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Traffic concepts for GPRS networks

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Traffic concepts for GPRS networks Powered By Docstoc
					Traffic Engineering Concepts
for Cellular Packet Radio Networks with Quality of Service Support
Presented by Yujing Wu Based on

Peter Stuckmann„s

Public PhD defense on 20/06/2003

Outline

• Motivation and objectives • Traffic models for existing and future applications • Simulation environment GPRSIM • Analytical Traffic Engineering Approaches • GPRS/EDGE performance analysis • Performance of different applications • Traffic engineering • QoS support • Mutual dependency of traffic engineering and traffic
management

Peter Stuckmann‘s thesis work 20/06/2003

2

Motivation: Cost-effective Network Evolution
•
Traffic Engineering and Traffic Management

  

Design and upgrade the network in a cost-effective way Based on traffic-performance relation Service differentiation ensured by admission control and scheduling ->Influence on traffic-performance relation

term traffic QoS parameter resources tool methodology

circuit-switched offered traffic in Erlang blocking probability traffic channels simple formula or table Erlang-B formula

packet-switched amount of data per time in kbit/s throughput, delay,... packet data channels dimensioning graphs or tables simulation results, analytical/algorithmic techniques
3

Peter Stuckmann‘s thesis work 20/06/2003

Evolution from 2G to 3G

Requirements for 3G systems:
high data rate (144kbit/s outdoor and 2Mbit/s indoor) ; asymmetric traffic; packet switched; high spectrum efficiency.
Peter Stuckmann‘s thesis work 20/06/2003

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Assignment of GSM Channels for GPRS
pool of GSM physical channels
GPRS packet data channels
x fixed PDCHs y on-demand PDCHs

• Packet Data Channels (PDCHs) assigned out of pool of GSM
• •
physical channels Fixed PDCHs are permanently available On-demand PDCHs only available if not used for GSM circuit-switched traffic
Peter Stuckmann‘s thesis work 20/06/2003

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Dimensioning Approach
• • • •
Dimensioning graphs for application-specific performance measures Valid for the cell and load scenarios of interest Applicability: only based on user number/ traffic volume in the busy hour Accuracy: derived from realistic models for the protocol stacks, traffic patterns and radio channel

QoS

QoS

resource configuration 3

QoS limit

QoS limit

resource configuration 2

resource configuration 1

acceptable traffic

offered traffic

predicted traffic

offered traffic 6

Peter Stuckmann‘s thesis work 20/06/2003

TE Methodology and Evaluation Scenarios

1. Analytical and algorithmic models:


2. Measurement: 3. Simulation:
  

Lack of details of protocol stacks and realistic traffic model (close-loop control of TCP and heavy tailed traffic)



Lack of tunable traffic load and different protocol options
Detailed implementations of GPRS and Internet protocols Traffic generator for common applications Models of the radio channel

Simulation Scenarios: • Per cell: max PDCH no 8; max IP throughput 80kbits; 1-40 active stations; • Traffic: Web browsing and email with small obj size; not much WAP traffic; no mobility model.
Peter Stuckmann‘s thesis work 20/06/2003

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Traffic Management
• •
Increase performance for best-effort services


  

Coupled RLC/MAC implementation considering urgency of RLC blocks for MAC scheduling MAC scheduler considering link quality
Priority queuing Fairer scheduling algorithms introducing weights for traffic classes
QoS application 2 application 2 QoS limit 2 QoS limit 1

Support application-specific QoS (class differentiation on MAC level)

QoS

QoS limit 2 QoS limit 1

application 1

application 1 capacity gain acceptable traffic offered traffic (aggregate) acceptable traffic offered traffic (aggregate) 8

Peter Stuckmann‘s thesis work 20/06/2003

Outline

• Motivation and objectives • Traffic models for existing and future applications • Simulation environment GPRSIM • Analytical Traffic Engineering Approaches • GPRS/EDGE performance analysis • Performance of different applications • Traffic engineering • QoS support • Mutual dependency of traffic engineering and traffic
management

Peter Stuckmann‘s thesis work 20/06/2003

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Multimedia Traffic Modelling
• Aim • Predicted applications for mobile users
       
Internet (WWW, e-mail, FTP) Wireless Application Protocol (WAP) Streaming (Video & Audio) Video-Conferencing, VoIP Use measurement results for fixed Internet from literature Perform own measurements Use standardized models (e.g. UMTS 30.03) Use market prediction studies

