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From Rateless to Distanceless: Enabling Sparse Sensor Network Deployment in Large Areas Wan DU, Zhenjiang LI, Jansen Christian LIANDO, and Mo LI School.

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Presentation on theme: "From Rateless to Distanceless: Enabling Sparse Sensor Network Deployment in Large Areas Wan DU, Zhenjiang LI, Jansen Christian LIANDO, and Mo LI School."— Presentation transcript:

1 From Rateless to Distanceless: Enabling Sparse Sensor Network Deployment in Large Areas Wan DU, Zhenjiang LI, Jansen Christian LIANDO, and Mo LI School of Computer Engineering, Nanyang Technological University (NTU), Singapore

2 Sensor network deployments 2 360m GreenOrbs [Y. Liu et al., INFOCOM’11, TPDS’12] LUSTER [L. Selavo et al., SenSys’07] Trio [P. Dutta et al., IPSN’06] Golden Gate Bridge [S. Kim et al., SenSys’ 06, IPSN’07]

3 Environmental monitoring normally requires sparse sampling in space.

4 Sparse environment monitoring 4 Soil organic matter [S. Ayoubi et al., Biomass and Remote Sensing of Biomass 2011].

5 Sparse environment monitoring 5 Agriculture [D. G. Hadjimitsis et al., Remote Sensing of Environment - Integrated Approaches 2013].

6 Sparse environment monitoring 6 Temperature [C. Guestrin et al., ICML’05, A. Krause et al., IPSN’06, JMLR’08]. Application Requirement Spatial Correlation

7 Sparse environment monitoring 7 Wind distribution [W. Du et al., IPSN’14, TOSN’14]. Application Requirement Spatial Correlation W01 W05 W04 W02 W08 W06 W09 W03 W10 W07 1 km W11 W12 2.5km 3km

8 Sparse environment monitoring 8 W01 W05 W04 W02 W08 W06 W09 W03 W10 W07 1 km W11 W12 2.5km 3km W01 W05 W04 W02 W08 W06 W09 W03 W10 W07 1 km W11 W12 2.5km 3km Wind distribution [W. Du et al., IPSN’14, TOSN’14]. Application Requirement Spatial Correlation

9 Sparse environment monitoring 9 Dense sensor networks. –Extra relaying nodes may not be able to add. Cost and maintenance. Regulation restrictions. W01 W05 W04 W02 W08 W06 W09 W03 W10 W07 1 km W11 W12 2.5km 3km

10 Sparse environment monitoring 10 Cellular communication module. –Cost ($4550/12 stations/year). –No coverage in some wild fields. WiMAX or WiFi with directional antenna. –Power consumption (around 200mW). –Installation on floating platforms. W01 W05 W04 W02 W08 W06 W09 W03 W10 W07 1 km W11 W12 2.5km 3km

11 Sparse environment monitoring 11 W01 W05 W04 W02 W08 W06 W09 W03 W10 W07 1 km W11 W12 2.5km 3km Low-power wireless sensor networks without adding extra relaying nodes?

12 Long-range wireless sensors TinyNode [H. Dubois-Ferrière et al., IPSN’ 06] – EPFL. –Semtech XE1205 Radio. –Up to 1.8km at 1.2kb/s. –868 or 915 MHz. Fleck-3 [P. Sikka et al., IPSN’ 07] – CSIRO. –Nordic nRF905 –Up to 1.3km at 100kb/s –868 or 915 MHz. 12

13 In-field test Packet Reception Rate 13 Reservoir

14 In-field test Packet Reception RateByte Reception Rate 14 Open field, Urban road and Lake 20% 60%

15 In-field test Packet Reception RateByte Reception Rate 15 Reservoir

16 Sparse sensor network 16 Enable long-distance link communication. Fully exploit the sparse network diversity.

17 Using the correct bits Forward Error Correction (FEC) coding. –Fixed correction capacity. –Accurate channel estimation. 17 Src Rec1 Data Codeword Received 10?001?? Data 00101

18 Using the correct bits Forward Error Correction (FEC) coding. –Fixed correction capacity. –Accurate channel estimation. Automatic Repeat-reQuest (ARQ). –Packet combining [H. Dubois-Ferrière et al., Sensys’ 05]. –Block retransmission [R. K. Ganti et al., Sensys’ 06]. Passively adapt to channel after transmissions. 18 Src Rec1 X1X2X3X1X2X3 X1X3 X1X2X3

19 Rateless codes Erasure channel. –Luby Transform (LT) code [M. Luby, FOCS’02] and Raptor code [A. Shokrollahi, TON’06]. Additive white Gaussian noise (AWGN). –Strider [A. Gudipati et al., SIGCOMM’11] and Spinal code [J. Perry et al., SIGCOMM’12]. 19 Transmitting an unlimited encoded stream to achieve the proper data rate.

