ACROSS ColloquiumACROSS Colloquium

Combined power management methods Combined power management methods in wireless networks of energy-hungry in wireless networks of energy-hungry

sensorssensors

Vana Jeličić, dipl.ing.

January 18, 2013

ContentContent

Research area WSNs – distributed event detection Communication energy Wake-up radio Energy-hungry sensors

Video surveillance and smart gas monitoring Hierarchical, adaptive, event-driven sensing

Motivation and challenges Problem approach

To-date results Future research

Activities of AIG

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Research area Research area

Wireless sensor networks Wireless sensor node Energy-efficiency

Communication!

Distributed sensing systems Event detection, alarm generation Video surveillance, gas monitoring

Energy-hungry sensors Power management

Comm. unit (RX, TX, idle state – cca 20 mA!) Sensing unit

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Power managementPower management

Duty-cycling (D) Reducing activity: sensors & radio

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Maximal reaction time

Critical event arrival worst case

tactive << T >>D = tactive / T

ENERGY LATENCY

Eliminating radio idle timeEliminating radio idle time

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“Classical” WSN problem! One-channel wake-up radio

Wake-On Radio (WOR) – radio periodically wakes up from sleep mode and listens for incoming packets without MCU interaction.

TI CC1000, CC1101, CC1100E, CC2500, CC430

MAC: B-MAC, S-MAC, X-MAC...

Optimization delay – energy trade-off

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Wake-up receiver (WURx)Wake-up receiver (WURx)

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Two-channel wake-up radio Ultra-low-power; Continuously monitoring No idle listening on main radio

Lin, Rabaey and Wolisz; “Power-efficient rendez-vous schemes for dense WSNs”, 2004, <50 uW to outperform one-channel radios!

Trade-offs wake-up range vs. energy consumption wake-up range vs. delay (multihops) in-band vs. out-of-band wake-up radio

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WURx prototypesWURx prototypes

Author Year f [GHz] Rate [kbps] S [dBm] d [m] P [uW] AD l [ms] Implement.

Le Huy 2008 2,4 50 -50 NA 20 Y NA simulation

Yu 2008 2,4 100 -75 NA 53 N NA simulation

Langevelde 2009 0,868 45 -89 NA 2400 N 1,36 130 nm

Pletcher 2009 2 100 -72 NA 52 N NA 90 nm

Durante 2009 2,4 100 -53 NA 12,5 Y, FPGA NA 120 nm

Gamm 2010 0,868 NA -52 40 2,78 Y 13 120 nm

Drago 2010 2,4 250 -87 NA 415 N NA 65 nm

500 -82 NA

Fraunhofer 2010 0,868 1 -60 30 33 Y 32 180 nm

Huang 2010 2,4 100 -64 NA 51 N NA 90 nm

0,915 100 -75 NA

Huang 2011 0,915 10 -86 NA 123 N NA 90 nm

Marinkovic 2011 0,433 5.5 -51 10 0,270 N, (MCU) 9 OTS SMD

Shih 2011 0,9165 0.370 -122 1000 1153 Y NA OTS

Hambeck 2011 0,868 100 -71 304 2,4 Y 40-110 130 nm

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Jelicic et al. Analytic Comparison of Wake-up receivers for WSNs and Benefits over the Wake-on Radio Scheme. PM2HW2N 2012.

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WURx prototypes (2)WURx prototypes (2)

Commercially available (LF, 125 kHz) Austriamicrosystems Atmel

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Addressing required Addressing not required

WURx applicationsWURx applications

Applications with WURx – proposals Building automation 1, 3, 4

Healthcare 2

No energy vs. latency trade-off!

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Still not used in WSNs!

very promising!

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1) Zhang et al. Improving Energy-Efficiency in Building Automation with Event-Driven Radio. WCSP 2011.2) Marinkovic et al. Power Efficient Networking Using a Novel Wake-up Radio. PervasiveHealth 2011.3) Gamm et al. Low Power Wireless Sensor Node for use in building automation. WAMICON 2011.4) Gamm et al. Smart Metering Using Distributed Wake-up Receivers. I2MTC 2012.

Sensing power managementSensing power management

Fixed duty cycle energy wasting Adaptive duty cycle

Wake-up latency: ton ≥ twakeup + tacquire

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Event-driven Context-awareness Energy-awareness

Heterogeneous WSNs for event detection Heterogeneous WSNs for event detection

Different sensing modalities Hierarchy Applications

Video surveillance: Camera + PIR Gas monitoring: Gas sensor + PIR

High-consuming sensors

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Smart video surveillanceSmart video surveillance

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Reducing transmitted data size Hierarchical, multi-tier, multimodal Pyroelectric InfraRed (PIR) sensor Energy-aware decisions

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Image transmissionImage transmission

Transmission of large amount of data Only when really necessary

Increasing tactive

ZigBee not intended to that Stack modificaton 1

Image fragmentation – maximal frame filling Disabled MAC acknowledgment APL layer control

Today – low power WiFi modules Avoiding transmitting large amounts of data only event

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1) Jelicic et al. Reducing Power Consumption of Image Transmission over IEEE802.15.4/ZigBee Sensor Network. I2MTC 2010.

Existing work – multimodal video networksExisting work – multimodal video networks

PIR sensor mounted on the camera board 1, 2, 3

Same FOV; Dynamically changed sensitivity

Multi-tier Multimodal WSNs 4, 5, 6, 7, 8, 9

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1) Magno et al. A Solar-powered Video Sensor Node for Energy Efficient Multimodal Surveillance. DSD 2008.2) Magno et al. Adaptive Power Control for Solar Harvesting Multimodal Wireless Smart Camera. ICDSC 2009.3) Magno et al. Multimodal abandoned/removed object detection for low power video surveillance systems. AVSS 2009.

