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 VisionLocalizersLocalizers“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’sMeso-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 circuitsTarget 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

Pbitsactualdist

PbitsdistP

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

Pbitsactualdist

PbitsdistP

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

Pbitsactualdist

PbitsdistP

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

SourceDest

Example:• 1 hop over 50 m

1.25 nJ/bit• 5 hops of 10 m each

5 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)

DSDVAODV

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

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10

Initial Position Error (%)

10 nodes, 25 waves, anchor weight=5, 30 iterations, 30% anchors, NO gradients

Range Error (%)

Ave

rage

Pos

ition

Err

or (

% o

f gr

id d

imen

sion

s)

2

1

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89

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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

Pbitsactualdist

PbitsdistP

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 RateTo Reduce Signaling Overhead (Shrink Address Space)

Truly Reactive MessagingPower Down the Whole Data RadioReduce Monitoring Energy Consumption by 103 TimesWakeup 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

Pbitsactualdist

PbitsdistP

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)

Car

rier 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)

Ene

rgy

Eff

icie

ncy

MO

PS/m

W (o

r M

IPS/

mW

)

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 ARM8Power 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

ReconfigurableState Machines

Embedded uP

FPGA

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

DACChip 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)

MemoryMemorySub-systemSub-system

Baseband Baseband ProcessingProcessing

FixedFixedProtocol StackProtocol Stack

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 EstimatesBatteries (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 Noise3E-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 Reaction80 mW/cm3

1E6 mWh/cm3 Published Data.

Fuel Cells300 - 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)

Solar15 mW/cm2 - direct sun 1mW/cm2 - ave. over 24 hrs.

Vibrations 0.05 - 0.5 mW/cm3

Inertial Human Power

Acoustic Noise3E-6 mW/cm2 at 75 Db 9.6E-4 mW/cm2 at 100 Db

Non-Inertial Human Power 1.8 mW (Shoe inserts)

Nuclear Reaction80 mW/cm3

1E6m Wh/cm3

One Time Chemical Reaction

Fluid Flow

Fuel Cells300 - 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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