sensor 1234
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ABSTRACTABSTRACT
we proposed a simple and efficientwe proposed a simple and efficient
approach for the placement of multipleapproach for the placement of multiple
sinks within largesinks within large--scale WSNs.scale WSNs.The objective is to determine optimalThe objective is to determine optimal
sinks positions that maximize the networksinks positions that maximize the network
lifetime by reducing energy consumptionlifetime by reducing energy consumption
related to data transmissions from sensorrelated to data transmissions from sensor
nodes to different sinks.nodes to different sinks.
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INTRODUCTIONINTRODUCTION
A sensor network is a static ad hoc networkA sensor network is a static ad hoc networkcomposed of hundreds or thousands ofcomposed of hundreds or thousands ofsensor nodes.sensor nodes.
Each sensor node is equipped with a sensingEach sensor node is equipped with a sensingdevice, a low computational capacitydevice, a low computational capacityprocessor, a shortprocessor, a short--range wireless transmitterrange wireless transmitter--receiver and a limited batteryreceiver and a limited battery--suppliedsuppliedenergy.energy.
It collects data from the surroundingIt collects data from the surroundingenvironment and forward it towards a closeenvironment and forward it towards a closebase station.base station.
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EXISTING SYSTEMEXISTING SYSTEM
The existing protocols and mechanismsThe existing protocols and mechanisms
are not scalable.are not scalable.
They are mostly conceived and adapted toThey are mostly conceived and adapted torelatively small networks.relatively small networks.
In particular, centralised approaches,In particular, centralised approaches,
where data from each sensor is sent to awhere data from each sensor is sent to a
central base station, are not efficient andcentral base station, are not efficient and
can not scale for large wireless sensorcan not scale for large wireless sensor
networks.networks.
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PROPOSED SYSTEMPROPOSED SYSTEM The use of multiple base stations is oneThe use of multiple base stations is one
possible solution for largepossible solution for large--scale WSNs.scale WSNs.
The idea is to shorten the path betweenThe idea is to shorten the path between
each sensor node and the nearest baseeach sensor node and the nearest basestation, to save energy consumption forstation, to save energy consumption fortransmission operations.transmission operations.
To achieve this efficiency, the multipleTo achieve this efficiency, the multiple
base stations should be optimally placedbase stations should be optimally placedwithin the sensed area.within the sensed area.
Graph theory technique is used to partitionGraph theory technique is used to partitionthe network.the network.
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SYSTEM REQUIREMENTSSYSTEM REQUIREMENTS
SOFTWAREREQUIREMENTSSOFTWAREREQUIREMENTS
Java 1.5Java 1.5
HARDWAREREQUIREMENTSHARDWAREREQUIREMENTS
Windows 2000,XpWindows 2000,Xp
4gb RAM4gb RAM
20gb hard disk/ ROM20gb hard disk/ ROM
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SYSTEM ANALYSISSYSTEM ANALYSIS
Model formulationModel formulation
---- The objective is to partition theThe objective is to partition the
connected graph into connected balancedconnected graph into connected balancedsubgraphs(in terms of number of nodes).subgraphs(in terms of number of nodes).
---- This partitioning technique shouldThis partitioning technique should
be applied as much as required accordingbe applied as much as required according
to the targeted size for the subto the targeted size for the sub--networksnetworks
and taking into account the number ofand taking into account the number of
available sinks to be placed.available sinks to be placed.
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start
Model formulation
(Nodes creation)
Problem resolution
(partitioning the
network)
Graph partitioning
approach
Collecting data from
node to sink
stop
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DFDDFD
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MODULESMODULES
Nodes Creation.Nodes Creation.
Dividing the network into subnetworksDividing the network into subnetworks
based onbased on Graph Partitioning Approach.Graph Partitioning Approach.Sink placement technique.Sink placement technique.
Downloading data from nodes to sink.Downloading data from nodes to sink.
Results.Results.
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MODULES DESCRIPTIONMODULES DESCRIPTION
NODES CREATION:NODES CREATION:
-- The Sensor Nodes were created forThe Sensor Nodes were created for
visual representation according to the uservisual representation according to the user
wish (based on cowish (based on co--ordinates).ordinates).
