application.ppt
TRANSCRIPT
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science
Applications of Sensor Networks
Chen, WeifengGong, YingLiu, Xiaotao
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science
Outline
Why sensor nets? Advantages Applications
Classifications of sensor nets Challenging issues
Common constraints Application-specific constraints
Discussions
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science
Outline
Why sensor nets? Advantages Applications
Classifications of sensor nets Challenging issues
Common constraints Application-specific constraints
Discussions
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science
Intimate connection with its immediate environment.
Advantages of Sensor Nets
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science
Intimate connection with its immediate environment.
No disturbance to environment, animals, plants, etc.
Advantages of Sensor Nets (cont.)
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science
Intimate connection with its immediate environment.
No disturbance to environment, animals, plants, etc.
Avoid unsafe or unwise repeated field studies.
Advantages of Sensor Nets (cont.)
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science
Intimate connection with its immediate environment.
No disturbance to environment, animals, plants, etc.
Avoid unsafe or unwise repeated field studies.
Economical method for long-term data collection
One deployment, multiple utilizations
Advantages of Sensor Nets (cont.)
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science
Habitat monitoring Environmental observation and
forecasting systems: Columbia River Estuary
Smart Dust Biomedical sensors
Applications of Sensor Nets
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science
Petrel habitat on Great Duck Island in Maine.
Questions to answer: Usage pattern of nesting burrows
over the 24-72 hour cycle Changes in the burrow and surface
environmental parameters Differences in the micro-
environments with and without large numbers of nesting petrels
Primitive requirement: no human disturbance.
Habitat Monitoring
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science
Approach to habitat monitoring
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science
Estuarine Environmental Observation and Forecasting System
Observation and forecasting system for the Columbia River Estuary
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science
CORIE Approach
Real-time observations Estuarine and offshore
stations Numerical modeling
Produce forecast, hindcast of circulation
Virtualization & application Vessel survey, navigation fishing, etc…
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science
Smart Dust: Mote
1-2 mm
Thick-Film Battery
Solar Cell
Power Capacitor
Analog I/O, DSP, Control
Active Transmitter with Laser
Diode and Beam SteeringPassive Transmitter with
Corner-Cube Retroreflector
Sensors
Receiver with Photodetector
Tiny & light-communication
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science
Military Applications of Smart Dust
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science
Biomedical Sensors Sensors help to create vision
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science
Outline
Why sensor nets? Advantages Applications
Classifications of sensor nets Challenging issues
Common constraints Application-specific constraints
Discussions
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science
Classifications of Sensor Nets Sensor position
Static (Habitat, CORIE, Biomedical) Mobile (Smart Dust, Biomedical)
Goal-driven Monitoring: Real-time/Not-real-time (Habitat, Smart
Dust) Forecasting (CORIE) Function substitution (Biomedical) …
Communication medium Radio Frequency (Habitat, CORIE, Biomedical) Light (Smart Dust)
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science
Outline
Why sensor nets? Advantages Applications
Classifications of sensor nets Challenging issues
Common constraints Application-specific constraints
Discussions
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science
Common Challenging Issues Limited computation and data storage Low power consumption Wireless communication
Medium, ad hoc vs. infrastructure, topology and routing
Data-related issues Continuous operation Inaccessibility – network adjustment and
retasking Robustness and fault tolerance
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science
Application-specific Constraints
Material Constraints Bio-Compatibility Inconspicuous
Imitative to environment Detect-proof: e.g. stealth flight
Secure Data Communications Regulatory Requirements – such
as FDA
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science
Limited Computation and Data Storage
Sensor design Multi-objective sensors and single (a few)-objective sensors.
Cooperation among sensors Data aggregation and
interpretation
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science
Low Power Consumption Low power functional components Power-manageable components
Several functional state (low state-transition overhead)
Deep-sleep, Sleep, On Provide different QoS with different power consumption.
