wireless sensor network

WIRELESS SENSOR NETWORKSWIRELESS SENSOR NETWORKS

Ian F. AkyildizIan F. Akyildiz

Broadband & Wireless Networking LaboratoryBroadband & Wireless Networking Laboratory

School of Electrical and Computer EngineeringSchool of Electrical and Computer Engineering

Georgia Institute of TechnologyGeorgia Institute of Technology

Tel: 404-894-5141; Fax: 404-894-7883 Tel: 404-894-5141; Fax: 404-894-7883

Email: [email protected]: [email protected]

Web: http://www.ece.gatech.edu/research/labs/bwnWeb: http://www.ece.gatech.edu/research/labs/bwn

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Internet, Internet, Satellite, Satellite, etcetc

Sink

Sink

TaskManager

1. INTRODUCTION1. INTRODUCTIONSENSOR NETWORKS ARCHITECTURESENSOR NETWORKS ARCHITECTURE

Several Several thousand nodesthousand nodes

Nodes are tens Nodes are tens of feet of each of feet of each otherother

Densities as high Densities as high as 20 nodes/m3as 20 nodes/m3

•I.F.Akyildiz, W.Su, Y. Sankarasubramaniam, E. Cayirci, I.F.Akyildiz, W.Su, Y. Sankarasubramaniam, E. Cayirci, ““Wireless Sensor Networks: A Survey”, Wireless Sensor Networks: A Survey”, Computer Networks (Elsevier) JournalComputer Networks (Elsevier) Journal, March 2002., March 2002.

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Key technologies that Key technologies that enableenable sensor networks: sensor networks:

Micro electro-mechanical Micro electro-mechanical systems (MEMS)systems (MEMS)

Wireless communicationsWireless communicationsDigital electronicsDigital electronics

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Sensor Network Sensor Network ConceptConcept

Sensors nodes are very close to each Sensors nodes are very close to each otherother

Sensor nodes have local processing Sensor nodes have local processing capabilitycapability

Sensor nodes can be randomly and Sensor nodes can be randomly and rapidly deployed even in places rapidly deployed even in places inaccessible for humansinaccessible for humans

Sensor nodes can organize themselves to Sensor nodes can organize themselves to communicate with an access pointcommunicate with an access point

Sensor nodes can collaboratively workSensor nodes can collaboratively work

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SENSOR NODE SENSOR NODE HARDWAREHARDWARE

Power UnitPower Unit Power GeneratorPower Generator

Sensor ADCSensor ADCProcessorProcessor

MemoryMemoryTransceiverTransceiver

Location Finding SystemLocation Finding System MobilizerMobilizer

SmallSmall Low powerLow power Low bit rateLow bit rate High density High density Low cost (dispensable)Low cost (dispensable) AutonomousAutonomous AdaptiveAdaptive

SENSING UNITPROCESSING UNIT

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Example: MICA MotesExample: MICA MotesBWN Lab @ GaTechBWN Lab @ GaTech

Processor andRadio platform(MPR300CB) isbased on Atmel ATmega 128Llow power microcontrollerthat runs TinyOsoperating systemfrom its internalflash memory.

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Berkeley MotesBerkeley Motes

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Specifications of the Specifications of the MoteMote

Processor/Radio Processor/Radio BoardBoard

MPR300CBMPR300CB RemarksRemarks

SpeedSpeed 4 MHz4 MHz

FlashFlash 128K bytes128K bytes

SRAMSRAM 4K bytes4K bytes

EEPROMEEPROM 4K bytes4K bytes

Radio FrequencyRadio Frequency 916MHz or 916MHz or 433MHz433MHz

ISM BandISM Band

Data RateData Rate 40 Kbits/Sec40 Kbits/Sec MaxMax

Power Power 0.75 mW0.75 mW

Radio Range Radio Range 100 feet100 feet ProgrammableProgrammable

PowerPower 2 x AA batteries2 x AA batteries

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Examples for Sensor Examples for Sensor NodeNodess

UC Berkeley: COTS DustUC Berkeley:

Smart Dust

UCLA: WINS

Rockwell: WINS

JPL: Sensor Webs

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Examples for Sensor Examples for Sensor NodeNodessRene Rene MoteMote

Dot Dot MoteMote

weC MoteMica node

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Zylog’s eZ80Zylog’s eZ80 Provides a way to Provides a way to

internet-enabled process internet-enabled process control and monitoring control and monitoring applications.applications.

Temperature sensor, Temperature sensor, water leak detector and water leak detector and many more applicationsmany more applications

Metro IPWorks™ Metro IPWorks™ software stack software stack embeddedembedded

Enables users to access Enables users to access Webserver data and files Webserver data and files from anywhere in the from anywhere in the world.world.

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Systronix STEP Systronix STEP boardboard

A first tool to support A first tool to support hardware development hardware development and prototyping with and prototyping with the new Dallas TINI the new Dallas TINI Java Module.Java Module.

Embedding the internet Embedding the internet with TINI javawith TINI java

A complete Java Virtual A complete Java Virtual Machine, TCP/IP stack, Machine, TCP/IP stack, ethernet hardware, ethernet hardware, control area network, control area network, iButton network and iButton network and dual RS232 all on dual RS232 all on SIMM72 moduleSIMM72 module

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2. Sensor Networks 2. Sensor Networks ApplicationsApplications

Sensor networks may consist of sensor types Sensor networks may consist of sensor types such as:such as:

Seismic Seismic Low sampling rate magneticLow sampling rate magnetic ThermalThermal VisualVisual InfraredInfrared AcousticAcoustic Radar. Radar.

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Sensor Networks Sensor Networks ApplicationsApplications

Sensors can monitor ambient conditions including:Sensors can monitor ambient conditions including: TemperatureTemperature HumidityHumidity Vehicular movementVehicular movement Lightning conditionLightning condition PressurePressure Soil makeupSoil makeup Noise levelsNoise levels The presence or absence of certain kinds of objectsThe presence or absence of certain kinds of objects Mechanical stress levels on attached objects, andMechanical stress levels on attached objects, and Current characteristics (speed, direction, size) of Current characteristics (speed, direction, size) of

an objectan object

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Sensors can be used for:Sensors can be used for:

Continuous sensing Continuous sensing Event detectionEvent detection Event identificationEvent identification Location sensingLocation sensing Local control of actuatorsLocal control of actuators

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MilitaryMilitary EnvironmentalEnvironmental HealthHealth HomeHome Other commercialOther commercial Space explorationSpace exploration Chemical processingChemical processing Disaster reliefDisaster relief

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Military Applications:Military Applications:Command, control, communications, computing, Command, control, communications, computing, intelligence, surveillance, reconnaissance, targeting intelligence, surveillance, reconnaissance, targeting (C4SRT)(C4SRT) Monitoring friendly forces, equipment and Monitoring friendly forces, equipment and

ammunition ammunition Battlefield surveillanceBattlefield surveillance Reconnaissance of opposing forces and Reconnaissance of opposing forces and

terrainterrain TargetingTargeting Battle damage assessmentBattle damage assessment Nuclear, biological and chemical (NBC) attack Nuclear, biological and chemical (NBC) attack

detection and reconnaissancedetection and reconnaissance

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SensIT: SensIT: Sensor Information Technology

“SensIT was a program for developing software for distributed wireless sensor networks.” SensIT pursued two key thrusts: * New networking techniques* New networking techniques * Network information processing.

“ SensIT nodes can support detection, identification, and tracking of threats, as well as targeting and communication.”

http://www.darpa.mil/DARPATech2000/Speeches/ITOSpeeches/ITOSensIT(Kumar).docS. Kumar, D. Shepherd, “SensIT: Sensor information technology for the warfighter,” 4th Int. Conference on Information Fusion, 2001.

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ForceNet (US Navy)ForceNet (US Navy)

ForceNet binds together Sea Strike, Sea Shield, and Sea ForceNet binds together Sea Strike, Sea Shield, and Sea Basing. Basing.

Sea StrikeSea Strike—Projecting Precise and Persistent Offensive —Projecting Precise and Persistent Offensive PowerPower Sea ShieldSea Shield—Projecting Global Defensive Assurance—Projecting Global Defensive Assurance Sea BasingSea Basing—Projecting Joint Operational Independence—Projecting Joint Operational Independence

It is It is the framework for naval warfarethe framework for naval warfare that integrates that integrates warriors, sensors, command and control, platforms, and weaponswarriors, sensors, command and control, platforms, and weapons into a networked, distributed combat force. into a networked, distributed combat force.

http://www.chinfo.navy.mil/navpalib/cno/proceedings.htmlhttp://www.chinfo.navy.mil/navpalib/cno/proceedings.html

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SAD: SEAL Attack Detection SAD: SEAL Attack Detection & Anti-Submarine Warfare& Anti-Submarine Warfare

antennaantenna

ledledhookshooks

sensorsensor

cablecable

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Other ProjectsOther Projects

ESG: ESG: Expeditionary Sensor Grid. .

NCCT: Network Centric Collaborative NCCT: Network Centric Collaborative Targeting.Targeting.

Sea Web. Sea Web.

Smart WebSmart Web

Sensor WebSensor Web

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Other Military ApplicationsOther Military Applications

Intrusion detection (mine fields)Intrusion detection (mine fields) Detection of firing gun (small arms) Detection of firing gun (small arms) locationlocation Chemical (biological) attack detectionChemical (biological) attack detection Targeting and target tracking systemsTargeting and target tracking systems Enhanced guidance and IFF systemsEnhanced guidance and IFF systems Battle damage assessment systemBattle damage assessment system Enhanced logistics systems,Enhanced logistics systems,

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Environmental Environmental ApplicationsApplications

Tracking the movements of birds, small animals, and insectsTracking the movements of birds, small animals, and insects Monitoring environmental conditions that affect crops and livestockMonitoring environmental conditions that affect crops and livestock IrrigationIrrigation Macroinstruments for large-scale Earth monitoring and Macroinstruments for large-scale Earth monitoring and planetary explorationplanetary exploration Chemical/biological detectionChemical/biological detection Biological, Earth, and environmental monitoring in marine, soil, and Biological, Earth, and environmental monitoring in marine, soil, and atmospheric contextsatmospheric contexts Meteorological or geophysical researchMeteorological or geophysical research Pollution study, Precision agriculturePollution study, Precision agriculture Biocomplexity mapping of the environmentBiocomplexity mapping of the environment Flood detection, andFlood detection, and Forest fire detection.Forest fire detection.

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Forest Fire Forest Fire DetectionDetection

Maybe strategically, randomly, and Maybe strategically, randomly, and densely deployeddensely deployed Millions of sensor nodes can be deployedMillions of sensor nodes can be deployed

Purpose: Detect fire before spread Purpose: Detect fire before spread uncontrollable.uncontrollable.

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Health Health ApplicationsApplications

Providing interfaces for the disabledProviding interfaces for the disabled Integrated patient monitoringIntegrated patient monitoring Diagnostics Diagnostics Monitoring the movements and internal Monitoring the movements and internal processes ofprocesses of insects or other small animals insects or other small animals Telemonitoring of human physiological dataTelemonitoring of human physiological data Tracking and monitoring doctors and Tracking and monitoring doctors and patients inside a patients inside a hospital, and hospital, and Drug administration in hospitalsDrug administration in hospitals

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Drug Administration in Drug Administration in HospitalsHospitals

Purpose: Minimize prescribing the wrong medication to Purpose: Minimize prescribing the wrong medication to patientspatients..

Identify patients allergies and required medicationsIdentify patients allergies and required medications Current computerized systems can reduce medication errors Current computerized systems can reduce medication errors and prevent many Adverse Drug Events (ADE) and prevent many Adverse Drug Events (ADE) Cost of ADEs is as high as $5.6 millions/year /hospital, Cost of ADEs is as high as $5.6 millions/year /hospital, and 770,000 Americans injured and die annually because of and 770,000 Americans injured and die annually because of ADEs.ADEs. Save hospitals up to $500,000/yearSave hospitals up to $500,000/year Only 5% of civilian hospitals have computerized systemOnly 5% of civilian hospitals have computerized system Can prevent 84% of dosage errorsCan prevent 84% of dosage errors Start-up cost is around $2 million (cheap sensor nodes can be Start-up cost is around $2 million (cheap sensor nodes can be deployed).deployed).

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Home ApplicationsHome Applications

Security Security Home automation, andHome automation, and Smart EnvironmentSmart Environment

Types: Types:

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Smart Smart EnvironmentEnvironment

Purpose: Allowing users to seamlesslyPurpose: Allowing users to seamlessly interact with their environment.interact with their environment.

Two perspectives: Two perspectives: human-centered, or technology-human-centered, or technology-centeredcentered Example: “Aware Home” project at Example: “Aware Home” project at Georgia Tech.Georgia Tech.

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Smart Smart EnvironmentEnvironment

Human-centered: Human-centered: A smart environment must adapt to A smart environment must adapt to the needs of the users in terms of I/O the needs of the users in terms of I/O capabilities.capabilities.

Technology-centeredTechnology-centeredNew hardware technologies, New hardware technologies, networking solutions and middleware networking solutions and middleware services must be developed.services must be developed.

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Smart Environment Smart Environment (Cont’d)(Cont’d)

Room 1Room 1 Room 2Room 2

User entersUser enters User entersUser enters

ComputersComputerswith embedded with embedded sensor nodes.sensor nodes.

Scanner and phoneScanner and phonewith embeddedwith embeddedsensor nodes.sensor nodes.

