smart dust training - ncar earth observing laboratory · pdf file ·...

© 2003 Crossbow Technology

Smart Dust Training


The Opportunity & MotivationQuotes from Time Magazine’s Special Report on “What’s Next” (Sept. 8, ’03)

“Wireless, Web, and sensors are a potent combination”

–Paul Saffo, Technology Forecaster

“A Brief History of The Next Big Thing: Smart-Dust”

..scatter a bunch of these radio equipped wireless sensors across a battlefield.. track troop movements..embed them in a road.. traffic report..already detecting climate conditions at a CA vineyard and monitoring energy use in supermarkets


Introduction to Smart-Dust and Motes

• Agenda• Who are we ?• What is TinyOS ?• What are applications ?


Agenda1) Introduction to Smart Dust and MOTES2) TinyOS Intsall3) 10-Min Break4) Mote Hardware Overview5) TinyOS Programming #16) Lunch7) TinyOS Programming #28) Wireless Communication Issues and Radio

Stack9) Multihop Hop Overview and Surge Demo


Agenda1) Power Management and Batteries2) TinyDB and TASK3) Stargate4) 10-Min Break5) Advanced Programming and Debugging6) Sensicast Demo7) Lunch8) Over-Air Programming (XNP) Lab9) Cricket Presentation MIT


Who is Crossbow ?• Founded 1995• Venture Funded - $13M in Financing

– Intel Corporate Investor• Shipping Sensors since 1996• ISO-9001, FAA Certified for Avionics• Two Major Product Lines

– Inertial MEMS Sensors– Wireless Sensor Networks


Personnel• Mike Horton• Matt Miller• Jaidev Prabhu• John Suh• Melissa Horton

• Michael Newman - Sensicast


Why Smart Dust ?

• The Wireless Digital Nervous System… A new breed of Intelligent Sensors that are smarter, smaller, and more adept at communications

• Low cost, low energy sensors:– mems, nanotechnology

• Low cost wireless platforms– integrated radio, uP


The Physical Internet

year

log

(peo

ple

per c

ompu

ter)

Streaming informationto/from physical world

Number CrunchingData Storage

ProductivityInteractive

Mainframe

Minicomputer

WorkstationPC

LaptopPDA

Courtesy: D. Culler, UC Berkeley


Environmental Monitoring

• Air Quality• Soil Moisture• Micro-climates• Animal Tracking


Structural Monitoring


15

13

14

6

5`

1512

11 9

8

Mote Layout

1.0

0.5

0.0

-0.5

-1.0

Acce

lera

tion

(g's

)

20151050Time (s)

North-South East-West

1.0

0.5

0.0

-0.5

-1.0

Acce

lera

tion

(gs)

20151050Time (s)


1.0

0.5

0.0

-0.5

-1.0

Acce

lera

tion

(g's

)

20151050Time (s)


1.0

0.5

0.0

-0.5

-1.0

Acce

lera

tion

(g's

)

20151050Time (s)


Input motion:Canoga Park Northridge Earthquake record(0.36 PGA)


The Alternative


Building Monitoring• 50 Node Conference Room Scheduling

System at Intel• Other Examples

– Energy Usage– Office Comfort– Wireless Thermostats– Wireless Light Switches


• Monitoring Environments– habitat monitoring, conservation biology, ...– Precision agriculture, land conservation, ... – built environment comfort & efficiency ... – alarms, security, surveillance, treaty verification

...• Monitoring Structures and Things

– structural response, condition-based maintenance

– disaster management– urban terrain mapping & monitoring

• Interactive Environments– manufacturing, asset tracking, fleet & franchise– context aware computing, non-verbal

communication– assistance

• home/elder care

Courtesy: D. Culler, UC Berkeley


Market Summary

Automotive

ResearchADOPTION TIME

SIZ

E Electric Power& Utilities

Environmental

IndustrialMonitoring

Building ControlsAsset Tracking

Defense


Ad-Hoc Mesh Networking

• Autonomous nodes self assembling into a network of sensors

• Sensor information propagatedto central collection point

• Sensor collaboration• Intermediate nodes assist distant

nodes to reach the base station.

Routing Tree LinkConnectivity

Base Station


Key Hardware Requirements

• Robust radio technology.• Low cost energy efficient processor.• Flexible I/O for various sensors.• Lifetime energy source.• Flexible, open source, development

platformMOTE


Key Software Requirements• Small foot print to run on small processors • Efficient resource utilization for energy

conservation (10 uA average)• Capable of fine grained concurrency• Highly modular• Robust, low power, ad-hoc mesh networking.

TOS (TinyOS): Tiny Operating System


What is TinyOS ?

• An Open-Source Development Environment

• A Simple Operating System

• A Programming Language and Model

• A Set of Services


TinyOS – Development Environment

• Windows and Linux• Multiple Hardware Platforms• Multiple Sensors• Debugging Tools• Reference Applications


TinyOS/Mote History• Originally developed at UC Berkeley

(David Culler, Kris Pister) • Intel supported Center at UC Berkeley

(Intel and UCB researchers).• University courses in wireless and

computer science• > 300 Groups Actively Use TinyOS


TinyOS: NesC Programming Language and Model

• Separation of construction and composition: – programs are built out of components

• Specification of component behavior in terms of set of interfaces

• Components are statically wired to each other via their interfaces.– This increases runtime efficiency


TinyOS Composition• Composed of Tasks, Signals (interrupts) and

Commands.• Similar to state machine model. Commands

usually start split phase operation.• Signals: Interrupt occurs, process, post task if

needed, go back to sleep.• Tasks: Small queue for background

processing, Each task executed to completion.


TinyOS - Services

• Radio, MAC (Media-Access-Control), Messaging, Routing

• Sensor Interfaces• Power Management• Security• Debug• Time


Ad-Hoc Routing (Self configuring)

• Links are not reliable over the long term

• Links change dynamically

• Requires networking topology that also dynamically changes.

• Low energy requirements limit types of protocols. Powered networks can afford to expend a lot more energy to manage links.

• Protocols where the motes dynamically determine the best parent are attractive.


TinyOS SupportsMultiple Radio Standards

GSM/CDMA GPRS/3G LDMS

802.15.4Zigbee Bluetooth1

802.11x

ShortRange

Low Data Rate High Data Rate

400/900* TinyOS

LongRange WAN

LAN

PAN


Network Stack & Standards

PHY Layer

MAC LayerMAC Layer

Data LinkLayer

Network Layer

Application Interface

Application

Multi-radio& MAC

Time SyncMulti-Hop

Best-EffortReliableSecurity

TASKSensicastSurge

TinyOSBluetoothZigBee (TBD)

IEEE802.15.4


Multiple Network Topologies

Stare.g., BluetoothPICONET

Hybrid Star Peer to Peer

Coordinator – typically powered

“Leaf Node”- typically battery powered


Mote Roadmap• Crossbow

– MICA2 / MICA2DOT– Future

• Cricket• MICA3• MICAz• Compact-Flash Mote

• Others– Motorola HCS08– Zeevo Bluetooth/ARM

smart dust training - ncar earth observing laboratory · pdf file ·...

Documents