SMART DUST

SMART DUST

B. Boser, D. Culler, J. Kahn, K. Pister

Berkeley Sensor & Actuator CenterElectrical Engineering & Computer Sciences

UC Berkeley

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Outline

• History

• Technology Ramblings

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Motivation

• Exponential decrease in size, power, cost• Digital computation• Analog/RF communication• Sensors

battery

Goals• Understand fundamental limits• Build working systems

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Moore’s Law, take 2

• Nanochips on a dime (Prof. Steve Smith, EECS)

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DoD Workshops

• RAND 1992• “Future Technology-Driven Revolutions in

Military Conflict”• “Smart Chaff”, “Floating Finks”• Bruno Augenstein, Seldon Crary, Noel

Macdonald, Randy Steeb, …

• Santa Fe, 1995• Xan Alexander, Ken Gabriel; Roger Howe,

George Whitesides, …

• ISAT 1995, 1996, 1997, 1998, 1999, 2000

• …

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University Programs (old slide)

• UCLA• Bill Kaiser (LWIM, WINS)• Greg Pottie (AWAIRS)

• U. Michigan• Ken Wise

• USC• Deborah Estrin

• UCB• K. Pister (Smart Dust)

• …

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Ken Wise, U. Michigan

• http://www.eecs.umich.edu/~wise/Research/Overview/wise_research.pdf

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Bill Kaiser, UCLA

• http://www.janet.ucla.edu/WINS

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August ’01 Goal

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COTS Dust - RF Motes

• Simple computer• Cordless phone radio• Up to 2 year battery life

N

S

EW 2 Axis Magnetic Sensor

2 Axis Accelerometer

Light Intensity Sensor

Humidity Sensor

Pressure Sensor

Temperature Sensor

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COTS Dust

GOALS:

• Create a network of sensors

• Explore system design issues

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COTS Dust

RESULTS:

• TinyOS – David Culler, UCB

• Manufactured by Crossbow ~ $150

• 100+ users, 40+ locations

• Military and civilian applications

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800 node demo at Intel Developers Forum

4 sensors$70,000 / 1000Concept to demo in 30 days!

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Structural performance due to multi-directional ground motions (Glaser & CalTech)

.

Wiring for traditional structural instrumentation+ truckload of equipment

Mote infrastructure15

13

14

6 

5` 

15

118 

Mote Layou

t 129 

Comparison of Results

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Cory Energy Monitoring/Mgmt System

• 50 nodes on 4th floor• 5 level ad hoc net• 30 sec sampling• 250K samples to database over 6 weeks

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29 Palms Sensorweb Experiment

• Goals• Deploy a sensor network onto a road from an unmanned

aerial vehicle (UAV)• Detect and track vehicles passing through the network• Transfer vehicle track information from the ground network

to the UAV• Transfer vehicle track information from the UAV to an

observer at the base camp.

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Flight Data

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Dragon WagonFrom UAV

Dragon Wagon

HMMWVFrom UAV

HMMWV

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Last 2 of 6 motes are dropped from UAV

• 8 packaged motes loaded on plane

Last 2 of six being dropped

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Detection algorithm

bAx

t

t

t

t

t

v

p

p

p

p

4

3

2

1

4

3

2

1

/1

1

1

1

1

Each vehicle V(v,t) has two parameters:1) Speed (v)2) Time at beginning of network (t)The n-node network is described by an n-entry pattern vector p:The jth entry is the time we expect that node j will see V(1,0)

Times when nodes detect V are collected in the t vector

Linear least-squares guess at v and t

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Room to spare!

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RF Sensitivity

• Pn = kBT f Nf

• Sensitivity = Pn + SNRmin

• e.g. GSM (European cell phone standard), 115kbps

kBT 200kHz ~8x SNRS = -174dBm + 53 dB + 9 dB + 10 dB = -102 dBm

RX power = ~200mWTX power = ~4W 50 uJ/bit

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RF Path Loss

• Isotropic radiator, /4 dipole• Pr=Pt / (4 (d/)n)

• Free space n=2

• Ground level n=2—7, average 4

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N=4

From Mobile Cellular

Telecommunications,

W.C.Y. Lee

Pt = 10-50W

-102dBm

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Path Loss

• Like to choose longer wavelength• Loss ~(d)n

• 916MHz, 30m, 92dB power loss need –92dBm receiver for 1mW xmitter power!

