Ultra-Low Energy Wireless Sensor and Monitor Networks Jan M. Rabaey jan In cooperation with Profs B....
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Transcript of Ultra-Low Energy Wireless Sensor and Monitor Networks Jan M. Rabaey jan In cooperation with Profs B....
Ultra-Low Energy WirelessUltra-Low Energy WirelessSensor and Monitor NetworksSensor and Monitor NetworksJan M. RabaeyJan M. Rabaeyhttp://www.eecs.berkeley.edu/~janhttp://www.eecs.berkeley.edu/~jan
In cooperation with Profs B. Brodersen, A. Sangiovanni-Vincentelli, K. Ramchandran, P. Wright, and the PicoRadio group.
“The Berkeley Endeavour project”
The New InternetThe New Internet
The VisionThe Vision
LocalizersLocalizers
“Tiny devices, chirping their impulse codes at one another, using time of flight and distributed algorithms to accurately locate each participating device. Severalthousands of them form the positioning grid … Togetherthey were a form of low-level network, providing information on the orientation, positioning and the relative positioning of the electronic jets…It is quite self-sufficient. Just pulse them with microwaves, maybe a dozen times a second …”Pham Trinli, Thousands of years from now
Vernor Vinge,“A Deepness in the Sky,” 1999
PicoRadio’sPicoRadio’s
Meso-scale low-cost (< 0.5 $) sensor-computation-communication nodes for ubiquitous wirelessdata acquisition that minimize power/energy dissipation – Minimize energy (<5 nJ/(correct) bit) for energy-limited source– Minimize power (< 100 W) for power-limited source (enabling
energy scavenging)
By using the following strategies– self-configuring networks– fluid trade-off between communication and computation– Integrated System-on-a-Chip, using aggressive low-energy
architectures and circuits
Target date: 2004
The Smart HomeThe Smart Home
SecurityEnvironment monitoring and controlObject taggingIdentification
Dense network of Dense network of sensor and monitor nodessensor and monitor nodes
Wireless in the HomeWireless in the Home
Source: IEEE Spectrum,December 99
Industrial Building Environment Industrial Building Environment ManagementManagement
• Task/ambient conditioning systems allow thermal condition in small, localized zones (e.g. work-stations) to be individually controlled by building occupants“micro-climates within a building”
• Requires dense network of sensor/monitor nodes
• Wireless infrastructure provides flexibility in composition and topology
The Interactive MuseumThe Interactive Museum
Cafe
Offices
Exhibits
Wireless node
Entrance
The Enhanced User InterfaceThe Enhanced User Interface
Other Applications:• Disaster mitigation, traffic management and control• Integrated patient monitoring, diagnostics, and drug administration• Automated manufacturing and intelligent assembly• Toys, etc
The “virtual” keyboard(Kris Pister, UCB)
System Requirements and ConstraintsSystem Requirements and Constraints• Large numbers of nodes — between 0.05 and 1
nodes/m2
• Cheap (<0.5$) and small ( < 1 cm3)• Limited operation range of network — maximum
50-100 m• Low data rates per node — 1-10 bits/sec average
– up to 10 kbit/sec in rare local connections to potentially support non-latency critical voice channel
• Low mobility (at least 90% of the nodes stationary)• Crucial Design Parameter:
Spatial capacity (or density) — 100-200 bits/sec/m2
Fact or Fiction?Fact or Fiction?
Today
Integrated radio+ sensor on–a-chip
Estimated: 2002-2003
How to get there?How to get there?
Functional & Performance Requirements
Network Architecture
Performance analysis
Constraints
Networklevel
Nodelevel
Functional & Performance Requirements
Node Architecture
Performance analysis
Think Energy!Think Energy!
OpportunitiesOpportunities• Exploit the application properties
– Sensor data is correlated in time and space– Sensor networks are “query-based”– Sensing without precise localization seldom makes
sense– Duty cycle of sensor nodes is very small
• And use node architectures that excel in the “common case”– Stream-based data flow processing for baseband– Concurrent Finite State Machines for protocol stack
Power & energy dissipationPower & energy dissipationin ad-hoc wireless networksin ad-hoc wireless networks
: computation energy for transceiving a single bit
: transmission cost factor for a single bit
: path-loss exponent (2..4) : overhead (in extra bits
needed for transmission of a single bit)
• Pstandby: standby power (eg., due to need to keep receiver on)
standby
standbylink
Pbitsactual
dist
Pbits
distP
sec
_sec
sec__ bitsactual
PdistE standby
bitactual
* These equations assume perfect power control
Saving Power at the Application LayerSaving Power at the Application Layer : computation energy for
transceiving a single bit : transmission cost factor
for a single bit : path-loss exponent (2..4) : overhead (in extra bits
needed for transmission of a single bit)
• Pstandby: standby power (eg., due to need to keep receiver on)
standby
standbylink
Pbitsactual
dist
Pbits
distP
sec
_sec
actual_bits/sec: actual_bits/sec: source codingsource coding Opportunity: sensor data is correlated in time and spaceOpportunity: sensor data is correlated in time and spaceTrading off communication for computationTrading off communication for computation
Distributed Source Coding (Ramchandran)Distributed Source Coding (Ramchandran)• Sensor networks present major spatial data
correlation, but exploitation requires major intra-node communication
Good theoretical question:How much performance loss if such communication unavailable?
