SENS: A Sensor, Environment and Network Simulator

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• SENS A Sensor, Environment and Network Simulator
• Sameer Sundresh, Wooyoung Kim and Gul Agha
• University of Illinois at Urbana-Champaign
• http//osl.cs.uiuc.edu
• Presented at ANSS 37
• April 21, 2004

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What is a Sensor Network?

• Many simple nodes with sensors deployed
  throughout an environment.
• Determination of sensor positions (localization)
• Cooperative target identification tracking
• Indoor or outdoor environment monitoring
• Civil structural health monitoring (SHM)

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Example Localization Experiment
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Example Structural Health Monitoring
Accelerometer board prototype, Ruiz-Sandoval,
Nagayama Spencer, Civil E., U. Illinois
Urbana-Champaign
Semi-active Hydraulic Damper (SHD), Kajima
Corporation, Japan
Model bridge with attached wireless sensors, B.F.
Spencers Lab, Civil E., U. Illinois U-C
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Characteristics of Sensor Networks

• Errors are common.
• Wireless communication
• Noisy measurements
• Node failures are to be expected
• Network interacts heavily with environment.
• Highly constrained nodes.
• e.g. 4k RAM, 2 AA batteries, 20msg/s radio
• Must operate for months, little supervision.
• Experiments are time- and space-intensive.

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Related Work

• Custom application-specific simulators
• Network simulators
• OPNET, ns-2, Monarch (based on ns-2), GloMoSim
• Sensor network wireless protocol simulators
• UCLA SensorSim, GeorgiaTech SensorSimII
• Sensor node simulators
• TOSSIM (for TinyOS), TOSSF (based on SWAN)
• Application-oriented simulators
• SENS, Siesta, EmStar

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Simulator Structure
SENS is composed of several concurrently
interacting components modeled as actors.
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Simulator Components

• Application
• sense/actuate interface
• message send/receive interface
• Physical
• handles sense/actuate together with Environment
• maintains radio sensor neighbor sets
• computes power usage (based on actuate requests
  to enable/disable simulated hardware)
• Network
• handles send/receive
• several interchangeable implementations

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Simple Application

• include "System/Sim.h"include
  "Interfaces/PhysicalMessages.h"// Message type
  definitions.MESSAGE_TYPE(AppMesg, int)//
  Application to be simulated on a node.class
  SimpleApplication public Application public
  SimpleApplication(SimController sc, node_id
  id_, vectorltstringgt args)
  Application(sc, id_) schedule(new
  AppMesg(77), 0.5) // Send message to self.
  registerHandler(SimpleApplicationonAppMes
  g) registerHandler(SimpleApplication
  onSensorValue) // Message handlers.
  void onAppMesg(AppMesg ) cout
  ltlt "I'm not really listening. " ltlt getTime() ltlt
  endl send(new AppMesg(77), 0.3) //
  Radio neighborhood broadcast. void
  onSensorValue(SensorValue sv) cout
  ltlt getTime() ltlt " SA " ltlt id ltlt " sensed
  something " ltlt endl // Add
  SimpleApplication to the ComponentRegistry so it
  is instantiable from config files.static
  RegisterApplicationltSimpleApplicationgt
  re_app("SimpleApplication")

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Network Components

• Trade off simulation efficiency and accuracy
• SimpleNetwork immediate, guaranteed delivery to
  all neighbors within range.
• ProbLossyNetwork probabilistic delivery and
  delay delivery probabilities can optionally
  decrease under heavy traffic.
• CollisionLossyNetwork calculates collisions at
  receiving end based on message overlap and
  relative signal strengths selectable interval
  size.

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Environment Simulation

• Environment is divided into tiles with different
  signal propagation characteristics.
• Based on experimental measurements.
• Each sensor is located on one tile.

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Environment Simulation

• Environment is divided into tiles with different
  signal propagation characteristics.
• Based on experimental measurements.
• Each sensor is located on one tile.

Maximum range cut-off
Soundmuffled by grass
Echo
Beep!
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Circular Wave Propagation
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Circular Wave Propagation
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Measurement and Attenuation

• Must translate total energy passing through a
  tile to energy of the signal received by a
  sensor.
• Can use f to calculate energy density.
• Else divide total energy by max. arclength,
  approx. by sin?cos?.
• Circular waves 2-D 1/r
• Simulate 3-D 1/r2 by propagating
  sqrt(energy)
• To simulate attenuation A observed by real
  sensors, apply M-1(A(M(e))).

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Simulation Parameters

• Determines behavior of nodes and signals.
• Can be adjusted forother scenarios.

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Observed Mica-2 Radio Range (sketch)
40 signal strength variation with angle
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Ranging Simulation vs. Experiment

• Wall effects evident.
• Similar behavior.
• Experiment was separate from calibration.

3m tall, 2/3m thick brick wall
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Simplified Localization Example

• Typical sensor data is location-dependent, hence
  localization is a necessary service.
• Anchor nodes know their locations.
• Perform triangulationusing ranging data.
• Errors due to obstacles(indirect sound paths).
• Anchor
• Grass or wall
• Real vs. localized

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Ranging/Localization Complications
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Localization vs. Obstacle Density
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Non-Anchor Power Usage Simulation

• Power savings of the black listing policyIf a
  non-anchor believes it will not make a successful
  ranging measurement to an anchor, it should not
  even bother trying.

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Simulator Performance

• n sensor nodes
• t simulated time
• Exec. time O(nt),PC much faster than sensor
  node
• Setup time O(n2) interactions

Time to simulate 1000 seconds ofsimplified
localization application.
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Ongoing Work

• More detailed measurements of node behavior
• acoustic ranging in presence of wind, echoes
• radio signal strength (e.g. imperfect antenna)
• inter- and intra-node timing characteristics
• Civil structure environment model
• Matlab model for environment
• Experimental validation of sensor simulations

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Ongoing Work

• Language/API refinement
• deployable sensor node code
• automatic annotation of timing and power
• Use in sensor network service development
• localization (acoustic, radio)
• Soham Mazumdar, Ashish Agarwal, Indranil Gupta,
  Wooyoung Kim Gul Agha, Fast Range Queries
  Using Pre-Aggregated In-Network Storage,
  submitted to ACM SenSys 2004.
• structural health monitoring
• geographic routing

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• http//osl.cs.uiuc.edu

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End of slides.
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A Typical Wireless Sensor Node

• Mica-2 from Crossbow
• 4MHz 8-bit Atmel AVR
• 4096 bytes RAM
• 128kB flash for program code
• 433MHz, 32kb/s radio ( 20 30-byte messages/s)
• Powered by 2 AA batteries
• Mica-2 sensor board
• 4kHz audio buzzer microphone tone detector
• 2-axis accelerometer, 2-axis magnetometer
• light/temperature sensor
• Currently costs 150, eventually under 10.