Roadmap 1 Thesis Objectives 2 Enhancements Propagation Loss Models - - PDF document

▶

Nov 26, 2022 324 likes •441 views

Accuracy Enhancements of the 802.11 Model and EDCA QoS Extensions in ns-3 Completion Talk Timo Bingmann Decentralized Systems and Network Services Research Group Institute of Telematics, University of Karlsruhe June 26, 2009 Roadmap 1 Thesis

SLIDE 1

Accuracy Enhancements of the 802.11 Model and EDCA QoS Extensions in ns-3

Completion Talk Timo Bingmann

Decentralized Systems and Network Services Research Group Institute of Telematics, University of Karlsruhe

June 26, 2009

Roadmap

1 Thesis Objectives 2 Enhancements

Propagation Loss Models Reception Criteria Frame Capture Effect EDCA Implementation

3 Speed Comparison 4 Conclusion

802.11 Enhancements in ns-3 Timo Bingmann - 2/19 University of Karlsruhe

SLIDE 2

1 Thesis Objectives

Objectives

Compare 802.11 implementations of new ns-3 network simulator with ns-2. Transfer extended ns-2 features added by the DSN to new ns-3 design. Implement EDCA extensions in ns-3. Evaluate performance gain of switching to ns-3.

802.11 Enhancements in ns-3 Timo Bingmann - 3/19 University of Karlsruhe 1 Thesis Objectives

Constraints

All features must be thoroughly tested, evaluated and documented. Integrate cleanly into ns-3 design, which uses state-of-the-art software engineering methods. Researchers must be able to use them without detailed lower-layer knowledge.

802.11 Enhancements in ns-3 Timo Bingmann - 4/19 University of Karlsruhe

SLIDE 3

2 Enhancements

Feature Comparison: ns-3.3 vs. ns-2.33

PHY Layer: − No probabilistic Nakagami propagation model. − Lacks modeling of frame capture effect. + BER/PER reception criterion for 802.11a. Results unequal to ns-2’s SINR criterion. MAC Layer: − Support for EDCA extensions missing. + Overall good software design.

802.11 Enhancements in ns-3 Timo Bingmann - 5/19 University of Karlsruhe 2 Enhancements 2.1 Propagation Loss Models

Nakagami Propagation Loss Model in ns-3

Ported Nakagami propagation loss model to ns-3. Extensively verified against ns-2 and the analytic probability density function.

ns-2

ns-2 Nakagami (defaults) 500 1000 1500 2000 2500 Distance (m)

200 -180 -160 -140 -120 -100 -80
60
40

rxPower (dBm) 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 Probability

ns-3

ThreeLogDistance + Nakagami (default m = 0.75) ThreeLogDistance 500 1000 1500 2000 2500 Distance (m)

200 -180 -160 -140 -120 -100 -80
60
40

rxPower (dBm) 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 Probability

802.11 Enhancements in ns-3 Timo Bingmann - 6/19 University of Karlsruhe

SLIDE 4

2 Enhancements 2.2 Reception Criteria

Reception Criteria: SINR

Implemented ns-2’s SINR reception criterion in ns-3 as Ns2ExtWifiPhy.

A B distance

ns-2

0.2 0.4 0.6 0.8 1 500 1000 1500 2000 2500 Reception Probability Distance (m) FreeSpace TwoRayGround Nakagami (Log Only) Nakagami Defaults Nakagami-1 Nakagami-3 Nakagami-5

ns-3

0.2 0.4 0.6 0.8 1 500 1000 1500 2000 2500 Reception probability Distance (m) Friis LogDistance (defaults) LogDistance (exponent = 2.2) ThreeLogDistance (defaults) ThreeLogDistance + Nakagami (defaults) ThreeLogDistance + Nakagami (m = 1.0) ThreeLogDistance + Nakagami (m = 3.0) ThreeLogDistance + Nakagami (m = 5.0)

802.11 Enhancements in ns-3 Timo Bingmann - 7/19 University of Karlsruhe 2 Enhancements 2.2 Reception Criteria

Discussion of SINR and BER/PER

Detailed explanation of existing BER/PER reception in ns-3. Discussion and comparison against SINR.