• Penetration of structures, foliage, …

• But…• Antenna efficiency • Size – /4 @ 1GHz = 7.5cm

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Output Power Efficiency

• RF• Slope Efficiency

• Linear mod. ~10%• GMSK ~50%

• Poverhead = 1-100mW

• Optical• Slope Efficiency

• lasers ~25%• LEDs ~80%

• Poverhead = 1uW-100mW

Slope Efficiency

TrueEfficiency

Pin

Pout

Poverhead

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Cassini

Limits to RF Communication

• 8 GHz (3.5cm)• 20 W• 1.5x109 km• 115 kbps• -130dbm Rx• 10-21 J/bit

• kT=4x 10-21 J @300K• ~5000 3.5cm photons/bit

Canberra• 4m, 70m antennas

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Video Semaphore Decoding

Diverged beam @ 5.2 km

In shadow in evening sun

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~8mm3 laser scanner

Two 4-bit mechanical DACs control mirror scan angles.

~6 degrees azimuth, 3 elevation

1Mbps

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Application to Microassembly

• Pattern complementary hydrophobic shapes onto parts and substrates using SAMs.• no shape constraints on parts• no bulk micromachining of

substrate• submicron, orientational

alignment

• Uthara Srinivasan, Ph.D. thesis,UC Berkeley Chem.Eng., May 2001

Courtesy: Roger Howe, UCB

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Mirrors in Solution

Courtesy: Roger Howe, UCB

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Mirrors on Microactuators

assembled mirror

Courtesy: Roger Howe, UCB

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CMOS Imaging Detector

Photosensor

Signal ProcessingA/D Conversion

SIPO ShiftRegister

CRC CheckLocal Bus Driver

Off ChipBus Driver

Pixel Array

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Power and Energy

• Sources• Solar cells ~0.1mW/mm2, ~1J/day/mm2

• Combustion/Thermopiles

• Storage• Batteries ~1 J/mm3

• Capacitors ~0.01 J/mm3

• Usage• Digital computation: nJ/instruction• Analog circuitry: nJ/sample• Communication: nJ/bit

10 pJ27 pJ/sample

11 pJ RX, 2pJ TX

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Smart Dust - Processes (CMOS)

13 state

FSMcontroller

ADC70kS/s, 1.8uW

ambient lightsensor

Photodiode

Sensor input

Oscillator

Power input PowerTX Drivers0-100kbpsCCR or diode

Optical Receiver1 Mbps, 11uW

1mm

330µ

m

What’s working – Oscillator, FSM, ADC, photosensor, TX drivers

What’s kind of working – Optical receiver (stability problems lead to occasional false packets)

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Power, sensor, motor fab

Isolation trenches are etched through an SOI wafer and backfilled with nitride and undoped polysilicon.

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Power, sensor, motor fab

Solar cells and circuits are created by ion implantation, drive-in, oxidation, contact etching, aluminum sputtering and etching.

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Actuators are deep reactive ion etched through device layer.

Power, sensor, motor fab

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Optional backside etch (would actually precede front side etch)

Power, sensor, motor fab

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Solar Cell Results

Solar Array Performance

-0.4

-0.3

-0.2

-0.1

0.0

0.1

0.2

0 5 10 15 20 25 30

Voltage (V)

Cu

rren

t (u

A)

0.5 to 100 V demonstrated10-14% efficiency

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Power from MEMS CombustionPower from MEMS Combustion

Thermopiles

Nozzle(w/ igniter)

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Closing in on 1mm3

2.8mm2.

1mm CCR

Accelerometer

Solar Cells

CMOS IC

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Smart Dust - Integration

Solar Cell Array CCR

XL

CMOSIC

16 mm3 total circumscribed volume~4.8 mm3 total displaced volume

SENSORS ADC FSMRECEIVER

TRANSMITTER

SOLAR POWER1V 1V 1V 2V3-8V

PHOTO 8-bits

375 kbps

175 bps

1-2V

OPTICAL IN

OPTICAL OUT

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175 bps from 10 mm3

CCR Drive Voltage

Detected Transmission

Sample from XL pad(connected to Vdd)

Echo ofDownlink data

Sample fromphotosensor

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Mote with Micro-battery from Lee & Lin, UCB

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Optical Communication

0-25% 25%

Path loss

Loss = (Antenna Gain) Areceiver / (4 d2)