ServerServerWired or wireless connectionWired or wireless connection

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Commercial Commercial ApplicationsApplications

Building virtual keyboardsBuilding virtual keyboards Monitoring product qualityMonitoring product quality Constructing smart office spacesConstructing smart office spaces Interactive toysInteractive toys Monitor disaster areasMonitor disaster areas Smart spaces with sensor nodes embedded Smart spaces with sensor nodes embedded insideinside Machine diagnosisMachine diagnosis Interactive museumsInteractive museums Managing inventory control Managing inventory control Environmental control in office buildingsEnvironmental control in office buildings Detecting, and monitoring car thefts, andDetecting, and monitoring car thefts, and Vehicle tracking and detection.Vehicle tracking and detection.

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Vehicle Tracking and Vehicle Tracking and DetectionDetection

Purpose: Locate a vehiclePurpose: Locate a vehicle

AMPS sensor nodes are deployedAMPS sensor nodes are deployed Two ways to detect and track the Two ways to detect and track the vehiclevehicle

- determine the line of bearing (LOB) - determine the line of bearing (LOB) in eachin each cluster and then forward to the cluster and then forward to the base-station, orbase-station, or - send all the raw data to the base-- send all the raw data to the base-stationstation (uses more power as distance (uses more power as distance increases)increases)

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iBadge - UCLAiBadge - UCLA

Investigate behavior of Investigate behavior of children/patientchildren/patient

Features:Features:– Speech recording/replayingSpeech recording/replaying– Position detectionPosition detection– Direction detection/estimation Direction detection/estimation

(compass)(compass)– Weather data: Temperature, Weather data: Temperature,

Humidity, Pressure, LightHumidity, Pressure, Light

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iBadge - UCLAiBadge - UCLA

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iButton iButton ApplicationsApplications

Caregivers AssistanceCaregivers Assistance– Do not need to keep a bunch of keys. Do not need to keep a bunch of keys.

Only one iButton will do the workOnly one iButton will do the work Elder AssistanceElder Assistance

– They do not need to enter all their They do not need to enter all their personal information again and again. personal information again and again. Only one touch of iButton is sufficientOnly one touch of iButton is sufficient

– They can enter their ATM card They can enter their ATM card information and PIN with iButtoninformation and PIN with iButton

– Vending Machine Operation AssistanceVending Machine Operation Assistance

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3. Factors Influencing 3. Factors Influencing Sensor Sensor Network Design Network Design

A. Fault Tolerance (Reliability)A. Fault Tolerance (Reliability)B. ScalabilityB. ScalabilityC. Production CostsC. Production CostsD. Hardware ConstraintsD. Hardware ConstraintsE. Sensor Network TopologyE. Sensor Network TopologyF. Operating EnvironmentF. Operating EnvironmentG. Transmission Media G. Transmission Media H. Power ConsumptionH. Power Consumption

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A.A. Fault ToleranceFault Tolerance(Reliability)(Reliability)

Sensor nodes may fail or be blocked due to lack of powerSensor nodes may fail or be blocked due to lack of power

have physical damage, or environmental interference.have physical damage, or environmental interference.

The failure of sensor nodes should not affect the overall The failure of sensor nodes should not affect the overall task of the sensor network.task of the sensor network.

This is called RELIABILITY or FAULT TOLERANCE,This is called RELIABILITY or FAULT TOLERANCE,

i.e., ability to sustain sensor networki.e., ability to sustain sensor network functionality without any interruptionfunctionality without any interruption

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Fault Tolerance Fault Tolerance (Reliability) (Ctn’d)(Reliability) (Ctn’d)

Reliability (Fault Tolerance) of a sensor node is modeled: Reliability (Fault Tolerance) of a sensor node is modeled:

i.e., by Poisson distribution, to capture the probability of not i.e., by Poisson distribution, to capture the probability of not having a failure within the time interval (0,t)having a failure within the time interval (0,t)with lambda_k is the failure rate of the sensor node k and with lambda_k is the failure rate of the sensor node k and t is the time period.t is the time period.

G. Hoblos, M. Staroswiecki, and A. Aitouche, “Optimal Design of Fault Tolerant Sensor Networks,” G. Hoblos, M. Staroswiecki, and A. Aitouche, “Optimal Design of Fault Tolerant Sensor Networks,” IEEE International Conference on Control ApplicationsIEEE International Conference on Control Applications, pp. 467-472, Anchorage, AK, September 2000., pp. 467-472, Anchorage, AK, September 2000.

)texp()t(Rkk

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EXAMPLE:EXAMPLE:Suppose: lambda = 3.5 * 10Suppose: lambda = 3.5 * 10-3 -3 t=10sec t=10sec R = 0.97 R = 0.97 t=20sec t=20sec R= 0.93 R= 0.93 t=30sec t=30sec R= 0.9 R= 0.9 t=50sec t=50sec R=0.84 R=0.84

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Reliability (Fault Tolerance) of a broadcast range with Reliability (Fault Tolerance) of a broadcast range with N sensor nodes is calculated from:N sensor nodes is calculated from:

])(1[1)(1

N

kk tRtR

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EXAMPLE:EXAMPLE: How many sensor nodes are needed within a broadcast How many sensor nodes are needed within a broadcast radius (range) to have 99% fault tolerated network?radius (range) to have 99% fault tolerated network?

Assuming all sensors within the radio range have same Assuming all sensors within the radio range have same reliability, prev. equation becomesreliability, prev. equation becomes

NtRtR )](1[1)(

Drop t and substitute f = (1 – R).o.99 = 1 – fN N = 2

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Fault ToleranceFault Tolerance(Reliability) (Ctn’d)(Reliability) (Ctn’d)

REMARK:REMARK:

1. Protocols and algorithms may be designed to 1. Protocols and algorithms may be designed to address the level of fault tolerance required by address the level of fault tolerance required by sensor networks.sensor networks.

2. If the environment has little interference, then 2. If the environment has little interference, then the requirements can be more relaxed.the requirements can be more relaxed.

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Fault ToleranceFault Tolerance(Reliability) (Ctn’d)(Reliability) (Ctn’d)

Examples:Examples:1. 1. HouseHouse to keep track of humidity and temperature to keep track of humidity and temperature levels levels the sensors cannot be damaged easily or the sensors cannot be damaged easily or

interfered interfered by environments by environments low fault tolerance (reliability) low fault tolerance (reliability)

requirement!!!!requirement!!!!2. 2. BattlefieldBattlefield for surveillance the sensed data are critical for surveillance the sensed data are critical

and sensors can be destroyed by enemies and sensors can be destroyed by enemies high high fault tolerancefault tolerance

(reliability) requirement!!!(reliability) requirement!!!

Bottomline: Bottomline: Fault Tolerance (Reliability)Fault Tolerance (Reliability) depends heavily on applications!!!depends heavily on applications!!!

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B. ScalabilityB. Scalability

The number of sensor nodes mThe number of sensor nodes may reach millions in ay reach millions in studyingstudying a field/applicationa field/application

The density of sensor nodes can range from few The density of sensor nodes can range from few to several to several hundreds in a region (cluster) which can be hundreds in a region (cluster) which can be less than 10m in less than 10m in diameter.diameter.

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Scalability Scalability (Ctn’d)(Ctn’d)

The Sensor Node DensityThe Sensor Node Density: : i.e., the number of expected i.e., the number of expected nodes nodes

within the radio range Rwithin the radio range R::

where N is the number of scattered sensor nodeswhere N is the number of scattered sensor nodesin region A and R is the radio transmission range.in region A and R is the radio transmission range.Basically: Basically: is the number of sensor nodes within is the number of sensor nodes within the the transmission radius of each sensor node in region transmission radius of each sensor node in region A.A.

The number of sensor nodes in a region is used to The number of sensor nodes in a region is used to indicate the node density depends on the indicate the node density depends on the application.application.

ARNR /)()( 2

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Network ConfigurationNetwork Configuration

Sensor nodesSensor nodes

Sink nodeSink node

Radio Range RRadio Range R

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ddhop hop = 2R/3= 2R/3

Scalability (Ctn’d)Scalability (Ctn’d)

e.g., R=20m e.g., R=20m 13.33m 13.33m

Assuming that connection establishment Assuming that connection establishment is equally likely with any node within the is equally likely with any node within the radio range radio range RR of the given node, the of the given node, the expectedexpected hop distancehop distance is: is:

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Network ConfigurationNetwork Configuration

Sensor nodesSensor nodes

Sink nodeSink node

Radio Range RRadio Range R

ddhoho

pp

ddnene

ii

ddneinei Expected distance to the nearest neighbor, may or may not be communicating neighbor. Expected distance to the nearest neighbor, may or may not be communicating neighbor.

ddhop hop Expected distance to the next hop, i.e., distance to communicating neighbor. d Expected distance to the next hop, i.e., distance to communicating neighbor. dhophop>=d>=dneinei

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Scalability Scalability (Ctn’d)(Ctn’d)

EXAMPLE:Assume sensor nodes are evenly distributed in the sensor field, determine the node density if 200 sensor nodes are deployed in a 50x50 m2 region where each sensor node has a broadcast radius of 5 m.

Use the eq.mu (R) = (200 * pi * 52 )/(50*50) = 2 * pi

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Scalability Scalability (Cont’d)(Cont’d)

Examples: Examples: 1. Machine Diagnosis Application: 1. Machine Diagnosis Application: less than 300 sensor nodes in a 5 m x 5 m region.less than 300 sensor nodes in a 5 m x 5 m region.

2. Vehicle Tracking Application:2. Vehicle Tracking Application: Around 10 sensor nodes per cluster/region.Around 10 sensor nodes per cluster/region.

3. Home Application: 3. Home Application: 2 dozens or more.2 dozens or more.

4.4. Habitat Monitoring Application:Habitat Monitoring Application: Range from 25 to 100 Range from 25 to 100 nodes/clusternodes/cluster

5. Personal Applications:5. Personal Applications: Ranges from 100s to 1000s, e.g., clothing, eye glasses, shoes, Ranges from 100s to 1000s, e.g., clothing, eye glasses, shoes, watch, jewelry.watch, jewelry.

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C. Production C. Production CostsCosts

Cost of sensors must be low so that theCost of sensors must be low so that the sensor networks can be justified!!!sensor networks can be justified!!! PicoNode: less than $1PicoNode: less than $1 Bluetooth system: around $10,- Bluetooth system: around $10,- THE OBJECTIVE FOR SENSOR COSTS THE OBJECTIVE FOR SENSOR COSTS must be lower than $1!!!!!!!must be lower than $1!!!!!!! Currently: Currently: COTS Dust Motes COTS Dust Motes ranges from $25 to $172ranges from $25 to $172 (STILL VERY EXPENSIVE!!!!)(STILL VERY EXPENSIVE!!!!)

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D. Sensor Node Hardware D. Sensor Node Hardware

A Sensor NodeA Sensor Node

Power UnitPower Unit Power GeneratorPower Generator

Sensor ADCSensor ADCProcessorProcessor

MemoryMemoryTransceiverTransceiver

Location Finding SystemLocation Finding System MobilizerMobilizer SmallSmall Low powerLow power Low bit rateLow bit rate High density High density Low cost (dispensable)Low cost (dispensable) AutonomousAutonomous AdaptiveAdaptive

SENSING UNITPROCESSING UNIT

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E. Sensor Network Topology

Internet, Internet, SatelliteSatellite, etc, etc

SinkSink

SinkSink

TaskTaskManagerManager

Several thousand Several thousand nodesnodes

Nodes are tens of Nodes are tens of feet of each otherfeet of each other

Densities as high as Densities as high as 20 nodes/m20 nodes/m33

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Sensor Network Topology Sensor Network Topology (Ctn’d)(Ctn’d)

Topology maintenance and change:Topology maintenance and change:

Pre-deployment and Deployment Pre-deployment and Deployment Phase Phase

Post Deployment PhasePost Deployment Phase Re-Deployment of Additional NodesRe-Deployment of Additional Nodes

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Pre-deployment and Deployment Pre-deployment and Deployment PhasePhase

Sensor networks can be deployed by:Sensor networks can be deployed by:

Dropping from a planeDropping from a plane Delivering in an artillery shell, rocket or Delivering in an artillery shell, rocket or

missilemissile Throwing by a catapult (from a ship board, Throwing by a catapult (from a ship board,

etc.)etc.) Placing in factoryPlacing in factory Being placed one by one by a human or a Being placed one by one by a human or a

robotrobot

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Initial deployment schemes mustInitial deployment schemes must

reduce installation cost reduce installation cost eliminate the need for any pre-eliminate the need for any pre-

organization and pre-planningorganization and pre-planning increase the flexibility of arrangement increase the flexibility of arrangement promote self organization and fault promote self organization and fault

tolerance.tolerance.

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POST-DEPLOYMENT PHASEPOST-DEPLOYMENT PHASE

After deployment, topology changes are due to After deployment, topology changes are due to change in sensor nodes’change in sensor nodes’

positionposition reachability (due to jamming, noise, moving reachability (due to jamming, noise, moving

obstacles, etc.)obstacles, etc.) available energyavailable energy malfunctioningmalfunctioning

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F. Operating EnvironmentF. Operating Environment

Sensor networks may workSensor networks may work in busy intersectionsin busy intersections in the interior of a large machineryin the interior of a large machinery at the bottom of an oceanat the bottom of an ocean inside a twisterinside a twister at the surface of an oceanat the surface of an ocean in a biologically or chemically contaminated field in in a biologically or chemically contaminated field in

a battlefield beyond the enemy linesa battlefield beyond the enemy lines in a house or a large buildingin a house or a large building in a large warehousein a large warehouse attached to animalsattached to animals attached to fast moving vehiclesattached to fast moving vehicles in a drain or river moving with currentin a drain or river moving with current …………………………………………

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G. TRANSMISSION G. TRANSMISSION MEDIAMEDIA

Radio or Infrared or Optical Media Radio or Infrared or Optical Media

ISM (Industrial, Scientific and Medical ISM (Industrial, Scientific and Medical Bands)Bands) 433 MHz ISM Band in Europe and 915 433 MHz ISM Band in Europe and 915 MHz MHz

as well as 2.4 GHz ISM Bands in North as well as 2.4 GHz ISM Bands in North

America.America.