• Answer: no performance loss! (under certain conditions) based on non-constructive information-theoretic argument (Slepian-Wolf).
Engineering question:How do we develop a practical and constructive framework to optimize global network usage?
Saving Power at the Network LayerSaving Power at the Network Layer : computation energy for
transmission of a single bit : transmission cost factor
for a single bit : path-loss exponent (2..4) : overhead (in extra bits
needed for transmission of a single bit)
• Pstandby: standby power (eg., due to need to keep receiver on)
standby
standbylink
Pbitsactual
dist
Pbits
distP
sec
_sec
dist: dist: network partitioning using multi-hopnetwork partitioning using multi-hop : cost of network discovery and maintenance: cost of network discovery and maintenance
Opportunities: exploit application (i.e. sensoring) properties merge with localization
Communicating over Long DistancesCommunicating over Long DistancesMulti-hop NetworksMulti-hop Networks
Source
Dest
Example:• 1 hop over 50 m
1.25 nJ/bit
• 5 hops of 10 m each5 2 pJ/bit = 10 pJ/bit
• Multi-hop reduces transmission energy by 125! (assuming path loss exponent of 4)
Optimal number of hops needed for free space path loss.
log(/)
But … network discovery But … network discovery and maintenance overheadand maintenance overhead
Low-Energy Network StrategiesLow-Energy Network Strategies• Reactive Routing good for rarely used routes• Proactive Routing good for frequently used routes
• Need solution that is more adequate for problem at hand:Need solution that is more adequate for problem at hand:class (contents)-based and location (geographic)-based class (contents)-based and location (geographic)-based addressing.addressing.
0500
1000150020002500300035004000
20 33 56
Number of Nodes
Routing Overhead (bytes)
DSDV
AODV
02000400060008000
10000120001400016000
20 33 56
Number of Nodes
Routing Overhead (bytes) Normalized
(discovering one route) (discovering n routes)
Example: Directed Diffusion (Estrin)Example: Directed Diffusion (Estrin)• Application-aware communication primitives
– expressed in terms of named data (not in terms of the nodes generating or requesting data)
– Example: “Give me temperature information”
• Nodes diffuse the interest towards producers via a sequence of local interactions
• This process sets up gradients in the network which channel the delivery of data
• Reinforcement and negative reinforcement used to converge to efficient distribution
• Intermediate nodes opportunistically fuse interests, aggregate, correlate or cache data
• Other options: swarm intelligence
Distributed PositioningDistributed Positioning
010
2030
4050
0
20
40
600
2
4
6
8
10
Initial Position Error (%)
10 nodes, 25 waves, anchor weight=5, 30 iterations, 30% anchors, NO gradients
Range Error (%)
Av
era
ge
Po
sit
ion
Err
or
(% o
f g
rid
dim
en
sio
ns
)
2
1
3
4
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Merging locationing with networking leads to pruningof overhead messaging
Saving Power at the Media Access Layer (Saving Power at the Media Access Layer (!!)) : computation energy for
transceiving a single bit : transmission cost factor
for a single bit : path-loss exponent (2..4) : overhead (in extra bits
needed for transmission of a single bit)
• Pstandby: standby power (eg., due to need to keep receiver on)
standby
standbylink
Pbitsactual
dist
Pbits
distP
sec
_sec
PPstandbystandby: : Power-management of inactive nodesPower-management of inactive nodes : Cost of collisions and retransmissions (interference): Cost of collisions and retransmissions (interference)
Opportunities: distribution of communication in time and frequency rendez-vous scheduling in local neighborhood usage of multiple virtual channels reduces interference
Where Does Energy Go?Where Does Energy Go?When idle: Channel MonitoringCollision and Retransmission Signaling overhead (header, control pkts)
Mostly-Sleepy MAC Layer ProtocolsMostly-Sleepy MAC Layer Protocols
• Computational energy for receiving a bit is larger than the computational energy to transmit a bit (receiver has to discriminate and synchronize)
• Most MAC protocols assume that the receiver is always on and listening!