-- The data can be uploaded for theThe data can be uploaded for the
nodes from the database.nodes from the database.
-- We can also upload different values toWe can also upload different values to
different nodes.different nodes.
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GRAPH PARTITIONING APPROACH:GRAPH PARTITIONING APPROACH:
-- Maximally Balanced ConnectedMaximally Balanced ConnectedPartition problem (MBCP) isPartition problem (MBCP) is
used here.used here.
-- SubSub--networks are formed in terms ofnetworks are formed in terms ofnumber of sensors.number of sensors.
-- This technique should be appliedThis technique should be applied
according to the size for the subaccording to the size for the sub--networksnetworksand no.of sinks to be placed on theand no.of sinks to be placed on the
network.network.
-- The final result should be pow(2,n)The final result should be pow(2,n)
where n is the no.of artitionin iterations.where n is the no.of artitionin iterations.
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SINK PLACEMENT TECHNIQUE:SINK PLACEMENT TECHNIQUE:
-- The sinks are deployed according toThe sinks are deployed according toeach subeach sub--network.network.
-- polynomial approximation concept ispolynomial approximation concept is
used.used.
-- To select the neighbouring nodesTo select the neighbouring nodes
within the same subwithin the same sub--network the sortingnetwork the sorting
list of nodes is calculated based on thelist of nodes is calculated based on the
distance of nodes.distance of nodes.
-- The sinks are placed in such a wayThe sinks are placed in such a way
that,they are movable around its partition.that,they are movable around its partition.
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DOWNLOADINGDATA FROM NODESDOWNLOADINGDATA FROM NODES
TO SINK:TO SINK:
-- To collect the data from the nodes,inTo collect the data from the nodes,in
existing concepts the data will passexisting concepts the data will pass
through their parent nodes to reach thethrough their parent nodes to reach the
sink.sink.
-- Thus the parent nodes will lose theirThus the parent nodes will lose their
energy very soon compare to leaf nodes.energy very soon compare to leaf nodes.
-- In proposed the sink will move to theIn proposed the sink will move to the
nodes place to collect the data with in thenodes place to collect the data with in the
partition.partition.
-- Thus we can avoid the energy of eachThus we can avoid the energy of each
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RESULTS:RESULTS:
-- To prove that our proposed approach isTo prove that our proposed approach isefficient the results are calculated andefficient the results are calculated and
compared for the energy loss of thecompared for the energy loss of the
nodes.nodes.
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ALGORITHMIC DESIGNALGORITHMIC DESIGN
MBCP problem:MBCP problem:Bw (Bw (V1,V2) = min ( w(V1), w(V2))V1,V2) = min ( w(V1), w(V2))
Subject toSubject to
1. (1. (V1,V2) is a partition ofV into nonV1,V2) is a partition ofV into non--emptyemptydisjoints setsdisjoints sets V1 andV2such that subV1 andV2such that sub--
graphs ofGgraphs ofGinduced byinduced by V1 andV2areV1 andV2are
connected.connected.2.2. w(V1)=sum(Vs) in the the partition.w(V1)=sum(Vs) in the the partition.
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TESTINGPLANTESTINGPLAN
The test cases should be planned beforeThe test cases should be planned before
testing begins. Then as the testingtesting begins. Then as the testing
progresses, testing shifts focus in anprogresses, testing shifts focus in an
attempt to find errors in integrated clustersattempt to find errors in integrated clustersof modules and in the entire system.of modules and in the entire system.
-- Each module is tested seperately byEach module is tested seperately by
unit testing.unit testing.-- The purpose is to exercise theThe purpose is to exercise the
different parts of the module code todifferent parts of the module code to
detect the errors.detect the errors.