REASONS:REASONS: Free radio, huge spectrum Free radio, huge spectrum allocation and global availability.allocation and global availability.

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Transmission MediaTransmission Media In a Multihop sensor network nodes are linked by

Wireless medium– Radio Frequency (RF)

Most of the current sensor node HW is based on itDo not need Line of Sight Can hide these sensors

– Infrared (IR)License freeRobust to interferenceCheaper and easier to buildRequire line of sightShort Range Solution

– Optical MediaRequire Line of sight

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H. POWER H. POWER CONSUMPTIONCONSUMPTION

Sensor node has limited power source Sensor node has limited power source (~1.2V).(~1.2V). Sensor node LIFETIME depends on battery Sensor node LIFETIME depends on battery

lifetimelifetime Sensors can be a DATA ORIGINATOR or a Sensors can be a DATA ORIGINATOR or a

DATA ROUTER.DATA ROUTER. Power conservation and power management Power conservation and power management

are important are important POWER AWARE PROTOCOLS POWER AWARE PROTOCOLS

must be developed.must be developed.

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Power Consumption Power Consumption (Ctn’d)(Ctn’d)

• Power consumption in a sensor network can be Power consumption in a sensor network can be divideddivided

into three domains into three domains

CommunicationCommunication Data Processing Data Processing SensingSensing

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Power Consumption Power Consumption (Ctn’d)(Ctn’d)

CommunicationCommunication

A sensorA sensor expends maximum energy expends maximum energy in in data communicationdata communication (both for (both for transmission and reception).transmission and reception).

NOTE:NOTE:For short range communication with low radiation power For short range communication with low radiation power (~0 dbm), transmission and reception power costs are (~0 dbm), transmission and reception power costs are

approximately the same,approximately the same, (e.g., modern low power short (e.g., modern low power short range transceivers consume between 15 and 300 milliwatts range transceivers consume between 15 and 300 milliwatts of power when sending and receiving).of power when sending and receiving).

Transceiver circuitry has both active and start-up Transceiver circuitry has both active and start-up

power consumptionpower consumption

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Power Consumption (Ctn’d)Power Consumption (Ctn’d)

Power consumption for Power consumption for data communicationdata communication (P(Pcc))

PPcc = P = Pte te + P + Prere + P + P0 0

PPte/rete/re is the power consumed in the transmitter/receiver is the power consumed in the transmitter/receiver electronics (including the start-up power)electronics (including the start-up power) PP0 0 is the output transmit power is the output transmit power

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Power Consumption in Power Consumption in Data Data CommunicationCommunication ( (PPCC) (Detailed ) (Detailed Formula)Formula)

)]([)]()([ stonRRonoutstonTTc RRPNTPTTPNP

wherewhere

PPTT is power consumed by is power consumed by transmittertransmitterPPR R is power consumed by is power consumed by receiverreceiverPPoutout is output power of is output power of transmittertransmitterTTonon is time for “transmitter on” is time for “transmitter on”

RRonon is time for “receiver on” is time for “receiver on”

TTstst is start-up time for is start-up time for transmitter transmitter

RRstst is start-up time for receiver is start-up time for receiver

NNTT is the number of times is the number of times

transmitter is switched on pertransmitter is switched on per

unit timeunit time

NNRR is the number of times receiver is the number of times receiver

is switched on per unit timeis switched on per unit time

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Power Consumption in Communication Power Consumption in Communication (Ctn’d)(Ctn’d)

TTonon = L / R = L / R

where L is the packet size and R is the data rate.where L is the packet size and R is the data rate.

Low power radio transceiver has typical Low power radio transceiver has typical PPTT andand

PPRR values around 20 dBm and values around 20 dBm and PPoutout close to 0 dBm.close to 0 dBm.

Note that PicoRadio aims at a Note that PicoRadio aims at a PPcc value of –20 dBm. value of –20 dBm.

67IFA’2004

Power Consumption in Communication Power Consumption in Communication (Ctn’d)(Ctn’d)

START-UP POWER: REMARK:START-UP POWER: REMARK:

Sensors communicate in short data packetsSensors communicate in short data packets Start-up power starts dominating as packet Start-up power starts dominating as packet

size is reduced size is reduced It is inefficient to turn the transceiver ON and OFF It is inefficient to turn the transceiver ON and OFF

because a large amount of power is spent inbecause a large amount of power is spent in

turning the transceiver back ON each time.turning the transceiver back ON each time.

68IFA’2004

Power Consumption in Data Processing Power Consumption in Data Processing (Ctn’d)(Ctn’d)

This is much less than in communication.This is much less than in communication.

EXAMPLE:EXAMPLE:

Energy cost of transmitting 1 KB a distance of Energy cost of transmitting 1 KB a distance of

100 m is approx. equal to executing 3 Million 100 m is approx. equal to executing 3 Million

instructions by a 100 million instructions per instructions by a 100 million instructions per

second processor.second processor.

Local data processing is crucial in minimizing Local data processing is crucial in minimizing

power consumption in a multi-hop networkpower consumption in a multi-hop network

69IFA’2004

Power Consumption in Data Processing Power Consumption in Data Processing (Ctn’d)(Ctn’d)

Complementary Metal Oxide SemiconductorComplementary Metal Oxide Semiconductor

(CMOS) technology used in designing processors (CMOS) technology used in designing processors

has energy limitationshas energy limitations

Dynamic Voltage Scaling and other Low power Dynamic Voltage Scaling and other Low power

CPU organization strategies need to be explored CPU organization strategies need to be explored

70IFA’2004

Power Consumption in Data Power Consumption in Data Processing (Processing (PPpp))

}'/exp{2Tddoddddp VnVIVfVCP

WhereWhere

C is the total switching capacitance; VC is the total switching capacitance; Vdddd is the voltage swing; is the voltage swing;

F is the switching frequencyF is the switching frequency

The second term indicates the power loss due to leakage currents.The second term indicates the power loss due to leakage currents.

71IFA’2004

Power Consumption Power Consumption (Ctn’d)(Ctn’d)(Another Simple Energy Model)(Another Simple Energy Model)

Assuming a sensor node is only operating in transmit and receive modes with the following assumptions: Energy to run circuitry: E_{elec} = 50 nJ/bit Energy for radio transmission: E_{amp} = 100 pJ/bit/m2

Energy for sending k bits over distance d E_Tx (k,D) = E_{elec} * k + E_{amp} * k * d2

Energy for receiving k bits: E_Rx (k,D) = E_{elec} * k

72IFA’2004

ENERGY MODELENERGY MODEL

73IFA’2004

Power Consumption Power Consumption (Ctn’d) (Ctn’d) (Another Simple Energy (Another Simple Energy Model)Model)

What is the energy consumption if 1 Mbit of information is transferred from the source to the sink where the source and sink areseparated by 100 meters and the broadcast radius of each node is 5 meters?Assume the neighbor nodes are overhearing each other’s broadcast.

74IFA’2004

Power Consumption Power Consumption (Ctn’d) (Ctn’d) (Another Simple Energy (Another Simple Energy Model)Model)

E_Rx (k,D) = E_{elec} * k

100 meters / 5 meters = 20 pairs of transmitting and receiving nodes (one node transmits and one node receives)

E_Tx (k,D) = E_{elec} * k + E_{amp} * k * D2 E_{Tx} = 50 nJ/bit . 106 + 100 pJ/bit/m2 . 106 . 52 = = 0.5J + 0.0025 J = 0.0525 J

E_{Rx} = 0.05 J

E_{pair} = E_{Tx} + E_{Rx} = 0.1025JE_{T} = 20 . E_{pair} = 20. 0.1025J = 2.050 J

75IFA’2004

Power Consumption in Sensing Power Consumption in Sensing (Ctn’d)(Ctn’d)

Depends onDepends on ApplicationApplication Nature of sensing: Sporadic or ConstantNature of sensing: Sporadic or Constant Detection complexity Detection complexity Ambient noise levelsAmbient noise levels

76IFA’2004

Sensor Networks Sensor Networks Communication Communication ArchitectureArchitecture

Collect dataCollect data Route data back to the sinkRoute data back to the sink


SinkSink


AABB

CC

DD

EEFF

Sensor NodeSensor Node

Sensor FieldSensor Field

77IFA’2004

Sensor Networks Sensor Networks Communication ArchitectureCommunication Architecture

Application LayerApplication Layer

Transport LayerTransport Layer

Network LayerNetwork Layer

Data Link LayerData Link Layer

Physical LayerPhysical Layer

Pow

er M

anagem

ent

Pow

er M

anagem

ent

Pla

ne

Pla

ne

Mobility

Managem

ent

Mobility

Managem

ent

Pla

ne

Pla

ne

Task M

anagem

ent P

lane

Task M

anagem

ent P

lane

Used by sink and all sensor nodesUsed by sink and all sensor nodes Combines power and routing awarenessCombines power and routing awareness Integrates data with networking protocolsIntegrates data with networking protocols Communicates power efficiently throughCommunicates power efficiently through wireless medium andwireless medium and Promotes cooperative efforts.Promotes cooperative efforts.

78IFA’2004

WHY CAN’T AD-HOC NETWORK WHY CAN’T AD-HOC NETWORK PROTOCOLS BE USED HERE?PROTOCOLS BE USED HERE?

Number of sensor nodes can be several Number of sensor nodes can be several orders of magnitude higherorders of magnitude higher

Sensor nodes are Sensor nodes are densely deployeddensely deployed and are and are prone to failuresprone to failures

The topology of a sensor network changes The topology of a sensor network changes very frequently due to very frequently due to node mobility and node mobility and node failurenode failure

Sensor nodes are limited in Sensor nodes are limited in power, power, computational capacities, and memorycomputational capacities, and memory

May not have global ID like IP address.May not have global ID like IP address. Need tight integration with sensing tasks.Need tight integration with sensing tasks.

79IFA’2004

5. APPLICATON LAYER 5. APPLICATON LAYER FRAMEWORKFRAMEWORK

Sensor Network Management Protocol Sensor Network Management Protocol (SMP)(SMP) Task Assignment and Data Advertisement Task Assignment and Data Advertisement ProtocolProtocol Sensor Query and Data Dissemination Sensor Query and Data Dissemination ProtocolProtocol

80IFA’2004

sensor node

gateway (gnode)

wireless link


Users

Server(Database)


Sensor Network Topology

81IFA’2004

APPLICATON LAYERAPPLICATON LAYERSMP: Sensor Managament SMP: Sensor Managament ProtocolProtocolSystem Administrators interact with Sensors using SMP.System Administrators interact with Sensors using SMP.

TASKS:TASKS: Moving the sensor nodesMoving the sensor nodes Turning sensors on and offTurning sensors on and off Querying the sensor network configuration and the status Querying the sensor network configuration and the status

of of nodes and re-configuring the sensor networknodes and re-configuring the sensor network

Authentication, key distribution and security in dataAuthentication, key distribution and security in data communicationcommunication Time-synchronization of the sensor nodesTime-synchronization of the sensor nodes Exchanging data related to the location finding algorithmsExchanging data related to the location finding algorithms Introducing the rules related to data aggregation, Introducing the rules related to data aggregation, attribute-based naming and clustering to the sensor attribute-based naming and clustering to the sensor

nodesnodes

82IFA’2004

APPLICATON LAYERAPPLICATON LAYER(Query Processing)(Query Processing)

Users can request data from the network-> Users can request data from the network-> Efficient Query Efficient Query ProcessingProcessing

User Query Types:User Query Types:

1. 1. HISTORICAL QUERIES:HISTORICAL QUERIES:

Used for analysis of historical data stored in a storage area Used for analysis of historical data stored in a storage area (PC),(PC),

e.g., what was the temperature 2 hours back in the NW e.g., what was the temperature 2 hours back in the NW quadrant.quadrant.

2. ONE TIME QUERIES: 2. ONE TIME QUERIES:

Gives a snapshot of the network, Gives a snapshot of the network, e.g., what is the current e.g., what is the current temperature in the NW quadrant.temperature in the NW quadrant.

3. PERSISTANT QUERIES:3. PERSISTANT QUERIES:

Used to monitor the network over a time interval with Used to monitor the network over a time interval with respect to some parameters, respect to some parameters, e.g., report the temperature e.g., report the temperature for the next 2 hours.for the next 2 hours.

83IFA’2004

QUERYINGQUERYING– ContinuousContinuous

Sensors communicate their data continuously at a prespecified Sensors communicate their data continuously at a prespecified rate. rate.

– Event DrivenEvent Driven The sensors report information only when the event of interest The sensors report information only when the event of interest

occurs.occurs.

– Observer Initiated (request-reply):Observer Initiated (request-reply): Sensors only report their results in response to an explicit request Sensors only report their results in response to an explicit request

from the observer. from the observer.

Aggregate queries

Complex queries

Queries for replicated data

– HybridHybrid

84IFA’2004

APPLICATON LAYERAPPLICATON LAYER

Sensor Query and Tasking Language (SQTL):Sensor Query and Tasking Language (SQTL):(C-C Shen, et.al., “Sensor Information Networking Architecture and Applications”, (C-C Shen, et.al., “Sensor Information Networking Architecture and Applications”, IEEE Personal Communications MagazineIEEE Personal Communications Magazine, pp. 52-59, August 2001.), pp. 52-59, August 2001.)

SQTL is a procedural scripting language.SQTL is a procedural scripting language. It provides interfaces to It provides interfaces to access sensor hardwareaccess sensor hardware: :

- getTemperature, turnOn- getTemperature, turnOn

for for location awarenesslocation awareness::

- isNeighbor, getPosition- isNeighbor, getPosition

and for and for communicationcommunication::

- tell, execute.- tell, execute.