• Activity in sensor networks is low and random• Careful scheduling of activity pays off big time, but
… has to be performed in distributed fashion
PicoMACPicoMAC
Spread Spectrum Multi-Channel SchemeTo Reduce Collision Rate
To Reduce Signaling Overhead (Shrink Address Space)
Truly Reactive MessagingPower Down the Whole Data Radio
Reduce Monitoring Energy Consumption by 103 Times
Wakeup Radio will Power Up Data Radio for Data Reception
Saving Power at the Physical LayerSaving Power at the Physical Layer : computation energy for
transceiving a single bit : transmission cost factor
for a single bit : path-loss exponent (2..4) : overhead (in extra bits
needed for transmission of a single bit)
• Pstandby: standby power (eg., due to need to keep receiver on)
standby
standbylink
Pbitsactual
dist
Pbits
distP
sec
_sec
: : Choice of data rate, modulation, physical channel accessChoice of data rate, modulation, physical channel access : Cost of framing, channel coding, synchronization, CRC: Cost of framing, channel coding, synchronization, CRC
Opportunities: radio’s with fast acquisition (and probably less perfect channel)
The Mostly Digital RadioThe Mostly Digital Radio
DigitalBasebandReceiver
RF input(fc = 2GHz)
LNA
cos[2(2GHz)t]
RF filter
chip boundary
I (50MS/s)
Q (50MS/s)
A/D
A/D
sin[2(2GHz)t]
Analog Digital
Integration/Power TradeoffIntegration/Power Tradeoff• Example: High carrier frequency allows small integrated
passive elements, but increases power consumption
• Why?– Increase Id to boost
device ft
– Increased power consumption in PLLs
Carrier Frequency Vs. Power Consumption
0.1
1
10
0.1 1 10 100 1000Pow er Consum ption (m W)
Carri
er F
requ
ency
(GHz
)
1.2V Receiver
Price Label Radio
WINS
Wireless Hearing Aid
Super-Regenerative
Pager
Philips Pager - UAA2080
Bluetooth
BWRC D.C. Radio
PicoRadio Implementation IssuesPicoRadio Implementation Issues• Dynamic nature of PicoRadio networks requires
adaptive, flexible solution• Traditional programmable platforms cannot meet
the stringent low-power requirements– 3 orders of magnitude in energy efficiency between custom
and programmable solutions
• Configurable (parameterizable) architectures combine energy efficiency with limited flexibility
• System-on-a-chip approach enables integration of heterogeneous and mixed mode modules on same die
• Predicted improvements: factor 10 each year!
The Energy-Flexibility GapThe Energy-Flexibility Gap
Embedded ProcessorsSA1100.4 MIPS/mW
ASIPsDSPs 2 V DSP: 3 MOPS/mW
DedicatedHW
Flexibility (Coverage)
En
ergy
Eff
icie
ncy
MO
PS
/mW
(or
MIP
S/m
W)
0.1
1
10
100
1000
ReconfigurableProcessor/Logic
Pleiades10-80 MOPS/mW
(Re)configurable Computing:(Re)configurable Computing:Merging Efficiency and VersatilityMerging Efficiency and Versatility
“Hardware” customized to specifics of problem.
Direct map of problem specific dataflow, control.
Circuits “adapted” as problem requirements change.
Spatially programmed connection of processing elements.Spatially programmed connection of processing elements.
Architecture ComparisonArchitecture ComparisonLMS Correlator at 1.67 MSymbols Data RateLMS Correlator at 1.67 MSymbols Data RateComplexity: 300 Mmult/sec and 357 Macc/secComplexity: 300 Mmult/sec and 357 Macc/sec
Note: TMS implementation requires 36 parallel processors to meet data rate - validity questionable
