Agenda
z Research background

An autonomous data gathering scheme
adaptive to sensing requirements
for industrial environment monitoringz Monitoring of shaft furnace in steel plantz An autonomous data gathering schemez Adaptive sensing task engagement

using response threshold model
Yoshiaki Taniguchi Naoki Wakamiya Masayuki Murata
Osaka University, Japanz Energy efficient transmission and sleep schedulingusing pulse-coupled oscillator modelz Simulation results and demonstration

Takashi Fukushima
Kobe Steel, Inc., Japanz Conclusion and future work

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Wireless sensor networks (1)Wireless sensor networks (2)z A data gathering scheme for wireless senorz In periodical data gathering, sleep scheduling isnetworks must be:2

good to save energy consumption

z Energy-efficient

A sensor node is typically powered by a battery thatcannot be easily replacedz Fully-distributed, self-organizing
A large number of sensor nodes are often deployed anddistributed in an uncontrolled way

z In some classes of applications,z A sensor node needs to change its sensing interval toBS (Base Station)

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3IFIP NTMS 2008@Tangiermonitor the region more frequently when it detects
unusual conditions and phenomena.
z The number of sensor nodes which monitor and report
the phenomena should be regulated in accordance with
its criticality and importance.
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Shaft furnace in steel plantResearch targetz Deployment of temperature and CO gas sensors

z Proposal of a data gathering scheme adaptive to4sensing requirementsz Temperature changes slowly or stays long periodz CO gas may suddenly appear, move fast, and dissipate

z To accomplish self-organizing control:z Three intervals of monitoring are requiredz Adaptive sensing task engagementz Monitoring temperature and CO gas in stable conditions

Æ Response threshold modelz Monitoring temperature more frequently when changes

are detectedz Monitoring CO gas more
frequently than temperaturewhen CO gas is detectedz Energy efficient transmission and sleep scheduling
Shaft Furnace
Cross bow

MPR2400J

MPR2400J

Cross bow

MPR2400J

MPR2400J

MPR2400J

Cross bow

MPR2400J

Shaft
Furnace BSCrossbow

Cross bow

Monitoring
Room

MPR2400J

MPR2400J

Cross bowCross bow

MPR2400J

MPR2400J
Cros sbow

MPR2400JSensor NodeFloor

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Æ Pulse-coupled oscillator model

MPR2400J
Cros sbow

Cros sbow

Cross bow

Cross bow

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Sensing state

Basic behavior in normal statez All sensor nodes have kmax sensing devices

z Timing of broadcast emissionz Ex) temperature, CO gas

BSBSz Sensor node i has two sensing state for each sensor kA

z Normal statez Monitoring at a normal interval of T sec.

CBz Frequent state

BCDD

z Monitoring at a new interval of Tk sec. (Tk < T)

Az To relay sensor data from sensor node i to a BS (base station),Esensor nodes on the path from sensor node i to the BS alsochange their operation interval to Tk sec.

Eτmax τmax Normal interval T

Wireless Sensor NetworkTimeRadio signals

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Active7 Nov. 2008

SleepBroadcast
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Basic behavior in frequent state

Decision of sensing state (1)z Timing of broadcast emission

z To decide a sensing state in self-organizing manner,

we use response threshold model

BSBS

z Mathematical model of division of labor and taskSensor node B
moves
A tofrequent stateA

allocation in social insectsz Demand of sensing target k at sensor node i

BCC
BTk

ds i , km (t )= δ i , k (t ) − α i , kdtni , k ( t )DDmi,k: the number of neighbor nodes in frequent stateni,k: total number of neighbor nodes
δi,k: rate of temperature change / CO gas value itselfEEτmax τmax Normal interval T

Wireless Sensor Network
Time
Radio signals
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ActiveSleep

If the number of workers is insufficient, the demand increases

Broadcast
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Decision of sensing state (2)Maintenance of broadcast timing (1)z Probability of state transitionz To autonomously generate and maintain timing ofmessage propagation, we use pulse-coupledoscillator model

