Rate Throughput

5/28/2018 Rate Throughput

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Sunil Kowlgi, Vacha Dave Univesity of Texasat Austin 1

Effect of Data Rate on

Throughput

Wireless and Mobile Computing Project Presentation

EE 382V project

Sunil KowlgiVacha Dave


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Presentation Outline

Motivation

Methodology Overview

Setup and Environment NS-2

802.11b

Experiments , Results and Analysis Experiments

Results

Analysis Furthering the work

Issues

References


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Motivation

Most wireless cards come with multiple data rates

The commonly held belief is that higher data rate

guarantees higher throughput.

Higher data rates require higher transmit powerwhich means lesser spatial reuse.

We would like to see how spatial reuse is affectedfor different data rates and how this effect manifestsas reduced throughput.


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Methodology Overview

We measured throughput for a single flow ona linear chain topology of nodes.

Measurements were carried out for differentdata rates and transmit power levels.

The number of concurrent successfultransmissions was measured to serve as anindication of spatial reuse.


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Setup and Environment: NS-2 PHY Layer

Phy/WirelessPhy: Frequency2.4GHz (802.11b)

RX thresholdvaried according to data rate

Transmit powerswept over a range 130dBm Carrier sense threshold - 1e-13W

Capture threshold10dB

Propagation/Shadowing: Path Loss Exponent2.0 (free space)

Shadowing deviation4.0 ( outdoor)


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Setup and Environment: NS-2 MAC Layer

Mac/802_11 :

RTS Threshold0 ( RTS/CTS turned on )

Data rate1, 2, 5.5, 11Mbps ( 802.11b)


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Setup and Environment: NS-2 Network

Layer - NOAH

Package that enables static routing for

wireless nodes

Lets you set the routing table by hand for

each node

Queue/DropTail/PriQueueinterface queue

type

Network interface queue length500


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Setup and Environment: Application layer

Constant Bit Rate (CBR) traffic is used

CBR parameters that were set: Time interval between packetsvaried for different

experiments Packet size1456 bytes + 24 MAC hdr + 20 IP hdr

Different transmit data rates can be achieved byvarying CBR parameters

CBR lets you limit the maximum number of packetsthat need to be sent from source to sink.


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Setup and Environment: Testing for

different Power levels

FCC mandates that wireless transmitters limit

power to 30dBm (1W).

Commonly used transmit power level for

wireless cards is 15dBm.

We ran experiments for all power levels in the

range 130dBm.


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Setup and Environment: Measuring

Throughput

Loss Monitor was used to measure the throughput

at the sink, over a given time window.

All simulations were run for 700 seconds

The initial and final 100 seconds of simulation were

excluded from throughput measurement. This is to

ensure that the system was in steady state.


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Experiments carried out

To determine the chain length

To determine of CBR value

To measure the throughput for different

power levels, for 802.11b data rates

Number of concurrent transmissions for

different power levels, for 802.11b data rates


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Experiment: Determining Chain Length

Trying to approximate an infinite chain length, forwhich throughput does not vary significantly withsmall change in number of nodes.

Before carrying out throughput v. data rateexperiments we determined the right chain lengthand that would be valid for different data rates.

Settings: Power level15dBm

Packet size1500 bytes

Distance between nodes550m


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Results: Determining Chain Length

Throughput vs. Number of Nodes for sending rate = 1Mbps,

distance between nodes = 550m

transmit power = 15dBm

0

100200

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1000

0 10 20 30 40 50 60 70 80 90Chain Length

Throughput(Kbps)


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Throughput for different number of nodes at 2Mbps Data Rate,

Distance= 550m,


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0 10 20 30 40 50 60 70 80 90

Number of Nodes

ThroughputinKbps


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Throughput Vs. Number of Nodes for 11Mbps sending rate,

distance between nodes= 550m


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200

300

400

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700

0 10 20 30 40 50 60 70 80 90

Number of Nodes

Throughput(Kbps)


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Analysis: Determining Chain Length

There is a quasi-exponential decay inthroughput as the chain length is increased.

The chain length for our experiments waspicked from the stable/flat region of thethroughput curve.

We picked a chain length of 60 nodes for allsubsequent simulations.


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Experiment: Determining CBR values

We need to determine the CBR value at

which there are no congestion losses.

For a chain length of 60 nodes, we measured

the throughput for different CBR values. This

was carried out for 1, 2 and 11Mbps data

rates, at a transmit power level of 15dBm.


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Results: Determining CBR values

Throughput for different CB rates, distance between nodes = 550m,

power = 15dBm, 1Mbps data rate

0

5

10

15

20

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30

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1 10 100 1000 10000

CBR ( Kbps)

Throughput(Kbps)


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Throughput for different CB rates, distance between nodes = 550m,

power = 15dBm, 2Mbps data rate

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5

10

15

20

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50

1 10 100 1000 10000

CBR ( Kbps)

Throughput(Kbp

s)


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Throughput for different CB rates, distance between nodes = 550,transmit power = 15dBm, 11Mbps data rate

0

1

2

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4

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1 10 100 1000 10000 100000

CBR (Kbps)

Throughput(Kbps)


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Analysis: Determining CBR Rate

Throughput increases with CBR value until a point, where itstarts to fall.

The reduction in throughput beyond a certain CBR value can beattributed to congestion.

For our subsequent experiments we use CBR values just belowthe inflection point so that it guarantees reasonable throughputwithout the worry of congestion. For 1Mbps31.6 Kbps

For 2Mbps60 Kbps

For 11Mbps60 Kbps


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Experiment: Power Vs. Throughput for a

given Data Rate

Simulations were run to measure the throughput for30 different transmit power levels ( 1- 30 dBm).

