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

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

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

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. Timo Bingmann - 5/19 802.11 Enhancements in ns-3 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-3 ns-2 Nakagami (defaults) ThreeLogDistance + Nakagami (default m = 0 . 75) ThreeLogDistance Probability Probability 0.08 0.08 0.07 0.07 0.06 0.06 0.05 0.05 0.04 0.04 0.03 0.03 0.02 0.02 0.01 500 0.01 500 0 1000 0 1000 -200 -180 -160 -140 -120 -100 -80 -200 -180 -160 -140 -120 -100 -80 1500 1500 Distance (m) Distance (m) 2000 2000 rxPower (dBm) rxPower (dBm) -60 2500 -60 2500 -40 -40 Timo Bingmann - 6/19 802.11 Enhancements in ns-3 University of Karlsruhe

2 Enhancements 2.2 Reception Criteria Reception Criteria: SINR Implemented ns-2’s SINR distance B A reception criterion in ns-3 as Ns2ExtWifiPhy . ns-2 ns-3 1 1 FreeSpace Friis TwoRayGround LogDistance (defaults) Nakagami (Log Only) LogDistance (exponent = 2.2) Nakagami Defaults ThreeLogDistance (defaults) 0.8 Nakagami-1 0.8 ThreeLogDistance + Nakagami (defaults) Nakagami-3 ThreeLogDistance + Nakagami (m = 1.0) Nakagami-5 ThreeLogDistance + Nakagami (m = 3.0) Reception Probability Reception probability ThreeLogDistance + Nakagami (m = 5.0) 0.6 0.6 0.4 0.4 0.2 0.2 0 0 0 500 1000 1500 2000 2500 0 500 1000 1500 2000 2500 Distance (m) Distance (m) Timo Bingmann - 7/19 802.11 Enhancements in ns-3 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) Free-space Reception Range 10 0 1 6 Mb/s 9 Mb/s 12 Mb/s 10 − 1 18 Mb/s 0.8 24 Mb/s Probability of packet error P per 36 Mb/s Ns2Ext at 6 or 9 Mb/s 48 Mb/s Yans at 6 Mb/s Reception probability 10 − 2 54 Mb/s Yans at 9 Mb/s Ns2Ext at 12 or 18 Mb/s 0.6 Yans at 12 Mb/s Yans at 18 Mb/s 10 − 3 Ns2Ext at 24 or 36 Mb/s Yans at 24 Mb/s 0.4 Yans at 36 Mb/s Ns2Ext at 48 or 54 Mb/s 10 − 4 Yans at 48 Mb/s Yans at 54 Mb/s 0.2 10 − 5 0 10 − 6 0 500 1000 1500 2000 2500 0 5 10 15 20 25 Distance (m) SINR per bit γ b (dB) Timo Bingmann - 8/19 802.11 Enhancements in ns-3 University of Karlsruhe

2 Enhancements 2.3 Frame Capture Effect Frame Capture Effect varying fixed B A C Added frame capture effect to Ns2ExtWifiPhy . Evaluated against ns-2. B ∆ t A Time ns-2 ns-3 500 500 450 450 400 400 350 350 Packet delay ∆ t (µs) Packet delay ∆ t (µs) 300 300 250 250 200 200 150 150 100 100 Impossible due to CSMA/CA Received always 50 50 Impossible due to CSMA/CA Received with preamble capture Received Received with data capture 0 0 0 500 1000 1500 2000 2500 0 500 1000 1500 2000 2500 Distance between nodes C and A (m) Distance between nodes C and A (m) Timo Bingmann - 9/19 802.11 Enhancements in ns-3 University of Karlsruhe 2 Enhancements 2.3 Frame Capture Effect Frame Capture Effect varying fixed B A C Added frame capture effect to Ns2ExtWifiPhy . B Evaluated against ns-2. ∆ t A Time ns-2 ns-3 500 500 1 450 400 400 0.8 350 Packet delay ∆ t (µs) Packet delay ∆ t (µs) 300 300 0.6 250 200 200 0.4 150 100 100 0.2 50 Impossible due to CSMA/CA Received 0 0 0 0 500 1000 1500 2000 2500 0 400 800 1200 1600 Distance between nodes C and A (m) Distance between nodes C and A (m) Timo Bingmann - 9/19 802.11 Enhancements in ns-3 University of Karlsruhe