 

definition of user profiles characterization of sessions

• Methodology

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WWW Session / Structure of Web Page

Sdfsadfsda safsdfsafd sadfasfdsaf sdfasfdsaf Sdfsadfsda safsdfsafdSdfsadfsdasaf sdfsafd Sdfsad fsdasafsdfsafdSdfs adfs a safs dfsafd Sdfsadfsda safsdfsafd Sdfsadfs da fgdfg dfg afsdfs afd gfdgs fgsdf sdfg sdg sdfg

Sdfsadfsda safsdfsafd sadfasfdsaf sdfasfdsaf Sdfsadfsda safsdfsafdSdfsadfsdasaf sdfsafd Sdfsad fsdasafsdfsafdSdfs adfs a safs dfsafd Sdfsadfsda safsdfsafd Sdfsadfs da fgdfg dfg afsdfs afd gfdgs fgsdf sdfg sdg sdfg

tread

page 1
picture links text

page n

object 1

tobject

object 2

object m
size m

page 2

Peter Stuckmann‘s thesis work 20/06/2003

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Mosaic Traffic Model [Arlitt and Williamson 1995]

Parameter Pages per session Objects per page [byte] Object size [byte]

Distribution Geometric Geometric

Mean Variance 5 12 s 2.5 20.0 144.0 3.75 1.36 x 10e6 5.2
12

Reading time between pages [s] Exponential

Log2-Erlang-k (k=17) 3700 Transformed Erlang 9.4

Peter Stuckmann‘s thesis work 20/06/2003

Choi‟s Behavioral Model of Web Traffic

• Larger WWW pages with higher object sizes • Not yet suitable for GPRS traffic engineering • Important when performance of wireless Internet access will

be comparable to today„s fixed networks, e.g. with EGPRS or UMTS
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E-mail Traffic Model
• Parameters derived by measurements made at the Lawrence • • •
Berkeley Laboratory (California, USA) by Paxson in 1994 Fixed overhead of 300 byte Bimodal distribution of e-mail sizes  Lower 80% can be interpreted as text-based mails  Upper 20% represents mails with attached files Maximum size 100 kbyte
Distribution Log2-Normal Transformed Normal E-mail size (upper 20%) [byte] Base quota [byte] Log2-Normal Transformed Normal C onstant Mean 1700 10.0 15700 9.5 300

Parameter E-mail size (lower 80%) [byte]

Variance 5.2 x 10e6 2.13 115 x 10e9 12.8 ---

Peter Stuckmann‘s thesis work 20/06/2003

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WAP Traffic Model
• Parameters are depending on the content • Values derived by measurements performed at a WAP gateway
in test operation

 

Suitable for introduction scenarios Will change over the next years (today: 1 kbyte for monochrome decks, 3 kbyte for colored decks)
Distribution Geometric Exponential Log2-Normal Log2-Normal Mean 20.0 14.1 96.1 562.6 Variance 3800 198.8 3.75 x 10e3 0.71 3.5 x 10e5 1.55

Parameter Decks per session Reading time between decks [s] Packet size 'Get Request' [byte] Packet size 'C ontent' [byte]

Transformed Normal 6.34 Transformed Normal 8.60

Peter Stuckmann‘s thesis work 20/06/2003

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Video Streaming Traffic Model
• Traffic model based on three real video sequences • •
coded with the H.263 codec specified by the ITU-T (similar to MPEG) Sequences proposed by the Video Quality Expert Group each one representing a particular group of motion intensity Sequences are randomly concatenated producing a continuous video stream
Q20 C laire C arphone Foreman 10.9 kbit/s 26.7 kbit/s 31.7 kbit/s Offered IP traffic 80-10-10 Mix

Sequences

}

14.39 kbit/s

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Outline

• Motivation and objectives • Traffic models for existing and future applications • Simulation environment GPRSIM • Analytical Traffic Engineering Approaches • GPRS/EDGE performance analysis • Performance of different applications • Traffic engineering • QoS support • Mutual dependency of traffic engineering and traffic
management

Peter Stuckmann‘s thesis work 20/06/2003

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GPRS Architecture

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GPRSIM
GPRSim Load Generator
Manager FTP
HTTP SMTP

Video WAP
WTP

Circuit Switched Generator

Session Arrival Process

• •

TCP IP

UDP

CAC
session mgmt.

