Automating Wireless Sensor Network Deployment
and Replacement in Pipeline Monitoring
Ted Tsung-Te Lai
Albert Wei-Ju Chen
Kuei-Han Li
Polly Huang
Hao-Hua Chu
National Taiwan University
Ted Tsung-Te Lai
Albert Wei-Ju Chen
Kuei-Han Li
Department of Computer Science and Information Engineering
Polly Huang
Graduate Institute of Networking and Multimedia
Department of Electrical Engineering
Hao-Hua Chu
Graduate Institute of Networking and Multimedia
Department of Computer Science and Information Engineering
Outline
Motivation
TriopusNet System Design
Evaluation
Limitations
Related Work
Conclusion
Water pipelines are everywhere people live
Pipelines carry important resources (gas, oil…etc.)
Pipeline monitoring is essential-clean water
•Motivation
leaking
leaking
Water contamination (Boston, 2010)
Difficult sensor deployment-traditional monitoring
WSN challenges (Deployment and maintenance)
• Deployment challenges
– Difficult to access pipelines to place sensors (often hidden
inside walls or underground)
– May need to break pipes to install sensors inside
• Maintenance challenge
– Difficult to replace out-of-battery sensors
• Real pipeline environment
– Difficult to ensure network connectivity during sensor
placement and replacement
Research question
• Can we automate WSN sensor placement and
replacement in pipeline?
– While minimize the number of sensor nodes
– Good sensing and networking coverage
• Reduce the human effort bottleneck for long-term,
large-scale WSN deployment & maintenance.
The system involves the following:
1.
Preparation Step
• Knowing the spatial topology(turning faucets on
one after another).
2.
Sensor Deployment Step
• Compute deployment location then send “release”
message and position to node.
3.
Sensor Latching Step
• Compute location, attach itself, completion
message.
4.
Sensor Replacement Step
• Consume battery power during the data collection
phase.
• Detach itself, go to faucet, exit.
Single-Release Point the enabling concept
Place sensors at a single release point
Sensors automatically place themselves in the pipes
Single-release point
How to realize single-release point?
• Sensor placement
–
–
–
–
Mobile sensors
Sensor latch mechanism
Sensor placement algorithm
Sensor localization
• Sensor replacement
– Sensor replacement algorithm
Limitations
1. The spatial topology of pipeline must be
known.
2. Manual effort is required to open faucets.(at
the beginning, at battery replacement)
3. Current sensor measures 6 cm in diameter.
Outline
Motivation
TriopusNet System Design
Evaluation
Limitations
Related Work
Conclusion
TriopusNet automate WSN deployment in pipeline
Triopus node
three arms for latching
Single-release point
Gateway node
Gateway node
Gateway node
TriopusNet automate WSN deployment in pipeline
• Sensor placement
–
–
–
–
Mobile sensors
Sensor latch mechanism
Sensor placement algorithm
Sensor localization
• Sensor replacement
– Sensor replacement algorithm
Mobile sensor (components)
Sensor mote(Kmote)
Actuator(motor)
pull/push a mechanical arm
Localization sensors
water pressure +
Vertical
Pipe
gyro
horizontal
pipe
Water proof
case
Mobile sensor (kmote)
+
=
Kmote
CPU board
(data processing)
USB board
(program uploading)
• A TelosB-like platform, TinyOS compatible
• Smaller form-factor, only CPU board is needed
Mobile sensor (latch & delatch mechanism)
Linear actuator, off-the-shelf from market
A motor with gear inside to control the arm
Spec:
• Stroke: 2cm
• Weight: 15gram
• Arm extending speed: 2cm/sec
2cm
1cm
0cm
Prototype #1 (8cm diameter)
Prototype #2
• One motor driving the three arms.
• Replace 3 AAA with lithium battery.
Prototype #2 (6cm diameter)
Sensor placement algorithm
• Where are the optimal locations to place
sensors in pipes (after releasing them from the single-release point)?
