Network Traffic #6 - University of Kansas

1Traffic

Network Traffic #6

Victor S. FrostDan F. Servey Distinguished Professor

Electrical Engineering and Computer ScienceUniversity of Kansas2335 Irving Hill Dr.

Lawrence, Kansas 66045Phone: (785) 864-4833 FAX:(785) 864-7789

e-mail: [email protected]://www.ittc.ku.edu/

Section 4.7.1, 5.7.2

2Traffic

Traffic CharacterizationGoals to:

Understand the nature of what is transported over communications networks. Use understanding to improve network design

Traffic Characterization describes the user demands for network resources

How often a customer:– Requests a web page– Down loads an MP3– Makes a phone call

Size/length – Web page– Song– Phone call

3Traffic

Voice Traffic: Aggregate Traffic

Requests for network resources from a large population of users.

Large Populationof Users System

SwitchingSystem

***

1

M

***1 N

Large Populationof Users

4Traffic

Voice Traffic:Aggregate Traffic

Arrival RateNumber of requests/time unit

– Calls/sec

Holding Time, length of time the request will use the network resources

Min./callsec/packet

Arrival rate = λ

Average Holding Time =hT

5Traffic


Traffic Intensity (load)Product of the average holding time and the arrival rate

Units of Traffic IntensityErlangsCCS [1 CCS is 100 call sec/hr ]1 Erlang = 36 CCS

Traffic intensity is specified for the 'Busy Hour'

hT Intensity Traffic λρ ==

6Traffic


A telephone line busy 100% of the time= 1 Erlang

A telephone busy 6 min/hour is how much traffic

0.1 Erlang100 telephones busy 10% of the time is how much traffic10 Erlangs

7Traffic


A telephone busy 100 sec (Centi call Seconds, CCS) per hour = 1

CCSArrival rate = 1 call/hourAverage holding time = 100 secSo

(100 sec/call)*(1 hour/3600sec)*(1call/hour) = 1/36 Erlangs

= 1 CCS36 CCS = 1 Erlang

8Traffic


Traffic is RandomHolding timeInterarrival time (time between calls)

Common assumptions for probability density function (pdf) for

Holding time ~ exponentialInterarrival time ~ exponential

Section 4.7.1 and A.1.1

9Traffic


Interarrival Histogram

10Traffic


P [ Th< t ] = 1 - e - µ t for t > 0 and 0 for t < 0

T h =1

µ

P [T I < t ] = 1 - e -λ t for t > 0 and 0 for t < 0

T I = Interarrival time

11Traffic


Time

TI

Time

Th

12Traffic

Voice Traffic:Aggregate Traffic-Diurnal Variation

13Traffic

Voice Traffic: Individual voice source

Speech inactivity factor

time

Talkspurt Talkspurt Talkspurt

SilenceSilence

14Traffic


Talkspurt durationRandomAverage duration ---> 0.350 s to 1.3 sExponentially distributed

Silence period RandomAverage duration ---> .58s to 1.6sExponentially distributed

Speech activity factor 0.35 to 4.36

Section 5.5.2

15Traffic


Digital Speech Interpolation (DSI) (Section 5.7.2)

Uses “silence detection” Multiplex at the talkspurt levelView as call set up at talkspurt level~Doubles the capacityAnalog version called “Time Assignment and Speech Interpolation (TASI)”Packet Voice with silence detectioneffectively does DSI

16Traffic


Signal redundancies Voice codingPulse code modulation (G.711) PCM 8bits/sample @ 8000 samples/sec 64kb/sAdaptive Differential PCM 32kb/sLinear Predictive 2.4 to 16 kb/sFor Voice over IP: rate < 8kb/s

G.723.1 is emerging as a popular coding choice. G.723 is an

algorithm for compressed digital audio over telephone lines.

