01 WSNProgramming Lecture Intro

8/3/2019 01 WSNProgramming Lecture Intro

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A part of Swedish ICT

Introduction to

Wireless SensorNetworksLuca Mottola (www.sics.se/~luca)

Networked Embedded Systems Group SICS

Programming WSNs: A System Perspective

KTH Graduate Course, Fall 2010


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Goals: understand the issues in building distributedsystems using wireless embedded devices

gain insights into state-of-the art solutions tosolve these issues

get practical hand-on experience at buildingsuch distributed systems

Achieved by covering a range of topics operating systems, communication

protocols, programming abstractions,

Hands-on labs and real-world projects!

About This Course

Introduction to Wireless Sensor Networks 2010 Luca Mottola


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Luca Mottola

SICS

About Us

Olaf Landsiedel

KTH

Adam Dunkels

SICS

Antonio Gonga

Ph.D. student at KTH,

class TA



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Computing on the Internet

Nodes are

resource-rich

#nodes #users

Interaction between people and

human-mediated data sources

Communication

among geographicallydistributed nodes

Focus: human-centered

interactive decision making



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Internet of Things

Nodes are

resource-scarce

#nodes >> #usersInteraction between people

and the instrumented world(e.g., sensors, actuators)

Answers are obtained by

fusing real-time informationfrom distributed nodes

Focus: support human-supervised

autonomous decision making



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Enabled by miniaturization ofprocessing, communication,sensing and actuating

devices

Many cheap devices withshort-range communication

More coverage with lessenergy (and no wires!)

Wireless Sensor Networks



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Example: Volcano Monitoring(adapted from M. Welsh)


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Anatomy of a WSN Node



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Anatomy of a WSN Node



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Example: TelosB/TMote Sky TI MSP 430 (16 bit RISC)

8 MHz 10 KB RAM 48 KB code, 1MB flash

Chipcon CC2420 radio IEEE 802.15.4 compliant 50 m. range indoor,

250 m. range outdoor

bandwidth 250 kbits/s On-board antenna Temperature, light, and

humidity sensors built-in


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Turns the green led on ifhumidity is below 50%

If humidity goes above50%, turns the red led on

Hello World Sensing DemosHumidity



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Hello World Sensing DemosAcceleration

Shake the mote to

turn the leds on!



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CrossBow

MICA2

MoteIV

TMote Sky

Intel iMote2 Sun SPOT

CPU and clock ATmega128L

16 MHz

TI MSP 430

8 MHz

Intel PXA271

416 MHz

ARM 920T

180 MHz

Memory

(RAM, code, flash)

4 KB, 128 KB,

512 KB

10 KB, 48 KB,

1 MB

256 KB, 32 MB,

32 MB

512 KB

(data+code),4 MB

Radio chip Chipcon 1000 Chipcon 2420 Chipcon 2420 Chipcon 2420

Power 2 AA 2 AA 3 AAA 3.7Vrechargeable

Language C-based C-based C-based Java2ME

Some Mote Platforms



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WSN Challenges: Power

Power consumption devices are battery-powered, meant to

operate unmanned for a long period of time

communication is typically the biggest energy drain duty cycle is critical: nodes sleep for most of the time

communication ~mA, stand-by ~A TMote mote always on: ~8 days;

2% duty cycle (1.2s/min): 9 months



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No radio

duty-cycleRadio

duty-cycle

Speaking of Radio..



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WSN Challenges: Reliability

Reliabilitywireless link quality fluctuates based on

environment

topology changes as the WSN operates!nodes are often deployed in a hostile

environment and may fail

the application/networkmust self-organize!



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Non-isotropic range, asymmetric links Collisions, hidden terminal problem What-you-see-is-not-what-you-get topologies

e.g., good connection to far nodes and bad to close ones

The Woes of Wireless



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Changing Topologies



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A Reference Architecture


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Operating Systems

OSs for WSNs differentfrom mainstream ones-basic run-time support for application programs- little or no support for user interaction

Programs are cross-compiled and linked withthe OS library- the resulting binary is deployed on the WSN node

Most popular: Contiki and TinyOS-alternatives: Mantis, LiteOS,

Main differences: model of concurrency,support for dynamic linking,

Adam and Luca to

tell more in Lecture2, 4, 5, and 7



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Medium Access Control (MAC)

Goals: avoid packet collisions and turn off the radiowhenever possible Much simpler than conventional MACs

some features are demanded to application code CSMA (Carrier Sense) and TDMA (Time Division)are dominant

CSMA good for changing topologies, may suffer underheavy load

TDMA guarantees predictableperformance, needs time synch

Olaf talks in

Lecture 3



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Hello World Comm DemoSteal the Light!(adapted from M. Lunden)



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Routing Concern: energy consumption WSN routing is different:

conventional protocols based onaddresses identifying the target(e.g., unicast or multicast IP addresses)

WSN nodes may not be relevant per se:it is their (individual or collective) features that matter

many-to-one, one-to-many, andmany-to-many vs. one-to-one

Attribute-based routing is also used message forwarding based on the nature of data similar to content-based routing