Power Management Power measurement Power budget allocation Control transitions between different power states.
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science
Wireless Communication
Communication mediums Radio Frequency: Habitat monitoring,
Biomedical sensors and CORIE estuarine observation
Light (active and passive): Smart Dust
Ad hoc versus infrastructure modes Topology Routing
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science
Smart Dust: Passive Transmitters
Asymmetric Link assumed: high power laser emit from BS, with larger scale imaging array
DownlinkLaser
Uplink
CCD Corner-Cube
Uplink
DataIn
Data
ImageSensor
Retroreflector
DataIn
Photo-
DownlinkDataOut
detector
Base-StationTransceiver
DustMote
Signal Selectionand Processing
UplinkData ...
OutNOut1
Array
UnmodulatedInterrogation
ModulatedReflected
ModulatedDownlinkDataor
BeamforUplink
BeamforUplink
Lens
Lens
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science
Smart Dust: Active Transmitter (cont.)
BS uses CCD or CMOS camera (operate at up to 1 Mbps) Using multi-hop routing, not all dust motes need LoS to BS
Transmitter Radiant IntensityReceiver Light Collection Area
Base
TransceiverStation
DustMote
DustMote
DustMote
Wall
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science
Smart Dust: Active Transmitter
LaserCollimating
Beam
Mirror(s)
Lens
Steering
Diode
Two-axis beam steering assembly
Active dust mote transmitter Beams have divergence << 1º
Steerable over a full hemisphere
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science
Ad hoc vs. Infrastructure Modes Sensor - Sensor communication:
Short distance Ad hoc
Sensor - Base station communication: Long distance sensor to base station
communication Infrastructure
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science
Wireless Communication: Topology
Fixed topology Tree based Cluster based
Dynamic topology - mobility Ad hoc Infrastructure Mixed
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science
Research on Fixed Topologies Vary # of neighbors Trade-offs exist
Number of hops Number of receivers Amount of contention
Evaluate power usage Test power-aware routing Results:
Power-aware routing reduces power usage
3D is better than 2D
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science
Research on Fixed Topologies (cont.)
Cluster-based Tree-based
Cluster-based approach provides better energy-efficiency than the tree-based approach.
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science
Wireless Communication: Routing
Route discovery Redundancy discovery Failure detection and recovery Distributed and localized
Avoid single-point failure Avoid bottleneck
Energy-efficient
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science
Energy-Efficient Routing Protocol
Routing protocol metrics: Traditional: packet loss, routing
message overhead, routing length New metric: energy consumption:
, =2~4 Imagine:
dE
5
S T
M
5
9
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science
Data-related issues Trade-off between latency and energy
Real-time Periodic
Data representation Raw/Compressed data Sampling Value: Absolute/Relative
Error calibration No access to real values Inferred from other sensors
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science
Continuous Operation
Long-term data collection Renewable power source.
Solar energy Mechanical vibrations Radio-Frequency inductance Infrared inductance
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science
Inaccessibility
Sensor location Embedded environment Avoid disturbance to sensing
objects Network adjustment Network retasking
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science
Robustness and Fault Tolerance
Self-adaptive sensors: Adapted to the environment changes. Adapted to the power change.
Distributed network: Each sensor operate autonomously from
neighbors. Overlapped services area. No single point of failure.
Health and status monitoring E.g. reporting power along data transmission
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science
Outline
Why sensor nets? Advantages Applications
Classifications of sensor nets Challenging issues
Common constraints Application-specific constraints
Discussions
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science
Discussions Unique solution to all applications exists? Most important considerations in designing:
Cost? Resource allocation? Manageability? Timeliness? Retasking? …
Scalability? Millions of sensor nodes?
Next generation sensor nets?
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UUNIVERSITY OF NIVERSITY OF MMASSACHUSETTSASSACHUSETTS, A, AMHERST • MHERST • Department of Computer Science Department of Computer Science
The EndThe EndThank you