Wireless Sensor Network Research and Experimental Experience

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Wireless Sensor Network Research and Experimental
Experience

• David Q. Liu, Ph.D.
• Dept. of Computer Science and Engineering
• The Ohio State University
• February 18, 2004

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Outline

• Introduction
• Wireless Sensor Network Architecture
• Network Layer Protocols
• LITeS and Echelon Projects at OSU
• Conclusion

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Sensor Networks

• A sensor network is composed of a large number of
  sensor nodes densely deployed either inside the
  phenomenon or very close to it sensing,
  communication, and data processing
• Features
• Random deployment
• Self-organizing
• Cooperating
• Local computation

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Applications

• Military
• Command, control, communication, intelligence,
  surveillance, reconnaissance, targeting systems
• Health
• Patient monitoring, disable patient helping
• Commercial
• Inventory management, product quality monitoring,
  disaster area monitoring

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Characteristics

• Large number of nodes (versus ad hoc networks)
• Densely deployed
• Prone to failure
• Frequent topological changes
• Broadcast communication (versus point-to-point)
• Limited power, computation, and memory
• No global identification (ID)

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Sensor Networks
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Sensor Node
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Berkeley TinyOS Motes
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Design Factors

• Fault Tolerance
• Power failure, physical damage, environmental
  interference
• Reliability
• Scalability
• Hundreds, thousands, even millions
• Density
• Product Costs
• Cheaper than traditional sensors

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Design Factors

• Hardware Constraints
• Smaller size
• Extreme low power consumption
• High volume density
• Dispensable and autonomous
• Unattended
• adaptive
• Sensor Network Topology
• Deployment (hand-placed, plan dropping,
  rocket/missile delivery
• Position changes, reliability, available energy,
  malfunctioning, task dynamics
• Additional nodes

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Design Factors

• Environment
• Unattended remote geographic areas
• Inside a large machinery at the bottom of an
  ocean
• Contaminated field
• Battlefield
• Home or large building
• Transmission Media
• Radio, infrared, optical media

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Design Factors

• Power Consumption
• A limited power source (lt0.5 Ah, 1.2 V)
• Battery life
• Power conservation and power management

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Sensor Network Protocol Stack
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Network Layer Protocol

• Design Principles
• Network Schemes and Routing Protocols

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Design Principles

• Power Efficiency
• Data-Centric
• Data Aggregation
• Attribute-based addressing and location awareness

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Power Efficiency of Routes

• Choices
• - Max PA
• Min ?
• Min hops
• MaxMin PA

Route 4 T-F-E-Sink, total PA 5. Total ? 6
Route 1 T-B-A-Sink, total PA 4, total ? 3
Route 3 T-C-D-Sink, total PA 3. Total ? 4
Route 2 T-C-B-A-Sink, total PA 6. Total ? 6
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Data Centric Routing

• Assign the sensing tasks to the sensor nodes
• Sink broadcast the interest
• Sensor nodes broadcast an advertisement
• Attribute-based naming
• The areas where the temperature is over 70º F
• versus
• the temperature read by a certain node

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Data Aggregation
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Network Schemes and Routing Protocols

• Small Minimum Energy Communication Network
  (SMECN)
• Flooding
• Gossiping
• Sensor Protocol For Information via Negotiation
  (SPIN)
• Sequential Assignment Routing
• Low-Energy Adaptive Clustering Hierarchy (LEACH)
• Directed Diffusion

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SPIN Protocol
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Direct Diffusion
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Network Layer Protocol Issues

• Higher topology Changes
• Higher Scalability
• Location Awareness

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OSU Research and Experiments

• DARP (Defense Advanced Research Program)s NEST
  (Networked Embedded Software Technology ) Program
• Self-Stabilization in NEST (2001)
• Line in the Sand (LITeS) (2003)
• how to detect, classify, and track various types
  of objects (such as persons and cars) using many,
  resource-poor smart dust sensor nodes (100).
• Echelon (Extreme Scaling) (2003 - 2004)
• to investigate the challenges in scaling to a
  network of 10,000 sensor nodes.