4) Kulkarni et al. SensEye: A Multi–tier camera sensor network. ACM Multimedia 2005.5) Prati et al. An Integrated MultiModal Sensor Network for Video Surveillance. VSSN 2005.6) He et al. Vigilnet: An integrated sensor network system for energy efficient surveillance. ACM Trans. Sen. Netw. 2006.7) Lopes et al. On the Development of a Multi-tier, Multimodal Wireless Sensor Network for Wild Life Monitoring. IFIP Wireless Days 2008.8) Magno et al. Energy Efficient Cooperative Multimodal Ambient Monitoring. EuroSSC 2010.9) Jelicic et al. An energy efficient multimodal wireless video sensor network with eZ430-RF2500 modules. ICPCA 2010.

Heterogeneous WVSNHeterogeneous WVSN

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Tier 1PIR nodes

Coordinator

Camera + PIR onboard

Two-tier network

WOR duty-cycling!

wakeup

HOMOGENEOUS NWK HETEROGENEOUS NWK

Tier 2Camera nodes

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Two-tier network

WURx NO duty-cycling

Further reducing cameras’ activities

Further reducing radio activities

Smart gas monitoringSmart gas monitoring

Metal Oxide Semiconductor (MOX) Small form factor Fast response Power-efficient

Heater Resistance change

Fabrication field System-level field TWO SEPARATED AREAS BY NOW!

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Related workRelated work

Fabrication field 1, 2

Pulse mode (duty-cycling) Temperature dependence Wake-up latency 9 mW

System-level application 3, 4, 5

Duty cycle Still high energy consumption

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1) Sayhan et al. Discontinuously operated metal oxide gas sensors for flexible tag microlab applications. IEEE Sensors J. 2008.2) Rastrello et al. Thermal Transient Measurements of an Ultra-Low-Power MOX Sensor. J. of Sensors 2010.

3) Ivanov et al. Distributed smart sensor system for indoor climate monitoring. KONNEX Sci. Conf. 2002.4) Postolache et al. Smart Sensors Network for Air Quality Monitoring applications. IEEE Trans. on Instrum. and Meas. 2009.5) Choi et al. Micro sensor node for air pollutant monitoring: HW and SW issues. Sensors 2009.6) De Vito et al. Wireless Sensor Networks for Distributed Chemical Sensing: Addressing Power Consumption Limits With On-Board Intelligence. IEEE Sensors J. 2011.

Energy consumption reduction on 3 levels:

System-level application – our solutionSystem-level application – our solution

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Sensor level duty-cycling gas sensor early detection of safe conditions

Node level ultra low sleep current (8 uA) duty-cycling sensor node people presence detection (modifying duty cycle)

Network level messages from neighbor nodes (modifying duty cycle)

Sensor

Node

Network

1) Jelicic et al. Design, Characterization and Management of a WSN for Smart Gas Detection. IWASI 2011. 2) Jelicic et al. Context-Adaptive Multimodal WSN for Energy-Efficient Gas Monitoring. IEEE Sensors J. 2012.

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Early detection of safe conditionsEarly detection of safe conditions

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R [kΩ]

Clean air – after long inactive time

Clean air – after short inactive time

Contaminated air – after short inactive time

threshold A

B

47

10000900080007000

1x10-1

1x100

1x101

1x102

1x103

0 1000 2000 3000

1x10-1

1x100

1x101

1x102

1x103

time [ms]

Stable difference between clean air and contaminated air signals

4000 5000 6000

0 200

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Adaptive sampling rate (t_ON = 1s)Adaptive sampling rate (t_ON = 1s)

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Quality ratio: node lifetime / worst case reaction time

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Motivation and challengeMotivation and challenge

Policies to reduce Communication energy Sensing energy

Combined methods Reducing amount of wirelessly transmitted data

adaptive sampling, event detection

Reducing radio idle consumption Wake-up receiver

Goal Context- and energy-awareness Good QoS

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To-date work and resultsTo-date work and results

Proposed energy saving policies in WVSN & WGSN 1, 2, 5

multimodal (PIR nodes); adaptive duty-cycling

Reducing communication energy 3, 6

Extensive study and comparison of WURx solutions 4

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1) Jelicic et al. Design, Characterization and Management of a WSN for Smart Gas Detection. IWASI 2011. 2) Jelicic et al. Context-Adaptive Multimodal WSN for Energy-Efficient Gas Monitoring. IEEE Sensors J. 2012.3) Jelicic et al. Reducing Power Consumption of Image Transmission over IEEE 802.15.4/ZigBee Sensor Network. I2MTC 2010.4) Jelicic et al. Analytic Comparison of Wake-up Receivers for WSNs and Benefits over the Wake-on Radio Scheme. PM2HW2N 2012.5) Jelicic et al. An energy efficient multimodal wireless video sensor network with eZ430-RF2500 modules. ICPCA 2010.6) Jelicic et al. MasliNET – A Wireless Sensor Network based Environmental Monitoring System. MIPRO 2011.

AIG – WSN activitiesAIG – WSN activities

Sensors and sensor interfaces HW (PCB) design Measurements

Embedded systems Microcontrollers FPGA Firmware

Wireless sensor networks Power management Signal processing

ACTIVITIES

Environmental monitoring

Asthma monitoring Wheeze detection Air quality monitoring

Berth monitoring Fall detection

APPLICATIONS

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Hvala na pažnji!Hvala na pažnji!

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