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Embracing Randomness Embracing Randomness ––A Roadmap to Truly Disappearing ElectronicsA Roadmap to Truly Disappearing Electronics
I&C Research Days Lausanne I&C Research Days Lausanne –– July 8, 04July 8, 04
Jan M. RabaeyJan M. Rabaeyand the PicoRadio Groupand the PicoRadio GroupBerkeley Wireless Research Center
Department of EECS, University of California, Berkeley
http://bwrc.eecs.berkeley.edu
Year
log
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eop
le p
er c
om
pu
ter)
Meaning in the Device
Meaning in the Connection
Meaning in the Collection
Bell’s Law: A New Computer Class Every 10 YearsBell’s Law: A New Computer Class Every 10 Years
Source: R. Newton
1940’s 2000’s
““Ambient Intelligence” (The Concept)Ambient Intelligence” (The Concept)
• An environment where technology is embedded, hidden in the background
• An environment that is sensitive, adaptive, and responsive to the presence of people and object
• An environment that augments activities through smart non-explicit assistance
• An environment that preserves security, privacy and trustworthiness while utilizing information when needed and appropriate
Fred Boekhorst, Philips, ISSCC02
Tackling Societal Tackling Societal Scale ProblemsScale Problems
Infrastructure maintenance
Trafficmanagement
Medical
Energymanagement
Smart buildings
Disaster Mitigation
The Technology is Not Quite There YetThe Technology is Not Quite There YetFrom 10’s of cm3 and 10’s to 100’s of mW
To 10’s of mm3 and 10’s of µW
Meso-scale low-cost wireless transceivers for ubiquitous wireless data acquisition that• are fully integrated
– Size smaller than 1 cm3
• are dirt cheap (“the Dutch treat”) – At or below 1$
• minimize power/energy dissipation– Limiting power dissipation to 100 µW
enables energy scavenging
• and form self-configuring, robust, ad-hoc networks containing 100’s to 1000’s of nodes
The Road to Truly Disappearing ElectronicsThe Road to Truly Disappearing Electronics
Berkeley PicoRadio ProjectBerkeley PicoRadio Project
Energy/Power as the Limiting FactorEnergy/Power as the Limiting Factor
--200Vibrations
--17Pressure Variation
--380Air flow
--330Human Power
--40Temperature
--10Solar (inside)
--15000Solar (outside)
0.5216400.52Radioactive(63Ni)
1063346-Heat engine
1.6-3.250-100-Ultra-capacitor
1103500-Micro-Fuel Cell
341080-Secondary Battery
902880-Primary Battery
P/cm3/yr(µW/cm3/Yr)
E/cm3
(J/cm3)P/cm3
(µW/cm3)Power Source
Courtesy Shad Roundy (ANU and UCB)
Reasonable Target: 100 µW/cm3(/year)
Practical Means of Energy ScavengingPractical Means of Energy Scavenging
Capacitive converter usingMEMS micro-vibrator 30 µW/cm3 (on microwave oven)
Piezoelectric bi-morphs
Photovoltaic
PZT
PVDF
10-1500 µW/cm2
90 µW/cm3
[Shad Roundy (IML,UCB)]
Towards a subTowards a sub--100 100 µµW Integrated NodeW Integrated Node
Baseband(mixed-signal)
RF+ Antenna
ClockGeneration
DigitalProcessor(s)
PowerSupply
NetworkSensors
Some Overall GuidelinesSome Overall Guidelines• Keep it simple!• Minimize the supply voltage and the ambient currents as much as possible• Aggressive use of new technologies (RF-MEMS, integrated passives, …)• Manufacturability is key
Towards a subTowards a sub--100 100 µµW Integrated NodeW Integrated Node
Baseband(mixed-signal)
RF+ Antenna
ClockGeneration
DigitalProcessor(s)
PowerSupply
NetworkSensors
64Kmemory DW8051
µc
BaseBand
SerialInterface
GPIOInterface
LocationingEngine
Neighbor List
SystemSupervisor
DLL
NetworkQueues
VoltageConv
• Simplest possible processor• Dedicated accelerators when needed• Aggressive power management• 1V supply, 16 MHz clock• 300 mV standby voltage• < 1 mW in full operation; < 1 µW standby
Towards a subTowards a sub--100 100 µµW Integrated NodeW Integrated Node
Baseband(mixed-signal)
RF+ Antenna
ClockGeneration
DigitalProcessor(s)
PowerSupply
NetworkSensors
Energy generation and conversion network
Energy Source 1(solar)
Energy Source 2(vibration, …)
Conversion
Netw
ork 1
Conversion
Netw
ork 2
Reservoir 1(capacitor)
Reservoir 2(microbattery)
Microbattery
Anchor Spring flexure Comb fingers
Electrostatic MEMS vibration converters
Towards a subTowards a sub--100 100 µµW Integrated NodeW Integrated Node
Baseband(mixed-signal)
RF+ Antenna
ClockGeneration
DigitalProcessor(s)
PowerSupply
NetworkSensors
1 µW oscillatorWineglass MEMS resonator
MEMS resonator die flips directly onto CMOS for a compact, integrated clock
module.