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Military Objective

• Given a relatively large, ad hoc
  perimeter/border,
• use a mote network in open, denied areas
• to extend/support detection, classification
  tracking of intruders
• with good cost performance

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Concept of Operations
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LITeS Military Problem Addressed

• Improve extant carefully-placed unattended ground
  sensors by
• dealing with extended/open/denied areas
• reducing need for careful placement of sensors
  radio repeaters
• automatic instrumentation remote monitoring and
  control
• Metrics
• Cost (dollars per unit area protected)
• Power (watts per unit area protected)
• Robustness (no single point of failure)
• Operational
• ease of distribution to denied areas
• ease of concealment
• ease of deployment effect on force reduction

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Research Objective

• Demonstrate that NEST-middleware enables a
  solution to the military objective in a manner
  that is
• robust (i.e., tolerates uncertain environment)
  
• accurate (i.e., low false negatives low false
  positives)
• cost effective (i.e., using middleware on dense
  set of cheap sensors vs. sparse set of
  resource rich sensors,
  e.g. Steel Eagle or REMBASS)

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LITeS Experiments

• A dense mote, resource poor solution for
  collaborative detection, classification
  tracking
• coherent incoherent coordination
• multi-modal sensing
• sample concept each intruder type has unique
  influence field
• By way of example, the demo involves
• 500 long line/perimeter, with 1 or 2 relays to
  outside network
• detect different types of intruders (vehicles,
  and persons)
• locate with modest accuracy (1-5 meters)
• track at least one intruder of each type,
  maintain approximate count

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Fault Tolerance

• several motes in a region are turned off, and
  then on again
• some mote locations are swapped
• some motes are displaced from their location

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Performance Requirement

• Probability of detection gt 95
• Probability of false alarm lt 1
• Detection latency lt 10 s
• A vehicle misclassified as a person zero
• A soldier misclassified as a person lt 1
• Goal Minimize false positives and false negatives

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Testing Diagram
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Intruders

• Intruders are of one of the following types
• soldier (person carrying metallic objects)
• Tank
• Person
• Intruders may be assumed to generally maintain
  constant heading and speed-range
• aggregate information is assumed to suffice

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Sensors
Enclosed mote with a magnetometer sensor
Enclosed mote with a MIR sensor
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Middleware Services

• Ad hoc network formation, routing
• Time synchronization
• Local matched filter
• Regional matched filter
• Snapshot
• Visualization
• Sensor calibration
• Localization
• Data aggregation
• Power management

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Freeze/Unfreeze the Visualization
Start/Stop the Simulation
Toggle to Turn Topology Display On/Off
Playback the Simulation (Enabled once the
simulation is frozen)
Mote Statistics
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Lines showing Parent-Child Relationships (Orange
end points to parent)
Magnified Mote with Readings Display
Magnified Target with Type/Speed etc.
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Echelon Project

• What is echelon ('e-sh-"län)?
• noun
• A DARPA-funded research project in the NEST
  Program that seeks to model, design, build,
  field, and test the world's largest sensor
  network consisting of over 10,000 nodes.
• A formation.
• A formation of troops in which each unit is
  positioned successively to the left or right of
  the rear unit to form an oblique or step like
  line.
• A flight formation or arrangement of craft in
  this manner.
• A similar formation of groups, units, or
  individuals.

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Echelon Project

• A subdivision of a military or naval force.
• A level of responsibility or authority in a
  hierarchy a rank.
• A diffraction grating consisting of a pile of
  plates of equal thickness arranged stepwise with
  a constant offset.
• (Mil.) An arrangement of a body of troops when
  its divisions are drawn up in parallel lines each
  to the right or the left of the one in advance of
  it, like the steps of a ladder in position for
  climbing.

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Echelon Project

• verb
• To arrange or take place in an echelon.
• What about Echelon Project
• - group sensors in clusters
• - provide the basis for a tactical military
  tool
• - have hierarchical communications and control
• - place nodes regular grid or in parallel
  lines
• - large number of nodes (gt 10,000)

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Conclusions

• Introduction
• Wireless Sensor Network Architecture
• Network Layer Protocols
• LITeS and Echelon Projects at OSU
• Conclusion

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Questions?
Contact Information David Q. Liu The Ohio State
University liuq_at_cis.ohio-state.edu