Transcript Smart Dust with Legs

SMART DUST
Hardware Limits to Wireless Sensor Networks
Kris Pister
Berkeley Sensor & Actuator Center
Electrical Engineering & Computer Sciences
UC Berkeley – [email protected]
(on leave to start Dust Inc – [email protected])
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Ken Wise, U. Michigan
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http://www.eecs.umich.edu/~wise/Research/Overview/wise_research.pdf
Bill Kaiser, UCLA
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http://www.janet.ucla.edu/WINS
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Wireless dawn sensor
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Computation
Difference Engine
Charles Babbage, 1822
Steve Smith, UCB
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Multi-hop message passing
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Lots of exponentials
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Digital circuits
• Speed, memory
• Size, power, cost
Communication circuits
• Range, data rate
• Size, power, cost
Computation
Communication
MEMS Sensors
• Measurands, sensitivity
• Size, power, cost
Sensing
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Smart Dust Goal
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COTS Dust - RF Motes
• Simple computer
• Cordless phone radio
• Up to 2 year battery life
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W
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S
2 Axis Magnetic
Sensor
2 Axis Accelerometer
Light Intensity
Sensor
Humidity Sensor
Pressure Sensor
Temperature Sensor
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Open Experimental Platform to
Catalyze a Community
Services
David Culler, UCB
Networking
TinyOS
WeC 99
“Smart Rock”
Rene 00
Small microcontroller
- 10 kb
EEPROM storage (32 KB)
Simple sensors
Mica 02
Demonstrate
scale
- 8 kb code, 512 B data
Simple, low-power radio
Dot 01
Designed for
experimentation
-sensor boards
-power boards
NEST open exp. platform
128 KB code, 4 KB data
50 KB radio
512 KB Flash
comm accelerators
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800 node demo at Intel Developers Forum
4 sensors
$70,000 / 1000
Concept to demo in 30 days!
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Structural performance due to multi-directional
ground motions (Glaser & CalTech)
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Mote
Layout
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6`
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Mote infrastructure
Comparison of Results
Wiring for traditional
structural instrumentation
+ truckload of equipment
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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
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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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Last 2 of 6 motes are dropped
from UAV
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8 packaged motes loaded
on plane
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Last 2 of six being dropped
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Available Sensors
• Demonstrated w/ COTS Dust
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Temperature, light, humidity, pressure, air flow
Acceleration, vibration, tilt, rotation
Sound
Demonstrated Actuators
GPS
• Motor controllers
Gases (CO, CO2)
• 110 VAC relays
Passive Infra-red
• Audio speaker
Contact/touch
• RS232: LCD, …
• Available
• Images, low-res video
• Gases (VOCs, Organophosphates, NOx…)
• Neutrons
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Blue Mote Hardware
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Chipcon cc1000 radio
• RX Power: 9.6-14 mA (-102 -> -105 dBm)
• TX Power: 12-25 mA, (-5 to 4 dBm) range
~50m indoors
• Bit rate up to 76,800 kbps
TI MSP430 Processor
• ~1mA @ 4MHz
Operating Voltage 2.1-3.3 V
Sleep mode = 3 mA
Same damn 51 pin connector
$50-$100
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Basic Operations
• Sleep
• Listen for activity on radio
• Sample sensors
• Synchronize clocks
• Scheduled chat with neighbor
• Message via multihop
• Data
• “Warning!”
• “We’re all fine down here”
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Cost of Basic Operations
Operation
Current
[A]
3u
1m
25m
Time Charge
[s]
[A*s]
20u
5m
20n
125m
10m
8m
80m
Sound an alarm
25m
1s?
25,000m?