20 Rateless codes Erasure channel. –Luby Transform (LT) code [M. Luby, FOCS’02] and Raptor code [A. Shokrollahi, TON’06]. Additive white Gaussian noise (AWGN). –Strider [A. Gudipati et al., SIGCOMM’11] and Spinal code [J. Perry et al., SIGCOMM’12]. 20 Transmitting an unlimited encoded stream to achieve the proper data rate.

21 LT code 21 X1 X2 X3 X4 Original Blocks

22 LT code 22 X1 X2 X3 X4 Y1 Y2 Y3 Y4 Y5 Y6 Y7 Original Blocks Encoded Blocks Robust Soliton

23 LT code 23 X1 X2 X3 X4 Y1 Y2 Y3 Y4 Y5 Y6 Y7 Received Blocks Y1 Y2 Y3 Y4 Y5 Y6 Robust Soliton Original Blocks Encoded Blocks

24 LT code 24 X1 X2 X3 X4 Y1 Y2 Y3 Y4 Y5 Y6 Y7 Y1 Y3 Y4 Y6 Robust Soliton Received Blocks Original Blocks Encoded Blocks

25 LT code 25 X1 X2 X3 X4 Y1 Y2 Y3 Y4 Y5 Y6 Y7 Gaussian Elimination Robust Soliton X1 X2 X3 X4 Recovered Data Y1 Y3 Y4 Y6 Received Blocks Original Blocks Encoded Blocks

26 Automatically achieve the best data rate. From rateless to distanceless 26 Transmitter X4X3X2X1 Y3Y2Y1 Receiver Y1Y4Y3Y2 X4X3X2X1 ACK Y5

27 Automatically achieve the best data rate. Release the distance constraints. From rateless to distanceless 27 Transmitter X4X3X2X1 Y3Y2Y1 Y4Y5Y3Y2Y6Y7 X4X3X2X1 ACK Receiver Insensitive to distance.

28 From distanceless link to distanceless network 28 Transmitter X4X3X2X1 Y3Y2Y1 Receiver1 Receiver2 Y1Y4Y3Y2 Y3Y2Y1 Y3Y2Y4 X4X3X2X1

29 From distanceless link to distanceless network 29 Transmitter Receiver2 Y1Y4 Y1Y3Y2Y4Y5Y6Y7Y8 X4X3X2X1 Y5Y6Y7Y8 X4X3X2X1 Insensitive to transmitters.

30 Distanceless Transmission (DLTs) 30 Distanceless Link Distanceless network Distanceless in duty-cycled mode

31 LT code on motes 31 Number of blocks4 Blocks8 Blocks16 Blocks Overhead (blocks) Robust Soliton + BP

32 LT code on motes 32 Number of blocks4 Blocks8 Blocks16 Blocks Overhead (blocks) Robust Soliton + BP Robust Soliton + GE

33 LT code on motes 33 Number of blocks4 Blocks8 Blocks16 Blocks Overhead (blocks) Robust Soliton + BP Robust Soliton + GE SYNAPSE + GE

34 LT code on motes 34 Number of blocks4 Blocks8 Blocks16 Blocks Overhead (blocks) Robust Soliton + BP Robust Soliton + GE SYNAPSE + GE Best seed + GE

35 LT code on motes 35 Number of blocks4 Blocks8 Blocks16 Blocks Overhead (blocks) Robust Soliton + BP Robust Soliton + GE SYNAPSE + GE Best seed + GE Decoding time (ms) GE

36 Parallel receiving and decoding 36 Receiving (R) Transceiver Microcontroller SPI Reading R RRR D Decoding (D) DDD Transceiver Microcontroller

37 Back Substitution New Blocks Accumulative Gaussian elimination 37 Triangularization New Blocks

38 Decoding time 38 < 0.4ms

39 From distanceless link to distanceless network 39 Transmitter X4X3X2X1 Receiver1 Receiver2 Y1Y4Y3Y2Y5Y6Y7Y8 X4X3X2X1 ETX=1 ACK Y3Y2Y1Y3Y2Y1 Y3Y2Y4 X4X3X2X1 Dynamic block size?