Event-driven Simulator based on C++ and SDL Prototype implementations of protocol stacks at

SNDCP LLC (SDL) RLC/ MAC (SDL) Transc.

Channel Mgmt.

SNDCP

LLC Relay
RLC/ MAC (SDL)
BSSGP Frame Relay Gb Downl. GbUplink

LLC (SDL)
BSSGP

•

  

Mobile Station (MS) Base Station (BS) SGSN

Channel Error Model Um

Frame Relay

Transc.

SGSN

MS

BS
G b

• • •

GIST Web Interface Statistical Evaluation
Throughput (S) 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 Funet 0.9 24 RA Slots 0.8 56 RA Slots 88 RA Slots 0.7 0.6 0.5 0.4 0.3 0.2 0.1 1000 3000500070009000 2000 400060008000 10000 Offered Load [byte/s] 1 Blocking Rate

Railway Mobitex 0.2 0.6 0.4 0.81 1.2 1.6 2 1.4 1.8 Offered Load (G)

Peter Stuckmann‘s thesis work 20/06/2003

Stochastic traffic models to generate well-defined traffic load Channel and mobility models Evaluation and graphical representation Validation by measurement
19

Simulation Results

IP user/cell throughput IP datagram delay application response time

session blocking rate,
circuit switch call blocking rate PDCH utilization assigned PDCHs

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Validation I (Analytical TCP Model, Meyer2001])
TCP Client TCP Server

SLOW START

PSH + Data ACK

} }

1st RTT

Transmission time t for a file of size F: ( F  BSS ) t ( F ) N SS ( RTT  TBFsetup )   DLCH RTCP Transition to steady state with the number of Round-trip periods Nss:   R ( RTT  TBF )  
W MSS N SS RTT  init k SS RTCP
 N SS  log      
TCP setup

2nd RTT

Winit MSS log(kss )

STEADY STATE

}

    

Amount of data Bss transmitted in slow start:
3rd RTT

 1  kSS N SS  BSS Winit MSS   1  kSS  

Model Analytical Simulation

WWW (3700 byte) 14.9 kbit/s 17.2 kbit/s

e-mail (1 kbyte) 22.7 kbit/s 22.9 kbit/s
21

Peter Stuckmann‘s thesis work 20/06/2003

Validation II (Measurement)
Downlink IP throughput [kbit/s]

Vodafone NL GPRS measurement settings • CS-2 • 4 fixed PDCHs • Multislot (dl/ul) 3/1
BTS

Downlink IP throughput (FTP) 30 GPRSim Measured

25

20

15

Notebook & GPRS mobile

10

Um
BSC

PPP infrared (WinDump)

5 G b SGSN 0 1 1.5 2 2.5 3 3.5 4 Number of mobile stations 4.5 5

Measurement Point

IP-Backbone
Network

GGSN Gi

External IP-Network Internet Web Server

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Outline

• Motivation and objectives • Traffic models for existing and future applications • Simulation environment GPRSIM • Analytical Traffic Engineering Approaches • GPRS/EDGE performance analysis • Performance of different applications • Traffic engineering • QoS support • Mutual dependency of traffic engineering and traffic
management

Peter Stuckmann‘s thesis work 20/06/2003

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Fluid-flow Model Approach
• Basic concept:
      
Traffic sources are water taps, being randomly turned on and off Regarded network element is a water reservoir with constant depletion rate C Single source: behavior controlled by two-state Markov Chain Multiple sources: Superimposing N equal MMRP„s again leads to an MMRP ON state probability  (activity factor) Mean burst length ENB Transmission rate during ON state h
alpha = 0.187, h = 3272 byte/s , EN_B = 9150 byte 100000 GPRSim with ON/OFF sources GPRSim with WWW sources Fluid-flow Analysis 10000

• Source model: Markov-modulated Rate Process (MMRP) • MMRP parameters:


OFF ON



h EN B

Mean IP Datagram Delay [ms]

1000



 

 1

100

4 5 6 7 Number of MS Peter Stuckmann‘s thesis work 20/06/2003

10 0

1

2

3

8

9 10

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MMAP/G/1 Queue [Vornefeld 2002]
• Arrival Process: analytically tractable representation of Choi„s
WWW model using Marked Markovian Arrival Process:



