Introduction to Sensor Network

2007. 10

Deokjai Choi

Lecture Outline

• 1st Week: (Introduction: 75 minutes)• Brief History and Overview of Wireless Sensor Network• Technology Trends, Application Classes• Critical Issues and factors (memory constraints, power, uncertainty and loss)• Physical Layer Concepts

• 2nd week: MAC Protocols• MAC in wireless networks• Fairness Issue at the MAC layer• Energy Efficient MAC Protocols• Rate Control and Power Control at MAC layer• Priority Scheduling•

• 3rd week: Routing Protocols• Address assignment for sensor network• Routing in Ad Hoc Networks• Routing in Sensor Networks

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This Lecture’s Outline

• Overview of Wireless Sensor Networks

– Technology Enablers

– Application Opportunities

– Systems Challenge

• Introductions

• Ubiquitous Networks => Integration Real World Information

Overview of WSN

• Technology Enabler– Moore’s Law: Microprocessor (18 month)

– Bell’s Law: New System emerges (10yrs)

– Hwang’s Law: Memory (12 month)

– Wireless Communications (WAN, LAN, PAN, BAN)

– Networking: IPv6

• Applications

• Challenges

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Broad Technology Trends

Today: 1 million transistors per $

Moore’s Law: # transistors on cost-effective chip doubles every 18 months

Mote!years

ComputersPer Person

103:1

1:106

Laptop

PDA

Mainframe

Mini

Workstation

PC

Cell

1:1

1:103

Bell’s Law: a new computer class emerges every 10 years

Same fabrication technology provides CMOS radios for communication and micro-sensors

Explosion of New Internet Appliances

IPv6 Coming

Much larger address space

IPv6 Addresses: 3.4X1038

Improved routing Route aggregation reduces the size of routing tablesSimplified header reduces router processing loads

Enhanced security and QoS Mandatory IPsec support all fully IPv6 compliant devices

Improved support for mobile IP and mobile computing devices

IP is everywhere

Data, Voice, Audio and Video integration is a Reality

IPv4 uses 32-bit (4-byte) addresses, which limits the address space to 4,294,967,296 (4.3x109)possible unique addresses.

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Enabling Technology

Microcontroller RadioCommunication

FlashStorage

Sensors

IEEE 802.15.4

Network

7/9/2007 AIIT Summer Course - M1 - Intro 9

Enabling Technology

PhysicalWorld

7/9/2007 AIIT Summer Course - M1 - Intro 10

Facts about components

• Microcontrollers: – 1-10 mW active, 1 uW passive => 10-100 uW average

• Micro-sensors (MEMS, Materials, Circuits)– acceleration, vibration, gyroscope, tilt, magnetic, heat, motion,

pressure, temp, light, moisture, humidity, barometric

– chemical (CO, CO2, radon), biological, microradar, ...

– actuators too (mirrors, motors, smart surfaces, micro-robots)

• Micro-Radios– CMOS, short range (10 m), low bit-rate (200 kbps), 10 mW

• Micro-Power– Batteries: 1,000 mW*s/mm3, fuel cells

– solar (10 mW/cm2, 0.1 mW indoors), vibration (~uW/gm), flow

• 1 cm3 battery => 1 year at 1 msgs/sec

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WSN Applications

• Monitoring Spaces– Env. Monitoring, Conservation biology, ...– Precision agriculture, – built environment comfort & efficiency ... – alarms, security, surveillance, EPA, OSHA, treaty verification …

• Monitoring Things– automated meter reading – condition-based maintenance– disaster management– Civil infrastructure

• Interactions of Space and Things– manufacturing, asset tracking, fleet & franchise– context aware computing, non-verbal communication– Assistance - home/elder care

• Action and control– Optimizing processes– Automation

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Early Industrial Examples

Temperature and Energy Monitoring

AMI – NURI Telecom & SK Telecom :

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Example: A Month in the Life of a Redwood Tree

• Time: 1 month• Period: 5 minutes• Height: 15m to 70m• Angle: west side• Radius: 10-100cm• Count: 33 nodes/tree

– 155 sensors

• Spacing: ~2m

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(Mariscal et al. 2004)

The Result: Spatial Gradients over time

Macroscope in the Redwoods, Tolle et all, ACM SENSYS 2005

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The Internet today

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The Real Internet ahead

0 2 4 6 8 10 12 14 16 18

-1

-0.5

0

0.5

1

Low resolution Sensor, Test4, Increasing frequency

Time (sec)

Accele

ration (

g)

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Why “Real” Information is so Important?

