP dialog.


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