17Traffic

Comparison of popular CODECs

LowGoodHigh8G.729 CS-ACELP

LowGoodVery high16G.728 LD-CELP

Very lowGood (40)Fair (24)

Low40/32/24G.726 ADPCM

HighGood (6.4)Fair (5.3)

Moderate 6.4/5.3G.723 MP-MLQ

N/AExcellentNot required64 (no compression)G.711 PCM

Added delayResultant voice quality

Required CPU resources

Compressed rate (Kbps)

Compression scheme

There is no "right CODEC". The choice of what compression scheme to use depends on what parameters aremore important for a specific installation.

In practice, G.723 and G.729 are more popular that G.726 and G.728.

For details of other VoIP Codecs see:http://www.zytrax.com/tech/protocols/voip_rates.htm

18Traffic


Example: How many calls can be supported on a system with the following parameters?

TDMCoding rate/voice channel = ADPCMDSI Line rate = 1.536 Mb/s

(note a T1/DS1 line is 1.544 Mb/s)

Number of ADPCM channels = (1.563 Mb/s)/(32 Kb/s) = 48

With DSI you get 2 calls/channel = 96

19Traffic

Voice Traffic: Packet VoiceExample: Parameters for a packet voice system

1 sourceSample rate = 8000 samples/sec (ITU G.711)8 bits/sample (1 byte/sample)8 ms/packet Critical parameterLink rate = 10 Mb/sbytes/packet = (8ms/packet)*(8000 bytes/sec)=

64 Bytes [assuming no overhead bytes]Holding time/packet = (64 bytes/packet)*8bits/byte)/(10 Mb/s)= 51.2us

20Traffic

Voice Traffic: Packet Voice51.2 us

8 ms time

51.2 us

X ms time

8 ms

Transmit at a Constant Bit Rate (CBR)

X not equal 8ms because of network delaysIf X is too big packet may arrive too late for play out

Receive with variable interpacket arrival times

21Traffic

Voice Traffic: Packet Voice

51.2 us

8 ms time

1 2 N 1

Perfect Multiplexing of N VoIP sources

22Traffic

Voice Traffic: Packet VoicePacket voice looks like a steady flow or Constant Bit Rate (CBR) trafficHowever, voice can be Variable Bit Rate or VBR

“silence detection”Variable rate coding

Problem: After going through the network the packets will not arrive equally spaced in time. Thus playback of packet voice must deal with variable network delays

23Traffic

Voice Traffic: Packet VoiceAssume network delay is uniformly distributed between [25 ms, 75 ms]

Same as having a fixed propagation delay of 25 ms with a random network delay uniformly distributed between [0 ms, 50 ms]

Note receiver will run out of bytes to play back after 8 ms.Solution:

Buffer 50 ms (or 8 packets or 2.8 Kbits)Worst case, receiver will run out of data just as a new packet arrives

24Traffic

Voice Traffic: Packet VoiceNew problem: networks delays are unknown and maybe unboundedA voice packet may arrive at 85 ms and be too late to be played back

Late packets are droppedLast packet may be played out in dead time

Packet voice (video) schemes must be able to deal with variable delay and packet loss

25Traffic

Voice Traffic: Packet VoiceG.723.1 is a voice codingstandard, linear predictioncompressionalgorithm

From: Performance Evaluation of the Architecture for End-to-End Quality-of-Service Provisioning,Katsuyoshi Iida, Kenji Kawahara, Tetsuya Takine, and Yuji Oie, IEEE Communications Magizine, April 2000

26Traffic

VoIP Quality

G.114_F010 100 200 300 400 50050

60

70

80

90

100

Nearly allusers

dissatisfied

Many usersdissatisfied

Some usersdissatisfied

Userssatisfied

Usersvery satisfied

Mouth-to-ear-delay/ms

E-m

odel

ratin

g R

ITU-T Recommendation G.114-One-way transmission time, May 2003

27Traffic

VoIP-Factors in End to End DelayAssumption: maximum delay from ear-to-ear needs

to be on the order of 200 -300 ms

From: http://www.protocols.com/papers/voip2.htm

ITU G.114 - < 150 ms acceptable for most applications- [150ms, 400 ms] acceptable for international- > 400 ms unacceptable