Listen for alarm
2m
2m
4m
Sleep
Sample
Talk to neighbor
15 byte payload
Listen to neighbor
15 byte payload
QAAbattery = 2000mAh = 7,200,000,000 mA*s
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Typical Topologies
Star
Linear
Tree
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Application Energy Breakdown
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Collect Data from 3 Children every 15 seconds (RX cost
include synchronization)
Send 4 data packets every 15 seconds
Alarm check once per second
Send 10 alarms per day
Expected Lifetime: 4.1 Years
Cost Each (mJ)
RX
0.24
TX
0.375
Alarm Check
0.012
Alarm Send
75
Number Per Day mJ per Day % of Total
17280
4147.2
28%
23040
8640
59%
86400
1036.8
7%
10
750
5%
Total:
14574
Battery Life (years):
4.1
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HDK Implementation
Report Interval (user controlled, 0 to 256 seconds)
Reporting Slots 32 ms
Collect data from children
Send to parent
Periodic Alarm Message Checks
Sensor Sampling
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Alarm Msg
Alarm Msg Forward
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Time period definitions
Report Interval (user controlled, 0 to 256 seconds)
Reporting Slots 32 ms
Tepoch
tslot
Periodic Alarm Message Checks
talarm
Sensor Sampling
tsample
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HDK Extrema
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Max data rate through a single mote: 1kB/s
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Max data rate via linear multihop: 300B/s
Latency in multihop communication: n*tslot
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Alarm lifetime = talarm*Qbat/Qcheck
Alarm latency < n*talarm
• E.g. talarm = 0.1s; n=20; N=1,000,000
Lifetime = 6 years
Latency < 2 s
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“We’re all fine” lifetime = (Qbat / (Qmsg )* (Tepoch /(1+nkids))
• E.g. Tepoch = 20 min; nkids = 1000
 Lifetime = 3 years
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Application Energy Breakdown
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Collect Data from 3 Children every 15 seconds (RX cost
include synchronization)
Send 4 data packets every 15 seconds
Alarm check once per second
Send 10 alarms per day
Expected Lifetime: 4.1 Years
Cost Each (mJ)
RX
0.24
TX
0.375
Alarm Check
0.012
Alarm Send
75
Number Per Day mJ per Day % of Total
17280
4147.2
28%
23040
8640
59%
86400
1036.8
7%
10
750
5%
Total:
14574
Battery Life (years):
4.1
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One Chip, Four Dissertations
• CMOS ASIC
• 8 bit microcontroller
• Custom interface circuits
• External components
Temp
~$1
uP
SRAM
Amp ADC Radio
~2 mm^2 ASIC
battery
antenna
inductor
crystal
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Working silicon
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8 bit uP
3k RAM
OS accelerators
World record low power 8
bit ADC (100kS/s, 2uA)
HW Encryption support
900 MHz transmitter
Functional, running TinyOS,
sending packets to Blue
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Working mote, happy grad student
Jason Hill
Jason’s mote
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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 10 pJ
• Analog circuitry: nJ/sample 20 pJ/sample
• Communication: nJ/bit 11 pJ RX, 2pJ TX (optical)
10 nJ/bit RF
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Energy and Lifetime
• 1 mAh ~= 1 micro*Amp*month (mAm)
• Lithium coin cell: 220 mAm
• AA alkaline ~ 2000 mAm
(CR2032, $0.16)
• 100kS/s sensor acquisition: 2mA
• 1 MIPS custom processor: 10mA
• 100 kbps, 10-50 m radio: 300mA
• 1 month to 1 year at 100% duty
• 10 year lifetime w/ coin cell  1% duty
• Sample, think, listen, talk, forward…
2 times/second!
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Energy Considerations
• Storage
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Batteries today: 700 Wh/kg (Tadiran)
Battery limits: 8,000 Wh/kg (Aluminum/air)
Gasoline: 12,700 Wh/kg (upper heating value)
H2: 50,000 Wh/kg (upper heating value)
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Energy Considerations
• Sensing
• 1pJ/S @ 10 bits
• Power ~ 22N f
(re: 20pJ/S @ 8 bits)
Scott, Boser, Pister, An Ultra-Low Power ADC for Distributed
Sensor Networks, ESSCIRC 2002.