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. Timo Bingmann - 10/19 802.11 Enhancements in ns-3 University of Karlsruhe 2 Enhancements 2.4 EDCA Implementation WifiQosTag QosAdhocWifiMac AC: int AC VO AC VI AC BE AC BK DcaTxop DcaTxop DcaTxop DcaTxop AIFSN: int AIFSN: int AIFSN: int AIFSN: int Backoff: int Backoff: int Backoff: int Backoff: int Queue Queue Queue Queue NAV MacLow Dcfmanager SIFS: Time CCA BUSY WifiPhy WifiChannel SlotTime: Time Timo Bingmann - 11/19 802.11 Enhancements in ns-3 University of Karlsruhe

2 Enhancements 2.4 EDCA Implementation Maximum Throughput Experiment AIFS CW AIFS CW AIFS CW DATA DATA DATA Time SIFS ACK Time Frame Frame Without ACK With ACK SIFS DATA SIFS SIFS AIFS CW DATA DATA DATA Time Frame ≤ TXOPLimit Superframe TXOP burst without ACKs SIFS SIFS AIFS CW DATA DATA DATA Time SIFS ACK SIFS ACK SIFS ACK Frame ≤ TXOPLimit Superframe TXOP burst with ACKs Timo Bingmann - 12/19 802.11 Enhancements in ns-3 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 ‰. Timo Bingmann - 13/19 802.11 Enhancements in ns-3 University of Karlsruhe

2 Enhancements 2.4 EDCA Implementation EDCA Traffic Streams Experiment Without ACK With ACK Payload rate received at listener (Mb/s) Payload rate received at listener (Mb/s) 1.8 2.0 AC VO 1.8 1.6 AC VI AC BE 1.6 1.4 AC BK 1.4 1.2 1.2 1.0 1.0 0.8 0.8 0.6 0.6 AC VO 0.4 0.4 AC VI AC BE 0.2 0.2 AC BK 0.0 0.0 0 5 10 15 20 25 30 0 5 10 15 20 25 30 Number of sending nodes Number of sending nodes Each node sends four 160 Kb/s streams with different ACs. As the number of nodes increases the medium is saturated. Timo Bingmann - 14/19 802.11 Enhancements in ns-3 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. Timo Bingmann - 15/19 802.11 Enhancements in ns-3 University of Karlsruhe

3 Speed Comparison Speed Comparison – Results Packets received (in millions) Packets sent (in thousands) 80 6 70 5 60 4 50 40 3 30 2 20 1 10 0 0 0 20 40 60 80 100 120 0 20 40 60 80 100 120 Number of nodes Number of nodes ns-2 unoptimized ns-3 optimized ns-3 32-bit optimized ns-2 optimized ns-3 optimized static ns-3 32-bit optimized static ns-2 icc optimized ns-3 icc optimized ns-2 nakagami optimized ns-3 debug ns-3 icc optimized static ns-3 nakagami optimized static Timo Bingmann - 16/19 802.11 Enhancements in ns-3 University of Karlsruhe 3 Speed Comparison Speed Comparison – Results 350 ns-2 unoptimized ns-2 optimized ns-2 icc optimized 300 Simulation run time (seconds) ns-3 debug ns-3 optimized ns-3 optimized static 250 ns-3 icc optimized ns-3 icc optimized static ns-3 32-bit optimized 200 ns-3 32-bit optimized static ns-2 nakagami optimized ns-3 nakagami optimized static 150 100 50 0 0 20 40 60 80 100 120 Number of nodes Timo Bingmann - 17/19 802.11 Enhancements in ns-3 University of Karlsruhe