These simulations were performed for different datarates1, 2, 11 Mbps.

CBR values determined in the previous experimentwere used ( to avoid congestion-related losses).

Nodes were separated by 550m.


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Result: Power Vs. Throughput for a given

Data Rate

Power v. Throughput for CBR=60Kbps,

chain length = 60, 550m between nodes

-5

0

5

10

15

20

25

30

35

40

0.001 0.01 0.1 1

Power (W)

Throughput(Kbps)

1Mbps

15dBm

15 dBm


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Analysis: Power Vs. Throughput for a

given Data Rate For very low values of transmit power, very few

data packets get across from source to sink, andthroughput is very low.

As the transmit power increases, transmissionsbecome more reliable and the throughput increasestill a point.

There is an inflection point corresponding to acertain transmit power beyond which fewer nodestransmit in a given time interval and thus spatialreuse decreases.


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Result: Putting them All together

Power v. Throughput for CBR=31.6Kbps,


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0

5

10

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20

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30

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0.001 0.01 0.1 1

Power (W)

Throughput(Kbps)

1Mbps

2Mbps

11Mbps

15dbm

15 dBm



-10

0

10

20

30

40

50

60

70

0.001 0.01 0.1 1

Power (W)

Throughput(Kbps)

1Mbps

2Mbps

11Mbps

15dBm

15 dBm


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Analysis: Putting them All together

For each data rate, throughput increases withincreased transmit power and beyond a certaintransmit power it starts to fall.

The graphs are testament to the fact that for a giventransmit power a higher data rate does not alwaysresult in higher throughput.

The envelope of the curve gives the data rate atwhich transmissions should happen, to achieve thehighest throughput possible for a given transmitpower.


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Analysis: Extrapolating the 11Mbps Curve

The 11Mbps throughput-transmit power curve

appears to flatten out, contrary to intuition!

But, if the curve is extrapolated for transmit

powers up to 5W (!) it shows the degradation

of throughput.


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Sunil Kowlgi, Vacha Dave Univesity of Texas

at Austin 28

Experiment: Measuring Spatial Reuse -

Possibilities Spatial reuse could be quantified in different ways

The minimum distance between nodes at which an optimalFairness Ratio of 1 is achieved is indicative of spatialreuse.

The number of transmissions that complete in a timeinterval ( defined by the transmission time of a standardsize data packet) is indicative of spatial reuse.

Using the queuing theory

First packet 59x , second at 59x + x, and so on

Measuring the deviation from ideal We adopted the second methodology to quantify

spatial reuse.


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at Austin 29

Experiment: Measuring Spatial Reuse

After a simulation run, the trace file was examined

by a script to determine the maximum number of

ACKs in a time interval.

The time interval was determined by measuring time

from sending of RTS to the reception of an ACK, for

a single CBR packet of 1500 bytes.

13 ms for 1Mbps 7.2 ms for 2Mbps

4 ms for 11 Mbps


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Result: Measuring Spatial Reuse



-10

0

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60

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0.001 0.01 0.1 1

Power (W)

Throughput(Kbps)

1Mbps

2Mbps11Mbps

15dBm

15 dBm

Measure of Spatial Reuse

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0

1

2

3

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6

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0.001 0.01 0.1 1

Power in Watts

NumberofAcksreceived/time

interval 1 Mbps

2 Mbps

11 Mbps


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Analysis: Measuring Spatial Reuse

Very Jittered Curveseems to follow the

general throughput curve

Binning the values and taking a weighted

average would result in a better curve

Pessimistic boundsince it counts only the

transmissions that have completed during the

given time interval.


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Furthering the Experiments

Effect of Distance between nodes on the

result

We have maintained a distance on 550 m

between nodes. This is just under thetransmission range for 1Mbps.

More exhaustive sweep over different

Application layer data rates.

Trying out for different packet sizes

Issue with 64 byte packets


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Some of the Exhaustive Sweep

CBR vs. Throughput (Kbps) for different power levels,

chain length = 60 nodes, 550 m apart

-5

0

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10

15

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2530

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40

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1 10 100 1000 10000 100000

Constant Bit Rate (Kbps)

Throughput(Kbp

s)

0.001259

0.001585

0.001995

0.002512

0.003162

0.003981

0.005012

0.00631

0.007943

0.01

0.0125890.015849


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Issues

We could not see any throughput for 5.5 Mbps, forall transmit power levels. Possibly because ofincorrect value of RX threshold.

The default TTL value for IP in NS-2 is set to 32. Aweek was spent in figuring out the mysteriouspacket drops for long chain lengths.

NS-2 simulations took a long time, which preventedus from performing more exhaustive experiments.For instance, sweeping across different CBR ratesfor different power levels.


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at Austin 35

References

The Network Simulator http://www.isi.edu/nsnam/ns/

Capacity of AdHoc Wireless Networks Jinyang Li,

Charles Blake, Douglas S. J. De Couto, Hu Imm Lee,

and Robert Morris , MOBICOM 01

Improving spatial reuse through tuning transmit power,

carrier sense threshold, and data rate in multihop

wireless networks, Kim et al. MOBICOM 2006

An Experimental Evaluation of Several Rate Adaptation

Protocols, Choi et. al.
http://www.isi.edu/nsnam/ns/http://www.isi.edu/nsnam/ns/

Documents

Rate Throughput