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Walking down the STAIRS: Efficient Collision Resolution with Constructive Interference

INFOCOM, 2014, Toronto. Walking down the STAIRS: Efficient Collision Resolution with Constructive Interference. Xiaoyu Ji , Yuan He, Jiliang Wang, Wei Dong, Xiaopei Wu and Yunhao Liu. Hong Kong University of Science and Technology. Motivation. Wireless Sensor Networks (WSNs)

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Walking down the STAIRS: Efficient Collision Resolution with Constructive Interference

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  1. INFOCOM, 2014, Toronto Walking down the STAIRS: Efficient Collision Resolution with Constructive Interference Xiaoyu Ji, Yuan He, Jiliang Wang, Wei Dong, Xiaopei Wu and Yunhao Liu Hong Kong University of Science and Technology

  2. Motivation • Wireless Sensor Networks (WSNs) • Event-driven mode • Low duty cycle operating • Large number of nodes • CSMA-like protocols • Limitations • Backoff...

  3. The Recent Art- COMA • COMA- Contend before data transmission • Contention packets reserve channel for real data packets • The drawback: dedicated contention packets in each round Can we resolve the collision in just one round! Ref: F. Osterlind, et. al, Strawman: resolving collisions in bursty low-power wireless networks,” in IEEE/ACM IPSN, 2012

  4. One-round Collision Resolution • The problem: • Count, identify and schedule • And of course in one round! • Approach • Active contention • Virtual ID • Fast identification

  5. Our weapon: RSSI Stair Pattern • The observation • Signals can constructively collide • Requirements of Constructive Interference (CI) • 0.5 μs • Identical signal waveform

  6. The Principle Proposition: Given the superposed signal CI(k) under CI, let A1 = A2 = … = A be the amplitude and τ1 = τ2= … = B denoting the phase offset with respect to the first signal generated by transmitter i = 1. Consider one IEEE 802.15.4 standard based communication system, RSSICI(k)is equal to: Where ωc is a constant and τ1 =0

  7. Design of STAIRS • Overview Through intentional contention, senders can be identified fromthe stair-like pattern of RSSI in one round.

  8. Design Challenges • Challenge 1: Synchronization • Requirement of CI: Δ≤0.5μs • Challenge 2: Falling edge detection • CP packets with the same length • External interference, e.g., WiFi signals False falling edges (1) False negatives (2) False positives

  9. Alignment for CP packets • Receiver-initiated (CR) • Triggering transmissions of CP packets • Serving as ACK/NACK • Coping with hidden terminals • Parallelizing receiving and reading

  10. S-CUSUM Edge Detection • Discrete lengths of CP packets • Total sender number N, maximum packet size L, increase step ΔL, length of CP is: • A paradox- how to find a good ΔL?

  11. Finding the optimal ΔL • p=1/m: choose any of the m lengths • α: the probability of false positives • Three cases for a schedule:

  12. Implementation • STAIRS • A plug-in between APP and MAC layer • Invoked when collision happens • Three main components

  13. Evaluation • Micro-benchmark • Synchronization • Edge detection • Multi-hop testbed • Completion time • Efficiency • Duty cycle • Large-scale simulation

  14. Micro-benchmark • Offset among arriving packets less than 0.25 μs! • S-CUSUM increases detection efficiency. • Average detection accuracy is > 85%.

  15. Testbed Settings • Multi-flow-multi-hop environment. • ΔL is set to 10 bytes. • 20 TelosB sensor nodes Flow number

  16. Compared with Strawman • STAIRS beats Strawman, especially with large number of senders. • Contention overhead of STAIRS is amortized.

  17. Duty Cycle Evaluation • Both sender and receiver duty cycles are improved, as contention time is reduced. • Energy efficiency is therefore improved.

  18. Simulation • Settings • Up to 50 senders • Linear backoff (CSMA-L) • Exponential backoff (CSMA-E)

  19. Results Pkt_size = 50 bytes Pkt_size = 100 bytes • No degraded performance • CSMA-L beats CSMA-E after the threshold • Backoff time dominates!

  20. Summary • Collision resolution with active contention • Observing the RSSI stair-like pattern, we then look into its principle • Design STAIRS based on the stair pattern and solve challenges like synchronization and finding optimal ΔL • Evaluation in both real testbed and large-scale simulation

  21. Thank you!

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