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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
Introduction to Wireless Sensor Networks 2010 Luca Mottola
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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
Introduction to Wireless Sensor Networks 2010 Luca Mottola
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Example: Volcano Monitoring(adapted from M. Welsh)
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Anatomy of a WSN Node
Introduction to Wireless Sensor Networks 2010 Luca Mottola
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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!
Introduction to Wireless Sensor Networks 2010 Luca Mottola
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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
Introduction to Wireless Sensor Networks 2010 Luca Mottola
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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
Introduction to Wireless Sensor Networks 2010 Luca Mottola
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Hello World Comm DemoSteal the Light!(adapted from M. Lunden)
Introduction to Wireless Sensor Networks 2010 Luca Mottola
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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
141
144
145
148
149
150
151
152
153
154
160
161
162
142
143
144
149
151
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161
162
0 160
146
146
150
141
153
148 154
142
143
145
Environmental
Acceleration
!!
* * * * *2* * * ** * * * * * * * *
*!
* *
*
!%! % ! ! ! 6!
! ! ! 9 ! !*
*!
%! % ! ! ! ! !
FOS
FOS
joint
Deformation
Introduction to Wireless Sensor Networks 2010 Luca Mottola
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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
# of sampling sessions N
10
10 min
infinite
Acceleration Sampling frequency F
Sampling duration D
# of sampling sessions N
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
0.2
0.4
0.6
0.8
1
#142
#143
#146
#148
#151
#152
Percentageoftime
04 Sept - 09 Sept
#142
#143
#146
#148
#151
#152
09 Sept - 14 Sept
1 Hop2 Hops3 Hops4 Hops5 Hops6 Hops
Introduction to Wireless Sensor Networks 2010 Luca Mottola
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Questions?
Introduction to Wireless Sensor Networks 2010 Luca Mottola