85IFA’2004

APPLICATON LAYERAPPLICATON LAYER

Sensor Query and Tasking Language (SQTL):Sensor Query and Tasking Language (SQTL):

By using the By using the uponupon command, a programmer can command, a programmer can create an event handling block for three types of create an event handling block for three types of events:events:- - Events generated when a message is received by a sensor Events generated when a message is received by a sensor node,node,

- Events triggered periodically,- Events triggered periodically,

- Events caused by the expiration of a timer.- Events caused by the expiration of a timer.

These types of events are defined by SQTL These types of events are defined by SQTL keywordskeywords receivereceive, , everyevery and and expireexpire, respectively., respectively.

87IFA’2004

Data Centric QueryData Centric Query

Attribute-based Attribute-based naming naming architecturearchitecture

Data centric Data centric protocolprotocol

Observer sends a Observer sends a query and gets query and gets the response from the response from valid sensor nodevalid sensor node

No global IDNo global ID

88IFA’2004

APPLICATON LAYER APPLICATON LAYER Task Assignment and Data Advertisement Task Assignment and Data Advertisement ProtocolProtocol

INTEREST DISSEMINATIONINTEREST DISSEMINATION * * Users send their interest to a sensor Users send their interest to a sensor node, node, a subset of the nodes or the entire a subset of the nodes or the entire network.network. * This interest may be about a certain * This interest may be about a certain attribute attribute of the sensor field or a triggering event.of the sensor field or a triggering event.

ADVERTISEMENT OF AVAILABLE DATAADVERTISEMENT OF AVAILABLE DATA * * Sensor nodes advertise the available Sensor nodes advertise the available data to data to the users and the users query the data the users and the users query the data which which they are interested in.they are interested in.

89IFA’2004

APPLICATON LAYERAPPLICATON LAYERSensor Query and Data Dissemination Sensor Query and Data Dissemination ProtocolProtocol

Provides user applicatons with interfaces to issue queries, respond to queries and collect incoming replies.These queries are not issued to particular nodes, instead

ATTRIBUTE BASED NAMING (QUERY) “The locations of the nodes that sense temperature higher than 70F”LOCATION BASED NAMING (QUERY) “Temperatures read by the nodes in region A”

90IFA’2004

Interest DisseminationInterest Dissemination

SinkSink

Query:Query:

Sensor nodes that read >70Sensor nodes that read >70ooF F temperaturetemperature

7171

6868

6868

6969

7171

7575

7171

6767

7171

6666

Interest dissemination is performed to assign the sensing tasks to the sensor nodes. Either sinks broadcast the interest or sensor nodes broadcast an advertisement for the available data and wait for a request from the sinks.

91IFA’2004

Data Aggregation (Data Data Aggregation (Data Fusion)Fusion)

Query:Query:

Sensor nodes that read >70Sensor nodes that read >70ooF F temperaturetemperature

7171

7575

SinkSink

6868

6868

6969

71717171

6767

7171

6666

The sink asks the sensor nodes to report certain conditions. Data coming from multiple sensor nodes are aggregated.

92IFA’2004

Location Awareness Location Awareness (Attribute Based Naming)(Attribute Based Naming)

SinkSink

Query:Query:

Temperatures read by the nodes Temperatures read by the nodes in Region A in Region A

7171

6868

6868

6969

7171

7575

7171

6767

7171

6666

Region ARegion A

Region BRegion B

Region CRegion C

Query an Attribute of the sensor field

Important for broadcasting, multicasting, geocasting and anycasting

93IFA’2004

APPLICATON LAYER RESEARCH APPLICATON LAYER RESEARCH NEEDSNEEDS

Sensor Network Management ProtocolSensor Network Management Protocol Task Assignment and Data Advertisement Task Assignment and Data Advertisement ProtocolProtocol Sensor Query and Data Dissemination Sensor Query and Data Dissemination ProtocolProtocol Sophisticated GUI Sophisticated GUI

(Graphical User Interface) Tool(Graphical User Interface) Tool

94IFA’2004

NETWORK LAYER NETWORK LAYER (ROUTING(ROUTING BASIC KNOWLEDGE) BASIC KNOWLEDGE)

The constraints to calculate the routes:The constraints to calculate the routes:1. Additive Metrics: 1. Additive Metrics: Delay, hop count, distance, assigned costs (sysadmin Delay, hop count, distance, assigned costs (sysadmin preference), preference), average queue length...average queue length...

2. Bottleneck Metrics: 2. Bottleneck Metrics: Bandwidth, residual capacity and other bandwidth Bandwidth, residual capacity and other bandwidth related metrics. related metrics.

REMARK:REMARK:All routing algorithms are based on the same principle used as in All routing algorithms are based on the same principle used as in Dijkstra's, Dijkstra's, which is used to find the which is used to find the minimum cost pathminimum cost path from source to from source to destination.destination.Dikstra and Bellman solve the SHORTEST PATH PROBLEM…Dikstra and Bellman solve the SHORTEST PATH PROBLEM…RIP (Distant Vector Algorithm) -> Bellman/Ford AlgorithmRIP (Distant Vector Algorithm) -> Bellman/Ford AlgorithmOSPF (Open Shortest Path Algorithm) OSPF (Open Shortest Path Algorithm) Dikstra Algorithm Dikstra Algorithm

95IFA’2004

Routing Algorithms Constraints Regarding Power Efficiency (Energy Efficient Routing)

SinkSink

E (PA=1)E (PA=1) F (PA=4)F (PA=4)

D (PA=3)D (PA=3)

A (PA=2)A (PA=2)B (PA=2)B (PA=2)

C (PA=2)C (PA=2)

TT

Route 1: Sink-A-B-T (PA=4)Route 1: Sink-A-B-T (PA=4)Route 2: Sink-A-B-C-T (PA=6)Route 2: Sink-A-B-C-T (PA=6)Route 3: Sink-D-T (PA=3)Route 3: Sink-D-T (PA=3)Route 4: Sink-E-F-T (PA=5)Route 4: Sink-E-F-T (PA=5)

Maximum power available (PA) routeMaximum power available (PA) route Minimum hop routeMinimum hop route Minimum energy routeMinimum energy route Maximum minimum PA node Maximum minimum PA node routeroute (Route along which the (Route along which the minimum PA is larger than the minimum PA is larger than the minimum PAs of the other routesminimum PAs of the other routes is preferred, e.g., Route 3 is the is preferred, e.g., Route 3 is the most efficient; Route 1 is the most efficient; Route 1 is the second).second).

96IFA’2004

Global (Unique) addresses, local addresses.

Unique node addresses cannot be used in many sensor networks

- sheer number of nodes- energy constraints- data centric approach

Node addressing is needed for- node management- sensor management- querying- data aggregation and fusion- service discovery- routing

Why can’t we use conventional routing algorithms here?

97IFA’2004

Addressing in Sensor Networks

1. Attribute based naming and data centric routing

2. Spatial addressing (location awareness)

3. Address reuse

4. Query mapping.

98IFA’2004

NETWORK LAYER NETWORK LAYER (ROUTING for SENSOR NETWORKS)(ROUTING for SENSOR NETWORKS)

Important considerations:Important considerations:

Sensor networks are mostly data Sensor networks are mostly data centriccentric

An ideal sensor network has attribute An ideal sensor network has attribute based addressing and location based addressing and location awarenessawareness

Data aggregation is useful unless it Data aggregation is useful unless it does not hinder collaborative effortdoes not hinder collaborative effort

Power efficiency is always a key factorPower efficiency is always a key factor

99IFA’2004

Some ConceptsSome Concepts

Data-Centric– Node doesn't need an identity

What is the temp at node #27 ?

– Data is named by attributesWhere are the nodes whose temp recently exceeded

30 degrees ? How many pedestrians do you observe in region X? How many pedestrians do you observe in region X? Tell me in what direction that vehicle in region Y is Tell me in what direction that vehicle in region Y is

moving?moving?

Application-Specific– Nodes can perform application specific

data aggregation, caching and forwarding

100

IFA’2004

Attribute Based NamingData-Centric RoutingData-Centric Routing

SinkSink

Query:Query:

Nodes that read >70Nodes that read >70ooF F temperaturetemperature

7171

6868

6868

6969

7171

7575

7171

6767

7171

6666

Interest dissemination is performed to assign the sensing tasks to the sensor nodes. Either sinks broadcast the interest or sensor nodes broadcast an advertisement for the available data and wait for a request from the sinks.

101

IFA’2004

Data Centric Data Centric RoutingRouting

Attribute-based Attribute-based naming naming architecturearchitecture

Data centric Data centric protocolprotocol

Observer sends a Observer sends a query and gets query and gets the response from the response from valid sensor nodevalid sensor node

No global IDNo global ID

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IFA’2004

Data Aggregation (Data Data Aggregation (Data Fusion)Fusion)

Query:Query:

Nodes that read >70Nodes that read >70ooF F temperaturetemperature

7171

7575

SinkSink

6868

6868

6969

71717171

6767

7171

6666

To solve the implosion and overlap problems in data centric routing. Sensor network is perceived as a reverse multicast tree. The sink asks the sensor nodes to report certain conditions. Data coming from multiple sensor nodes are aggregated.

103

IFA’2004

Data AggregationData Aggregation

Categorization of Data Aggregation Schemes:

1. Temporal or spatial aggregation

2. Snapshot or periodical aggregation

3. Centralized or distributed aggregation

4. Early or late aggregation

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IFA’2004

Polygonal (Spatial) Polygonal (Spatial) AddressingAddressing Location AwarenessLocation Awareness

SinkSink

Query:Query:

Temperatures read by the nodes Temperatures read by the nodes in Region A in Region A

7171

6868

6868

6969

7171

7575

7171

6767

7171

6666

Region ARegion A

Region BRegion B

Region CRegion C

Important for broadcasting, multicasting, geocasting and anycasting

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Taxonomy of Routing Taxonomy of Routing ProtocolsProtocols for Sensor Networksfor Sensor NetworksCategorization of Routing Protocols for Wireless Sensor

Networks:(K. Akkaya, M. Younis, “A Survey on Routing Protocols for Wireless Sensor Networks,” Elsevier AdHoc (K. Akkaya, M. Younis, “A Survey on Routing Protocols for Wireless Sensor Networks,” Elsevier AdHoc Networks, 2004)Networks, 2004)

1. Data Centric Protocols Flooding, Gossiping, SPIN, SAR (Sequential Assignment Routing) , Directed Diffusion, Rumor Routing, Gradient Based Routing, Constrained Anisotropic Diffused Routing, COUGAR, ACQUIRE

2. Hierarchical LEACH, TEEN (Threshold Sensitive Energy Efficient Sensor Network

Protocol), APTEEN, PEGASIS, Energy Aware Scheme

3. Location Based MECN, SMECN (Small Minimum Energy Com Netw), GAF (Geographic Adaptive Fidelity), GEAR

106

IFA’2004

Conventional Conventional ApproachApproachFLOODINGFLOODING

B

D E

FG

C

A

Broadcast data to all neighbor nodesBroadcast data to all neighbor nodes

107

IFA’2004

ROUTING ALGORITHMSROUTING ALGORITHMSGossipingGossiping

GOSSIPING:Sends data to one randomly selected neighbor.

Example:Example:

108

IFA’2004

Problems ofFlooding and Gossiping

PROBLEMS:PROBLEMS:

Although these techniques are simple and Although these techniques are simple and reactive, they have some disadvantages reactive, they have some disadvantages including: including:

* * Implosion (NOTE: Gossiping avoids this by selecting only one node; but this causes delays to propagate the data through the network)

* Overlap * Resource Blindness * Power (Energy) Inefficient

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IFA’2004

ProblemsProblems

A B

C (r,s)(q,r)

q s

Data OverlapData OverlapImplosionImplosion

A

B C

D

(a)

(a)

(a)

(a)

Resource BlindnessResource Blindness

No knowledge about the available power of resourcesNo knowledge about the available power of resources

r

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IFA’2004

GossipingGossiping

Uses randomization to save energyUses randomization to save energySelects a single node at random and sends the Selects a single node at random and sends the data to itdata to it

Avoids implosionsAvoids implosions Distributes information slowlyDistributes information slowly Energy dissipates slowlyEnergy dissipates slowly

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IFA’2004

The Optimum The Optimum ProtocolProtocol

B

D E

FG

C

A““Ideal”Ideal”

– Shortest-path routesShortest-path routes– Avoids overlapAvoids overlap– Minimum energyMinimum energy– Need global topology Need global topology

informationinformation

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IFA’2004

Ideal DisseminationIdeal Dissemination

No implosion No implosion and no and no overlapoverlap

Disseminate Disseminate in shortest in shortest possible timepossible time

113

IFA’2004

SPIN: Sensor Protocol for Information via Negotiation(W.R. Heinzelman, J. Kulik, and H. Balakrishan, “Adaptive Protocols for (W.R. Heinzelman, J. Kulik, and H. Balakrishan, “Adaptive Protocols for Information Dissemination in Wireless Sensor Networks”,Information Dissemination in Wireless Sensor Networks”, Proc. ACM MobiCom’99Proc. ACM MobiCom’99, pp. 174-185, 1999 ), pp. 174-185, 1999 )

Two basic ideas:Two basic ideas: Sensors communicate with each other Sensors communicate with each other

about the data that they already have about the data that they already have and the data they still need to obtainand the data they still need to obtain

to conserve energy and operate efficientlyto conserve energy and operate efficiently exchanging data exchanging data aboutabout sensor data may be sensor data may be

cheapcheap

Sensors must monitor and adapt to Sensors must monitor and adapt to changeschanges

in their own energy resourcesin their own energy resources

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IFA’2004

SPINSPIN

- - Uses three types of messages: ADV, REQ, and DATA.- When a sensor node has something new, it broadcasts- an advertisement (ADV) packet that contains the new - data, i.e., the meta data.- Interested nodes send a request (REQ) packet. - Data is sent to the nodes that request by DATA - packets.- This will be repeated until all nodes will get a copy.