LowLow--Power RF: Back to The FuturePower RF: Back to The Future(Courtesy of Brian Otis)(Courtesy of Brian Otis)
D. Yee, UCB
© 2000 - Direct Conversionfc= 2GHz>10000 active devicesno off-chip components
© 1949 - superregenerativefc= 500MHz2 active deviceshigh quality off-chip passives - hand tuning
Back to the FutureBack to the Future
MatchingNetwork
MOD1
MOD2
OSC1
OSC2 Preamp PA
• Minimizes use of active components – exploits new technologies• Uses simple modulation scheme (OOK)• Allows efficient non-linear PA• Down-conversion through non-linearity (Envelope Detector)• Tx and Rx in 1-2 mW range (when on)
FBARFBAR--basedbased
RF Filter A
fclockRF Filter
EnvDet
∫
fclockRF Filter
EnvDet
∫
Thin-Film Bulk Acoustic Resonator
The Incredibly Shrinking RadioThe Incredibly Shrinking Radio
RF Filter LNA
fclock
RF FilterEnvDet ∫
fclock
RF FilterEnvDet ∫
RF Filter LNA
fclock
RF FilterEnvDet ∫
fclock
RF FilterEnvDet ∫
RXOn: 3 mWOff: 0 mW
RXOn: 3 mWOff: 0 mW
MatchingNetwork
MOD1
MOD2
OSC1
OSC2 Preamp PAMatchingNetwork
MOD1
MOD2
OSC1
OSC2 Preamp PA
TXOn: 4 mW
Stby: 1 mWOff: 0 mW
TXOn: 4 mW
Stby: 1 mWOff: 0 mW
• 130 nm CMOS• Carrier frequency: 1.9 GHz• 0 dBm OOK• Channel Spacing ~ 50MHz• 10-160 kbps/channel• 10 µs start-up time• Total area < 5 mm2
FBAR
Light Level Duty Cycle
Low Indoor Light 0.36%
Fluorescent Indoor Light 0.53%
Partly Cloudy Outdoor Light 5.6%
Bright Indoor Lamp 11%
High Light Conditions 100%Vibration Level Duty Cycle
2.2m/s21.6%
5.7m/s22.6%
An exercise in miniaturization and energy scavenging
Antenna(ceramic)
Single solar cell
Regulator
RF Transmitter
Energy StorageCapacitor (10 µF)
PicoBeaconPicoBeacon: An Energy: An Energy--Scavenging RadioScavenging Radio
The Return of SuperThe Return of Super--regenerativeregenerative• Fully Integrated Receiver
Front-end
• 400µA when active(~200µW) with 50% quench duty cycle
1500µm
1200
µm
OOK modulated(80 dbm signal)
“1”
“0”
How to go even further?How to go even further?Trading off accuracy for power!Trading off accuracy for power!
Example: sub-threshold RF oscillatorusing integrated LCs
124mV
1.354 GHz
3-layer inductor
150mV
1.5GHz
Simulations
76mVDiff. Output Swing
1.452 GHzOscillation Frequency
2-layer inductor
Measurement bias conditions: Vdd=0.5V, Itail=400µA
2.4 ns start-up time
The Roadmap to UltraThe Roadmap to Ultra--dense Networksdense NetworksTrading off “accuracy” for powerTrading off “accuracy” for power
Super-regenerative:< 500 µW
Untuned Subthreshold< 50 µW
Resonant bodyFinfet (NEMS)
Untuned mostly passive< 5 µW
The Challenge: Simplicity Threatens ReliabilityThe Challenge: Simplicity Threatens Reliability
0
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60
10/19 h 11/31 h 12/43 h 13/55 h 15/07 h 16/19 h 17/31 h
Time
Bro
adca
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ucc
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Rat
e [%
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PicoRadio Meeting NAMP Meeting
-36 -35 -34 -33 -32 -31 -3010
-7
10-6
10-5
10-4
10-3
10-2
10-1
100
effective path loss
BE
R
20 kbps, +1.5dBm40 kbps, +3dBm80 kbps, +4.5dBm
6 db
Factor 105 inerror rate
Narrowband radios very sensitive to fast fading
effects
A Host of Reliability IssuesA Host of Reliability Issues
• Channels are unreliable– Rapidly changing multi-path environment
• Nodes are inherently unreliable– May appear at will– May move– May temporarily run out of energy– May break down
• Cost and power concerns explicitly decrease reliability– Narrow-band radios increase sensitivity to fast fading– Nodes are duty cycled to preserve energy– Further reductions in power affect tuning and calibration
• Other issues such as sensor calibration …
Providing RobustnessProviding Robustness• Traditional radio’s provide robustness
through diversity:– Frequency: e.g. wide-band solutions (hopping)– Time: e.g. spreading– Spatial: e.g. multiple antenna’s
• All these approaches either come with complexity, synchronization, or acquisition overhead, or might not even be applicable– Data traffic irregular, and in very short bursts
• A more attractive approach: – Exploit redundancy– Embrace randomness
Exploiting Redundancy and Exploiting Redundancy and Randomness at the Network Level Randomness at the Network Level
Multi-hop sensornetwork
• Multi-hop approach reduces transmission overhead• Shortest path algorithm seems to be the optimal choice• But …