Packet Error Rate (PER)

10−6 10−5 10−4 10−3 10−2 10−1 100 5 10 15 20 25 Probability of packet error Pper SINR per bit γb (dB) 6 Mb/s 9 Mb/s 12 Mb/s 18 Mb/s 24 Mb/s 36 Mb/s 48 Mb/s 54 Mb/s

Free-space Reception Range

0.2 0.4 0.6 0.8 1 500 1000 1500 2000 2500 Reception probability Distance (m) Ns2Ext at 6 or 9 Mb/s Yans at 6 Mb/s Yans at 9 Mb/s Ns2Ext at 12 or 18 Mb/s Yans at 12 Mb/s Yans at 18 Mb/s Ns2Ext at 24 or 36 Mb/s Yans at 24 Mb/s Yans at 36 Mb/s Ns2Ext at 48 or 54 Mb/s Yans at 48 Mb/s Yans at 54 Mb/s

802.11 Enhancements in ns-3 Timo Bingmann - 8/19 University of Karlsruhe

SLIDE 5

2 Enhancements 2.3 Frame Capture Effect

Frame Capture Effect

Added frame capture effect to Ns2ExtWifiPhy. Evaluated against ns-2.

A B C fixed varying Time B A ∆t

ns-2

50 100 150 200 250 300 350 400 450 500 500 1000 1500 2000 2500 Packet delay ∆t (µs) Distance between nodes C and A (m) Impossible due to CSMA/CA Received

ns-3

50 100 150 200 250 300 350 400 450 500 500 1000 1500 2000 2500 Packet delay ∆t (µs) Distance between nodes C and A (m) Impossible due to CSMA/CA Received always Received with preamble capture Received with data capture

802.11 Enhancements in ns-3 Timo Bingmann - 9/19 University of Karlsruhe 2 Enhancements 2.3 Frame Capture Effect

Frame Capture Effect

Added frame capture effect to Ns2ExtWifiPhy. Evaluated against ns-2.

A B C fixed varying Time B A ∆t

ns-2

50 100 150 200 250 300 350 400 450 500 500 1000 1500 2000 2500 Packet delay ∆t (µs) Distance between nodes C and A (m) Impossible due to CSMA/CA Received

ns-3

400 800 1200 1600 Distance between nodes C and A (m) 100 200 300 400 500 Packet delay ∆t (µs) 0.2 0.4 0.6 0.8 1

802.11 Enhancements in ns-3 Timo Bingmann - 9/19 University of Karlsruhe

SLIDE 6

2 Enhancements 2.4 EDCA Implementation

EDCA Implementation

Extended ns-3 with EDCA capabilities. Builds up on the well designed DCF classes. Added TXOP limits and burst sequences. Tested individual maximum throughput against analytical reference values. Experiment with differently prioritized traffic streams shows relative QoS.

802.11 Enhancements in ns-3 Timo Bingmann - 10/19 University of Karlsruhe 2 Enhancements 2.4 EDCA Implementation

QosAdhocWifiMac WifiPhy MacLow Queue Queue Queue Queue Dcfmanager

SIFS: Time SlotTime: Time

DcaTxop DcaTxop DcaTxop DcaTxop AC BE AC VO AC VI AC BK WifiQosTag

AIFSN: int Backoff: int AIFSN: int Backoff: int AIFSN: int Backoff: int AIFSN: int Backoff: int AC: int