115

IFA’2004

SPINSPIN

Good for disseminating information to all sensor nodes.Good for disseminating information to all sensor nodes. SPIN is based on data-centric routing where the sensors SPIN is based on data-centric routing where the sensors broadcast an broadcast an advertisement for the available data and wait for a request from advertisement for the available data and wait for a request from interested sinksinterested sinks

1. ADV1. ADV2. REQ2. REQ3. DATA3. DATA

1.1.

2.2.

3.3.

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IFA’2004

SPINSPIN

ADV- advertise/name ADV- advertise/name datadata

REQ- request specific REQ- request specific datadata

DATA- requested dataDATA- requested data

A B

ADV

A B

REQ

A B

DATA

Meta-Data <=> Data Naming

117

IFA’2004

SPINSPIN

ADVADVREQREQ

DATADATA

ADVADVREQREQDATADATA

118

IFA’2004

B

A

EXAMPLEEXAMPLE

Sensor A sends meta-data to neighborSensor A sends meta-data to neighbor

ADV

119

IFA’2004

Sensor B requests data from Sensor ASensor B requests data from Sensor A

REQB

A

120

IFA’2004

Sensor A sends data to Sensor BSensor A sends data to Sensor B

DATA

B

A

121

IFA’2004

Sensor B aggregates data and sends meta-Sensor B aggregates data and sends meta-data for A and B to neighborsdata for A and B to neighbors

ADV

AD

VADV

ADV

AD

V ADV

B

A

122

IFA’2004

All but 1 neighbor request dataAll but 1 neighbor request data

REQ

RE

Q

REQ

RE

Q

REQB

A

123

IFA’2004

Sensor B sends requested data to Sensor B sends requested data to neighborsneighbors

DATA

DA

TA

DATA

DA

TA

DATA

B

A

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IFA’2004

SPIN-1 ProtocolSPIN-1 Protocol

SPIN-1SPIN-1– 3-stage handshake protocol3-stage handshake protocol– AdvantagesAdvantages

SimpleSimpleImplosion avoidanceImplosion avoidance

DisadvantagesDisadvantages

* Cannot isolate the nodes that do not want to receive the * Cannot isolate the nodes that do not want to receive the information.information. * Consume unnecessary power.* Consume unnecessary power.

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SPIN-2SPIN-2

Spin-2Spin-2– SPIN-1 + low-energy thresholdSPIN-1 + low-energy threshold– Modifies behavior based on Modifies behavior based on

current energy resourcescurrent energy resources

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IFA’2004

SPIN-2SPIN-2

Adds a simple energy conservation Adds a simple energy conservation heuristicheuristic

When energy is plentiful, SPIN-2 When energy is plentiful, SPIN-2 behaves like SPIN-1behaves like SPIN-1

When energy approaches a low-energy When energy approaches a low-energy threshold, SPIN-2 node reduces its threshold, SPIN-2 node reduces its participation in the protocol participation in the protocol (DORMANT)(DORMANT)

participate in a stage of protocol only if the nodeparticipate in a stage of protocol only if the node

believes that it can complete all the remaining believes that it can complete all the remaining stagesstages

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IFA’2004

SPIN Algorithm SPIN Algorithm VariantsVariants

Zzz...

FloodingFlooding -- Each node floods new data -- Each node floods new data to all of its neighbors. to all of its neighbors.

GossipingGossiping -- Each node floods all its -- Each node floods all its data to one, randomly selected data to one, randomly selected neighbor.neighbor.

NegotiatingNegotiating -- nodes decide what data -- nodes decide what data to send based on meta-data to send based on meta-data advertisements. SPIN-1advertisements. SPIN-1

SleepingSleeping -- Same as negotiating, -- Same as negotiating, except that nodes stop sending except that nodes stop sending messages when energy is lowmessages when energy is low. SPIN-2. SPIN-2

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CONCLUSIONSCONCLUSIONS

Flooding converges firstFlooding converges first– No delaysNo delays

SPIN-1 SPIN-1 – Reduces energy by 70%Reduces energy by 70%– No redundant DATA messagesNo redundant DATA messages

SPIN-2 distributes SPIN-2 distributes – 10% more data per unit energy than 10% more data per unit energy than

SPIN-1SPIN-1– 60% more data per unit energy than 60% more data per unit energy than

floodingflooding

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ROUTING ALGORITHMROUTING ALGORITHM(DIRECTED DIFFUSION)(DIRECTED DIFFUSION)

(C. Intanagonwiwat, R. Gowindan and D. Estrin, “Directed Diffusion: A Scalable and Robust (C. Intanagonwiwat, R. Gowindan and D. Estrin, “Directed Diffusion: A Scalable and Robust

Communication Paradigm for Sensor Networks”, Communication Paradigm for Sensor Networks”, Proc. ACM MobiCom’00Proc. ACM MobiCom’00, pp. 56-67, 2000.), pp. 56-67, 2000.)

- This is a DATA CENTRIC ROUTING scheme!!!!This is a DATA CENTRIC ROUTING scheme!!!!- The idea aims at diffusing data through sensor nodes by The idea aims at diffusing data through sensor nodes by using using

a a naming schemenaming scheme for the data. for the data.- The main reason behind this is to get rid off The main reason behind this is to get rid off unnecessaryunnecessary

operation of routing schemes tooperation of routing schemes to save save EnergyEnergy..

Also Also RobustnessRobustness and and ScalingScaling requirements need to be requirements need to be considered.considered.

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Data CentricData Centric

Data-CentricData-Centric– Sensor node does not need an identitySensor node does not need an identity

What is the temp at node #27 ?What is the temp at node #27 ?

– Data is named by attributesData is named by attributesWhere are the nodes whose temp recently exceeded Where are the nodes whose temp recently exceeded

30 degrees ?30 degrees ? How many pedestrians do you observe in region X? How many pedestrians do you observe in region X? Tell me in what direction that vehicle in region Y is Tell me in what direction that vehicle in region Y is

moving?moving?

Application-SpecificApplication-Specific– Nodes can perform application specific Nodes can perform application specific

data aggregation, caching and forwardingdata aggregation, caching and forwarding

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DIRECTED DIFFUSIONDIRECTED DIFFUSION

* * DD is data centric, i.e., data generated by sensor nodes is NAMED by ATTRIBUTE-VALUE pairs. * A sensor node requests data by sending interests for named data. * Data matching the interest is then drawn down towards that node. * Intermediate sensor nodes can cache or transform data and may direct interests based on previously cached data.

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* * An arbitrary sensor node (usually the SINK) uses attribute-value pairs (interests) for the data and queries the sensors in an on-demand basis. * In order to create a query, an interest is defined using a list of attribute-value pairs such as name of objects, interval, duration, geographical area, etc. * The sink queries the sensors in an on-demand basis using these pairs. * The sink broadcasts this interest to sensor nodes. * Each sensor node then stores this interest entry in its cache. * The interests in the caches are then used to compare the received data with the values in the interests.-

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Example: * The users query is transformed into an interest that is diffused towards nodes in regions X or Y.

* When a node in that region receives an interest it activates its sensors which begin collecting information about pedestrians.

* When the sensors report the presence of pedestrians this returns along the reverse path of interest propagation.

* Intermediate nodes might aggregate the data, e.g., more accurately pinpoint the pedestrians location by combining reports from several sensors.

* An important feature of directed diffusion is that interest and data propagation and aggregation are determined by localized interactions (message changes between neighbors or nodes within some vicinity)

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Data is named using attribute-value pairs, e.g.,Data is named using attribute-value pairs, e.g.,

Example: (Animal Tracking Task)Example: (Animal Tracking Task)

TypeType = four legged animal = four legged animal (detect animal location)(detect animal location)

IntervalInterval = 20 ms = 20 ms (send back events every 20 ms)(send back events every 20 ms)

DurationDuration = 10 seconds = 10 seconds (.. for the next 10 seconds)(.. for the next 10 seconds)

Rec Rec = [-100,100,200,00] = [-100,100,200,00] (from sensors within the rectangle)(from sensors within the rectangle)

The task description specifies an interest for data matching for The task description specifies an interest for data matching for attributesattributes

called INTEREST.called INTEREST.

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The data sent in response to interests are also named similarly.The data sent in response to interests are also named similarly.

Example: Example:

Sensor detecting the animal generates the following data:Sensor detecting the animal generates the following data:

Type Type – four legged animal – four legged animal (type of animal seen)(type of animal seen)

InstanceInstance= elephant = elephant (instance of this type)(instance of this type)

LocatonLocaton = (125,220) = (125,220) (node location)(node location)

IntensityIntensity = 0.6 = 0.6 (signal amplitude measure)(signal amplitude measure)

ConfidenceConfidence = 085 = 085 (confidence in the match)(confidence in the match)

TimestampTimestamp= 01:20:40 = 01:20:40 (event generation time)(event generation time)

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Directed DiffusionDirected Diffusion

Interest PropagationInterest Propagation

SourceSource SinkSink

Gradient SetupGradient SetupData DeliveryData Delivery

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INTERESTS and GRADIENTSINTERESTS and GRADIENTS

The named task description constitutes an INTEREST.The named task description constitutes an INTEREST.

An interest is injected into the network at some (arbitrary) node in the An interest is injected into the network at some (arbitrary) node in the network.network.

Suppose it is SINK.Suppose it is SINK.

INTERESTS are diffused through the sensor network.INTERESTS are diffused through the sensor network.

Example:Example:• A task with a specified A task with a specified typetype and and rectrect, a duration of 10 minutes and an , a duration of 10 minutes and an

interval of 10 ms is initiated by a sensor node in the network.interval of 10 ms is initiated by a sensor node in the network.

* The interval parameter specifies an event data rate.* The interval parameter specifies an event data rate.

* Here the specified data rate is 100 events per second.* Here the specified data rate is 100 events per second.

* The sink node records the task, the task state is purged from the node * The sink node records the task, the task state is purged from the node

after the time indicated by the duration attribute.after the time indicated by the duration attribute.

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* For each active task, SINK periodically broadcasts an interest * For each active task, SINK periodically broadcasts an interest message message

to each of its neighbors.to each of its neighbors.

* This initial interest contains the specified* This initial interest contains the specified rect rect and and duration duration attributesattributes, ,

but contains a much larger interval attribute.but contains a much larger interval attribute.

• Every node maintains an interest cache. Every node maintains an interest cache.

* Each item in the cache corresponds to a distinct interest.* Each item in the cache corresponds to a distinct interest.

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DIRECTED DIFFUSIONDIRECTED DIFFUSIONAn ENTRY in the interest cache has several fields:An ENTRY in the interest cache has several fields:

* A * A TIMESTAMP fieldTIMESTAMP field (timestamp of the last received matching (timestamp of the last received matching

interest) and several interest) and several GRADIENT fieldsGRADIENT fields up to one per neighbor. up to one per neighbor.

* A GRADIENT is a relay link to a neighbor from which the interest * A GRADIENT is a relay link to a neighbor from which the interest

was received.was received.

-* Each GRADIENT contains * Each GRADIENT contains - A data rate field A data rate field (requested by the specific neighbor)(requested by the specific neighbor)

A duration field A duration field (approximate lifetime of the interest)(approximate lifetime of the interest)

REMARK: Hence by utilizing interest and gradients, paths are REMARK: Hence by utilizing interest and gradients, paths are

established between sink and sources, i.e., sensors.established between sink and sources, i.e., sensors.

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When a node receives an interest it checks to see of the interest When a node receives an interest it checks to see of the interest existsexists

in the cache.in the cache.

If no matching exists, the node creates a new entry.If no matching exists, the node creates a new entry.

If there exists an entry, but no gradient for the sender of the interest,If there exists an entry, but no gradient for the sender of the interest,

the node adds a gradient with the specified value.the node adds a gradient with the specified value.

It also updates the entry’s timestamp and duration fields.It also updates the entry’s timestamp and duration fields.

Finally, if both an entry and gradient exist, the node simplyFinally, if both an entry and gradient exist, the node simply

updates the timestamp and duration fields.updates the timestamp and duration fields.

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Directed DiffusionDirected Diffusion

FeaturesFeatures

Sink sends interest, i.e., task descriptor, to all sensor nodes.Sink sends interest, i.e., task descriptor, to all sensor nodes. Interest is named by assigning attribute-value pairs.Interest is named by assigning attribute-value pairs.

sinksink

sourcesource

sinksink

sourcesource

sinksink

sourcesource

Interest PropagationInterest Propagation Gradient SetupGradient Setup Data DeliveryData Delivery

DrawbacksDrawbacks

Cannot change interest unless a new interest is broadcast.Cannot change interest unless a new interest is broadcast.

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LEACHLEACH

Low Energy Adaptive Clustering Hierarchy Low Energy Adaptive Clustering Hierarchy (LEACH)(LEACH)(W. R. Heinzelman, A. Chandrakasan, and H. Balakrishnan, “Energy-Efficient (W. R. Heinzelman, A. Chandrakasan, and H. Balakrishnan, “Energy-Efficient Communication Protocol for Wireless Microsensor Networks,'' Communication Protocol for Wireless Microsensor Networks,'' IEEE IEEE Proceedings of the Hawaii International Conference on System SciencesProceedings of the Hawaii International Conference on System Sciences, pp. , pp. 1-10, January, 2000.)1-10, January, 2000.)

- * * LEACH is a clustering based protocol which minimizes LEACH is a clustering based protocol which minimizes energy dissipation energy dissipation

in sensor networks.in sensor networks.

