Download Sensor Networks - Gordon College

By Ryan Berger
What are sensor networks?
Network consisting of spatially distributed
autonomous devices using sensors to
cooperatively monitor physical or
environmental conditions, such as
temperature, sound, vibration, pressure,
motion or pollutants, at different locations.
 The sensors themselves can range from
small passive microsensors (e.g, "smart
dust") to larger scale, controllable weathersensing platforms.

Quick Rundown
 They
have micro-sensors, on-board
processing, wireless interfaces
feasible at very small scale
 Can monitor phenomena “up close”
 Enables spatially and temporally
dense environmental monitoring
Who uses Sensor Networks?
The development of wireless sensor
networks was originally motivated by
military applications such as battlefield
surveillance.
 Sensor networks are now used in many
civilian application areas, including
environment and habitat monitoring,
healthcare applications, home
automation, and traffic control.

Potential Uses
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High-rise buildings self-detect structural faults (e.g.,
weld cracks)
Schools detect airborn toxins at low concentrations,
trace contaminant transport to source
Buoys alert swimmers to dangerous bacterial levels
Earthquake-rubbled building infiltrated with robots and
sensors: locate survivors, evaluate structural damage
Ecosystems infused with chemical, physical, acoustic,
image sensors to track global change parameters
Battlefield sprinkled with sensors that identify track
friendly/foe air, ground vehicles, personnel
Parking lots or garages keep track of which spots are
occupied and which aren’t
Seismic Structure response
Ecosystems, Biocomplexity
Possible Scenario

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
May 1st, 2003
Two days before the
collapse of the Old
Man in the Mountain
Could this have
been prevented by
using sensors?
Possible Scenario
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May 2nd, 2003
Movement in the rock
structure detected
Data archiving begins
Models generate
predictions, provided
to local emergency
managers for
planning
Possible Scenario
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May 3rd, 2003
Because instability
was detected early, a
team is sent in to
brace the structure to
prevent further
movement
Team begins
renovations on
structure
Local residents and
tourists are evacuated
to prevent possible
injury
Possible Scenario
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May 24th, 2003
The old man lives!
Renovations are
complete
Sensors have reported
that the rocks are
structurally sound (for
now)
Citizens are welcomed
back into their homes
This use of sensors is
known as area
monitoring
Another Application
Invaluable Fire Fighting Tool
FIRE Eye
Receiver Hardware Types

ZigBee
Other Hardware Types
Wibree
 6lowpan

Programming Languages
Implemented
c@t (Computation at a point in space
(@) Time )
 DCL (Distributed Compositional
Language)
 galsC
 nesC
 Protothreads
 SNACK
 SQTL

Generally Runs Using…

TinyOS
An Example of an Interface
(MonSense)
Characteristics of Each Sensor
Embedded
Control system w/
Small form factor
Untethered nodes
Sensing
Tightly coupled
to physical
world
Networked
Exploit
collaborative
Sensing, action
Types of Sensors

Passive elements: seismic, acoustic, infrared,
strain, salinity, humidity, temperature, etc.

Passive arrays: imagers (visible, IR), biochemical

Active sensors: radar, sonar
 High energy, in contrast to passive elements
Desired Designs

Self-configuring systems that adapt to
unpredictable environment
 Dynamic, messy (hard to model), environments include
pre-configured behavior

Leverage data processing inside the network
 Collaborative signal processing
 Achieve desired behavior with localized algorithms
(distributed control)
Why simply adapting an IP “endto-end” network doesn’t work


Internet routes data using IP Addresses in Packets and
Lookup tables in routers
 Humans get data by “naming data” to a search engine
 Many levels of indirection between name and IP address
 Embedded, unattended systems can’t tolerate
communication overhead of indirection
Special purpose system functions: don’t need or want
Internet general purpose functionality designed for elastic
applications that may change without warning.
The Importance of Time and
Location

Unlike Internet, node time/space location essential
for local/collaborative detection
 Fine-grained localization and time synchronization needed
to detect events in space and compare detections across
nodes

GPS provides solution where available
 GPS not always available, too “costly,” too bulky
 other approaches under study

Localization of sensor nodes has many uses
 Beamforming for localization of targets and events
 Geographical forwarding
 Geographical addressing
Coverage Measures

D
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S
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Area coverage: fraction
of area covered by
sensors
Detectability: probability
sensors detect moving
objects
Node coverage: fraction
of sensors covered by
other sensors
Control:
 Where to add new nodes
Sensor field (either known
sensor locations, or spatial
density)
for max coverage
 How to move existing
nodes for max coverage
Traditional Approach: Warehousing
Warehouse
Front-end
Sensor Nodes
Alternative Approaches