CCA BUSY

WifiChannel

NAV

802.11 Enhancements in ns-3 Timo Bingmann - 11/19 University of Karlsruhe

SLIDE 7

2 Enhancements 2.4 EDCA Implementation

Maximum Throughput Experiment

DATA

AIFS CW

DATA

AIFS CW

Frame

Time

Without ACK

DATA

SIFS ACK AIFS CW

Frame

Time

With ACK

DATA

SIFS DATA AIFS CW

Frame ≤ TXOPLimit Superframe DATA

SIFS

DATA

SIFS Time

TXOP burst without ACKs

DATA

SIFS ACK AIFS CW

DATA

SIFS ACK SIFS

DATA

SIFS ACK SIFS

Superframe Frame ≤ TXOPLimit

Time

TXOP burst with ACKs

802.11 Enhancements in ns-3 Timo Bingmann - 12/19 University of Karlsruhe 2 Enhancements 2.4 EDCA Implementation

Maximum Throughput Experiment

Reference value in B/s and relative difference of experimental result with 99 % error margin for 54 Mb/s data rate. 80 B - noACK 80 B - ACK 2304 B - ACK DCF 4 522 908 3 176 179 34 810 198 0.01 ± 0.11 ‰ 0.01 ± 0.10 ‰ 0.01 ± 0.04 ‰ AC VO 7 314 286 4 338 983 38 763 407

802.11p/D4.02

0.03 ± 0.05 ‰ 0.01 ± 0.02 ‰ 0.01 ± 0.01 ‰ AC BK 3 129 584 2 419 660 31 108 861

802.11p/D4.02

−0.06 ± 0.1 ‰ 0.02 ± 0.09 ‰ 0.01 ± 0.04 ‰

Tested 216 configurations. Maximum relative difference was 0.85 ± 0.11 ‰.

802.11 Enhancements in ns-3 Timo Bingmann - 13/19 University of Karlsruhe

SLIDE 8

2 Enhancements 2.4 EDCA Implementation

EDCA Traffic Streams Experiment

Without ACK

0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 5 10 15 20 25 30 Payload rate received at listener (Mb/s) Number of sending nodes AC VO AC VI AC BE AC BK

With ACK

0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 5 10 15 20 25 30 Payload rate received at listener (Mb/s) Number of sending nodes AC VO AC VI AC BE AC BK

Each node sends four 160 Kb/s streams with different ACs. As the number of nodes increases the medium is saturated.

802.11 Enhancements in ns-3 Timo Bingmann - 14/19 University of Karlsruhe 3 Speed Comparison

Speed Comparison – Highway Scenario

Modeled identically in both ns-2 and ns-3. Made possible with newly added components.

802.11 Enhancements in ns-3 Timo Bingmann - 15/19 University of Karlsruhe

SLIDE 9

3 Speed Comparison

Speed Comparison – Results

10 20 30 40 50 60 70 80 20 40 60 80 100 120 Packets sent (in thousands) Number of nodes 1 2 3 4 5 6 20 40 60 80 100 120 Packets received (in millions) Number of nodes

ns-2 unoptimized ns-2 optimized ns-2 icc optimized ns-3 debug ns-3 optimized ns-3 optimized static ns-3 icc optimized ns-3 icc optimized static ns-3 32-bit optimized ns-3 32-bit optimized static ns-2 nakagami optimized ns-3 nakagami optimized static

802.11 Enhancements in ns-3 Timo Bingmann - 16/19 University of Karlsruhe 3 Speed Comparison

Speed Comparison – Results

50 100 150 200 250 300 350 20 40 60 80 100 120 Simulation run time (seconds) Number of nodes

802.11 Enhancements in ns-3 Timo Bingmann - 17/19 University of Karlsruhe

SLIDE 10

3 Speed Comparison

Speed Comparison – Results

Slowest configuration: ns-3 in debug mode. ns-3 optimized mode gives 76.3±0.5% reduction. ns-3 optimized with static linking yields further reduction of 42.6±1.2%. Compilation without -fPIC yielded a reduction of

nly 1.1±0.3%.

icc vs. gcc: no improvement, even slight speed decrease (1.9±0.4%). Speed increase of ns-3 over identical ns-2 simulation: 58.6±1.8%. Enabling Nakagami propagation increases run time by 8.1±1.0% in ns-3 and 3.8±0.4% in ns-2.

802.11 Enhancements in ns-3 Timo Bingmann - 18/19 University of Karlsruhe 4 Conclusion

Conclusion

Extended ns-3 802.11 PHY layer to show equivalent behavior as ns-2. Improved MAC layer with EDCA extensions. All enhancements thoroughly verified. Speed test of ns-3 shows up to 59 % execution time reduction over ns-2. Thank you for your attention.

802.11 Enhancements in ns-3 Timo Bingmann - 19/19 University of Karlsruhe