wireless sensor networks in practice · wireless sensor networks in practice ... mobile nodes,...

What are Wireless Sensor Networks Technical aspects and challenges DIY platforms Business - requirements and status quo

Wireless sensor networks in practiceIncluding a cute rabbit

Ruzena Chamrova

March 17, 2011


Efficient disaster relief through Wireless Sensor Networks ?


Outline

What are Wireless Sensor Networks

Technical aspects and challenges

DIY platforms

Business - requirements and status-quo


Wireless sensor networks (WSNs)

Network of small spatially distributed devices that cancommunicate with each other over a medium

enabled by recent advances in processing, sensing andcommunication domain

deployed to monitor (sensors) and/or control (actuators) theenvironment


Example 1: Strain sensors of a train rail on a bridge

Small pre-planned WSN, event-driven data collection

Ben Franklin Bridge, PH

one-many (10 sensor nodes)

transmission range 100 m

low-power sampling mode (6Hz = 0.17s),increases when train present

strain rates logged to the nodes Flashmemory

data collected periodically by the basestation

J.S.Wilson / Sensor Technology Handbook (2005), Fig. www.zazzle.com


Example 2: ZebraNet - habitat monitoring in Kenya (2005)

Ad-hoc WSN, mobile nodes, mobile sink, necessity todiscover network routes

Zebra with a collar, Kenya

nodes mounted on zebras

harsh environment (water, bite)

GPS position sampled every 3 min

detailed information sampled every hour(sun/shade indication, speed)

base station moves and is onlyintermittently availablewww.princeton.edu/ mrm/zebranet.html


Example 3: Underwater acoustic WSN

Pre-planned network with underwater vehicles, acousticsignal

Autonomous underwater vehicle

high attenuation

high bit errors

temporary loss of connectivity

corrosion of sensors

battery lifetime (solar energy cannot beexploited)

bandwidth limitations

J. M. Daladier / PhD thesis University od South Florida (2009)


WSNs have many faces ...

Taxonomy of WSNs

L. Mottola et al. / ACM Computing Surveys (2010)


...which are are addressed at many levels

J. Yick et al. / Computer Networks 52 (2008) 2292–2330


Challenges

1 Use less power

2 Self-organize, be fault tolerant

3 Efficiently process data

4 Be secure

goo.gl/EZTND


Challenge 1: Use less power

Most energy in WSNs is spent on communication.

strict power management mechanisms (sleep modes)

data compression

application specific operating system (e.g. TinyOS)

efficient data management (TinyDB)

energy scavenging for battery (solar power)


Challenge 2: Self-organize, be fault tolerant

WSNs are often established in an ad-hoc way, thus requirethe capability to self-organize.

Internet routing protocols not suitable

Optimal clustering necessary for energy-efficiency

Sensors may fail (lack of power, damage, interference)

Necessity to change sensing rate, reroute packets

J.N. Al-karaki et al., IEEE Wireless Communications (2004)


Challenge 2: Self-organize, be fault tolerant

Mesh topology enables routing through alternative paths in caseof node failures (unlike star or tree topology). www.meshnetics.com


Challenge 3: Data processing

Processing can be performed on:

Nodeto save on communication requirements

Sinkprocessing to get the big picture (possibly react throughactuators)


Challenge 4: Security - better encryption, higher overhead

General issues: Denial of service, Host impersonation, informationdisclosure

Wireless specific security issues:

Resource Consumption critical node traffic or filling routingtable with rubbish

Interference strong noise signal disturbs communicationwithin WSN

Physical security nodes can be taken away


DIY WSN platforms

Enabled thanks to:

Decreasing hardware costs

Simplified embedded development

Maturity and availability of technologies


Components of a WSN node

1 Wireless tranceiver with an antenna (transmission

range, power consumption)

2 Microcontroller and memory (processes received data,

determines software limitations)