Idea:Idea:

* Randomly select sensor nodes as cluster heads, so the * Randomly select sensor nodes as cluster heads, so the high energyhigh energy

dissipation in communicating with the base station is dissipation in communicating with the base station is spread to all sensor spread to all sensor

nodes in the sensor network. nodes in the sensor network.

* Forming clusters is based on the received signal * Forming clusters is based on the received signal strength.strength.

* Cluster heads can then be used kind of routers (relays) * Cluster heads can then be used kind of routers (relays) to the sink.to the sink.

-

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LEACHLEACH

Two Phases: Set-up Phase and Steady-PhaseTwo Phases: Set-up Phase and Steady-Phase In Set-up Phase: * Sensors may elect themselves to be a local cluster head at any time with a certain probability. (Reason: to balance the energy dissipation) * A sensor node chooses a random number between 0 and 1. * If this random number is less than the threshold T(n), the sensor node becomes a cluster-head. T(n) = P / {1 – P[r mod (1/P)]} if n is element of G

where P is the desired percentage to become a cluster head (e.g., 0.05) r is the current round G is the set of nodes that have not been a cluster head in the last 1/P rounds.* After the cluster heads are selected, the cluster heads advertise to all sensor nodes in the network that they are the new cluster heads.

- Each node accesses the network through the cluster head Each node accesses the network through the cluster head that requires that requires

minimum energy to reach.minimum energy to reach.

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Dynamic ClustersDynamic Clusters

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LEACHLEACH

Once the nodes receive the advertisement, they determine Once the nodes receive the advertisement, they determine the clusterthe cluster

that they want to belong based on the that they want to belong based on the signal strengthsignal strength of of the advertisement the advertisement

from the cluster heads to the sensor nodes.from the cluster heads to the sensor nodes.

The nodes inform the appropriate cluster heads that they The nodes inform the appropriate cluster heads that they will be a memberwill be a member

of the cluster.of the cluster.

Afterwards the cluster heads assign the time on which the Afterwards the cluster heads assign the time on which the sensor nodes can sensor nodes can

send data to them.send data to them.

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LEACHLEACH

STEADY STATE PHASE:STEADY STATE PHASE:

Sensors begin to sense and transmit data to the cluster Sensors begin to sense and transmit data to the cluster heads whichheads which

aggregate data from the nodes in their clusters.aggregate data from the nodes in their clusters.

After a certain period of time spent on the steady state,After a certain period of time spent on the steady state,

the network goes into start-up phase again and enters the network goes into start-up phase again and enters another round ofanother round of

selecting cluster heads.selecting cluster heads.

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LEACHLEACH

Optimum Number of Clusters ---????????

- too few: nodes far from cluster heads– too many: many nodes send data to SINK.

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LEACHLEACH

Achieves over a factor of 7 reduction in energy dissipation compared to direct communication.

The nodes die randomly and dynamic clustering increases lifetime of the system.

It is completely distributed and requires no global knowledge of the network.

It uses single hop routing where each node can transmit directly to the cluster head and the sink.

It is not applicable to networks deployed in large regions.

Furthermore, the idea of dynamic clustering brings extra overhead, e.g., head changes, advertisements etc. which may diminish the gain in energy consumption.

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Other ProtocolsOther Protocols

1. Energy Aware Routing R. Shah, J. Rabaey, “Energy Aware Routing for Low Energy Ad Hoc Sensor Networks,” IEEE WCNC’02, Orlando, March 2002.

2. Rumor Routing D. Braginsky, D. Estrin, “Rumor Routing Algorithm for Sensor Networks,” ACM WSNA’02, Atlanta, October 2002.

3. Threshold sensitive Energy Efficient sensor Network (TEEN) A. Manjeshwar, D.P. Agrawal, “TEEN: A Protocol for Enhanced Efficiency in Wireless Sensor Networks,” IEEE WCNC’02, Orlando, March 2002.

4. Constrained Anisotropic Diffusion Routing (CADR) M. Chu, H.Hausecker, F. Zhao, “Scalable Information-Driven Sensor Querying and Routing for Ad Hoc Heterogeneous Sensor Networks,” International Journal of High Performance Computing Applications, Vol. 16, No. 3, August 2002.

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Other ProtocolsOther Protocols

5. Power Efficient Gathering in Sensor Information Systems (PEGASIS) S. Lindsey, C.S. Raghavendra, “PEGASIS: Power Efficient Gathering in Sensor Information Systems,” IEEE Aerospace Conference, Montana, March 2002.

6. Self Organizing Protocol L. Subramanian, R.H. Katz, “An Architecture for Building Self Configurable Systems,” IEEE/ACM Workshop on Mobile Ad Hoc Networking and Computing, Boston, August 2000.

7. Geographic Adaptive Fidelity (GAF) Y. Yu, J. Heideman, D. Estrin, “Geography-informed Energy Conservation for Ad Hoc Routing,” ACM MobiCom’01, Rome, July 2001.

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Open Research Open Research IssuesIssues

• Store and Forward Technique that combines data fusion and aggregation.

• Routing for Mobile Sensors Investigate multi-hop routing techniques for high mobility environments.

• Priority Routing Design routing techniques that allow different priority of data to be aggregated, fused, and relayed.

• 3D Routing

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TRANSPORT LAYERTRANSPORT LAYER(PRIOR KNOWLEDGE)(PRIOR KNOWLEDGE)

END TO END RELIABILITY END TO END RELIABILITY CONGESTION CONTROLCONGESTION CONTROL

TCP (Transmission Control Protocol)TCP (Transmission Control Protocol) for for Data TrafficData Traffic

UDP (User Datagram Protocol)UDP (User Datagram Protocol) for Real for Real Time TrafficTime Traffic

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Transport LayerTransport Layer


SinkSink

SinkSink

UserUser

End-to-end End-to-end communication communication between a sensor between a sensor node and usernode and user

End to end reliable End to end reliable event transfer event transfer

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TRANSPORT LAYERTRANSPORT LAYERRelated WorkRelated Work

RMST (Reliable Multisegment Transport) RMST (Reliable Multisegment Transport) F. Stann and J. Heidemann, “RMST: Reliable Data Transport in Sensor Networks,” In Proc. IEEE SNPA’03, May 2003, Anchorage, Alaska, USA

RMST is a transport layer protocol for directed diffusion.RMST is a transport layer protocol for directed diffusion. RMST provides end-to-end data-packet transfer reliability.RMST provides end-to-end data-packet transfer reliability. RMST is a selective NACK-based protocol that can be RMST is a selective NACK-based protocol that can be configured for in-network caching and repair.configured for in-network caching and repair. There are two modes for RMST: There are two modes for RMST: Caching Mode and Non-Caching ModeCaching Mode and Non-Caching Mode.. CACHING MODE:CACHING MODE: A number of nodes along a reinforced path, A number of nodes along a reinforced path, (path being used to convey the data to the sink by directed(path being used to convey the data to the sink by directed diffusion), are assigned as RMST nodes.diffusion), are assigned as RMST nodes.

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Reliable Multi-Segment Reliable Multi-Segment Transport (RMST)Transport (RMST)

SinkSink

RMST NodeRMST NodeSource NodeSource Node

Each RMST node caches the Each RMST node caches the fragments identified by FragNo of a fragments identified by FragNo of a flow identified by RmstNo.flow identified by RmstNo. Watchdog timers are maintained Watchdog timers are maintained for each flow. When a fragment is for each flow. When a fragment is not received before the timer not received before the timer expires, a negative expires, a negative acknowledgement is sent backward acknowledgement is sent backward in the reinforced path.in the reinforced path. The first RMST node that has the The first RMST node that has the required fragment along the path required fragment along the path retransmitretransmitss the fragment. the fragment. Sink acts as the last RMST node. Sink acts as the last RMST node. In non-caching In non-caching mmode, sink is the ode, sink is the only RMST node.only RMST node. RMST relies on directed diffusion RMST relies on directed diffusion scheme for recovery from the failed scheme for recovery from the failed reinforced paths.reinforced paths.

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C. Y. Wan, A. T. Campbell and L. Krishnamurthy, “PSFQ: A Reliable Transport Protocol for Wireless C. Y. Wan, A. T. Campbell and L. Krishnamurthy, “PSFQ: A Reliable Transport Protocol for Wireless Sensor Networks,” Sensor Networks,” In Proc. ACM WSNA’02In Proc. ACM WSNA’02, September 2002, Atlanta, GA, September 2002, Atlanta, GA

Related Work Related Work PSFQ - Pump Slowly Fetch PSFQ - Pump Slowly Fetch Quickly Quickly

– Slow injection of packets into the networkSlow injection of packets into the network– Aggressive hop-by-hop recovery in case of packet lossesAggressive hop-by-hop recovery in case of packet losses– ““PUMP” performs controlled flooding and requires each PUMP” performs controlled flooding and requires each

intermediate node to create and maintain a data cache intermediate node to create and maintain a data cache to be used for local loss recovery and in-sequence data to be used for local loss recovery and in-sequence data delivery.delivery.

– Applicable only to strict sensor-sensor guaranteed Applicable only to strict sensor-sensor guaranteed deliverydelivery

– And for control and management end-to-end reliability And for control and management end-to-end reliability for the downlink from sink to sensorsfor the downlink from sink to sensors

– Does not address congestion controlDoes not address congestion control

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Pump Slowly Fetch Quickly Pump Slowly Fetch Quickly (PSFQ)(PSFQ)

PSFQ comprises three functions: PSFQ comprises three functions: * * Message Relaying (PUMP operation), Message Relaying (PUMP operation), * Relay initiated error recovery (FETCH operation) and * Relay initiated error recovery (FETCH operation) and * Selective status reporting (REPORT operation).* Selective status reporting (REPORT operation). Every intermediate node maintains a data cache.Every intermediate node maintains a data cache. A node that receives a packet checks its content against its A node that receives a packet checks its content against its local local cache, and discards any duplicates.cache, and discards any duplicates. If the received packet is new, the TTL field in the packet is If the received packet is new, the TTL field in the packet is decremented.decremented. If the TTL field is higher than 0 after being decremented, and If the TTL field is higher than 0 after being decremented, and there there is no gap in the packet sequence numbers, the packet is is no gap in the packet sequence numbers, the packet is scheduled toscheduled to be forwarded. be forwarded. The packets are delayed for a random period between Tmin The packets are delayed for a random period between Tmin andand Tmax, and then relayed.Tmax, and then relayed. A node goes to FETCH mode once a sequence number gap is A node goes to FETCH mode once a sequence number gap is detected.detected. The node in FETCH mode requests a retransmission from The node in FETCH mode requests a retransmission from neighboringneighboring nodes.nodes.

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Related WorkRelated Work

Wireless TCP variants are NOT suitable for Wireless TCP variants are NOT suitable for sensor networkssensor networks– Different notion of end-to-end reliabilityDifferent notion of end-to-end reliability– Huge buffering requirementsHuge buffering requirements– ACKing is energy drainingACKing is energy draining

BOTTOMLINE:BOTTOMLINE: Traditional end-to-end Traditional end-to-end guaranteed reliability guaranteed reliability (TCP solutions)(TCP solutions) cannot be applied here.cannot be applied here.

New Reliability Notion is required!!!New Reliability Notion is required!!!

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Event Radius Sink

Sensor nodes

Event-to-Sink Reliability Event-to-Sink Reliability (ESRT) (ESRT) O. B. Akan, I. F. Akyildiz and Y. Sankarasubramaniam, O. B. Akan, I. F. Akyildiz and Y. Sankarasubramaniam, to appear in IEEE Transactions on Networking, Fall 2004.to appear in IEEE Transactions on Networking, Fall 2004.Also in Also in Proc. of ACM MobiHoc’03, Annapolis, Maryland, June Proc. of ACM MobiHoc’03, Annapolis, Maryland, June 20032003..

Sensor networks are Sensor networks are event-drivenevent-driven Multiple correlated data flows from event to Multiple correlated data flows from event to

sink sink GOAL:GOAL: To reliably detect/estimate event To reliably detect/estimate event

features based on the collective reports of features based on the collective reports of several sensor nodes observing the event.several sensor nodes observing the event.

Event-to-sink collective reliability notionEvent-to-sink collective reliability notion

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Event-to-Sink Reliable Transport Event-to-Sink Reliable Transport (ESRT)(ESRT)

ESRT is the first scheme that focuses on the end-to-end ESRT is the first scheme that focuses on the end-to-end reliable event transfer.reliable event transfer. The end-to-end event transfer reliability is controlled The end-to-end event transfer reliability is controlled based on the reporting frequencies of sensor nodes.based on the reporting frequencies of sensor nodes.

SinkSink

aa

bb

cc

dd

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End-to-end Reliable Event End-to-end Reliable Event TransferTransfer

SinkSink

rr

aa

bb

cc

dd

rr

event regionevent region

sensor coveragesensor coverage

sensor rangesensor range

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Event-to-Sink Event-to-Sink ReliabilityReliability

Sink decides about event features every Sink decides about event features every time units (decision intervals) time units (decision intervals) DEFINITION 1: Observed Event Reliability DEFINITION 1: Observed Event Reliability

rrii is the number of data packets received in decision interval is the number of data packets received in decision interval i i at sinkat sink DEFINITION 2: Desired Event ReliabilityDEFINITION 2: Desired Event Reliability RR is the number of packets required for reliable event detection is the number of packets required for reliable event detection (a(application specific and is known a-priori at pplication specific and is known a-priori at

the sink)the sink)

((If If rrii > > R, then the event is reliably detected. Else, appropriate R, then the event is reliably detected. Else, appropriate actions must be taken to achieve R.)actions must be taken to achieve R.) DEFINITION 3: Reporting Rate DEFINITION 3: Reporting Rate ff is the frequency of packet transmissions at a source node is the frequency of packet transmissions at a source node

TRANSPORT PROBLEM IN SENSOR NETWORKS:TRANSPORT PROBLEM IN SENSOR NETWORKS: To configure the reporting rate, f, of source nodes so as to achieve the required event detection reliability, R, at To configure the reporting rate, f, of source nodes so as to achieve the required event detection reliability, R, at

the sink with minimum resource utilization.the sink with minimum resource utilization.

