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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 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
4
Soil organic matter [S. Ayoubi et al., Biomass and Remote Sensing of Biomass 2011].
Sparse environment monitoring
5
Agriculture [D. G. Hadjimitsis et al., Remote Sensing of Environment - Integrated Approaches 2013].
Sparse environment monitoring
6
Temperature [C. Guestrin et al., ICML’05, A. Krause et al., IPSN’06, JMLR’08].
Application Requirement
Spatial Correlation
Sparse environment monitoring
7
Wind distribution [W. Du et al., IPSN’14, TOSN’14].
Application Requirement
Spatial Correlation
W01
W05
W04W02
W08
W06
W09
W03W10
W07
1 kmW11
W12
2.5km
3km
Sparse environment monitoring
8
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].
Application Requirement
Spatial Correlation
Sparse environment monitoring
9
• 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
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
W04W02
W08
W06
W09
W03W10
W07
1 kmW11
W12
2.5km
3km
Sparse environment monitoring
11
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.
12
In-field test
Packet Reception Rate
13
Reservoir
In-field test
Packet Reception Rate Byte Reception Rate
14
Open field, Urban road and Lake
20%
60%
In-field test
Packet Reception Rate Byte Reception Rate
15
Reservoir
Sparse sensor network
16
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.
17
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.
18
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].
19
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].
20
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
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
LT code
24
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
25
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
26
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
27
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
28
Transmitter
X4 X3 X2 X1
Y3 Y2 Y1
Receiver1
Receiver2
Y1Y4 Y3 Y2
Y3 Y2 Y1
Y1Y3 Y2Y4
X4 X3 X2 X1
From distanceless link to distanceless network
29
Transmitter
Transmitter
Receiver2
Y1Y4
Y1Y3 Y2Y4Y5Y6Y7Y8
X4 X3 X2 X1
Y5Y6Y7Y8
X4 X3 X2 X1
Insensitive to transmitters.
Distanceless Transmission (DLTs)
30
Distanceless Link
Distanceless network
Distanceless in duty-cycled mode
LT code on motes
31
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
Number of blocks 4 Blocks 8 Blocks 16 Blocks
Overhead (blocks)
Robust Soliton + BP 5.1 18.5 28.3
Robust Soliton + GE 3.0 6.0 10.9
LT code on motes
33
Number of blocks 4 Blocks 8 Blocks 16 Blocks
Overhead (blocks)
Robust Soliton + BP 5.1 18.5 28.3
Robust Soliton + GE 3.0 6.0 10.9
SYNAPSE + GE 1.8 2.0 1.8
LT code on motes
34
Number of blocks 4 Blocks 8 Blocks 16 Blocks
Overhead (blocks)
Robust Soliton + BP 5.1 18.5 28.3
Robust Soliton + GE 3.0 6.0 10.9
SYNAPSE + GE 1.8 2.0 1.8
Best seed + GE 0.76 0.97 1.5
LT code on motes
35
Number of blocks 4 Blocks 8 Blocks 16 Blocks
Overhead (blocks)
Robust Soliton + BP 5.1 18.5 28.3
Robust Soliton + GE 3.0 6.0 10.9
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
36
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
38
< 0.4ms
From distanceless link to distanceless network
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
Distanceless in duty-cycled mode
42
Receiver1
Receiver2
Transmitter
Distanceless in duty-cycled mode
43
Receiver1
Receiver2
Transmitter
• Rateless preamble in low duty-cycled mode.
Distanceless in 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
• Rateless preamble in low duty-cycled mode.
Distanceless in duty-cycled mode
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
• Rateless preamble in low duty-cycled mode.
Distanceless in duty-cycled mode
46
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
47
System Implementation
48
PHY
MAC
Network
Application
Bits
Packets
Packets
System Implementation
49
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
51
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)
54
A single 1.0-km link (W01->W06)
55
A single 1.0-km link (W01->W06)
56
2.3X
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].
Data yield
58
Latency
59
Energy consumption
60
Overhead
61
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.
Thank you!
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]
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 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
66
67