Antenna Gain = 4 / ½2

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Theoretical Performance

Ptotal = 50mWPt = 5mW½ = 1mradBR = 5 Mbps

Areceiver = 1cm2 Pr = 10nW (-50dBm)Ptotal = 50uWSNR = 15 dB~10,000 photons/bit

5km

Photosensor

Signal ProcessingA/D Conversion

SIPO ShiftRegister

CRC CheckLocal Bus Driver

Off ChipBus Driver

Pixel Array

10nJ/bit

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Theoretical Performance

Ptotal = 100uWPt = 10uW½ = 1mradBR = 5 Mbps

Areceiver = 0.1mm2 Pr = 10nW (-50dBm)Ptotal = 50uWSNR = 15 dB

5m

20pJ/bit!

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~2 mm^2 ASIC

RF mote

• CMOS ASIC• 8 bit microcontroller• Custom interface circuits

• External components

uP SRAM

RadioADC

Temp

Ampinductor

crystal

battery

antenna

~$1

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Radio basics

• Tuneable frequency, 900MHz +/-100 MHz

• Programmable power output• -10 – 0 dBm out, 1 – 10 mW in• 100 kbps?

Tuneable cap.

Oscillator core

Tuneable power

13 bit freq. reg.

8 bit power reg.

uP

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Radio basics

• Tuneable frequency, 900MHz +/-100 MHz

• Programmable sensitivity• -100 – -90 dBm, 0.1 – 10 mW in• 100 kbps?

• Many interface options• Direct memory• Low power vigilance?

Oscillator core

DMA pointer

uP SRAM

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Crystal-free radio?

• ~20% variation in frequency reference in CMOS

• I measure your frequency output in my coordinate system, and vice versa

• Theory of coupled oscillators

• Digital feedback between nodes

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Wakeup synchronization

• Watch crystals• 32kHz, 30nW• 10-100 ppm drift

• 1-10 ms/min• 1-10 sec/day• 5-50 min/year

• Temperature is primary source of drift• Compensate to sub-ppm – 100ppb?

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RF Mote Summary

• Available 2003• Radio

• 900 MHz• 10+ m range• 10 nJ/bit (0.3mA, 100kbps)

• 8 bit Atmel-ish uP• 10pJ/inst (0.03mA)

• 10 bit ADC• 100kS/s, 30nJ/sample (0.01mA)

• Batteries• Lithium coin cell ~ 220mAh• AA batteries 1000mAh

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Abstracting the Hardware

• Goal:• Provide realistic energy (and time) metrics to

drive algorithm development• Allow software/algorithms to drive hardware

design.

Rene mote Mica moteLaptops & Wavelan

Abstract representation of hardware

Diffusion routing Routing tables…

Centralizedlocalization

Distributedlocalization

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Abstracting the Hardware

• Too simple:• “computation” = x pJ• Comm = y nJ/bit*m^4• Sensing = z pJ/sample

• Too complex:• 16 bit add register to non-cached main

memory = x pJ, • …

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Abstracting the Hardware

• Need a representation(s) of• Energy cost• Latency

• Probabilistic?

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Example: maximize sensor net lifetime

• Given:• Costs of sensing, computation, communication• Fixed sensor locations

• Connectivity matrix• One or more base stations

• Find:• Energy-optimal routing to get data back from each

node (define it first!)

• Everyone on all the time

• Duty cycling

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Example: minimal coverage

• Given:• Costs of sensing, computation, communication• Sensor range, communication range• Mote weight dominated by battery

• Find:• Minimal dispersion of motes (in kg/km2 !) st.

events x,y,z can be sensed for time t

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Example: minimal coverage

• Workstation?

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Example: minimal coverage

• Smart dust?

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Example: minimal coverage

• Some of both?

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Mobility

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Other topics

• Simulation of big networks

• Data fusion/compression

• Information theory• Shannon for sensor networks• What is “capacity”?

• Collaborative signal processing• Definition• Existence?

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Summary

• Cubic-inch RF motes working in applications

• 10 mm3 optical motes demonstrated

• 10 mm3 RF motes coming

• Peer-to-peer networking

• Most communication is relay

• Energy cost to communicate 1 bit is at least 1000x greater than an 8 bit instruction

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Conclusion

1 mm3 or bust!!!