28Traffic

VoIP-Factors in End to End Delay

Example: Delay Budget (depends on assumptions)Formation of VoIP packet at TX ~ 30 ms

20ms of voice/packet is default for Cisco 7960 routerOther VoIP packet processing ~70 ms

(see: http://www.rmav.arauc.br/pdf/voip.pdf)Propagation ~20 msExtraction of VoIP packet at Rec ~30 msJitter Buffer ~ 100 ms

Compensates for variable network delayTotal 250 ms

Ref: http://www.lightreading.com/document.asp?site=lightreading&doc_id=53864&page_number=6

29Traffic

Data Traffic: General Characteristics

Highly variableNot well knownLikely to change as new services and applications evolve.

30Traffic


Highly bursty, where one definition of burstyness is:

Burstyness = Peak rateAverage rate

31Traffic


Example: During a typical remote login connectionover a 19.2kb/s modem a user types at a rate of 1 symbol/sec or 8 bits/sec and then transfers a 100 kbyte file. Assume the total holding time of the connection is 10 min.

What is the burstyness of this data session?

32Traffic


The time to transfer the file is (800,000 bits)/(19,200 b/s) = 41 sec.So for 600 - 41sec = 559 sec. the data rate is 8 bits/sec or 4,472 bits were transferred in 559 sec. Thus in 600 sec. 4,472 + 800,000 bits were transferred, yielding a average rate of:804,472 bits/600 sec = 1,340 bits/sec.The peak rate was 19.2 Kb/s so the burstyness for this data session was:

19,200/1,340 = 14.3

33Traffic


Session Interarrivals

Session Duration

Packet Interarrivals

Packet Lengths

CallArrival

CallDuration

VoIPPacket Arrivals

VoIPPacket Lengths

34Traffic


User Burst

Idle TimeComputer Burst

Think Time

User Burst

Idle TimeComputer Burst

Asymmetric Nature of Interactive Traffic

This Asymmetric property has lead to asymmetric services

35Traffic


In Time Division Multiplexing (TDM) user must wait for turn to use link. Statistical Multiplexing (Stat Mux)

Note high burstness leads to “long” idle timesBy transmitting the ‘bursts’ on demand the link can be efficiently shared.To help insure fairness break the ‘burst’into packets and transmit on a packet basis

36Traffic

TDM vs Stat Mux

Server

Dwell time = one time slotUser 1

User N

Server

User 1

User N

37Traffic


Element lengthMessagePacketCell

Arrival rateMessage/secPackets/secCells/sec

38Traffic


Traffic intensity (< 1 with one server)ρ = λ T

h

where

T h=

Average Packet Length in Bits

Link Capacity in Bits / sec=

L

C

Average Packet Length in Bits = L

Link Capacity in Bits / Sec = C

39Traffic


Standard AssumptionsMessage length has an exponential pdfInterarrival time has an exponential pdf

Data was taken from special traces in http://www.nlanr.net/Data was captured at the Internet Uplink of the University of Auckland by the Wand Research group in the year 2000. The tap was installed on an OC-3 link.

40TrafficFrom: Long-Range Dependence Ten Years of Internet Traffic Modeling, IEEE Internet Computing, Sept, Oct, 2004

Figure 2. Complementary Cumulative Distribution Function ofpacket interarrival times over two backbone networks. For OC48link traces on (a) January 2003, backbone 1, and (b) January 2004,backbone 2, as well as for (c) the BC-pAug89 1989 Bellcore trace,the y-axis is plotted in logarithmic scale.We can approximate thedistributions of OC48 traces with an exponential distribution(straight line in log-linear scale), but the BC-pAug89 data set clearlydeviates from the exponential distribution.

