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Experimental Study of Concurrent Transmission in Wireless Sensor Networks. Dongjin Son , Bhaskar Krishnamachari (USC/EE), and John Heidemann (USC/ISI). Motivation. Prior work Understanding wireless propagation essentials Zhao, Ganesan, Aguayo, Cerpa, Woo, Lal, Zuniga, Son, etc.
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Experimental Study of Concurrent Transmission in Wireless Sensor Networks Dongjin Son, Bhaskar Krishnamachari (USC/EE), and John Heidemann (USC/ISI)
Motivation • Prior work • Understanding wireless propagation essentials • Zhao, Ganesan, Aguayo, Cerpa, Woo, Lal, Zuniga, Son, etc. • Only few consider concurrent packet transmission • Whitehouse, Jamieson, Kochut • Concurrent transmission is endemic in dense networks • Applications • Event detection and targettracking • Code distribution and flooding for route discovery
Research goals Understanding concurrent packet transmissions ! • Systematic experimental study • Single and multiple interferers • Develop a better interference model
Main findings • Single Interferer effects • Capture effect is significant • SINR threshold varies due to hardware • SINR threshold does not vary with location • SINR threshold varies with measured RSS • Groups of radios show ~6 dB gray region • New SINR threshold (simulation) model • Multiple interferer effects • Measured interference is not additive • Measured interference shows high variance • SINR threshold increases with more interferers
Main findings • Single Interferer effects • Capture effect is significant • SINR threshold varies due to hardware • SINR threshold does not vary with location • SINR threshold varies with measured RSS • Groups of radios show ~6 dB gray region • New SINR threshold (simulation) model • Multiple interferer effects • Measured interference is not additive • Measured interference shows high variance • SINR threshold increases with more interferers
Part I: Single interferer • Main research questions • Does concurrent transmission imply a collision ? • Can we identify a constant SINR threshold (SINRӨ) for capture? • Experiments • Two concurrent senders • varying transmitter hardware and power
Methodology Mica2 PC104 Sender1 (SRC1) Receiver Sender2 (SRC2) Synchronizer (Sync) Time Sync Synchronizes the clocks of both senders
Methodology Sender1 (SRC1) Receiver Sender2 (SRC2) Synchronizer (Sync) Time Sync SRC1 Measure an ambient Noise (N) Measure the RSS of Sender1 (S1)
Methodology Sender1 (SRC1) Receiver Sender2 (SRC2) Synchronizer (Sync) Time Sync SRC1 Sync SRC2 Measure the ambient Noise (N) Measure the RSS of Sender2 (S2)
Methodology Sender1 (SRC1) Receiver Sender2 (SRC2) Synchronizer (Sync) Time Sync SRC1 Sync SRC2 Sync SRC1 SRC2 Test the delivery of the sender’s packet under the CTX
Methodology vary Tx power, hardware, location Sender1 (SRC1) Receiver • Stronger packet ►Signal • Weaker packet ►Interference Sender2 (SRC2) Synchronizer (Sync) Time Sync SRC1 Sync SRC2 Sync SRC1 SRC2 Test the delivery of the sender’s packet under the CTX epoch Repeat this epoch and measure PRR
Power and PRR based regions White > 90% PRR Black < 10% PRR Gray 10~90% PRR • Black-Gray-White due to power change • Prior work (Zhao, woo etc) use a distance based definition • SINR threshold (SINRθ) • SINR (Signal-to-interference-plus-noise) value which ensures reliable packet reception
Capture effect White Gray Black Gray White [Finding] Capture effect is significant & SINRθ is not constant • Concurrent packet transmission does not always means packet collision (capture effect: recently studiedby Whitehouse et al.) • Systematically study capture effects and quantify the SINRθ value
Modeling SINR to PRR relationship • Regression model for simple description of experimental data f: frame size of the packet in bytes l: preamble size in bytes - Model based on the link layer model by Zuniga and Krishnamachari ▪ ß0changes the shape (ß0 is set to 2.6 based on the empirical data) ▪ß1 changes the location ß0=1 ß0=2 ß0=3 -1 0 1 2 β0,β1 ß1 β0,β1 β0,β1 β0,β1 β0,β1 β0,β1
Transmitter hardware effect • How much SINR threshold change does transmitter hardware can make ? • Does hardware variation dominate other effects? • E.g., compared to the location effect • Experiments • Hold location constant • Swap one of the transmitter hardware