Distributed Storage
 Event-to-Sink
Reliable Transport
Distributed Storage

Data Centric Protocols, In-network Processing goal:
 Network does in-network processing based on distribution
of data
 Queries automatically directed towards nodes that
maintain relevant/matching data

Pattern-triggered data collection
 Multi-resolution data storage and retrieval
 Distributed edge/feature detection
 Index data for easy temporal and spatial searching (quick
access to recently recorded data)
Distributed Storage Approach
Sensor
DB
Sensor
DB
Sensor
DB
Sensor
DB
Front-end
Sensor
DB
Sensor
DB
Sensor
DB
Sensor Nodes
Sensor
DB
Performance of Distributed Storage

High accuracy?
 Distance between ideal answer and actual answer differs
 Ratio of sensors participating in answer also differs

Low latency
 Time between data is generated on sensors and answer is
returned within a short period of time

Limited resource usage
 Energy consumption is high
Distributed Storage Issues

Need for Coordination/Distributed Resource
Allocation
 Multiple sensors need to collaborate on tasks
○ View objects of interest from multiple angles with
different types of sensors
○ Sensing time windows need to be closely aligned
 Environmental Dynamics
○ Sensor configuration changes as target moves
○ Multiple target in overlapping sensor regions
Distributed Storage Issues, cont.

Soft Real-time
 Limited time window for sensing
 Must anticipate where target is moving in order to
effectively allocate sensor resources
 Time for coordination affects time for sensing
Scalability: need to be able to handle large
numbers of sensor nodes
 Robustness: local failures should not induce
global collapse

 Handle uncertain information,
sensor/processor/communication failures
Soft vs. Hard Real-Time

Soft: There are not catastrophic effects
if events are occasionally not interpreted
correctly
 If lose sight of target for a bit, time steps and
then reacquire (generally works okay)

Hard: Computation/Sensing after the
“deadline” may or may still have value
 Reduction in certainty of target location
Event-to-Sink Reliable Transport (ESRT)
Event-to-sink reliability
S
 Self-configuration
 Energy awareness (low power
consumption requirement!)
 Congestion Control
 Variation in complexity at source and
sink (computation complexity)

ESRT Approach
Sensor
DB
Sensor
DB
Sensor
DB
Sensor
DB
Front-end
Sensor
DB
Sensor
DB
Index
Node DB
Sensor Nodes
Sensor
DB
Reliability of an ESRT
 Reliability
is measured in terms of the
number of packets received
 Number of received data packets in
decision interval at the sink
 Number of packets required for
reliable event detection
 Normalized reliability =
observed ÷ desired
Issues with ESRT
Information can be lost if the indexing
node fails
 Indexing node can become overloaded
 Because of this, indexing node may
need to be selective in the nodes it
processes
 Time taken for selection/transfer from
sensors to index may result in the
processing of “old” data

How to “Overcome” Shortcomings
Avoid processing overloads
 Avoid communication overloads
 Have information/processing co-located
 Avoid failure of network based on single
location failure
 Allocate sensing so that as many targets can
be tracked with reasonable success
 Allocate processing/sensing so that real-time
constraints can be met

Radar Parameter Display Image
Transfer with 90% losses
Radar Parameter Display Image
Transfer with no losses
Error Detection

Node information is propagated through the use of
directory services
 Sensors provide sector managers with their information.
 “Track managers” query sector managers for sensor
details.
 This information is cached for future use at each step

The directory held in sector manager maintains
historical query information
 New data is analyzed for relevance to those queries
 Relevant information is automatically propagated to the
query source

This process quickly updates each node’s data,
allowing them to adapt to change
What We’ve Learned (In a Nutshell)…
What sensor networks are
 Examples of how they might be used
 Overview of how they work
 Desired designs
 Coverage measures
 Different approaches to set-up
 Error detection (very brief)

Sensor Networks in the News
Researchers plan to install 100 sensors
by 2011 on streetlamps throughout the
city of Cambridge, MA
 Distributed Traffic Light Control
 Microfluidics for water supply protection
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In Conclusion…
Sensor Networks = Incredibly useful,
perhaps vital technology
 There is no one best approach

 Very sensitive to characteristics/capabilities
of sensors, quality of sensor data, amount
and type of processing required, system
objectives, communication and processing
capabilities, environment, etc…

This is a technology that will only become
more prevalent in our everyday lives