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r vs f relationshipr vs f relationship

rr shows initial linear increase with shows initial linear increase with ff until until f = ff = fmaxmax

For For f > ff > fmaxmax , , rr drops due to congestion because the drops due to congestion because the network is unable to handle the network is unable to handle the increased injection of data packets increased injection of data packets

This behavior is independent of the number of nodes This behavior is independent of the number of nodes nn ffmaxmax decreases with increasing decreases with increasing nn (congestion occurs at lower reporting frequencies (congestion occurs at lower reporting frequencies

with greater number of source nodes n)with greater number of source nodes n)

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ESRT: Event-to-Sink ESRT: Event-to-Sink Reliable TransportReliable Transport

OBJECTIVE: OBJECTIVE: Achieve reliable event detection with minimum Achieve reliable event detection with minimum

energy expenditure and congestion resolution.energy expenditure and congestion resolution. SALIENT FEATURES:SALIENT FEATURES:

– Self-configurationSelf-configuration – Adapts to random, dynamic – Adapts to random, dynamic network topologynetwork topology

– Collective identification Collective identification – Does not require – Does not require individual node IDsindividual node IDs

– Biased implementation Biased implementation – Graceful transfer of – Graceful transfer of complexity to the sink complexity to the sink

Sensor nodes need only two additional functionsSensor nodes need only two additional functions– Implement a congestion detection mechanismImplement a congestion detection mechanism– Listen to sink broadcasts for frequency updatesListen to sink broadcasts for frequency updates

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f

ESRT: Protocol ESRT: Protocol OverviewOverview

Determine reporting frequency Determine reporting frequency ff to achieve to achieve desired reliability desired reliability RR with minimum resource with minimum resource utilizationutilization

Source (Sensor nodes): Source (Sensor nodes): – Send data with reporting frequency Send data with reporting frequency f f – Monitor buffer level and notify congestion to the sinkMonitor buffer level and notify congestion to the sink

Sink: Sink: – Measures the Measures the observed event reliabilityobserved event reliability rrii at the end of at the end of

decision interval decision interval ii – Normalized reliability Normalized reliability i i == rri i / R/ R – Performs congestion decision based on the feedback Performs congestion decision based on the feedback

from the sources nodes (to determine from the sources nodes (to determine f f >><< f fmaxmax). ).

– Update Update f f based on based on ii and and f f >><< f fmaxmax (congestion) to achieve (congestion) to achieve

desired event reliabilitydesired event reliability RR

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StateState DescriptionDescription ConditionCondition

(NC,LR)(NC,LR) (No congestion, Low reliability)(No congestion, Low reliability) f < ff < fmaxmax and and < 1 - < 1 -

(NC,HR)(NC,HR) (No congestion, High (No congestion, High reliability)reliability)

f f f fmaxmax and and > 1+ > 1+

(C,HR)(C,HR) (Congestion, High reliability)(Congestion, High reliability) f < ff < fmaxmax and and > 1 > 1

(C,LR)(C,LR) (Congestion, Low reliability)(Congestion, Low reliability) f < ff < fmaxmax and and 1 1

OOROOR Optimal Operating RegionOptimal Operating Region f < ff < fmaxmax and and [[1- 1- , 1+ , 1+ ]]

ESRT: Network ESRT: Network StatesStates

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ESRT: ESRT: Congestion Detection MechanismCongestion Detection Mechanism

ACK/NACK not suitableACK/NACK not suitable We use local buffer level monitoring in We use local buffer level monitoring in

sensor nodes sensor nodes

Mark Congestion Notification (CN ) field in packet if congested, i.e., bk + b > B (the node infers that it will experience congestion in the next reporting interval)

bk bk-1

b

B

f

Event

IDCNCN

(1 bit)Destinatio

n

Time

Stamp Payload FEC

bk : Buffer fullness level at the end of reporting interval k

b : Buffer length increment

B : Buffer size

f : reporting frequency

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StateState Frequency UpdateFrequency Update CommentsComments

(NC,LR)(NC,LR) ffi+1i+1 = f = fi i / / iiMultiplicative increase, achieve desired Multiplicative increase, achieve desired reliability asapreliability asap

(NC,HR)(NC,HR) ffi+1i+1 = f = fi i ((i i + 1) / 2+ 1) / 2iiConservative decrease, no compromise on Conservative decrease, no compromise on reliabilityreliability

(C,HR)(C,HR) ffi+1i+1 = f = fi i / / iiAggressive decrease to state (NC,HR)Aggressive decrease to state (NC,HR)

(C,LR)(C,LR) ffi+1i+1 = f = fi i ii

Exponential decrease, relieve congestion asapExponential decrease, relieve congestion asap

OOROOR ffi+1i+1 = f = fiiUnchangedUnchanged

ESRT: Frequency ESRT: Frequency UpdateUpdate

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S0 = (NC,LR) S0 = (NC,HR)

ESRT PerformanceESRT Performance

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S0 = (C,HR) S0 = (C,LR)

ESRT PerformanceESRT Performance

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ConclusionsConclusions

Sensor network paradigm necessitates the Sensor network paradigm necessitates the notion of notion of event-to-sink reliabilityevent-to-sink reliability

Existing end-to-end guaranteed reliability Existing end-to-end guaranteed reliability solutions lead to over-utilization of scarce solutions lead to over-utilization of scarce sensor resourcessensor resources

ESRT is a novel solution propose exclusively for ESRT is a novel solution propose exclusively for reliable event transport in sensor networksreliable event transport in sensor networks– Tailored for sensor environments Tailored for sensor environments – Biased implementationBiased implementation– Energy conservationEnergy conservation– Collective identification, self-configurationCollective identification, self-configuration– ESRT can also address concurrent multiple ESRT can also address concurrent multiple

eventsevents

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Open Research Open Research IssuesIssues

Extend Extend ESRTESRT to address reliable transport of to address reliable transport of concurrent multiple events concurrent multiple events in the sensor field.in the sensor field.

Explore possible other Explore possible other reliability metricsreliability metrics– Total expected mean square distortionTotal expected mean square distortion– Minimum mean squared error estimationMinimum mean squared error estimation

Develop unified transport layer protocols for Develop unified transport layer protocols for sink-to-sensorssink-to-sensors and and bi-directional bi-directional reliable reliable transport in WSNtransport in WSN

Research to Research to integrate WSN domain into NGWI integrate WSN domain into NGWI (Next Generation Wireless Internet)(Next Generation Wireless Internet)– Adaptive Transport Protocols for WSN-Ad Hoc Adaptive Transport Protocols for WSN-Ad Hoc

environmentsenvironments

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Medium Access Control Medium Access Control (MAC)(MAC)

Multiple users need to access the limited available communication resources.

MAC aims at providing fair and efficient resource access

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Medium Access Control Medium Access Control (MAC)(MAC)(Prior Knowledge)(Prior Knowledge)

ALOHAALOHA Slotted ALOHASlotted ALOHA Reserved ALOHAReserved ALOHA CSMA (nonpersistant, p-persistant,1-CSMA (nonpersistant, p-persistant,1-persistant)persistant) TDMATDMA FDMAFDMA CDMACDMA

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AlohaAloha

Slotted AlohaSlotted Aloha

Aloha/Slotted AlohaAloha/Slotted Aloha

sender A

sender B

sender C

collision

sender A

sender B

sender C

collision

t

t

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User 1

User 2

User n

…Time

Frequency

FDMA (Frequency FDMA (Frequency Division Multiple Access)Division Multiple Access)

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1 2 3 … nFrequency

Total bandwidth

4

FDMA Bandwidth FDMA Bandwidth StructureStructure

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Frequency 1 User 1

Frequency 2 User 2

Frequency n User n

Base Station

… …

Mobile Stations

FDMA Channel FDMA Channel AllocationAllocation

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Use

r 1

Use

r 2

Use

r n

…

Time

Frequency

TDMA (Time Division TDMA (Time Division Multiple Access)Multiple Access)

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1 2 3 … nTime

Frame

4

TDMA Frame TDMA Frame StructureStructure

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Time 1

Time 2

Time n……

Base Station

User 1

User 2

User n

…

Mobile Stations

TDMA Frame TDMA Frame AllocationAllocation

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ser

1

Time

Frequency

Use

r 2

Use

r n

Code

...

CDMA (Code Division CDMA (Code Division Multiple Access )Multiple Access )

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Medium Access Control Medium Access Control (MAC)(MAC)

Existing MAC protocols cannot be used for sensorExisting MAC protocols cannot be used for sensor

networks because sensor MACs must have inbuilt networks because sensor MACs must have inbuilt

Power management, mobility management and Power management, mobility management and

failure recovery strategies failure recovery strategies

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Medium Access Control Medium Access Control (MAC)(MAC)for Sensor Networksfor Sensor Networks

Self-Organizing Medium Access Control for Sensor Self-Organizing Medium Access Control for Sensor

Networks (SMACS) and Eavesdrop and Register Networks (SMACS) and Eavesdrop and Register (EAR)(EAR) Hybrid TDMA-FDMAHybrid TDMA-FDMA CSMA basedCSMA based

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Medium Access Control Medium Access Control (MAC)(MAC) SMACS and EARSMACS and EAR

Available bandwidth is far greater than the maximum data rate Available bandwidth is far greater than the maximum data rate of sensorsof sensors

Neighbor discovery and channel assignment combinedNeighbor discovery and channel assignment combined Random wake up during the connection phaseRandom wake up during the connection phase In EAR mobile nodes are given full control of the connection In EAR mobile nodes are given full control of the connection processprocess

Mobile nodes keep a record of neighbor nodesMobile nodes keep a record of neighbor nodes

EAR is transparent to SMACSEAR is transparent to SMACS

ShortcomingsShortcomings

Nodes belonging to different subnets might not be able to Nodes belonging to different subnets might not be able to connect connect A mainly static network is assumedA mainly static network is assumed

W. Ye, J. Heidemann and D. Estrin, “An Energy Efficient MAC W. Ye, J. Heidemann and D. Estrin, “An Energy Efficient MAC Protocol for Wireless Sensor Networks,” Protocol for Wireless Sensor Networks,” In Proc. ACM MOBICOM In Proc. ACM MOBICOM ’01, ’01, pp. 221–235, Rome, Italy 2001pp. 221–235, Rome, Italy 2001

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CSMA BasedCSMA Based

Traffic in sensor networks is highly correlated, Traffic in sensor networks is highly correlated, dominantly periodic, variable.dominantly periodic, variable.

Constant listening times are energy efficientConstant listening times are energy efficient Random delay avoids repeated collisions Random delay avoids repeated collisions

Not suitable for delay-sensitive applicationsNot suitable for delay-sensitive applications Under higher load, RTS/CTS involves Under higher load, RTS/CTS involves considerable considerable messaging overheadmessaging overhead

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Motivation for Our Motivation for Our WorkWork

WSN are characterized by dense deployment of sensor WSN are characterized by dense deployment of sensor nodesnodes

MAC Layer ChallengesMAC Layer Challenges– Limited power resourcesLimited power resources– Need for a self-configurable, distributed protocolNeed for a self-configurable, distributed protocol– Data centric approach rather than per-node fairnessData centric approach rather than per-node fairness

Exploit Exploit spatial correlationspatial correlation to to reduce transmissions in MAC reduce transmissions in MAC layer !layer !

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Collaborative Medium Access Based on Spatial Correlation in Sensor Networks M. C. Vuran and I. F. Akyildiz, December 2003.M. C. Vuran and I. F. Akyildiz, December 2003.

Nodes Nodes nnii observe variables observe variables XXi i ,, i=1,2,3,4,5i=1,2,3,4,5

Minimum of 5 transmissions are requiredMinimum of 5 transmissions are required Due to correlation, assume Due to correlation, assume XX11=X=X22 and X and X33=X=X44

Only 3 transmissions needed!Only 3 transmissions needed! Regulate medium access to decrease number of Regulate medium access to decrease number of

transmissions!transmissions!

1 2 3 4

5

S

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DefinitionsDefinitions

Correlation region Correlation region of node of node nnii

– Region of radius Region of radius r r centered around nodecentered around node n nii

Correlation neighborsCorrelation neighbors of node of node nnii

– Nodes inside the correlation region of node Nodes inside the correlation region of node nnii

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Collaborative MAC Collaborative MAC ProtocolProtocol

If a node If a node nnii transmits data then transmits data then all its correlation neighbors all its correlation neighbors have redundant informationhave redundant information

Route-thru data has higher Route-thru data has higher priority over generated datapriority over generated data

Filter outFilter out transmission of transmission of redundant data and redundant data and prioritizeprioritize filtered data through the network!filtered data through the network!