3 Networking and application software

4 Power supply

5 Sensors and/or actuators

6 Other peripherals

www.meshnetics.com


Radio options for wireless sensor networks

T. Myllys / National Instruments (2009)


Available WSN platforms

Programmableand expandable

Programmable Adjustable

Platform Sun SPOT, Imote2,Make, Phidgets, Ar-duino, Telos

Mindstorms,Vex

Violet Rabbit

Market Researchers, start-ups, geeks

Children Wide com-munity

inspired by I.Pletikosa et al. (2010)


Platforms based on TI MSP430 processor 8-16 MHz

Telos (Crossbow)

10kB RAM, 48kB Flash

802.15.4 Radio

Humidity and temperature sensor

TinyOS, Contiki, Mantis

2x80$

www.wsnblog.com

Shimmer

10kB RAM, 40kB Flash

802.15.4 Radio, Bluetooth radio

3-Axis Accelerometer, ECG extra

TinyOS

2x200$

www.shimmer-research.com


General-purpose high processing power platforms

Imote2 (Crossbow)

XScale processor, 13-416 MHz

256kB SRAM,32MBFLASH,32MB SDRAM

802.15.4 Radio

separate sensor boards

TinyOS, Linux

www.xbow.com

Sun SPOT (Oracle)

ARM920T processor, 180 MHz

512kB RAM, 4MB Flash

802.15.4 Radio

Accelerometer, temp., light sensor

Java

400$

sun.blogs.com


Extensible microcontroller platform

Arduino

flexible popular open-source prototyping platform

programmable with Arduino language similar to C

can be easily extended with wireless communication andsensors

FLASH 16 - 256 kB, SRAM 1 - 8 kB

arduino.cc


Demonstration: Simple temperature WSN, dataavailability anywhere

goo.gl/aXYlk

Node 1 - Coordinator

Computer

Xbee radio module

Node 2 - Router

Microcontroller ArduinoDuemilanove

Xbee radio module

Temperature sensor

Power supply


Simple temperature WSN

Node 1 - Coordinator

Node 2 - Router

Transmission range: 40 m, Data rate: 250 kb/s, Price: 130CHF, 15 + 15 lines of code


Simple temperature WSN - Pachube - data anywhere


Attractive target markets

B. Kennedy, NRC Canada (2009)


Logistics: Sense-aware packets

real-time tracking (expensive, perishable goods)

exact location, temperature, light, vital signs

120$ / month (FedEx, 2009), still in testing

FedEx SenseAware technology

www.senseaware.com


Environment: Tsunometer network

comparison of measured (buoys) and predicted values (nodes)

buoys often damaged by ships, weather or vandals

false alarms - 9 out of 10 earthquakes do not generate tsunami

DART sensors on the Ring Of Fire

goo.gl/RJi2I


Consumer WSNs: Violet Rabbit (Karotz)

wireless friend which reads out news, mails

senses and actuates (speaks when unhappy, practises Tai-Chi)

adjustable functions, RFID tags

its time will perhaps come soon

Violet nabaz rabbit

www.nabaztag.com


Bringing IOT concept closer - data brokerage platformsand mash-ups

Data brokerage platforms:

upload and share sensor data

public data can be displayed and queried

Pachube, Sensorbase, Sensorpedia, HP CeNSE

Mash-ups:

new data created by combining two or more resources

SensorMap (Microsoft)

A. Broring et.al, Sensors (2011)

goo.gl/1Sog


Market - technology push rather than market pull

Positive

active and growing market

core tech. developed

standards emerging

many suppliers

Negative

power management

lack of system integrators

immature app. level software

privacy

S.Methley, Plextek (2008)


Where next?

How far can you go with WSNs (technology-push vs.market-pull)?

Where could the problem of data integration lie (interest)?

How do you work around the privacy concerns of consumerWSNs?

www.ascendingtogether.com

wireless sensor networks in practice · wireless sensor networks in practice ... mobile nodes,...

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