Improve Productivity

Protect HealthHigh-Confidence Transport

Enhance Safety & Security

Improve Food & H20

Save Resources

Preventing Failures

IncreaseComfort

Enable New Knowledge

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The Web Today

Shopping

Weather

Science

Technology

Financial NEWS

Maps

Sports

Integrates the World’s Human Generated Information

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Most Real World Information goes “down the drain”

Wate

r Usa

ge, Te

mp.,

Qualit

y

Secu

rity

and A

ccess

Control

Gas

and E

lect

ric

Usa

ge

Heating, AC, and V

entila

tion

Sm

oke

, Fi

re, CO

, Radon

Sm

art

Applia

nce

s

Dig

ital H

ealth D

evi

ces

Baby

Monitor

(Eld

er

care

)

Ente

rtain

ment Sys

tem

Vid

eo G

am

e C

onso

les

Clo

cks

and C

ale

ndars

Exe

rcise U

nits

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Physical Information Streams

• Sensors are everywhere– But the data is mostly dropped on the floor

• Physical => Digital => Information

• Each sensor becomes a network citizen

0 2 4 6 8 10 12 14 16 18

-1

-0.5

0

0.5

1

Low resolution Sensor, Test4, Increasing frequency

Time (sec)

Accele

ration (

g)

010010001…

<value>temp=35

<\value>

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Our goal: Ubiquitous Real Internet

802.15.4

<value>source=librarytime=12:31temp=25.1

<\value>

0 2 4 6 8 10 12 14 16 18

-1

-0.5

0

0.5

1

Low resolution Sensor, Test4, Increasing frequency

Time (sec)

Accele

ration (

g)

Physical Signal

Wireless Packets

11 010010001Sampled Value010010001int temp;

<request service>

ServiceDescription

< get temp …

set sample_rate

set alarm … >

Web Services www.weather.com

XML information

<value>source=librarytime=12:53temp=26.7

<\value>

11 010110111

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Technology Push / Application

PullMonitoring & Managing Spaces and Things

technology

MEMSsensing

Power

Comm. uRobotsactuate

Miniature, low-power connections to the physical world

Proc

Store

7/9/2007 AIIT Summer Course - M1 - Intro 24

Technology Push / Application

Pull

applications

Monitoring & Managing Spaces and Things

technology

MEMSsensing

Power

Comm. uRobotsactuate

Miniature, low-power connections to the physical world

Proc

Store

7/9/2007 AIIT Summer Course - M1 - Intro 25

Battery

Shielding skirt

O-rings

Top endcap

Cylindrical enclosure

Bottom endcap

Top Sensing Surface(incident PAR and TSR)

Bottom Sensing Surface(temperature, humidity,barometric pressurereflected PAR and TSR)

mote

The Node

The Complete Solution

DBMS(PostgreSQL)

TinyDB Sensor Network

TASK Gateway

GPRSModem

The Infrastructure

SELECT

result_time, epoch, nodeid,

parent, voltage, depth,

humidity, humid_temp, hamatop,

hamabot

FROM sensors

SAMPLE PERIOD 5 min

The Program

wake1.3%

sample

log send

forward

sleep98.7%

The Behavior

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NIMS RD Merced and San Joaquin River Confluence(Harmon, Kaiser, et al)

confluence

nitrate distribution

San Joaquin R.

Merced R.

mixing zone

gaging station

river bedmap

Sonar-based bathymetry (depth)

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Environmental Monitoring Characteristics

• Large number of nodes spread over physical space of interest

• Low sample rate (of multiple sensor modes)– Further reduced by node signal processing and compression

• Reliable dissemination of configuration, command, or query

• Low-rate scalar data collection– Many options for reliability, Predictable reporting delays

• Low duty cycle for long lifetime

• Energy availability is application specific

• Extension to event detection and triggering demands more responsive protocols

• Extension to control requires predictable outward routing

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Intel Fab & BP Machine Monitoring

• Goal: Pre-empt equipment failures through non-destructive analysis

• Media Gap: Majority of data is collected by hand– Thousands of sense points

• Intel Fab and an Oil Tanker engine room• Wireless vibration data collection

– High-speed sampling, reliable bulk transfer– Sensor-to-Analysis App flow– Overcome interference– Support disconnected operation

