1. Exploiting Constructive Interference for Scalable Flooding in Wireless Networks InfoCom 2012 Yin Wang, Yuan He, Xufei Mao, Yunhao Liu, Zhiyu Huang, Xiangyang Li NSLab study group 2013/1/21 Presented by: Yu-Ting 1

2. Outline Theoretical Analysis Scalability Problem Lower Bound of PRR SCIF 2

3. Modulation & Demodulation Symbol (4bits) period: 16us (4bit/250kbps) Chip period Ts: 16(us/symbol) ÷ 32(chip/symbol) = 0.5us bits (MSB)…0101…(LSB) bit → symbol symbol …5… symbol→PN series O-QPSK Mod. PN series (LSB)…00110101001000101110110110011100…(MSB) modulating wave noise O-QPSK Demod. PN series→symbol ( find the highest correlation) PN series (with 1 bit error) (LSB)…10110101001000101110110110011100…(MSB) symbol …5… (correctly Demod.) symbol → bit bits (MSB)…0101…(LSB) 3

4. Modulation of QPSK & O-QPSK (from Wiki) QPSK O-QPSK 4

5. Threshold of Maximum Temporal Displacement ∆ Tc = 0.5us 5

6. Theoretical Analysis 6 Interference Gain Factor (IGF)

7. Simulation of Theoretical Analysis Amplitudes: [1, 1, 0.5, 1.5 ] Phase offsets: [0, 0.25, 0.5, 0.75] 7

8. Outline Theoretical Analysis Scalability Problem Lower Bound of PRR SCIF 8

9. Scalability Problem To be simple, there's time uncertainty τ e during transmission in each hop For a path of h hops, the PMF of accumulated τ e is: For m independent paths, each of which consists h hops originated at the sink node: ∆ = max( τ h e ) − min(τ h e ) ∆ increases as m & h increase PRR decreases as ∆ increases 9

10. m = 5 10

11. Outline Theoretical Analysis Scalability Problem Lower Bound of PRR SCIF 11

12. Lower Bound of PRR Assume in grid networks Γ h m (∆ ≤ t): CDF of ∆ of a common ancestor node propagates a packet CDF of ∆ ≤ 0.5µs between node N8 and N9: N5 → {N8,N9} N2 → {N4,N5} → {N8,N9} N0 → {N1,N2} → {N4,N5} → {N8,N9} (Skip proof) For 32 bytes packet length, Γ h m (∆ ≤ 0.5) between parent and childs >= 95.4% 12

13. Outline Theoretical Analysis Scalability Problem Lower Bound of PRR SCIF 13

14. SCIF Spine Constructive Interference based Flooding Key: – Decrease the # of m – Length of a grid cell=0.5 of communication range => guarantee connection 14

15. Simulation Result 15

16. Comments Decent mathematical analysis Good introduction to related work No implementation With capture effect (strong capture), Glossy is actually not so vulnerable With noise, SCIF is probably not so good 16

17. Q&A 17

18. BACKUP SLIDES 18

19. Scalability Problem Time uncertainty τ e during transmission in each hop In Glossy: τ e = τ sw + τ d + τ tx + τ p τ sw : software delay τ d : radio processing τ tx : clock uncertainty due to clock frequency drifts τ p : propagation delay 19