- Tends to exhaust some paths faster
- Breaks down in presence of unreliable nodes
R. Shah et al, 2003.
The Impact of Spatial DiversityThe Impact of Spatial Diversity
Adding a single node already changes broadcast reliabilitydramatically – spatial diversity is the preferred way toprovide robustness in sensor networks
0.00
10.00
20.00
30.00
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80.00
90.00
100.00
0 10 20 30 40 50 60 70 80 90 100 110 120 130 140 150 160 170 180 190 200 210
distance [cm]
Bro
adca
st s
ucc
ess
rate
[%
]
Deepfade due tomultipath
2 nodes
3 nodes
Data gathered usingPicoNodeI testbed
RegionRegion--based Opportunistic Routingbased Opportunistic Routing
One-hop neighbors
Forwarding region
Opportunistic routing:• Network specifies forwarding region• MAC “randomly” chooses next-hop based on connectivity• Improves reliability and energy efficiency
Probability of packet successE
nerg
y pe
r no
de
Maximizing SleepMaximizing Sleep--TimeTime
Dominated bychannel monitoring power
Dominated by TX (+RX) power
Parameters:• 3 packets/sec• 200 bits/packet• 20 bit pre-amble• 5 neighbors• Range: 10 m• Synchronization using cycled receiver with Ton/T = 0.1
*based on analytical model including actual PicoRadio power numbers
Average power of node
En-Yi Lin et al, ICC 2004
Maximizing SleepMaximizing Sleep--TimeTimeA pseudoA pseudo--asynchronous approach: The Cycled Receiverasynchronous approach: The Cycled Receiver
Allows deep sleep mode of node at the expense ofrendez-vous overhead (power and time)
How to choose the wake-up periodicity?
Every node wakes up occasionally and asks for “work”
DATA (Tp)
ACK (Tb)
TwaitSrc
T
Dest
Wakeup beacon (Tb)
Randomizing the Sleep DisciplineRandomizing the Sleep DisciplineSLEEP IF YOU CAN• If the node is not necessary, goes to sleep and saves power• Maintain sufficient connectivity• Create a sense of “virtual density”• Allows nodes that run low in power to back off
Given:1. Loss rate2. Delay constraint3. Data generation
requirement
Choose wake-up time• Adaptive
• Traffic & node density• Random
• Exponentially distributed sleeping times.
• Avoid phase synchronization.
Incoming traffic
Incoming traffic
ControllerSensors
For how long should the node be allowed to sleep ?
Maximizing the SleepMaximizing the Sleep--TimeTime
JanaVan Greunen et al, ICC 2004
Duty-cycle as a function of density & channel quality
Changing densities
Deteriorating channel
• Nodes estimate traffic and density based on per-hop delay.• Adaptively change their mean wake-up time based on estimated wake-up rate and latency requirements• Sleep time an exponential random variable
Under all network conditions, only 1% ofthe packets fail to meet the latency constraints
Going One Step Further:Going One Step Further:NarrowNarrow--band band UntunedUntuned RadiosRadios
fLO
Dis
trib
utio
n ftol
freq
Carrier-frequency variance much larger than the bandwidthChallenge: How to make these unmatched radios communicate?
A Statistical Communication ParadigmA Statistical Communication Paradigm“Strength in Numbers”“Strength in Numbers”
1 2 3 … H
DestinationSource
“Random frequency multi-hopping”• Information packet traverses from source to destination in a multi-hop fashion.• Transmitter broadcasts signal to neighboring block on random channel (as determined by process variations).• Receivers randomly select channel to listen to.
Forwarding node
1 2 3 4 5 K…4 Rx’s 1 Rx 6 Rx’s2 Rx’s
No Tx Collisions Receptions
Legal transmission only when single TX, multiple RX
A Statistical Communication ParadigmA Statistical Communication ParadigmSome Amazing Properties• Reliable communication over this unreliable platform indeed possible.• Even more, reliability improves EXPONENTIALLYwith a linear increase in network density.
Too many Tx’s cause collisions
Few Tx’sclean channels
• And the process is self-regulating
D. Petrovic et al., 2004
Summary And PerspectivesSummary And Perspectives• Scaling of technology leads to ever smaller
communication and computation nodes• Severe energy (power) constraints can only
be met by compromising on complexity (or size).
• But simple nodes/algorithms tend to be unreliable …
• An appealing solution: exploit the power of the numbers, and avoid brittleness by embracing randomness
• An opportunity for bold innovation!
The support of CEC, NSF, DARPA, GSRC Marco, and the BWRC sponsoring companies is greatly appreciated.
"Research is what I'm doing when I don't know what I'm doing."– W. Von Braun