Does transmitter hardware affect SINRӨ? • Vary transmitter hardware (SRC1-SRC2, SRC1-SRC3) while keeping the same receiver SRC1 (with SRC2) SRC2 (with SRC1) SRC1 (with SRC3) SRC3 (with SRC1) +1 dB -1.7 dB 3.4 dB 5.3 dB [Finding] SINRӨchanges with different transmitter hardware
Signal strength effect • Is SINR threshold constant at different signal (or interference) strength level? • I.e., Can we always identify a constant SINR threshold for the same hardware pair ? • Experiments • Hold location and use the same transmitter pair • Vary transmission power of both transmitters
Does signal strength level affect SINRӨ? • Same transmitter hardware, but vary both sender and interferer’s transmission power levels. [Finding] SINRӨchanges at different signal strength levels
Implications of findings (4.6 dB) Signal strength + Hardware Hardware (dB) Signal strength • Protocols based on constant SINR threshold assumption will fail • Power control protocol and capture-aware protocol should consider variable SINRθ • New interference model is necessary
Part II: Multiple interferers • Main research questions • Textbook says “Interference is additive”, • How about the reality with low-power RF transceiver ? • Experiments • Empirically test the additive signal strength assumption • Varying the number of interferers and Tx power
Methodology Mica2 PC104 Sender Receiver Interferer1 (IFR1) Interferern (IFRn) Synchronizer (Sync) Time Sync Sender Measure an ambient Noise (N) Measure the RSS of Sender (S)
Methodology Sender Receiver Interferer1 (IFR1) Interferern (IFRn) Synchronizer (Sync) Time Sync Sender Sync IFR1 Measure an ambient Noise (N) Measure the RSS of Interferer1 (I1)
Methodology Sender Receiver Interferer1 (IFR1) Interferern (IFRn) Synchronizer (Sync) Time Sync Sender Sync IFR1 Sync IFRn Measure the ambient Noise (N) Measure the RSS of Interferern (In)
Methodology Sender Receiver Interferer1 (IFR1) Interferern (IFRn) Synchronizer (Sync) Time Sync Sender Sync IFR1 Sync IFRn Sync IFR1 IFRn Measure the Joint Interference
Methodology Sender Receiver Interferer1 (IFR1) Interferern (IFRn) Synchronizer (Sync) Time Sync Sender Sync IFR1 Sync IFRn Sync IFR1 Sync Sender IFR1 IFRn IFRn Test the delivery of the sender’s packet
Joint interference (JRIS) estimators Time IFR1 IFR1 Jointly Measured Independently Measured IFR2 IFR2 IFR3 IFR3 RIS RIS RIS IFR1 IFR2 IFR3 measured JRIS(m) Average of the actual joint interference measurements expected JRIS(e) Summation of independent interference measurement Direct measurement! Textbook prediction!
Does joint interference show additivity? RIS (dBm) Individual RIS of IFR1 and IFR2 (dBm) Comparison between JRIS(e) and JRIS(m) when two interferers (IFR1 and IFR2) have equivalent RISs at the receiver [Finding] Measured interference is not additive • JRIS(e) is higher than JRIS(m) • Additive behavior is different at different signal strength levels
Joint Interference and SINRθ 4Interferer 3Interferer 2Interferer -64.1 dBm -68.8 dBm -64.1 dBm -68.8 dBm 1Interferer -73 dBm -73 dBm JRIS(m) JRIS(e) SINR threshold measurements with different number of interferers [Finding] SINR threshold increases with more interferers • SINR threshold changes with different number of interferers which changes the joint received interference strength
Potential of capture-aware MAC • Compare the number of CTXable (Concurrently Transmittable) links • Methodology • Trace-based Simulation • Uses real measured RSS • Without Tx power control • Assume red link Tx, who can CTX together? • Observation • More available links for the capture-aware medium access RTS/CTS based CTXable links with RTS/CTS based MAC Capture-aware CTXable links with capture-aware MAC
Generalized for all links in the testbed • The number of CTXable links comparison between traditional and capture-aware MAC Capture-aware Capture-unaware [Finding] Capture-aware MAC shows about 3 times more CTXable links on average
Conclusion • Experimental results show • the significance of capture effects as Tx power varies • some of the theoretical assumption does not hold for the measurements (1) SINR threshold varies (not constant) (2) Multiple interference worse than addition (not additive) • better understanding of single and multiple interference on packet delivery • Experimental results imply • need better SINR threshold simulation models • more efficient use of wireless channel is possible with better understanding of concurrent packet transmission E.g.,) Capture-aware medium access protocol USC ANRG: http://ceng.usc.edu/~anrg I-LENSE: http://www.isi.edu/ilense