• Loch Rannoch Network– 150 accelerometers– 26 motes– 4 stargates– 1 PC

• Efficient installation and management– 36hr install period on tanker– No crew intervention

Intranet

802.11

Backbone

Cluster Head

Root

Stargate

Enterprise

Server

Sensor

Clusters

Stargate Gateway

Bridge

Stargate

Intranet

802.11

Backbone

Cluster Head

Root

Stargate

Enterprise

Server

Sensor

Clusters

Stargate Gateway

Bridge

Stargate

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GGB Structural Monitoring

Base Station

Berkeley SF Bay

mid-spanquarter-span

59260ft

16ft27 1

1310 38 41211

14

L3L5 L1L4 L2

50 51 52 53 54 55 56 57 58 59 60-15

-10

-5

0

5

10

15

Time (sec)

Acc

ele

ration (m

g)

V2V4V13V7V9

-0.99

0.19-0.73

1.000.74

Frequency: 1.41 Hz

Damping Ratio: 2%

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Machine Monitoring Characteristics

• Nodes clustered on specific equipment• High sample rate (over short bursts)

– Substantial local signal processing• Control and management is like Env.

Monitoring• Data collection in single-point streams

– Reliable end-to-end transport• Shallow networks in practice

• Well understood– but not yet well supported

• Energy availability is site specific• Natural extensions for local access (inspector)• Structural monitoring is much harder than CBM

– Time coordinated samples, cross-node data analysis

• Environmental factors critical to sensing accuracy

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Medical Monitoring

Wireless module

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Large-Scale Security and Tracking

• 557 nodes over several km

• Self-powered, self-maintaining

• 2 person-day deployment

• OTA programming and management infrastructure

Solar Cell

Buzzer

Passive IR x4

User / Reset

USB Port

Microphone

Magnetometer

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Example Tiers

telos-USB

telos

USB-WiFi

WiFi repeater

WiFi AP

Root Server

trio

557 node DARPA NEST Aug 05

UCB Trio node

802.15.4 – 802.11 gateway

Transit Network(IP or not)

Access point- Base station- Proxy

Sensor PatchPatch Network

Data Service

Intranet/Internet (IP)

Client Data Browsingand Processing

Sensor Node

Gateway

Other information sources

Sensor Node

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Sensing => Understanding

Plus UAV exfiltration, distributed tracking

Wireless PIR readings

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Transit Network(IP or not)

Access point- Base station- Proxy

Sensor Patch

Patch Network

Data Service

Intranet/Internet (IP)

Client Data Browsingand Processing

Sensor Node

GatewayGateway

Verification links

Other information sources

Sensor Node

Canonical SensorNet Network Architecture

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Proximity, Tracking, Compliance

Industrial:Asset mgmt

CBMProcess controlEnergy mgmtenvironmental

MedicalAgriculture

HLS…

Home:LightingHVACaccess

Prox. Tracking Shipping QoS:Vibration threshold

Temperature/humidity threshold

Safety:Chemical-to-chemical

safety alertsHuman-to-chemical

safety alerts

Building:SecurityHVACAMR

LightingAccess control

“The information about the package is as valuable as the delivery of the package itself.”

-Fred SmithCEO, FedEx

Current Conditions:

In Motion, No Magnetic Fields, 67°

• Humidity Range: 30-35%

• Temp. Range: 55 ° - 78 °

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Interaction Monitoring Characteristics

• Many different forms of monitoring– Untagged vs tagged items

• Mobility is central– Mobile nodes moving through stationary

networks– Networks moving through networks– Proximity detection and action

• Wide range of communication patterns– Mobile-mobile routing

• Adaptive protocols• Sophisticated routing• Reliability through custody transfer• Deep interactions with IT infrastructure

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Example: Petroleum Industry

Condition-based Maintenance

Safety

workers

storage

process

Pipelines

integrity

security

Tracking

tank

cars

construction

assets

“This technology will transform everything we touch, not just in

business but in our personal lives as well.”