• • • •



Sojourn times in on and off phase approximated with PH-type distributions (EM algorithm) Poisson arrivals of single IP datagrams during on phase

Accounts for complicated stochastic nature of arrival process Traffic sources can have individual service time distributions No batch arrivals of IP datagrams

Service Process: n-point distribution describing the number of time slots required for transmission of an IP datagram

• Approximation of n-point distribution by cont. PH-dist. (EM alg.)
Peter Stuckmann‘s thesis work 20/06/2003 25

  

Link-level simulations, models of channel coding and radio channel Each IP packet (576 byte) leads to batch arrival of RLC blocks Size of batch determined by applied Coding Scheme (CS)

Result Comparison: System Capacity and CIR
Scenario parameters: • 1 MS • CS-2 • MSC = #PDCHs
Mean IP packet delay [ms]
1e+06

Simulation 2 PDCHs Analysis 2 PDCHs Simulation 4 PDCHs Analysis 4 PDCHs

1e+05

Deviations caused by TCP protocol behavior:  Batch arrivals on IP level  Slow start and congestion avoidance (elastic traffic)

1e+04

1e+03

1e+02

1e+01 5 10 15 20 25 30

Mean C/I [dB]

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Outline

• Motivation and objectives • Traffic models for existing and future applications • Simulation environment GPRSIM • Analytical Traffic Engineering Approaches • GPRS/EDGE performance analysis • Performance of different applications • Traffic engineering • QoS support • Mutual dependency of traffic engineering and traffic
management

Peter Stuckmann‘s thesis work 20/06/2003

27

Performance and system measures
• • • •
Application response time



for each received file (WAP deck, e-mail or WWW page) the difference between the date of request from the client (GET request) and the date of reception at the client is calculated during an ongoing transmission the downlink IP throughput for each user is calculated for each TDMA frame for each received IP packet the difference between the date of transmission (IP data request) and the date of reception (IP data indication) is calculated the quotient of the total amount of received IP bytes in one radio cell divided by the regarded time period equals the offered IP traffic (loss-free system) the quotient of the number of transmitted radio blocks containing data or control information divided by the total number of transmitted radio blocks
Peter Stuckmann‘s thesis work 20/06/2003 28

Downlink IP throughput per user

 

Downlink IP datagram delay

Downlink IP system throughput per radio cell



•

 

Downlink PDCH utilization

General Simulation Parameter Settings
multislot cap. (DL/UL) coding scheme PDCHs fixed PDCHs on-demand C/I [dB] cluster size cell radius [m] MS velocity [km/h] TCP version TCP MSS [byte] TCP maximum window size [kbyte] HTTP version Traffic mix WWW / email Traffic mix WAP / WWW / email Traffic mix Streaming / WWW / email 4/1 CS-2 8 0, 8 12 (BLER = 13.5 %) 3, 7 300, 3000 7, 100 Reno 512 8 1.1 30% / 70% 60% / 12% / 28% 10% / 27% / 63%

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GPRS with Fixed PDCHs

• Maximum user throughput of 22 kbit/s • Maximum system throughput of 56 kbit/s for 8 fixed PDCHs
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Effect of Multislot Capability and C/I

• Effect of multislot capability only visible in situations with low

•

traffic load Low sensitivity of performance to mean C/I

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GPRS with on-demand PDCHs

• Performance degradation only occurring with high coexisting •

speech traffic Effect of lower speech traffic visible in situations with medium GPRS traffic
Peter Stuckmann‘s thesis work 20/06/2003 32

Outline

• Motivation and objectives • Traffic models for existing and future applications • Simulation environment GPRSIM • Analytical Traffic Engineering Approaches • GPRS/EDGE performance analysis • Performance of different applications • Traffic engineering • QoS support • Mutual dependency of traffic engineering and traffic
management

Peter Stuckmann‘s thesis work 20/06/2003

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WAP vs. Conventional Internet Applications (I)

• WAP and e-mail response times remain below 5 s for the whole •
load range for pure traffic scenarios, while WWW exceeds 30 s In the traffic mix scenario (60% WAP, 28% email and 12% WWW), WWW performance increases, while e-mail and WAP performance decreases slightly
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WAP vs. Conventional Internet Applications (II)

• Low throughput performance for WAP because of small deck size • E-mail performance remains stable in pure traffic scenario •
because of low offered traffic per session Similar behavior of WWW and e-mail in traffic mix scenario because of equal load conditions
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Streaming vs. Background Applications (I)