2

P(normal state Æ frequent state) =si ,k (t )si ,k (t ) + θ i ,k (t )22

P(frequent state Æ normal state) = pi , k (t )z Mathematical model of synchronization observed in agroup of flashing firefliesz Adjustment of threshold θidθ i ⎧ − ξ=⎨dt ⎩+ ϕif i performs frequent sensing
otherwiseThis threshold adjustment makes specialists having a small
threshold and keep sensing the target frequently.
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Maintenance of broadcast timing (2)Control parametersz Sensor node behaviorz Sensor node i has:Sensor node has phase φ∈[0,T]z When the phase reaches T, the sensor node i broadcasts a
message and the phase jumps back to 0z Neighboring sensor node closer to edge of WSN are stimulatedand advance their phase by an amount Δ(φ)
EdgeT
By exchanging messages
zφjΔ (φ j )Δ (φ j )

0T

φi0
τ

BS side7 Nov. 2008

τ timeand using appropriate Δ,
message propagation
keeping a fixed phasedifference τ isaccomplished regardlessof initial condition [2]13IFIP NTMS 2008@Tangier

Level 2BSz Level value liz Number of hops from BSz Sensing state vector Xi
z Relay flag vector Fiz Used to notify downstream nodes of the existence of upstream

nodes in frequent statez Parameters of response threshold modelz Sensor data Di

7 Nov. 2008z Sensor node behaves in accordance with its phasez Simulation settings

Area A

200 nodes are randomly distributedin 100x100 m2 regionz Range of radio signals is fixed at 20 m
z Energy model is based on MICAz
z Data gathering intervals

Area Bzz Wake upz Receive broadcast messages from upstream nodez Receive broadcast messages from same-hop nodezz

z Monitor and broadcast a messagezz Receive broadcast messages from downstream nodezz Details are in the paperz

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Normal state: 160 sec.
Temperature frequently state: 40 sec.
CO gas frequently state: 10 sec.

BSTEMP.

GASArea CArea D

Wireless sensor network

z Simulation scenario

z Sleep

Timing of message emissions

From 500 to 1500 seconds, temperature increases in Area D
From 1000 to 2000 seconds, CO gas leaks in Area C and moves
to Area A at 0.08m/sec.

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16Energy consumption / duty cyclez Adaptive intervals at 10/40/160 sec. (Proposal)

CO gas moving
Temperature changing

z Total energy consumption: 57.6 mJ/node
Area B Area C Area D

20015010050

Area A

Label of sensor node

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Simulation experiments

and relay flag vectorz Sensor node periodically acts as follow:

Level 0z Offset τiSensor node behavior

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Level 1z Phase φiz Duty cycle: 0.03/node
Area A

Area Bz Fixed intervals at 10 sec.

BSTEMP.
GASArea C

Area Dz Total energy consumption: 632 mJ/nodez Duty cycle: 0.2 /node

Wireless sensor network

000

500
500

1000
1000

1500
1500

2000
2000

2500
2500

Time [sec]7 Nov. 2008

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3Demonstration

Conclusion and future workz Simulatorz Proposal of a data gathering scheme for industrial

environment monitoring

Red node: active
z Gray node: sleepingz Pink region: temperature is changing
z Blue region: CO gas is existzz Adaptive sensing task engagement using response

threshold modelz Energy efficient transmission and sleep scheduling usingz Data gathering intervals

pulse-coupled oscillator model

Normal state: 32 sec.
Temperature frequently state: 8 sec.
z CO gas frequently state: 4 sec.
zz Preliminary simulation experiments

zz Autonomous and energy-efficient data gatheringz Future workz Simulation scenariozzTemperature increases and stays in an area
CO gas leaks, moves, and disappears

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JAVA simulatorz In-depth evaluation of the sensing adaptabilityz Implementation of our scheme
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Thank you4