16 Mmacs/mW!
Intercom TDMA MACIntercom TDMA MACImplementation alternativesImplementation alternatives
ASIC: 1V, 0.25 ASIC: 1V, 0.25 m CMOS processm CMOS processFPGA: 1.5 V 0.25 FPGA: 1.5 V 0.25 m CMOS low-energy FPGAm CMOS low-energy FPGAARM8: 1 V 25 MHz processor; n = 13,000ARM8: 1 V 25 MHz processor; n = 13,000Ratio: 1 - 8 - >> 400Ratio: 1 - 8 - >> 400
ASIC FPGA ARM8
Power 0.26mW 2.1mW 114mWEnergy 10.2pJ/op 81.4pJ/op n*457pJ/op
Idea: Exploit model of computation: concurrent finite state machines,Idea: Exploit model of computation: concurrent finite state machines,communicating through message passingcommunicating through message passing
ReconfigurableDataPath
ReconfigurableDataPath
ReconfigurableState Machines
ReconfigurableState Machines Embedded uPEmbedded uP
FPGAFPGA
DedicatedDSP
DedicatedDSP
Envisioned PicoNode PlatformEnvisioned PicoNode Platform• Small footprint direct-
downconversion R/F frontend• Digital baseband processing
implemented on combination of fixed and configurable datapath structures
• Protocol stack implemented on combination FPGA/reconfigurable state machines
• Embedded microprocessor running at absolute minimal rates
Motorola StarTac Cellular Battery (3.6V)
Pico Radio Test Bed
Casing Cover
Serial Port Window
PicoNode IPicoNode I
Connectors forsensor boards
• Flexible platform for experimentation on networking and protocol strategies
• Size: 3”x4”x2”• Power dissipation <
1 W (peak)• Multiple radio
modules: Bluetooth, Proxim, …
• Collection of sensor and monitor cards
PicoNode II (two-chip) PicoNode II (two-chip)
ADC
DAC
Chip 2Chip 1
Custom analog
circuitry
Mixed analog/ digital
Digital Baseband processing
Fixed logic
Program-mable logic
Software running on processor
Analog RF
Protocol
Direct down-conversion front-endDirect down-conversion front-end(Yee et al)(Yee et al)
EmbeddedEmbedded Processor Processor(Xtensa)(Xtensa)
EmbeddedEmbedded Processor Processor(Xtensa)(Xtensa)
MemoryMemorySub-systemSub-system
MemoryMemorySub-systemSub-system
Baseband Baseband ProcessingProcessingBaseband Baseband ProcessingProcessing
FixedFixedProtocol StackProtocol Stack
FixedFixedProtocol StackProtocol Stack
ProgrammableProgrammableProtocol StackProtocol Stack
(FPGA)(FPGA)
ProgrammableProgrammableProtocol StackProtocol Stack
(FPGA)(FPGA)
Interconnect Network (Sonics Silicon Backplane)Interconnect Network (Sonics Silicon Backplane)
The Holy Grail: The Holy Grail: Energy ScavengingEnergy Scavenging
SOURCE:SOURCE:P. Wright & S. RandyP. Wright & S. RandyUC ME Dept.UC ME Dept.
Power (Energy) Density Source of Estimates
Batteries (Zinc-Air) 1050 -1560 mWh/cm3 (1.4 V) Published data from manufacturers
Batteries(Lithium ion) 300 mWh/cm3 (3 - 4 V) Published data from manufacturers
Solar (Outdoors)
15 mW/cm2 - direct sun
0.15mW/cm2 - cloudy day. Published data and testing.
Solar (Indoor)
.006 mW/cm2 - my desk
0.57 mW/cm2 - 12 in. under a 60W bulb Testing
Vibrations 0.001 - 0.1 mW/cm3 Simulations and Testing
Acoustic Noise
3E-6 mW/cm2 at 75 Db sound level
9.6E-4 mW/cm2 at 100 Db sound level Direct Calculations from Acoustic TheoryPassive Human
Powered 1.8 mW (Shoe inserts >> 1 cm2) Published Study.
Thermal Conversion 0.0018 mW - 10 deg. C gradient Published Study.
Nuclear Reaction
80 mW/cm3
1E6 mWh/cm3 Published Data.
Fuel Cells
300 - 500 mW/cm3
~4000 mWh/cm3 Published Data.
Integrated Manufacturing Lab
Example: MEMS Variable CapacitorExample: MEMS Variable Capacitor
springs
500
50
Proof mass
Out of the plane, variable gap capacitorOut of the plane, variable gap capacitor
Up to 10 W of power demonstrated
PicoRadio Design ChallengesPicoRadio Design Challenges
Power (Energy) Density
Batteries (Zinc-Air) 1050 -1560 mWh/cm3
Batteries (rechargeable Lithium) 300 mWh/cm3 (3 - 4 V)
Solar
15 mW/cm2 - direct sun
1mW/cm2 - ave. over 24 hrs.
Vibrations 0.05 - 0.5 mW/cm3
Inertial Human Power
Acoustic Noise
3E-6 mW/cm2 at 75 Db
9.6E-4 mW/cm2 at 100 DbNon-Inertial Human Power 1.8 mW (Shoe inserts)
Nuclear Reaction
80 mW/cm3
1E6m Wh/cm3
One Time Chemical Reaction
Fluid Flow
Fuel Cells
300 - 500 mW/cm3
~4000 mWh/cm3
Cafe
Offices
Exhibits
PicoNode
Entrance
ReconfigurableDataPath
FPGA Embedded uP
Dedicated FSM
DedicatedDSP
10Totaloptimal distceilhops
Energy Constraints
Use Cases Conceptual Modeling
Performance Analysis
Positioning Network Architecture
PicoNode Architecture DesignPicoNode Architecture Design
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