By Ryan Berger

flangeeasyMobile - Wireless

Nov 21, 2013 (3 years and 9 months ago)

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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 weather
-
sensing 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


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


May 1
st
, 2003


Two days before the
collapse of the Old
Man in the Mountain


Could this have
been prevented by
using sensors?

Possible Scenario


May 2
nd
, 2003


Movement in the rock
structure detected


Data archiving begins


Models generate
predictions, provided
to local emergency
managers for
planning


Possible Scenario


May 3
rd
, 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


May 24
th
, 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

Networked

Exploit

collaborative

Sensing, action

Sensing

Tightly coupled
to physical
world

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 “end
-
to
-
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


Area
coverage: fraction
of area covered by
sensors


Detectability
: probability
sensors detect
moving
objects


Node
coverage: fraction
of sensors covered by
other sensors


C
ontrol
:


Where
to add new nodes
for max coverage


How
to move existing
nodes for max coverage


Sensor field (either known
sensor locations, or spatial
density)

S

D

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

Sensor

DB

Sensor

DB

Sensor

DB

Sensor

DB

Front
-
end

Sensor Nodes

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


Self
-
configuration


Energy awareness (low power
consumption requirement!)


Congestion Control


Variation in complexity at source and
sink (computation complexity)


S

ESRT Approach

Sensor

DB

Sensor

DB

Sensor

DB

Index

Node DB

Sensor

DB

Sensor

DB

Sensor

DB

Sensor

DB

Front
-
end

Sensor Nodes

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

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