Design of a Wireless Sensor Network Platform for Detecting Rare, Random, and Ephemeral Events

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Design of a Wireless Sensor Network Platform for
Detecting Rare, Random, and Ephemeral Events
Prabal Dutta
with Mike Grimmer (Crossbow), Anish Arora,
Steven Bibyk (Ohio State) and David Culler (U.C.
Berkeley)
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Origins A Line in the Sand

• Put tripwires anywhere in deserts, or other
  areas where physical terrain does not constrain
  troop or vehicle movement to detect, classify,
  and track intruders

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Evolution Extreme Scale (ExScal) Scenarios
ExScal Focus Areas Applications, Lifetime, and
Scale

• Border Control
• Detect border crossing
• Classify target types and counts
• Convoy Protection
• Detect roadside movement
• Classify behavior as anomalous
• Track dismount movements off-road
• Pipeline Protection
• Detect trespassing
• Classify target types and counts
• Track movement in restricted area

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Common Themes

• Protect long, linear structures
• Event detection and classification
• Passage of civilians, soldiers, vehicles
• Parameter changes in ambient signals
• Spectra ranging from 1Hz to 5kHz
• Rare
• Nominally 10 events/day
• Implies most of the time spent monitoring noise
• Random
• Poisson arrivals
• Implies continuous sensing needed since event
  arrivals are unpredictable
• Ephemeral
• Duration 1 to 10 seconds
• Implies continuous sensing or short sleep times
• Robust detection and classification requires high
  sampling rate

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The Central Question

• How does one engineer a wireless sensor network
  platform to reliably detect and classify, and
  quickly report, rare, random, and ephemeral
  events in a large-scale, long-lived, and
  wirelessly-retaskable manner?

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Our Answer

• The eXtreme Scale Mote
• Platform
• ATmega128L MCU (Mica2)
• Chipcon CC1000 radio
• Sensors
• Quad passive infrared (PIR)
• Microphone
• Magnetometer
• Temperature
• Photocell
• Wakeup
• PIR
• Microphone
• Grenade Timer
• Recovery
• Integrated Design
• XSM Users
• OSU
• Berkeley

• Why this mix? Easy classification
• Noise ?PIR ? ? MAG ? ? MIC
• Civilian PIR ? ? MAG ? ? MIC
• Soldier PIR ? MAG ? MIC
• Vehicle PIR ? MAG ? MIC

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The Central Question Quality vs. Lifetime

• How does one engineer a wireless sensor network
  platform to reliably detect and classify, and
  quickly report, rare, random, and ephemeral
  events in a large-scale, long-lived, and
  wirelessly-retaskable manner?

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Quality vs. Lifetime A Potential Energy Budget
Crisis

• Quality
• High detection rate
• Low false alarm rate
• Low reporting latency
• Lifetime
• 1,000 hours
• Continuous operation
• Limited energy
• Two AA batteries
• lt 6WHr capacity
• Average power lt 6mW

• A potential budget crisis
• Processor
• 400 (24mW)
• Radio
• 400 (24mW on RX)
• 800 (48mW on TX)
• 6.8 (411?W on LPL)
• Passive Infrared
• 15 (880?W)
• Acoustic
• 29 (1.73mW)
• Magnetic
• 323 (19.4mW)
• Always-on requires 1200 of budget

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Quality vs. Lifetime Duty-Cycling

• Processor and radio
• Has received much attention in the literature
• Processor duty-cycling possible across the board
• Radio LPL with TDC 1.07 draws ? 7 of power
  budget
• Radio needed to forward event detections and meet
  latency

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Quality vs. Lifetime Sensor Operation
Power Consumption (with respect to budget)
Low (ltlt Pbudget) Medium (lt Pbudget) High (? Pbudget)
Short (ltlt Tevent) Duty-cycle or Always-on Duty-cycle Duty-cycle
Medium (lt Tevent) Duty-cycle or Always-on ? ?
Long (? Tevent) Always-on ? Unsuitable
Startup Latency (with respect to event duration)
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Quality vs. Lifetime Sensor Selection
Key Goals low power density, simple
discrimination, high SNR
2,200 x difference!
Power density may be a more important metric than
current consumption
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Quality vs. Lifetime Passive Infrared Sensor