41Traffic

KU/ITTC has collected aggregate traffic data from Sunflower Datavision

42Traffic

From the Internet into DatavisionMean = 8.876 Mb/s.

Maximum = 18.952 Mb/s

From Datavision out to the Internet Mean = 5.133 Mb/s.


43Traffic

From the Internet into DatavisionMean = 8.555 Mb/s.


From Datavision out to the Internet Mean = 4.343 Mb/s.


44Traffic

Data Traffic: Conclusions

Very burstyProblems with traffic modeling

Rapidly evolving applicationsComplex network interactions

Issues:Do models match “real” traffic flows?Are the performance models based on specific traffic assumption robust

45Traffic

Video: Analog video

Bandwidth ~ 4 MhzUncompressed rate 64 Mb/sComponents of the signal

LuminanceChrominanceAudioSynchronization

46Traffic

Digital Video: JPEG"Joint Photographic Expert Group". Voted as international standard in 1992. Suitable for color and grayscale images, e.g., satellite, medical applications.Targeted for still imagesCapable of reducing continuous true color or gray-scale images to less than 5% of their original sizeJPEG (GIF and MPEG) define the compression as well as the video data format

Section 12.3

47Traffic

Digital Video: MPEGMoving Pictures Experts GroupCompresses moving pictures taking advantage of frame-to-frame redundanciesMPEG Initial Target: VHS quality on a CD-ROM (320 x 240 + CD audio @ 1.5 Mbits/sec)

48Traffic

Digital Video: MPEGConverts a sequence of frames into a compressed format of three frame typesI Frames (intrapicture)P frames (predicted picture)B frames (bidirectional predicted picture)

49Traffic

Digital Video: MPEG

Exploits frame to frame redundancies

50Traffic

Frame sizesfor talking head video.

Frame sizes foraction video.

From:Transmission of MPEG-2 Video Streams

over ATM Steven Gringeri, et.al, IEEE Multimedia, 1998

Each frame would be transported using multiple packets

51Traffic

MP3- MPEG Layer 3 AudioMPEG specifies a family of three audio coding schemes, Layer-1,-2,-3, Each Layer has and increasing encoder complexity and performance(sound quality per bitrate) The three codecs are compatible in a hierarchical way, i.e. a Layer-N decoder is able to decode bit stream data encoded in Layer-N and all Layers below NThe MP3 compression algorithm is based on a complicated psycho-acoustic modelThe majority of the files available on the Internet are encoded in 128 kbits/s stereo. A high quality file is 12 times smaller than the original CDs can be created that contain over 160 songs and can play for over 14 hours on a PC.Music can be efficiently stored on a hard disk and then directly played

from there

52Traffic

Digital Video: MPEGCompression ranges:

30-to150-to-1

MPEG is evolvingMPEG 1MPEG 2MPEG 4MPEG 7

53Traffic

Digital Video: MPEG-4

Audio-video coding for “low bit-rate”channels,

InternetMobile applications

MPEG-4 is a significant change from MPEG-2Scalability is a key feature of MPEG-4MPEG-4 contains a Intellectual Property rights (IPR) management infrastructure

54Traffic

Digital Video: MPEG-4Object based: Audio-visual objects (AVO)AVO are described mathematically and given a position in 2D or 3D spaceViewer can change vantage point and update calculations done locallyNo distinction between “natural” and “synthetic” AVOs: treats two in an integrated fashionEach AVO is represented separately and becomes the basis for an independent streamEach AVO is reusable, with the capability to incorporate on-the-fly elements under application controlContent transport with QoS for each component

55Traffic

ConclusionsNetwork traffic defines the demands for network resourcesNetwork traffic is dynamic

Changes with the deployment of new applicationTime of day

Models for network traffic are continuing to evolve

Network Traffic #6 - University of Kansas

Documents

Transcript of Network Traffic #6 - University of Kansas