Plethora of protocols available a small subset used for real

sink

sourcesource

Olaf

discusses in

Lecture 6



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IP Networking Interoperability and integration with

the Internet motivate using IP Issues:

network overhead size of stack implementations address assignment routing

Several activities 6LowPan

header compression, ROLL

routing, ISA100

Adam talks in

Lecture 10



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Time Synchronization

Often necessary to correlatethe data to the time it was sampled

e.g., structural monitoring, earthquake detection Nodes have different times

differences in clock quartzes and in their drifts

well-known problem in distributed systems (NTP):peculiarity here is wireless and energy-awareness

Several protocols availableprecision down to milliseconds require periodic network-wide message exchanges



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Node Localization

It is often necessary to know the physicallocation of a node

interpret sensed data, determine span of actuationoften determined at deployment time and known to

both nodes and gateway

What if location is not known?assume nodes are GPS-equipped

easy and precise but energy hungry

use radio-based localization e.g., based on RSSI



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In Practice, However

Each component is often built separately The programmer is forced to deal with low-level details

instead of the application logic



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Wide variety ofapplicationrequirements

Inherent tension between: the desire to shield programmers

from complexity

the need to enable cross-layer design

January 28th, 2008

centralized

decentralized

homogeneous heterogeneous

Habitat

monitoring

Wildlife

monitoring

Healthcare

Smart

ambient

Wireless

Sensor and

Actor Networks

WSN Challenges: ProgrammingLuca tells more in

Lecture 8 and 9



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Putting All Togheter:

The Torre Aquila Deployment(Trento, Italy)

M. Ceriotti, L. Mottola, G. P. Picco, A. L. Murphy, S. Guna, M. Corr, M. Pozzi, D. Zonta, and P. Zanon.

"Monitoring Heritage Buildings with Wireless Sensor Networks: The Torre Aquila Deployment.

In IPSN/SPOTS, 2009. Best paper award.


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Heritage buildings requiremaintenance and carefulassessment

Typically achieved withwired data loggers cumbersome and invasive especially in the presence of

works of art

WSNs as a viable alternative untethered monitoring minimum invasiveness high sensing granularity flexibility and ease of relocation

Traditional data logger

WSN node

Motivation



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Torre Aquila 31-meter tall medieval tower

part of the complex of Castellodel Buonconsiglio in Trento, Italy The 2nd floor contains the

Ciclo dei 12 mesi internationally-renowned

frescoes, attracting thousands of

visitors each year Originally the Eastern gate to

the city today, surrounded by high volume

of vehicular traffic

Concerns due to the plan ofdiverting traffic into a roadtunnel near the tower


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Deployment in Torre Aquila

FIRST FLOORNORTH SECTION

SECOND FLOOR

THIRD FLOOR

0

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Environmental

Acceleration

!!

* * * * *2* * * ** * * * * * * * *

*!

* *

*

!%! % ! ! ! 6!

! ! ! 9 ! !*

*!

%! % ! ! ! ! !

FOS

FOS

joint

Deformation



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Software

Functionality fully decoupled, asynchronousinteractions through a middleware layer

Sampling and Taskingto drive sensing basedon user parametersData Collection to report sensed data reliablyData Dissemination to distribute user

parametersTime Synchronization to correlate readings



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SoftwareSampling & Data Collection

Different classesof trafficBursty, high-rate

w/ strong reliability (compressed)

vibration data

Low-rate w/ weak reliability environmental, deformation data

Best effort system monitoring

Node type Operatingparameters

Typicalvalues

Environmental Sampling period P

# of sampling sessions N

10 min

infinite

Deformation # of samples averaged A

Sampling period P


10

10 min

infinite

Acceleration Sampling frequency F

Sampling duration D


200 Hz

20 s

infinite



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Sampling & Data CollectionRouting Details

Hop-by-hop reliabilityscheme

Child

send(tuple 6)

Parent

retrieve(tuple 7)

4 5 6

cache

send(tuple 7)

send(tuple 8)

5 6 7

cache

6 7 8

cache

send(tuple 9)

7 8 9

cache


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Torre Aquila Demo



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Monitoring Heritage Buildings with WSNs: The Torre Aquila Deployment2009 Matteo Ceriotti and Luca Mottola

Vibration

!

Vibrational Modes

D. Zonta et al. Real-Time Health Monitoring of of Historic Buildings with Wireless Sensor Networks

In Proc. of the 7th Int. Conf. On Structural Health Monitoring, 2009.

Deformation

!

!

!

The breath of

the structure

(Preliminary) Data Analysis


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Lessons Learned Thick walls drastically affect wireless propagation

small changes in node placement modify the topology

motes are tempting Moved the sink

node by 1 meter!0

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Percentageoftime

04 Sept - 09 Sept

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09 Sept - 14 Sept

1 Hop2 Hops3 Hops4 Hops5 Hops6 Hops



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Questions?


01 WSNProgramming Lecture Intro

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