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Sensor NetworksSensor Networks
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5/17/20115/17/2011 Prasant MohapatraPrasant Mohapatra 2020
OutlineOutline
Introduction and IssuesIntroduction and Issues
Architecture and ApplicationsArchitecture and Applications
LocalizationLocalization
Routing and IntercommunicationRouting and Intercommunication
MAC LayerIssuesMAC LayerIssues
Security IssuesSecurity Issues
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What are Sensor Networks?What are Sensor Networks?
A group of wireless nodes or embedded devicesA group of wireless nodes or embedded devices
Collectively the nodes sense, collect, andCollectively the nodes sense, collect, andanalyze dataanalyze data
The sensor nodes are small, low power,The sensor nodes are small, low power,inexpensive, and have high SNR.inexpensive, and have high SNR.
The network usually consists of a large numberThe network usually consists of a large numberof dense nodes distributed at randomof dense nodes distributed at random
They can be deployed in any kind of terrain withThey can be deployed in any kind of terrain with
hostile environment; places where traditionalhostile environment; places where traditionalwired network cannot be deployedwired network cannot be deployed
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Sensor Network ArchitectureSensor Network Architecture
SINK
TASK
MANAGER
Internet/
Satellite
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Sensor Node ArchitectureSensor Node Architecture
Sensor nodes include a combination ofSensor nodes include a combination of
Microelectromechanical systems (MEMS)Microelectromechanical systems (MEMS)
such as sensing devices, actuators, RFsuch as sensing devices, actuators, RF
components, and CMOS building blockscomponents, and CMOS building blocks
Low power computing and wirelessLow power computing and wireless
networking supportnetworking support
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Architecture of a Sensor NodeArchitecture of a Sensor Node
Sensing
UnitA/D
Processor
Memory
Trans-
ceiver
Software
Battery Power
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Applications of SensorApplications of Sensor
NetworksNetworksSurveillance and securitySurveillance and securityEnvironmental monitoringEnvironmental monitoring
Transport monitoringTransport monitoringPrecision agriculturePrecision agriculture
Smart spacesSmart spaces
Manufacturing and inventory controlManufacturing and inventory controlOther specialized tasksOther specialized tasks
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Operational ChallengesOperational Challenges
Ad hoc deployment: should be able toAd hoc deployment: should be able todiscover the topology and selfdiscover the topology and self--configureconfigurefor intercommunicationfor intercommunication
Dynamically adapt to changes in topologyDynamically adapt to changes in topologydue to node failures and environmentaldue to node failures and environmentalconditionsconditions
Automatic configuration/reconfigurationAutomatic configuration/reconfigurationUntethered for energy and communicationUntethered for energy and communication
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Localization IssuesLocalization Issues
What is Localization?What is Localization?
Why is it important?Why is it important?
CategorizationCategorizationSome Localization MechanismsSome Localization Mechanisms
GPSGPS
Beacon based rangingBeacon based ranging Range free methodsRange free methods
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What is Localization?What is Localization?
A mechanism for discoveringA mechanism for discovering
spatial relationships betweenspatial relationships between
objectsobjects
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Why is Localization Important?Why is Localization Important?
