From Rateless to Distanceless: Enabling Sparse Sensor Network Deployment in Large Areas Wan DU,...

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

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 GateBridge [S. Kim et al., SenSys’ 06, IPSN’07]

Environmental monitoring normally requires sparse sampling in space.

Sparse environment monitoring

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


5

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


6

Temperature [C. Guestrin et al., ICML’05, A. Krause et al., IPSN’06, JMLR’08].

Application Requirement

Spatial Correlation


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Wind distribution [W. Du et al., IPSN’14, TOSN’14].


Spatial Correlation

W01

W05

W04W02

W08

W06

W09

W03W10

W07

1 kmW11

W12

2.5km

3km


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W01

W05

W04W02

W08

W06

W09

W03W10

W07

1 kmW11

W12

2.5km

3km

W01

W05

W04W02

W08

W06

W09

W03W10

W07

1 kmW11

W12

2.5km

3km

Wind distribution [W. Du et al., IPSN’14, TOSN’14].


Spatial Correlation


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• Dense sensor networks.– Extra relaying nodes may not be able to add.

• Cost and maintenance.• Regulation restrictions.

W01

W05

W04W02

W08

W06

W09

W03W10

W07

1 kmW11

W12

2.5km

3km


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• 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

W04W02

W08

W06

W09

W03W10

W07

1 kmW11

W12

2.5km

3km


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W01

W05

W04W02

W08

W06

W09

W03W10

W07

1 kmW11

W12

2.5km

3km

Low-power wireless sensor networks without adding extra relaying nodes?

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.

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In-field test

Packet Reception Rate

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Reservoir

In-field test

Packet Reception Rate Byte Reception Rate

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Open field, Urban road and Lake

20%

60%

In-field test

Packet Reception Rate Byte Reception Rate

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Reservoir

Sparse sensor network

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Enable long-distance link communication.

Fully exploit the sparse network diversity.

Using the correct bits

• Forward Error Correction (FEC) coding.– Fixed correction capacity.– Accurate channel estimation.

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Src Rec1

Data00101

Codeword10100101

Received10?001??

Data00101

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.

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Src Rec1

X1 X2 X3 X1 X2 X3

X1 X3

X1 X2 X3

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].

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Transmitting an unlimited encoded stream to achieve the proper data rate.

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].

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Transmitting an unlimited encoded stream to achieve the proper data rate.

LT code

21

X1

X2

X3

X4

Original Blocks

LT code

22

X1

X2

X3

X4

Y1

Y2

Y3

Y4

Y5

Y6

Y7

Original Blocks

Encoded Blocks

Robust Soliton

211 XXY

32 XY

23 XY

314 XXY

415 XXY

46 XY

27 XY

LT code

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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

LT code

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X1

X2

X3

X4

Y1

Y2

Y3

Y4

Y5

Y6

Y7

Y1

Y3

Y4

Y6

211 XXY

23 XY

314 XXY

46 XY

Robust Soliton

Received Blocks

Original Blocks

Encoded Blocks

LT code

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X1

X2

X3

X4

Y1

Y2

Y3

Y4

Y5

Y6

Y7

Gaussian Elimination

Robust Soliton

311 YYX

32 YX

4313 YYYX

64 YX

X1

X2

X3

X4

Recovered Data

Y1

Y3

Y4

Y6

Received Blocks

Original Blocks

Encoded Blocks

• Automatically achieve the best data rate.

From rateless to distanceless

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Transmitter

X4 X3 X2 X1

Y3 Y2 Y1

Receiver

Y1Y4 Y3 Y2

X4 X3 X2 X1

ACK

Y5

• Automatically achieve the best data rate.• Release the distance constraints.

From rateless to distanceless

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Transmitter

X4 X3 X2 X1

Y3 Y2 Y1 Y1Y4Y5 Y3 Y2Y6Y7

X4 X3 X2 X1

ACK

Receiver

Insensitive to distance.

From distanceless link to distanceless network

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Transmitter

X4 X3 X2 X1

Y3 Y2 Y1

Receiver1

Receiver2

Y1Y4 Y3 Y2

Y3 Y2 Y1

Y1Y3 Y2Y4

X4 X3 X2 X1


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Transmitter

Transmitter

Receiver2

Y1Y4

Y1Y3 Y2Y4Y5Y6Y7Y8

X4 X3 X2 X1

Y5Y6Y7Y8

X4 X3 X2 X1

Insensitive to transmitters.