• Streaming performance in traffic mix scenario stable over the • •

whole load range for EGPRS, up to 20 MSs for pure Streaming For GPRS only 5 MSs (pure) and 15 MSs (mix) acceptable for Streaming applications WWW performance only affected in GPRS scenario
Peter Stuckmann‘s thesis work 20/06/2003 36

Outline

• Motivation and objectives • Traffic models for existing and future applications • Simulation environment GPRSIM • Analytical Traffic Engineering Approaches • GPRS/EDGE performance analysis • Performance of different applications • Traffic engineering • QoS support • Mutual dependency of traffic engineering and traffic
management

Peter Stuckmann‘s thesis work 20/06/2003

37

Dimensioning for Fixed and On-demand PDCHs

• Dimensioning graph for fixed PDCHs based on the performance for •
different resource configurations over the offered IP traffic Dimensioning graph for on-demand PDCHs based on the performance for different coexisting speech loads over the offered IP traffic
Peter Stuckmann‘s thesis work 20/06/2003 38

Traffic Engineering Rules

1)Define the QoS target 2)Estimate the number of users per cell 3)Define the offered IP traffic per user 4)Calculate the offered IP traffic per cell 5)Regard the operating point p defined by the QoS

target on the y-axis and the offered traffic per cell on the x-axis and choose the next curve that lies above p 6)Result: Number of fixed PDCHs to be allocated or the acceptable coexisting speech traffic

Peter Stuckmann‘s thesis work 20/06/2003

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Outline

• Motivation and objectives • Traffic models for existing and future applications • Simulation environment GPRSIM • Analytical Traffic Engineering Approaches • GPRS/EDGE performance analysis • Performance of different applications • Traffic engineering • QoS support • Mutual dependency of traffic engineering and
traffic management

Peter Stuckmann‘s thesis work 20/06/2003

40

Dimensioning Graphs without QoS support

• Streaming performance starts to decrease with an offered traffic •
of 20 kbit/s and 4 fixed PDCHs Streaming application can be seen as the critical application
Peter Stuckmann‘s thesis work 20/06/2003

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Dimensioning Graphs with QoS support

• In using DWRR the performance of Streaming applications can be •
increased Depending on the QoS target for lower prioritized applications a resource configuration with 4 fixed PDCHs might be sufficient
Peter Stuckmann‘s thesis work 20/06/2003 42

Conclusions
• Traffic engineering rules for the cost-effective evolution of
cellular packet radio networks

• Advanced traffic management techniques
    

  

Requirements: applicability and accuracy Approach: traffic models and prototype implementation (GPRSIM) Result: Dimensioning graphs for fixed and on-demand configurations
Proposed scheduling algorithms for best-effort services • DPARR very effective and easy to implement Proposed scheduling algorithms for traffic class support • Solution should be based on the operator´s strategy Connection admission control parameterization

• Mutual dependency of traffic engineering and traffic management
Estimate the effects of QoS support and best-effort scheduling on traffic engineering rules Stay inline with network evolution
Peter Stuckmann‘s thesis work 20/06/2003 43

Research Contributions
• Development of a comprehensive GPRS/EDGE emulation tool for

•
•

•
• • • • •

radio interface performance analysis and capacity planning Identification and development of traffic models for existing and future mobile applications Comprehensive performance analysis for GPRS and EDGE networks considering a wide range of applications and system parameters Derivation of radio resources traffic engineering rules for the cost-effective evolution of cellular packet radio networks Development and performance evaluation of advanced QoS management algorithms for cellular packet radio networks Book publication “The GSM Evolution” (Wiley 2002) 2 journal publications More than 20 conference papers 1 patent
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What can we learn from this work? Thoughts on TE of CDMA Cellular Networks
• Can we borrow the TE methodology in this work? • Survey of simulators of CDMA networks (not complete yet): •NS-2, Glomosim, SSF, Telesim: not provide. any other free network simulator? •Several commercial products: e.g. Opnet wireless module, MACdma, Netplan (Motorola), CELLsim (Nomad Access) etc. • At the initial stage, can we build a simple simulator (without implementation of full protocol stack) for a good enough evaluation? Must consider the key features of CDMA systems: interference-limited capacity. • Theoretic analysis is always a good starting point.
Peter Stuckmann‘s thesis work 20/06/2003 45


				
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