TEAM 2: 802.11 WLAN MAC layer modeling

Mentor: Radu V. Balan

802.11 WLAN MAC Layer Modeling

Lisa Driskell Yejun Gong Xueying HuPurdue University Michigan Technological

UniversityUniversity of Michigan

Rashi Jain Mechie NkenglaNew Jersey Institute of

TechnologyUniversity of Illinois-Chicago

August 17, 2007

TEAM 2: 802.11 WLAN MAC layer modeling

Outline

v Objectivev Overviewv ns-2v Results (.nam)v Results (.tr)v Conclusionsv Future Objectives

TEAM 2: 802.11 WLAN MAC layer modeling

Project Objective: Analyze the relationships of the parameters for a modified EO Markov model and validate the model under certain assumptions with (ns2) network simulations.

Objective

TEAM 2: 802.11 WLAN MAC layer modeling

Overview

MAC MAC

Packets Generated

IFQ

Agent/UDP Transmission

Agent/NullFinal

Destination

System Layout

TEAM 2: 802.11 WLAN MAC layer modeling

p

Overview

TEAM 2: 802.11 WLAN MAC layer modeling

Prob (packet dropped due to collision) =

Avg # of retries = )p1(p1

p L−−

1Lp +

pL(1-p) + pLp

…pb(1-p)…p2(1-p)p(1-p)1-pProbability

L…b…210Exact # retries

Previous Analysis of Markov Model

Overview

TEAM 2: 802.11 WLAN MAC layer modeling

• Analyzed Markov model• Compared analytical results with computed

results to verify the analysis.• Use analytical results compared with network

simulations to determine whether the system can indeed be modeled with a Markov chain.

Outline

Overview

TEAM 2: 802.11 WLAN MAC layer modeling

Ns-2

Ns-2 simulator

Ns-2 SimulatorInput

.tcl file

.tr file

Output Trace File

.nam file

TEAM 2: 802.11 WLAN MAC layer modeling

Ns-2

Ns-2 simulator

• Closely relates to real world.

• A packet-based event-driven simulation.

• Can incorporate the wireless mechanism

• Allows for mobile stations

• Provides animations

TEAM 2: 802.11 WLAN MAC layer modeling

Ns-2

Example of a ns2 simulation

TEAM 2: 802.11 WLAN MAC layer modeling

Nam Trace

Nam Trace Format<type> -t <time> -s <source id> -d <destination id> -p <pkt-type> -e <extent> -c <conv> -a <packet attribute> -i <id> -k <trace level>

0~#pkts

i

AGT, MAC

k

cbr,ACK

0~NSTA

0~simTime

h, r, d, +, -

psttype

TEAM 2: 802.11 WLAN MAC layer modeling

Nam Trace : Medium Busy Time

The packet is on the air from t, if at ttype=‘h’ AND k=‘MAC‘ (Hop)

The medium is busy in[t, t+pktTransTime]

The medium is busy in collision case.

TxFrame 1

TxFrame 2

BusyCollision

TEAM 2: 802.11 WLAN MAC layer modeling

Nam Trace : Medium Busy Time

Medium Busy Time ? , if NSTA ? < critical numberMedium Busy Time ? , if NSTA ? > critical number

TEAM 2: 802.11 WLAN MAC layer modeling

1-Hop# cket)Retries(pa# with

ThisNodepktsSendTo#

packet thisof Retries#(node)AvgRetries hisNodepktSendToT

=

=∑Numerical:

Theoretical:

But how to find p?

retries. #max theis L andy probabilitcollision theis p where

)p1(*p-1

p(node)AvgRetries L−=

TEAM 2: 802.11 WLAN MAC layer modeling

1LcpktTransSuColpktDropDue

ColpktDropDuep +

+=

pktSend=

pktDropDueCol+

pktDropDueQueue+

pktDropDueEnd+

pktTransSuc

Type=‘h’ AND k=‘AGT’ AND p=‘cbr’

Type=‘d’ AND k=‘IFQ’ AND p=‘cbr’

LastHopTime+pktTransTime>sucTime

Type=‘r’ AND k=‘AGT’ AND p=‘ACK’

TEAM 2: 802.11 WLAN MAC layer modeling

Results (.nam)

Average number of retries

TEAM 2: 802.11 WLAN MAC layer modeling

Results (.nam)

Average number of retries

TEAM 2: 802.11 WLAN MAC layer modeling

Example of a .tr output

TEAM 2: 802.11 WLAN MAC layer modeling

Results (.tr)

Average number of retriesFrom simulation

From calculation

TEAM 2: 802.11 WLAN MAC layer modeling

Results (.tr)

Average number of retries for AP with varying packet period and offset

TEAM 2: 802.11 WLAN MAC layer modeling

Average number of retries with varying packet period and offset

5 Stations

TEAM 2: 802.11 WLAN MAC layer modeling

Results (.tr)

Comparison between of the average number of retries from calculation and simulation

TEAM 2: 802.11 WLAN MAC layer modeling

Conclusions

Conclusions

• Estimated parameter ‘p’• Determined the saturation value• Established validity of the Markov model• Established importance of assumption of

synchronicity

TEAM 2: 802.11 WLAN MAC layer modeling

Future Objectives

• Use the .nam and .tr files to extract information about– Average service time – Average wait time

• Use the above times to find relationships between parameters

• Compare computed results and simulated results for different packet arrival configurations

• Compute the throughput/delay

• Create a deterministic model

(Someone Else’s) Future Objectives

TEAM 2: 802.11 WLAN MAC layer modeling

Questions

Questions?