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Energy Considerations
• Computation
• Power ~ CV2 f
• C = NgC0
• C0 = er e0 A/d
~ 5fF/mm2
• For 8 bit ops, Ng ~100
• A ~ Ld2
• A = 0.020mm2 today (Ld =0.13)  10pJ
• A = 0.001mm2 2010 (Ld =50nm)  0.5pJ
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RF Sensitivity
• Pn = kBT Df Nf
• Sensitivity = Pn * SNRmin
• e.g. GSM (European cell phone standard),
115kbps
k BT
200kHz ~8x
SNR
S = -174dBm + 53 dB + 9 dB + 10 dB
= -102 dBm
RX power = ~200mW
TX power = ~4W  50 uJ/bit
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RF Path Loss
• Isotropic radiator, l/4 dipole
• Pr=Pt / (4p (d/l)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 ~(l/d)n
• 916MHz, 30m,  92dB power loss
•  need –92dBm receiver for 1mW xmitter
•  power!
• Penetration of structures, foliage, …
• But…
• Antenna efficiency
• Size – l/4 @ 1GHz = 7.5cm
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Output Power Efficiency
• RF
• Slope Efficiency
• Linear mod. ~10%
• GMSK ~50%
• Poverhead = 1-100mW
Pout
True
Efficiency
Slope
Efficiency
• Optical
• Slope Efficiency
• lasers ~25%
• LEDs ~50%
• Poverhead = 1uW-100mW
Poverhead
Pin
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Limits to RF Communication
Cassini
• 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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Integrated Microwatt Transceiver,
Howe/Rabaey, UCB
•Radios need filters
•The best filters are electromechanical
•Power is related to size
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Mike Sailor’s Smart Dust
M. Sailor
UCSD Chemistry
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CMOS Cameras
• Today
• 5mm scale
• 1mJ/image
• 110,000 pixels
• Tomorrow
• 1mm scale
• 50pJ * #pixels / image ~ 1uJ
• 16k pixels
• Soon
• 1mm scale
• 1pJ * # pixels /image ~ 1uJ
• 1M pixel
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Single Nanotube Inverter - IBM
Atomic Force Microscope image showing the design of an intramolecular logic gate. A single carbon nanotube (shaded in blue) is
positioned over gold electrodes to produce two p-type carbon
nanotube field-effect transistors in series. The device is covered
by an insulated layer (called PMMA) and a window is opened by ebeam lithography to expose part of the nanotube. Potassium is
then evaporated through this window to convert the exposed ptype nanotube transistor into an n-type nanotube transistor, while
the other nanotube transistor remains p-type.
Derycke, Martel, Appenzeller, Avouris; Carbon nanotube
inter- and intra-molecular logic gates; Nano Letters,
August 26, 2001
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Carbon Nanotube Circuits - Delft
A. Bachtold, P. Hadley, T. Nakanishi, C. Dekker; Logic circuits with carbon
nanotube transistors Science, 294, 1317-1320 (2001).
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Nano Dust?
• Nanotube sensors
• Nanotube computation
• Nanotube hydrogen storage
• Nanomechanical filters for communication!
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Mobility
• Walking
• Hopping
• Flying
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Mobility
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Milli-Millennium Falcon
Increase the thrust and
decrease the mass,
while controlling
thermal losses
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Thrust (millinewtons)
Thrust Measurements vs. Theory
25
20
15
10
5
0
0
0.5
1
1.5
2
2.5
Time (sec)
Predicted altitude: 50 m
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Rocket in Action
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Synthetic Insects
(Smart Dust with Legs)
Goal: Make silicon walk.
•Autonomous
•Articulated
•Size ~ 1-10 mm
•Speed ~ 1mm/s
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2 Degree of Freedom Legs
1st Link
Motor
2nd Link
Motor
1mm
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Silicon Inchworm Motors
1mm
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Legs
Linkages
CMOS
Motor
Solar Cells
Current Layout for Motor and Legs
Motor
7.6 mm
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Solar Powered Robot Pushups
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Big Products from Small Workers
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The Dark Side
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Conclusion
• Tremendous promise
• More new questions than answers
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