--P.P. Darukhanavala, CTO, British Petroleum

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Core challenges• Long-lived, unattended, reliable operation

– Power• Wireless often means self-powered

– Batteries

– Ambient sources (light, current, vibration, heat, …)

– Limited Memory

– Self-organization and Management

– Error, fault, noise mitigation

• Ease of broad application development– New forms of information

– Integration into enterprise processes and actions

– Extracting value from vast, novel sources of information

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A Systems Challenge

applications

service

network

system

architecture

data mgmt

Monitoring & Managing Spaces and Things

technology

MEMSsensing

Power

Comm. uRobotsactuate

Miniature, low-power connections to the physical world

Proc

Store

7/9/2007 AIIT Summer Course - M1 - Intro 42

Mote Architecture Evolution

SmartDustWeC

Rene Mica

Intel/UCBdot

InteliMOTE

XBOWcc-dot

XBOWmica2

Intel

rene’

XBOWrene2

Intelcf-mica

Boschcc-mica

Dust Incblue cc-TI

digital sunrain-mica

XBOWmica

zeevo BT

Telos

XBOWmicaZ

IntelMOTE2

EyesBTNode

trio

97

LWIM-III(UCLA)

9998 00 01 0302 04 0605 07

DARPA

SEN

SIT

LWIM

Expeditio

n

NEST

NETS/

NO

SS

CEN

S

STC

NSF

Cyb

er-

Phys

ical

WINS(UCLA/ROckwell)

7/9/2007 AIIT Summer Course - M1 - Intro 43

Storage ProcessingWireless SensorsWSN mote platform

Operating Systems and Networking

Radio Serial

Flash ADC, Sensor I/F

MCU, Timers, Bus,…

Link

NetworkProtocols Blocks,

Logs, FilesScheduling, Managemen

t

Streaming drivers

Over-the-air Programming

Applications and Services

Communication CentricResource-ConstrainedEvent-driven Execution

Tin

yOS 2

.0

7/11/2007 AIIT Summer Course - W2 Low Power 44

What we mean by “Low Power”• 2 AA => 1.5 amp hours (~4 watt hours)

• Cell => 1 amp hour (3.5 watt hours)

Cell: 500 -1000 mW => few hours active

WiFi: 300 - 500 mW => several hours

GPS: 50 – 100 mW => couple days

WSN: 50 mW active, 20 uW passive

450 uW => one year

45 uW => ~10 years

Ave Power = fact * Pact + fsleep * Psleep + fwaking * Pwaking

* System design

* Leakage (~RAM)

* Nobody fools mother nature

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Where the energy goes• Sleep

– 7 uA for TI MSP

• Sensing• Transmitting results• Management Traffic• Routing Structure Maintenance

– only parent tracking for leaf

• Listening• Forwarding

– non-leaf

• Overhearing packets destined for others

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The “Idle Listening” Problem

• The power consumption of “short range” (i.e., low-power) wireless communications devices is roughly the same whether the radio is transmitting, receiving, or simply ON, “listening” for potential reception– includes IEEE 802.15.4, Zwave, Bluetooth, and the many

variants– WiFi too!– Circuit power dominated by core, rather than large

amplifiers

• Radio must be ON (listening) in order receive anything.– Transmission is infrequent. Reception α Transmit x Density– Listening (potentially) happens all the time

Total energy consumption dominated by idle listening

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Communication Power Consumption

Sleep~10 uA

Transmit~20 mA x 1-5 ms[20 - 100 uAs]

I

I

Time

Time

Listen~20 mA

Receive~20 mA x 2-6 ms

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Radio

• Trade-offs: – resilience | performance => slow wake up

– Wakeup vs interface level

– Ability to optimize vs dedicated support

* Polastre, Culler, BMAC, Sensys 2005

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Power States at Node Level

Sleep WakeUP Work Sleep WakeUP Work

Active Active

Telos: Enabling Ultra-Low Power Wireless Research, Polastre, Szewczyk, Culler, IPSN/SPOTS 2005

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3 Basic Solution Techniques

Goal: listen only when there is likely to be something useful to hear.

• Listen during scheduled time slots– Arrange a schedule of possible communication opportunities– Maintain appropriately coordinated clocks and schedule– Only listen during specific “slots”– Many variants: Aloha, Token-Ring, TDMA, Beacons, Bluetooth piconets, …

TSMP, …

• Sampled Listening– Listen for very short intervals to detect eminent transmissions– On detection, listen actively to receive

• Listen after send (with powered infrastructure)– Generally, device is not listening and will not receive.– After it transmits to a receptive device, it listens for a time window– Many variants: 802.11 AMAT, Key fobs, remote modems, …

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Approaches

• Powered Router / Duty cycle Leaf

• Coordinator / Beacon

• Network schedule

• Preamble Sampling

• Slotted Preamble Sampling

• Quasi-scheduled