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Collaborative MAC Collaborative MAC ProtocolProtocol

Two reasons for medium Two reasons for medium access;access;

Source function: Source function: Transmit event Transmit event

informationinformation Router function: Router function: Forward packets from Forward packets from

other nodes in the multi-other nodes in the multi-hop path to the sinkhop path to the sink

Two componentsTwo components– Event MAC (E-MAC)Event MAC (E-MAC)– Network MAC (N-MAC)Network MAC (N-MAC)

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Event MAC (E-MAC)Event MAC (E-MAC)

Aims to filter out correlated sensor Aims to filter out correlated sensor recordsrecords

First Contention Phase (FCS)First Contention Phase (FCS)– Nodes contend using IEEE 802.11 Nodes contend using IEEE 802.11

structure for the first timestructure for the first time After a node After a node nnii captures the channel all captures the channel all

the correlation neighbors of the correlation neighbors of nnii – Drop their packetsDrop their packets– Enter Enter Suspicious Sleep State (SSS)Suspicious Sleep State (SSS)

Nodes enter FCS after a period of time to Nodes enter FCS after a period of time to maintain equal load-sharingmaintain equal load-sharing

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Network MAC (N-Network MAC (N-MAC)MAC)

Since correlation is filtered out by Since correlation is filtered out by E-MAC, route-thru packet has E-MAC, route-thru packet has higher priorityhigher priority

N-MAC prioritizes these packets N-MAC prioritizes these packets during medium access usingduring medium access using– Smaller backoff window sizeSmaller backoff window size– PIFS (<SIFS) during contentionPIFS (<SIFS) during contention

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PerformancePerformance

Both energy consumption and latency Both energy consumption and latency decreases when spatial correlation is exploiteddecreases when spatial correlation is exploited

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ConclusionsConclusions

Spatial correlation in sensor networks is exploited in Spatial correlation in sensor networks is exploited in the MAC layerthe MAC layer

MAC protocol collaboratively regulates medium access MAC protocol collaboratively regulates medium access such that redundant transmissions is suppressedsuch that redundant transmissions is suppressed

Event MAC (E-MAC)Event MAC (E-MAC) filters out correlation whereas filters out correlation whereas Network MAC (N-MAC) Network MAC (N-MAC) prioritizes the route-thru packetsprioritizes the route-thru packets

Number of transmissions are reduced instead of Number of transmissions are reduced instead of number of transmitted bitsnumber of transmitted bits

Collaborative Medium Access achieves low energy Collaborative Medium Access achieves low energy consumption as well as improving event detection consumption as well as improving event detection latencylatency

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MEDIUM ACCESS CONTROL MEDIUM ACCESS CONTROL (MAC) (MAC) FURTHER RESEARCH NEEDSFURTHER RESEARCH NEEDS

MAC for sensor networks must have inbuilt MAC for sensor networks must have inbuilt power power

management, mobility management and failure management, mobility management and failure recovery recovery

strategiesstrategies Need for a self-configurable, distributed Need for a self-configurable, distributed protocolsprotocols Data centric approach rather than per-node Data centric approach rather than per-node fairnessfairness Develop MACs which differentiate Multimedia Develop MACs which differentiate Multimedia TrafficTraffic

Exploit Exploit Spatial & Temporal CorrelationSpatial & Temporal Correlation

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Some sensor network applications like mobile Some sensor network applications like mobile trackingtracking require high data precisionrequire high data precision

Coding gain is generally expressed in terms of the Coding gain is generally expressed in terms of the additionaladditional transmit power needed to obtain the same BER transmit power needed to obtain the same BER without codingwithout coding

FEC is preferred over ARQFEC is preferred over ARQ

Since power consumption is crucial, we must take Since power consumption is crucial, we must take intointo account encoding and decoding energy account encoding and decoding energy expendituresexpenditures

Coding is profitable only if the encoding and decodingCoding is profitable only if the encoding and decoding power consumption is less than the coding gain.power consumption is less than the coding gain.

Error ControlError Control

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ERROR CONTROL ERROR CONTROL RESEARCH NEEDSRESEARCH NEEDS

Design of suitable FEC codes with minimal Design of suitable FEC codes with minimal encoding encoding and relatively higher decoding complexitiesand relatively higher decoding complexities

Feasibility of ARQ schemes in multihop sensor Feasibility of ARQ schemes in multihop sensor networks networks (hop by hop ARQ instead of end-to-end). This is (hop by hop ARQ instead of end-to-end). This is needed for needed for reliable communications (data critical)reliable communications (data critical)

Adaptive/Hybrid FEC/ARQ schemes Adaptive/Hybrid FEC/ARQ schemes

Extension to Rayleigh/Rician fading conditions Extension to Rayleigh/Rician fading conditions with mobilewith mobile nodesnodes

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Optimal Packet Size for Wireless Optimal Packet Size for Wireless Sensor NetworksSensor Networks

Y. Sankarasubramaniam, I. F. Akyildiz, S. McLaughlin, Y. Sankarasubramaniam, I. F. Akyildiz, S. McLaughlin, ”Optimal ”Optimal Packet Size Packet Size

for Wireless Sensor Networks”, IEEE SNPA, May 2003.for Wireless Sensor Networks”, IEEE SNPA, May 2003.

Determining the optimal packet size for sensor networks is necessary to Determining the optimal packet size for sensor networks is necessary to operate at high operate at high energy efficienciesenergy efficiencies..

The The multihop wireless channelmultihop wireless channel and and energy consumption characteristicsenergy consumption characteristics are the two most are the two most important factors that influence choice of packet size. important factors that influence choice of packet size.

Payload (Payload (<=73<=73))Header (Header (22)) Trailer (FEC) (Trailer (FEC) (>=3>=3))

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PHYSICAL LAYERPHYSICAL LAYER

New Channel Models (I/O/Underwater/Deep New Channel Models (I/O/Underwater/Deep Space) Space)

Explore Antennae Techniques Explore Antennae Techniques

(e.g., Smart Antennaes)(e.g., Smart Antennaes)

Software Radios??Software Radios??

New Modulation SchemesNew Modulation Schemes

SYNCH SchemesSYNCH Schemes

FEC Schemes on the Bit LevelFEC Schemes on the Bit Level

New Data EncryptionNew Data Encryption

Investigate UWB Investigate UWB

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FINAL REMARKSFINAL REMARKS

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Basic Research Basic Research NeedsNeeds

• An Analytical Framework for Sensor Networks Find a Basic Generic Architecture and Protocol Development which can be tailored to specific applications. • More theoretical investigations of the Architecture and Protocol developments

• Network Configuration and Planning Schemes

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FURTHER OPEN RESEARCH FURTHER OPEN RESEARCH ISSUESISSUES

Research to Research to integrate WSN domain into NGWI integrate WSN domain into NGWI (Next Generation Wireless Internet)(Next Generation Wireless Internet)

e.g., interactions of Sensor and AdHoc e.g., interactions of Sensor and AdHoc Networks or Sensor and Satellite or any other Networks or Sensor and Satellite or any other combinations…combinations…

Explore the SENSOR/ACTOR NETWORKSExplore the SENSOR/ACTOR NETWORKS

Explore the SENSOR-ANTISENSOR NETWORKSExplore the SENSOR-ANTISENSOR NETWORKS

SECURITY ISSUESSECURITY ISSUES

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Some ApplicationsSome Applications

• Clear Demonstration of Testbeds and Realistic Applications

• Not only data or audio but also video as well as integrated traffic.

SOME OF OUR EFFORTS IN BWN LAB @ GaTech

• MAN for Meteorological Observations• SpINet for Mars Surface• Airport Security Sensors/Actors• Sensor Wars• Wide Area Multi-campus Sensor Network

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FURTHER CHALLENGESFURTHER CHALLENGESProtocol StackProtocol Stack

• Follow the TCP/IP Stack, i.e., keep the Strict Layer Approach ??? • Or Interleave the Layer functionalities???

• Cross Layer Optimization

• Standardization???

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Commercial Commercial Viability of WSN Viability of WSN ApplicationsApplications

Within the next few years, distributed sensing and Within the next few years, distributed sensing and computing will be everywhere, i.e., homes, offices, computing will be everywhere, i.e., homes, offices, factories, automobiles, shopping centers, super-factories, automobiles, shopping centers, super-markets, farms, forests, rivers and lakes. markets, farms, forests, rivers and lakes.

Some of the immediate commercial applications of Some of the immediate commercial applications of wireless sensor networks are wireless sensor networks are – Industrial automation (Industrial automation (process controlprocess control))– Defense (Defense (unattended sensors, real-time unattended sensors, real-time

monitoringmonitoring))– Utilities (Utilities (automated meter readingautomated meter reading), ), – Weather predictionWeather prediction– Security (Security (environment, building etc.environment, building etc.))– Building automation (Building automation (HVAC controllersHVAC controllers). ). – Disaster relief operationsDisaster relief operations– Medical and health monitoring and instrumentationMedical and health monitoring and instrumentation

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XSILOGY SolutionsXSILOGY Solutions is a company which provides wireless sensor is a company which provides wireless sensor network solutions for various commercial applications such as tank network solutions for various commercial applications such as tank inventory management, stream distribution systems, commercial inventory management, stream distribution systems, commercial buildings, environmental monitoring, homeland defense etc. buildings, environmental monitoring, homeland defense etc. http://www.xsilogy.com/home/main/index.htmlhttp://www.xsilogy.com/home/main/index.html

In-Q-TelIn-Q-Tel provides distributed data collection solutions with sensor provides distributed data collection solutions with sensor network deployment. network deployment. http://www.in-q-tel.com/tech/dd.htmlhttp://www.in-q-tel.com/tech/dd.html

ENSCO Inc.ENSCO Inc. invests in wireless sensor networks for meteorological invests in wireless sensor networks for meteorological applications. applications. http://www.ensco.com/products/homeland/msis/msis_rnd.htmhttp://www.ensco.com/products/homeland/msis/msis_rnd.htm

EMBEREMBER provides wireless sensor network solutions for industrial provides wireless sensor network solutions for industrial automation, defense, and building automation. automation, defense, and building automation. http://www.ember.comhttp://www.ember.com

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H900 Wireless SensorNet System(TM)H900 Wireless SensorNet System(TM), the first commercially , the first commercially available end-to-end, low-power, bi-directional, wireless mesh available end-to-end, low-power, bi-directional, wireless mesh networking system for commercial sensors and controls is networking system for commercial sensors and controls is developed by the company called developed by the company called Sensicast SystemsSensicast Systems. The . The company targets wide range of commercial applications from company targets wide range of commercial applications from energy to homeland security. energy to homeland security. http://www.sensicast.comhttp://www.sensicast.com

The Sensor-based Perimeter SecurityThe Sensor-based Perimeter Security product is introduced by a product is introduced by a company called company called SOFLINX Corp.SOFLINX Corp. (a wireless sensor network (a wireless sensor network software company) software company) http://www.soflinx.comhttp://www.soflinx.com

XYZ On A Chip: Integrated Wireless Sensor Networks for the XYZ On A Chip: Integrated Wireless Sensor Networks for the Control of the Indoor Environment In BuildingsControl of the Indoor Environment In Buildings is another is another commercial application project currently performed by Berkeley. commercial application project currently performed by Berkeley. http://www.cbe.berkeley.edu/research/briefs-wirelessxyz.htmhttp://www.cbe.berkeley.edu/research/briefs-wirelessxyz.htm

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The CrossbowThe Crossbow wireless sensor products and its environmental wireless sensor products and its environmental monitoring and other related industrial applications of such as monitoring and other related industrial applications of such as surveillance, bridges, structures, air quality/food quality, surveillance, bridges, structures, air quality/food quality, industrial automation, process control are introduced. industrial automation, process control are introduced. http://www.xbow.comhttp://www.xbow.com

Japan's Omron CorpJapan's Omron Corp has two wireless sensor projects in the US has two wireless sensor projects in the US that it hopes to commercialize in the near future. that it hopes to commercialize in the near future. Omron's Omron's Hagoromo Wireless Web Sensor projectHagoromo Wireless Web Sensor project consists of wireless consists of wireless nodes equipped with various sensing abilities for providing nodes equipped with various sensing abilities for providing security for major cargo-shipping ports around the world. security for major cargo-shipping ports around the world. http://www.omron.comhttp://www.omron.com

Possible business opportunity with a big home improvement Possible business opportunity with a big home improvement store chain, Home Depot, with Intel and Berkeley using wireless store chain, Home Depot, with Intel and Berkeley using wireless sensor networkssensor networkshttp://www.svbizink.com/otherfeatures/spotlight.asp?iid=314http://www.svbizink.com/otherfeatures/spotlight.asp?iid=314

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Millennial NetMillennial Net builds wireless networks combining sensor builds wireless networks combining sensor interface endpoints and routers with gateways for industrial interface endpoints and routers with gateways for industrial and building automation, security, and telemetryand building automation, security, and telemetryhttp://www.millennial.nethttp://www.millennial.net

CSEMCSEM provides sensing and actuation solutions provides sensing and actuation solutions http://www.csem.ch/fs/acuating.htmhttp://www.csem.ch/fs/acuating.htm

Dust Inc.Dust Inc. develops the next-generation hardware and software develops the next-generation hardware and software for wireless sensor networks for wireless sensor networks http://www.dust-inc.comhttp://www.dust-inc.com

Integration AssociatesIntegration Associates designs sensors used in medical, designs sensors used in medical, automotive, industrial, and military applications to cost-automotive, industrial, and military applications to cost-effective designs for handheld consumer appliances, barcode effective designs for handheld consumer appliances, barcode readers, and wireless computer input devices readers, and wireless computer input devices http://www.integration.comhttp://www.integration.com

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MelexisMelexis produces advanced integrated semiconductors, produces advanced integrated semiconductors, sensor ICs, and programmable sensor IC systems. sensor ICs, and programmable sensor IC systems. http://www.melexis.comhttp://www.melexis.com

ZMDZMD designs, manufactures and markets high performance, designs, manufactures and markets high performance, low power mixed signal ASIC and ASSP solutions for low power mixed signal ASIC and ASSP solutions for wireless and sensor integrated circuits.wireless and sensor integrated circuits.http://www.zmd.bizhttp://www.zmd.biz

ChipconChipcon produces low-cost and low-power single-chip 2.4 produces low-cost and low-power single-chip 2.4 GHz ISM band transceiver design for sensors. GHz ISM band transceiver design for sensors. http://www.chipcon.comhttp://www.chipcon.com

ZigBee AllianceZigBee Alliance develops a standard for wireless low-power, develops a standard for wireless low-power, low-rate devices. low-rate devices. http://www.zigbee.comhttp://www.zigbee.com

wireless sensor network

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