Distanceless Transmission (DLTs)

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Distanceless Link

Distanceless network

Distanceless in duty-cycled mode

LT code on motes

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Number of blocks 4 Blocks 8 Blocks 16 Blocks

Overhead (blocks) Robust Soliton + BP 5.1 18.5 28.3

LT code on motes

32


Overhead (blocks)

Robust Soliton + BP 5.1 18.5 28.3

Robust Soliton + GE 3.0 6.0 10.9

LT code on motes

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Overhead (blocks)



SYNAPSE + GE 1.8 2.0 1.8

LT code on motes

34


Overhead (blocks)



SYNAPSE + GE 1.8 2.0 1.8

Best seed + GE 0.76 0.97 1.5

LT code on motes

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Overhead (blocks)



SYNAPSE + GE 1.8 2.0 1.8

Best seed + GE 0.76 0.97 1.5

Decoding time (ms) GE 0.9 2.4 10.1

Parallel receiving and decoding

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Receiving (R)Transceiver

Microcontroller

SPI Reading

R R R R

D

Decoding (D)

D D D

Transceiver

Microcontroller

Back Substitution

New

Blocks

Accumulative Gaussian elimination

37

Triangularization

New

Blocks

Decoding time

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< 0.4ms


39

Transmitter

X4 X3 X2 X1

Receiver1

Receiver2

Y1Y4 Y3 Y2Y5Y6Y7Y8

X4 X3 X2 X1

ETX=1

ETX=1

ACK

Y3 Y2 Y1Y3 Y2 Y1

Y1Y3 Y2Y4

X4 X3 X2 X1

Dynamic block size?

• Expected Distanceless Transmission Time (EDTT).

Distanceless networking

40

Lb

bb DTTPEDTT

R

L

BLRREL

LDTT b

bcb

datab

8)1(*

1*

1*

Number of original blocks

Coding efficiency

Block reception rate

Distanceless networking

41

Transmitter

X4 X3 X2 X1

Receiver1

Receiver2

Y1Y4 Y3 Y2Y5Y6Y7Y8

X4 X3 X2 X1

EDTT=11ms

EDTT=18msY3 Y2 Y1Y3 Y2 Y1

Y1Y3 Y2Y4

X4 X3 X2 X1

Sink

Receiver2

EDTT=16ms

EDTT=10ms

Data Packet

Data Packet

Data Packet

Data Packet

Data Packet


42

Receiver1

Receiver2

Transmitter


43

Receiver1

Receiver2

Transmitter

• Rateless preamble in low duty-cycled mode.


44

Y1 Y2 Y3 Y4 Y5

Y11 Y12 Y13 Y14 Y15

Y6 Y7 Y8 Y9 Y10

Y16 Y17 Y18 Y19 Y20

Y21 Y22 Y23 Y24 Y25

Receiver1

Receiver2

Y1 Y2 Y3 Y4 Y5

Transmitter



45

Receiver1

Receiver2Y11 Y12 Y13 Y14 Y15

Y6 Y7 Y8 Y9 Y10

Y16 Y17 Y18 Y19 Y20

Y21 Y22 Y23 Y24 Y25

Y6 Y7 Y8 Y9 Y10

Y6 Y7 Y8 Y9 Y10

Transmitter

Y11 Y12 Y13 Y14 Y15



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Receiver1

Receiver2Y11 Y12 Y13 Y14 Y15

Y16 Y17 Y18 Y19 Y20

Y21 Y22 Y23 Y24 Y25

Y6 Y10

Y11 Y12 Y13 Y14 Y15

X4 X3 X2 X1

ACK

Transmitter

System Implementation

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48

PHY

MAC

Network

Application

Bits

Packets

Packets


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PHY

MAC

Network

Application

Parallel receiving and decoding

RoutingForwarder checking

Logical link controlDecoding

Encoding

Encoded blocksBits

Bits

Data /ACK

ACK

Packets

Packets

Wind measurement deployment

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W01

W05

W04W02

W08

W06

W09

W03

W10

W07

1 kmW11

W12

2.5km

3km

[W. Du et al., IPSN’14, TOSN’14]

53TinyNode

Data LoggerBattery

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

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55


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2.3X

Wind data collection network

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• 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].

Data yield

58

Latency

59

Energy consumption

60

Overhead

61

Conclusions

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• 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.

Thank you!

TinyNode-based deployment

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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]

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]

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Packet-level coding Per-hop transmission

Do not adapt to channelOverhead and decoding time

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

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From Rateless to Distanceless: Enabling Sparse Sensor Network Deployment in Large Areas Wan DU,...

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