• Quad PIR sensors
• Power consumption low
• Startup latency long
• Operating mode always-on
• Sensor role wakeup sensor

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Quality vs. Lifetime Acoustic Sensor

• Single microphone
• Power consumption medium (high with FFT)
• Startup latency short (but noise estimation is
  long)
• Operating mode duty-cycled snippets or
  triggered

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Quality vs. Lifetime Magnetic Sensor

• Magnetometer
• Power consumption high
• Startup latency medium (LPF)
• Operating mode triggered

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Quality vs. Lifetime Passive Vigilance
Energy-Quality Hierarchy
High
Low
Multi-modal, reasonably low-power sensors that
are Duty-cycled, whenever possible, and arranged
in an Energy-Quality hierarchy with low (E, Q)
sensors Triggering higher (E, Q) sensors, and so
on
False Alarm Rate
Energy Usage
Low
High

• Trigger network includes hardware wakeup, passive
  infrared, microphone, magnetic, fusion, and
  radio, arranged hierarchically
• Nodes sensing, computing, and communicating
  processes
• Edges lt? E, ? PFAgt ? lt ? E, ? PFAgt

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Quality vs. Lifetime Energy Consumption

• How to Estimate Energy Consumption?
• Power idle power energy/event x events/time
• Estimate event rate probabilistically p(tx)
• from ROC curve and decision threshold for H0
  H1
• How to Optimize Energy-Quality?
• Let x (x1, x2,..., xn) be the n decision
  boundaries between H0 H1. for n processes.
  Then, given a set of ROC curves, optimizing for
  energy-quality is a matter of minimizing the
  function f(x) Epower(x) subject to the
  power, probability of detection, and probability
  of false alarm constraints of the system.

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The Central Question Engineering Considerations

• How does one engineer a wireless sensor network
  platform to reliably detect and classify, and
  quickly report, rare, random, and ephemeral
  events in a large-scale, long-lived, and
  wirelessly-retaskable manner?

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Engineering Considerations Wireless Retasking

• Wireless multi-hop programming is extremely
  useful, especially for research
• But what happens if the program image is bad?
• No protection for most MCUs!
• Manually reprogramming 10,000 nodes is
  impossible!
• Current approaches provide robust dissemination
  but no mechanism for recovering from Byzantine
  programs

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Engineering Considerations Wireless Retasking

• No hardware protection
• Basic idea presented by Stajano and Anderson
• Once started
• You cant turn it off
• You can only speed it up
• Our implementation

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Engineering Considerations Logistics

• Large scale 10,000 nodes!
• Ensure fast and efficient human-in-the-loop ops
• Highly-integrated node
• Easy handling (and lower cost)
• Visual orientation cues
• Fast orientation
• One-touch operation
• Fast activation
• One-listen verification
• Fast verification
• Some observations
• One-glance verification
• Distracting, inconsistent, time-consuming
• Telescoping antenna
• Accidental handle

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Engineering Considerations Packaging
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Evaluation

• Over 10,000 XSM nodes shipped
• 983 node deployment at Florida AFB
• Nodes
• Survived the elements
• Successfully reprogrammed wirelessly
• Reset every day by the grenade timer
• Put into low-power listen at night for
  operational reasons
• Passive vigilance was not used
• PIR false alarm rate higher than expected
• 1 FA/10 minutes/node
• Poor discrimination between person and shrubs

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Conclusions

• Passive vigilance architecture
• Energy-quality tradeoff
• Beyond simple duty-cycling
• Extend lifetime significantly (72x compared to
  always-on)
• Optimize energy, quality, or latency
• Scaling Considerations
• Wirelessly-retaskable
• Highly-integrated system
• One-touch
• One-listen
• DARPA classified the project effective 1/31/05
• Crossbow commercialized XSM (MSP410) on 3/8/05