– Networking coverage
• Interconnectivity among all nodes
– Sensing coverage
• Each pipe segment has at least one sensor
– Minimize # of sensor nodes for deployment
Sensor placement algorithm
root
water
inlet
branch 2
n7
branch 1
faucet 1
branch 3
n6
n1
faucet 4
faucet 3
n4
n5
faucet 2
n2
n3
Sensor placement algorithm
root
water
inlet
branch 2
n7
branch 1
faucet 1
branch 3
n6
n1
faucet 4
faucet 3
n4
n5
faucet 2
n2
n3
Sensor placement algorithm
root
water
inlet
branch 2
n7
branch 1
faucet 1
branch 3
n6
n1
faucet 4
faucet 3
n4
n5
faucet 2
n2
n3
Sensor placement algorithm
root
water
inlet
branch 2
n7
branch 1
faucet 1
branch 3
n6
n1
faucet 4
faucet 3
n4
n5
faucet 2
n2
n3
Sensor placement algorithm
root
Post-order traversal : n1 -> n2 -> … n7
n7
n6
n1
n4
n2
n5
n3
Sensor placement algorithm
root
Post-order traversal : n1 -> n2 -> … n7
n7
1st
n6
n1
n4
n2
n5
n3
Sensor placement algorithm
root
Post-order traversal : n1 -> n2 -> … n7
n7
1st
n6
n1
2nd
n2
n4
n5
n3
Sensor placement algorithm
root
Post-order traversal : n1 -> n2 -> … n7
n7
1st
n6
n1
2nd
n2
n4
3rd
n3
n5
Sensor placement algorithm
root
Post-order traversal : n1 -> n2 -> … n7
n7
1st
n1
4th
2nd
n2
n4
n6
3rd
n3
n5
Sensor placement algorithm
root
Post-order traversal : n1 -> n2 -> … n7
n7
1st
n1
4th
2nd
n2
n4
n6
3rd
n3
5th
n5
Sensor placement algorithm
root
Post-order traversal : n1 -> n2 -> … n7
n7
6th
1st
n1
4th
2nd
n2
n4
n6
3rd
n3
5th
n5
Sensor placement algorithm
root
Post-order traversal : n1 -> n2 -> … n7
7th
n7
6th
1st
n1
4th
2nd
n2
n4
n6
3rd
n3
5th
n5
Sensor placement algorithm
Post-order traversal : n1 -> n2 -> … n7
root
Reasons:
1. Assure nodes cover all pipes
2. Allow blockage-free movement
(bottom-up placement)
7th
n7
6th
1st
n1
4th
2nd
n2
n4
n6
3rd
n3
5th
n5
Sensor placement algorithm
Single-release point
Gateway node
Testing packet received ratio
Bad link quality
Good link quality, placement completed
Gateway node
Gateway node
Sensor localization
Pressure graph
• Previous PipeProbe system
– cm-level positional accuracy
• Vertical pipe location
– Water pressure changes at different height levels
• Horizontal pipe location
– Node distance = node velocity * node flow time
• Pipe turn detection
– Gyroscope
Data Collection
• Collection Tree Protocol (CTP) in TinyOS
• Multi-sink tree to balance network load
(reduce the hope count and packet loss)
Single-release point
Gateway node
Gateway node
Gateway node
Sensor replacement algorithm
Single-release point
Gateway node
Gateway node
Low Battery…
Gateway node
Outline
Motivation
TriopusNet System Design
Evaluation
Limitations
Related Work
Conclusion
Testbed
Testbed spatial layout
Single-release point
150cm
200cm
200cm
200cm
200cm
200cm
Evaluation metrics
• Automated sensor placement
– # Nodes for pipeline deployment
– Data collection rate
– Energy consumption
• Automated sensor replacement
– Data collection rate
Experimental procedure (4 test scenarios)
Single-release point
5 tests for each scenario
gateway
Scenario 3
Scenario 2
Scenario 4
Scenario 1
gateway
gateway
# Deployed Nodes (Static v.s. TriopusNet deployment)
Real node location of three test runs from
scenario 4.
It shows the dynamic of each deployment.
Static (90cm)
TriopusNetA
TriopusNetB
TriopusNetC
# Automated Sensor Deployment
Avg # of nodes deployed
-Static: 7.5
-TriopusNet: 4.4
Avg. node-to-node distance: 173cm
Std: 58cm
• The overall large variation implies that
the Radio range varies significantly
from location to location.
Avg. node-to-node distance
Avg. node-to-node distance
Avg. node-to-node distance
Avg. node-to-node distance
• I-shape radio signal travel through water which absorb energy and limits its range.
Data collection rate-cumulative density function
Each node sent 1000 packets to gateway
-80% nodes achieve 99% packet receive rate
-All nodes > 86.5% rate
CDF of Positional Errors
• Overall median error 7.14 cm
• 90% of errors are less than 20.45 cm
Location
Estimates:
18
20
20
30
• Node positional accuracy is important for achieving sensing coverage in node deployment.
Energy consumption (node placement)
The energy consumed by a single act of latching is 1.01 W ,2 seconds
The average of latching is 2.35
90% required less than 5
Evaluation metrics
• Automated sensor placement
– # nodes for sensing/networking coverage
– Data collection rate
– Energy consumption
• Automated sensor replacement
– Data collection rate
Test scenario and result for replacement
Data collection rate
Initial
deployment
After
replacement
Without
replacement
0.989
0.984
0.81
The effectiveness of the
automated replacement
Set these two nodes to low
battery level and trigger
replacement
The reason of high data loss rate:
1-some sensors change route
2-isolated nodes report zero
Outline
Motivation
TriopusNet System Design
Evaluation
Limitations
Related Work
Conclusion
Limitation: Lack automatic faucets
automatic faucet
The TriopusNet
gateway control
each faucet by
sending signals
to the sensor
trigger node.
Limitation: Node size
Limitation: Node size
Single-release point
Low Battery…
Outline
Motivation
TriopusNet System Design
Evaluation
Limitations
Related Work
Conclusion
Mobile WSN Deployment
Breadcrumb System
Liu
SensorFly System
Purohit
PipeNet (pipeline monitoring)
Detect and localize leakage by pressure and ultrasonic sensors
NAWMS (water flow sensing)
HydroSense (Ubicomp’09, water event sensing)
Single-point pressure-based sensor of water usage
toilet
kitchen sink
shower
PipeProbe
(determining the spatial topology)
Outline
Motivation
TriopusNet System Design
Evaluation
Limitations
Related Work
Conclusion
Conclusion
TriopusNet: automating WSN deployment
and replacement in pipeline monitoring
Automated sensor placement and replacement to
reduce human deployment and maintenance effort:
mobile sensors with self-latching mechanism from a
single-release point
Results show smaller number of sensor nodes with
good sensing/networking coverage
Thank You