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C-MAC: Model-driven Concurrent Medium Access Control for Wireless Sensor Networks

C-MAC: Model-driven Concurrent Medium Access Control for Wireless Sensor Networks. Mo Sha, Guoliang Xing, Gang Zhou, Shucheng Liu, Xiaorui Wang Proceedings of IEEE Infocom 2009. Presented by Zakhia Abichar Iowa State University 07/02/2009. Problem.

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C-MAC: Model-driven Concurrent Medium Access Control for Wireless Sensor Networks

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  1. C-MAC: Model-driven Concurrent Medium Access Control for Wireless Sensor Networks Mo Sha, Guoliang Xing, Gang Zhou, Shucheng Liu, Xiaorui Wang Proceedings of IEEE Infocom 2009 Presented by Zakhia Abichar Iowa State University 07/02/2009

  2. Problem We need to transmit the data from the sensors to a center node Some applications have a lot of traffic Accelerometer measures the vibrations on a structure at 100 HZ The sensor has limited capacity Sensors have limited battery power Route to sink has multiple hops often Rate is limited by interference We need an efficient Medium Access Control scheme

  3. Previous work CSMA-based reduce the collisions References: S-MAC [24], T-MAC [21], B-MAC [12], WiseMac [5] TDMA-based make the channel slotted References: TRAMA [13], DCQS [4], DRAND [16] Hybrid approaches References: SCP [25], Funneling-MAC [1] Many previous approaches focus on the energy efficiency This paper focuses on the high throughput for data-intensive scenarios

  4. Concurrent transmissions s1 to r1 on link 1 Power increases from 3 (-25dBm) to 31 (0 dBm) s2 to r2 on link 2 Fixed power to level 15 (7dBm) Two links are in interference range

  5. Empirical Models We need to operate in the transition region To estimate that, we need to estimate the following empirical models: 1. Transmit Power vs. Received Signal Strength 2. Packet Reception Ratio vs. SINR

  6. Transmit Power vs. Received Signal Strength RSS model based on empirical study of [10] v: the receiver u: the sender Pu: transmit power Au,v: time-varying attenuation Bu,v: time-varying (I think it’s the noise) They run the experiment to see if the model is good

  7. EMPIRICAL POWER CONTROL AND INTERFERENCE MODELS Experimental Methodology Experiments are conducted on a test-bed composed of 16 Tmote Sky motes with four different environments: an office, a corridor, a grass field and an open parking lot.

  8. Evaluate the accuracy of the linear model • RSS grows nearly linearly in all environments • Correlation between transmit power and RSS varies significantly in different environments. • Transmit power does not yield a linear correlation with distance in logarithmic scale.

  9. Packet Reception Ratio vs. SINR Transmit from sender to receiver The jammer attempts to interfere

  10. Results “…the relationship between PRR and SINR (or SNR) yields a transitional region about 4 dB in all three settings, where the PRR quickly increases from 0 to 100%” Second observation, there are more variations with higher number of jammers.

  11. Measurement by cluster Similar to sliding window PRR-SNR model is a good approximation of PRR-SINR model

  12. Online model estimation NdBm: average noise energy N’: number of received beacons N: number of transmitted beacons • Each node periodically broadcasts N beacon messages at K power levels in turn • A node estimates its neighbors’ RSS models and its own interference model • Neighbors exchange the information • A pair of PRR-SNR values can be calculated as:

  13. DESIGN AND IMPLEMENTATION OF C-MAC

  14. Before Transmission • The transmitter listens to the channel and finds the set K • Set K = { (s1,r1), (s2,r2),…} • All the TXer-RXer tuples

  15. Concurrency check If PRR(si, ri) is smaller than a threshold α, the concurrency check fails. That is, node s0 cannot transmit concurrently with si because the PRR of the link from si to ri would drop below α. If the PRRs of all links in set K are above α, the concurrency check passes and the RTS/CTS exchange is started.

  16. Interference Assessment • After concurrency check, send RTS/CTS • RTS contains ID of receiver • CTS includes the sum of current interference and noise energy • RTS and CTS transmitted at full power • Avoid primary interference (2 senders to same receiver)

  17. Throughput Prediction • After RTS/CTS, sender estimates if its transmission will improve total throughput in its interference region • sum of PRRs of all active links (including s0 to r0)

  18. EXPERIMENTS Performance with fixed block size

  19. same topology for C-MAC and B-MAC

  20. “We denote the lowest energy consumption of all links under B-MAC as 100%”

  21. Performance with different block sizes

  22. Block size =1 for B-MAC

  23. Energy consumption of all nodes under C-MAC and B-MAC

  24. Thank You

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