1 / 19

Exploiting Constructive Interference for Scalable Flooding in Wireless Networks

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. Outline. Theoretical Analysis Scalability Problem Lower Bound of PRR

ava-bradshaw
Download Presentation

Exploiting Constructive Interference for Scalable Flooding in Wireless Networks

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Exploiting Constructive Interference for Scalable Flooding in Wireless Networks InfoCom 2012 Yin Wang, Yuan He, XufeiMao, YunhaoLiu, ZhiyuHuang, XiangyangLiNSLab study group 2013/1/21 Presented by: Yu-Ting

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

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

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

  5. Threshold ofMaximum Temporal Displacement ∆ • Tc= 0.5us

  6. Theoretical Analysis 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]

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

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

  10. m = 5

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

  12. Lower Bound of PRR • Assume in grid networks • Γhm(∆ ≤ t): CDF of ∆ of a common ancestor node propagates a packet • CDF of ∆ ≤ 0.5µs between nodeN8 and N9:N5 → {N8,N9}N2 → {N4,N5} → {N8,N9}N0 → {N1,N2} → {N4,N5} → {N8,N9} • (Skip proof)For 32 bytes packet length,Γhm(∆ ≤ 0.5) between parent and childs >= 95.4%

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

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

  15. Simulation Result

  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

  17. Q&A

  18. Backup slides

  19. Scalability Problem • Time uncertainty τeduring transmission in each hop • In Glossy: τe= τsw+ τd+ τtx+ τpτsw: software delayτd: radio processingτtx: clock uncertainty due to clock frequency driftsτp: propagation delay

More Related