Sensor Network Data is typicallySensor Network Data is typicallyinterpreted based on a sensors locationinterpreted based on a sensors location
report event originsreport event origins
giving raw sensor readings a physical contextgiving raw sensor readings a physical context
Temperature readingsTemperature readings temperature maptemperature map
objects trackingobjects tracking
Enables dataEnables data--centric network designcentric network design assist with routingassist with routing
evaluate network coverageevaluate network coverage
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CategorizationCategorization [Bulusu00][Bulusu00]
CoarseCoarse--grained Localizationgrained Localization
Proximity to a given reference pointProximity to a given reference point
E
.g.,A
ctive BadgeE
.g.,A
ctive BadgeFineFine--grained Localizationgrained Localization
Coordinates estimationCoordinates estimation
E.g., Distance to a given reference pointE.g., Distance to a given reference point
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FineFine--Grained LocalizationGrained Localization
Ranging based methodsRanging based methods
TimingTiming
Signal StrengthSignal Strength
Directionality BasedDirectionality Based
Ranging free methodsRanging free methods
E.g.: Centroid based, DVE.g.: Centroid based, DV--hop, APIThop, APIT
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Ranging (Distance Measuring)Ranging (Distance Measuring)
TechniquesTechniquesTime based methodsTime based methods
Time ofArrival (ToA), TDoATime ofArrival (ToA), TDoA
Used with radio, IR, acoustic, ultrasoundUsed with radio, IR, acoustic, ultrasound
Signal StrengthSignal Strength
Uses received signal strength indicator (RSSI)Uses received signal strength indicator (RSSI)
readings and wireless propagation modelreadings and wireless propagation model
Directionality basedDirectionality based Angle ofArrival (AoA) measured with directionalAngle ofArrival (AoA) measured with directional
antennas or arraysantennas or arrays
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TimingTiming
Time of flight of communication signalTime of flight of communication signal
Signal PatternSignal Pattern
Global Positioning SystemGlobal Positioning System Local Positioning SystemLocal Positioning System
Pinpoints 3DPinpoints 3D--iDiD
Different modalities of communicationDifferent modalities of communication
Active BatActive Bat
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Signal StrengthSignal Strength
Attenuation of radio signal increases withAttenuation of radio signal increases with
increasing distanceincreasing distance
RADARRADAR
Wall Attenuation Factor based SignalWall Attenuation Factor based Signal
Propagation ModelPropagation Model
RF mappingRF mapping
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Directionality Based FineDirectionality Based Fine--
Grained
Localization
Grained
LocalizationSmall Aperture Direction FindingSmall Aperture Direction Finding
Used in cellular networksUsed in cellular networks
Requires complex antenna arrayRequires complex antenna array
DisadvantagesDisadvantages
CostlyCostly
Not a receiver based approachNot a receiver based approach
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Basic Concepts in RangingBasic Concepts in Ranging
TrilaterationTrilateration
TriangulationTriangulation
MultiMulti--laterationlateration Considers all available beaconsConsiders all available beacons
A
B
Cab
c
c
C
b
B
a
A
sinsinsin!!
)cos(2
)cos(2
)cos(2
222
222
222
aBCCBC
bBCCAB
cABBAC
Sines Rule
Cosines Rule
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Localization MechanismsLocalization Mechanisms
GPSGPS
Beacon based rangingBeacon based ranging
Range free methodsRange free methods
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Global Positioning System (GPS)Global Positioning System (GPS)
[Getting93][Getting93]
Started in 1973, built in 1993Started in 1973, built in 1993
WideWide--area radio positioning systemarea radio positioning system
RangingRanging--based methodbased method Using Timing ofArrival (ToA)Using Timing ofArrival (ToA)
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GPS System ArchitectureGPS System Architecture
Constellation of 24Constellation of 24
NAVSTAR satellitesNAVSTAR satellites
made by Rockwellmade by Rockwell
Altitude: 10,900 nauticalAltitude: 10,900 nauticalmilesmiles
Orbital Period: 12 hoursOrbital Period: 12 hours
At least five satellites inAt least five satellites in
view from every point inview from every point inthe Globethe Globe
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How GPS WorksHow GPS Works
The basis ofGPS isThe basis ofGPS istrilateration" from satellitestrilateration" from satellites
Distance measuring based on ToADistance measuring based on ToA
accurate timing is importantaccurate timing is important
Along with distance, you need to know exactlyAlong with distance, you need to know exactlywhere the satellites are in spacewhere the satellites are in space
High orbits and careful monitoring are the secretHigh orbits and careful monitoring are the secret
Finally you must correct for any delays the signalFinally you must correct for any delays the signal
experiences as it travels through the atmosphereexperiences as it travels through the atmosphere
A Fourth satellite used for correction purposeA Fourth satellite used for correction purpose
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GPS ot Al a s Appli a lGPS ot Al a s Appli a l
Man ont xts ou annot hav GPS on v r Man ont xts ou annot hav GPS on v r
nodnod
form fa torform fa tor
n rgn rg
ostost
o stru tionso stru tions
Beacon based approaches for sensor networks
Ranging based v.s. ranging free
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Beacon Based Location DiscoveryBeacon Based Location Discovery
Known LocationUnknown Location
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Beacon Based Location DiscoveryBeacon Based Location Discovery
No need ofGPSNo need ofGPS
No infrastructure supportNo infrastructure support
Ad hoc deployableAd hoc deployable
Use RSSI for measuring node separationUse RSSI for measuring node separation
But how should the beacons be placed?But how should the beacons be placed?