40 Expected Distanceless Transmission Time (EDTT). Distanceless networking 40 Number of original blocks Coding efficiency Block reception rate

41 Distanceless networking 41 Transmitter X4X3X2X1 Receiver1 Receiver2 Y1Y4Y3Y2Y5Y6Y7Y8 X4X3X2X1 EDTT=11ms EDTT=18ms Y3Y2Y1Y3Y2Y1 Y3Y2Y4 X4X3X2X1 Sink Receiver2 EDTT=16ms EDTT=10ms

42 Data Packet Distanceless in duty-cycled mode 42 Receiver1 Receiver2 Transmitter

43 Distanceless in duty-cycled mode 43 Receiver1 Receiver2 Transmitter Data Packet

44 Rateless preamble in low duty-cycled mode. Distanceless in duty-cycled mode 44 Y1Y2Y3Y4Y5Y11Y12Y13Y14Y15Y6Y7Y8Y9Y10 Y16Y17Y18Y19Y20 Y21Y22Y23Y24Y25 Receiver1 Receiver2 Y1Y2Y3Y4Y5 Transmitter

45 Rateless preamble in low duty-cycled mode. Distanceless in duty-cycled mode 45 Receiver1 Receiver2 Y11Y12Y13Y14Y15Y6Y7Y8Y9Y10 Y16Y17Y18Y19Y20 Y21Y22Y23Y24Y25 Y6Y7Y8Y9Y10Y6Y7Y8Y9Y10 Transmitter

46 Y11Y12Y13Y14Y15 Rateless preamble in low duty-cycled mode. Distanceless in duty-cycled mode 46 Receiver1 Receiver2 Y11Y12Y13Y14Y15 Y16Y17Y18Y19Y20 Y21Y22Y23Y24Y25 Y6Y10 Y11Y12Y13Y14Y15 X4X3X2X1 ACK Transmitter

47 System Implementation 47

48 System Implementation 48 PHY MAC Network Application Bits Packets

49 System Implementation 49 PHY MAC Network Application Parallel receiving and decoding Routing Forwarder checking Logical link control Decoding Encoding Encoded blocks Bits Data /ACK ACK Packets

50

51 Wind measurement deployment 51 W01 W05 W04 W02 W08 W06 W09 W03 W10 W07 1 km W11 W12 2.5km 3km [W. Du et al., IPSN’14, TOSN’14]

52

53 53 TinyNode Data Logger Battery

54 A single 1.0-km link (W01->W06) 54

55 A single 1.0-km link (W01->W06) 55

56 A single 1.0-km link (W01->W06) X

57 Wind data collection network 57 Traffic load. –1 packet/min. –64 byte/packet. Benchmark approaches. –CTP + BoX-MAC [D. Moss et al., TP Standford’08]. –ORW (Opportunistic Routing in Wireless sensor networks) [O. Landsiedel et al., IPSN’12]. –ORW + Seda [R. K. Ganti et al., Sensys’06].

58 Data yield 58

59 Latency 59

60 Energy consumption 60

61 Overhead 61

62 Conclusions 62 Distanceless - A networking paradigm for sparse wireless sensor networks. In-field deployment for wind distribution measurement over an urban reservoir. Orthogonal to the hardware platforms.

63 Thank you!

64 TinyNode-based deployment 64 SensorScope [G. Barrenetxea et al., SenSys'08, IPSN’08], 16 TinyNode in 500m*500m PermaDAQ [J. Beutel et al., IPSN'09] X-Sense [J. Beutel et al., DATE‘11]

65 Rateless code on motes Rateless Deluge [IPSN’08], SYNAPSE [SECON’08], AdapCode [INFOCOM’08], SYNAPSE++ [TMC’10], ReXOR [TMC’11], ECD [ICNP’11], MT-Deluge [DCOSS’11] 65 Packet-level coding Per-hop transmission Do not adapt to channel Overhead and decoding time

66 Challenges Rateless link transmissions on motes –Coordinating the sender and receiver –Rateless codes on source-constrained motes Tradeoff between decoding efficiency and decoding time Harnessing network diversity –Proper metric to evaluate byte-level links –Optimize the performance in low duty cycled networks 66

67 67


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