Distributed LocalizationDistributed Localization
Iterative multilaterationIterative multilateration
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Localization ApproachLocalization Approach
Single hop beaconingSingle hop beaconing
Iterative multilaterationIterative multilaterationDynamic estimate theDynamic estimate the
wireless channel parameterswireless channel parameters
Can be done in conjunctionCan be done in conjunctionwith routingwith routing
Beacon
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AdvantagesAdvantages
Data packets also act as beacon signalsData packets also act as beacon signals
Location discovery is almost freeLocation discovery is almost free
DistributedDistributed
relies on neighborhood informationrelies on neighborhood information
Fault tolerantFault tolerant
However, Ranging still requires expensive circuits!
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Range Free MethodsRange Free Methods
Centroid approach [Bulusu00]Centroid approach [Bulusu00]
Adaptive beacon placement [Bulusu01]Adaptive beacon placement [Bulusu01]
SelfSelf--configuring localization [Bulusu03]configuring localization [Bulusu03]
DVDV--hop [Niculescu01]hop [Niculescu01] AoA approach [Niculescu03]AoA approach [Niculescu03]
APIT [He03]APIT [He03]
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Centroid Based ApproachCentroid Based Approach[Bulusu00][Bulusu00]
Multiple nodes serve as reference pointsMultiple nodes serve as reference points
(Beacons)(Beacons)
Reference points transmit periodic beaconReference points transmit periodic beacon
signals containing their positionssignals containing their positions
Receiver node finds reference points in its rangeReceiver node finds reference points in its range
and localizes to the intersection of connectivityand localizes to the intersection of connectivity
regions of these pointsregions of these points
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ModelModel
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Centroid Based LocalizationCentroid Based Localization
DisadvantagesDisadvantages
D
esign using a idealized radio model withD
esign using a idealized radio model withperfect spherical radio propagationperfect spherical radio propagation
Assume a regular grid of nodes with knownAssume a regular grid of nodes with known
location information to serve as Beaconslocation information to serve as Beacons
(Xest, Yest) = (avg(Xi1++Xik), avg(Yi1++Yik))
k = No. of beacon nodes within connectivity range
Xi1Xik Yi1Yik: Beacon nodes locations
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Impact of Beacon PlacementImpact of Beacon Placement
Beacons uniformly placed:SMALLER mean granularity
Beacons randomly placed:LARGER mean granularity
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CONCLUSIONCONCLUSION
we proposed the use of graph partitioningwe proposed the use of graph partitioning
techniques to obtain smaller and balancedtechniques to obtain smaller and balanced
subsub--networks over which existing sinknetworks over which existing sink
placement techniques that are optimizedplacement techniques that are optimized
for small to medium scale WSNs.for small to medium scale WSNs.
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REFERENCESREFERENCES
S. Tilak, A. Murphy and W. Heinzelman,S. Tilak, A. Murphy and W. Heinzelman,"Non"Non--Uniform Information DisseminationUniform Information Dissemination
for Sensor Networks,.for Sensor Networks,.
http://users.sdsc.edu/~sameer/pubs/Samehttp://users.sdsc.edu/~sameer/pubs/Sameer_Tilak.pdf.er_Tilak.pdf.
S. R. Gandham et al., Energy EfficientS. R. Gandham et al., Energy Efficient
Schemes for Wireless Sensor NetworksSchemes for Wireless Sensor Networks
With Multiple Mobile Base Stations,.With Multiple Mobile Base Stations,.
http://www.eecs.berkeley.edu/~dtse/ton_mhttp://www.eecs.berkeley.edu/~dtse/ton_m
ob_final_3.pdf.ob_final_3.pdf.
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