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Future Work

• Perpetual Deployment
• Evaluate year-long deployment
• 1,000 node sensor network
• Areas surrounding Berkeley
• Trio Mote
• Telos platform
• XSM sensor suite
• Grenade timer system
• Prometheus power system

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Closing Thoughts

• Data Collection
• Phenomena Omni-chronic
• Signal Reconstruction
• Reconstruction Fidelity
• Data-centric
• Data-driven Messaging
• Periodic Sampling
• High-latency Acceptable
• Periodic Traffic
• Store Forward Messaging
• Aggregation
• Absolute Global Time

• Event Detection
• Rare, Random, Ephemeral
• Signal Detection
• Detection and False Alarm Rates
• Meta-data Centric (e.g. statistics)
• Decision-driven Messaging
• Continuous Passive Vigilance
• Low-latency Required
• Bursty Traffic
• Real-time Messaging
• Fusion, Classification
• Relative Local Time

vs. ? ? ? ? ? ? ? ? ? ? ? ?
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Discussion
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Deconstructing Startup Latency

• Low bandwidth sensors
• Humidity
• Temperature
• Large time-constant analog filtering circuits
• PIR band pass filter
• Magnetometer anti-aliasing low pass filter
• Analog filtering is easy on the energy budget
• If analog filtering (e.g. anti-aliasing) required
• Either
• Decouple sensing and signal condition
• Duty-cycle sensor, T/H sensor output, analog
  always-on
• Or
• Use sensing hierarchy with low-quality, low-power
  sensors triggering high-quality, high-power
  sensors

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Common Themes

• Event detection
• Passage of civilians, soldiers, vehicles
• Parameter changes in ambient signals
• Spectra ranging from 1Hz to 5kHz
• Large scale
• Long, linear structures
• Requires 1,000s of nodes for coverage
• Long lifetime
• Network must last for a long period of time

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Quality vs. Lifetime Passive Vigilance

• Multi-modal, reasonably low-power sensors that
  are
• Duty-cycled, whenever possible, and arranged in
  an
• Energy-Quality hierarchy with low (E, Q) sensors
• Triggering higher (E, Q) sensors, and so on

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Quality vs. Lifetime Duty-Cycling

• Sensors
• Acoustics duty-cycling possible for periodic
  snippets
• Magnetic duty-cycling impossible (Poweravg, fs
  and Tstartup conflict)
• Infrared duty-cycling impossible (Tstartup too
  big, but not needed)

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Differing Energy Usage Patterns
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Quality vs. Lifetime Passive Vigilance
Energy-Quality Hierarchy
High
Low
False Alarm Rate
Energy Usage

• Multi-modal, low-power sensors that are
• Duty-cycled, where possible, and arranged in an
• Energy-Quality hierarchy with low (E, Q) sensors
• Triggering higher (E, Q) sensors, and so on

Low
High

• Trigger network includes hardware wakeup, passive
  infrared, microphone, magnetic, fusion, and
  radio, arranged hierarchically
• Nodes sensing, computing, and communicating
  processes
• Edges lt? E, ? PFAgt ? lt ? E, ? PFAgt

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Requirements (of the hardware platform)

• Functional
• Detection, Classification (and Tracking) of
• Civilians, Soldiers and Vehicles
• Reliability
• Recoverable Even from a Byzantine program image
• Performance
• Intrusion Rate 10 intrusions per day
• Lifetime 1000 hrs of continuous operation (gt 30
  days)
• Latency 10 30 seconds
• Coverage 10km2 (could not meet given
  constraints)
• Supportability
• Adaptive Dynamic reconfiguration of thresholds,
  etc.

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XSM RF Performance
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Genesis The Case for a New Platform

• Cost
• Eliminate expensive parts from BOM
• Eliminate unnecessary parts from BOM
• Optimize for large quantity manufacturing and use
• ? Network Scale by 100x (10,000 nodes)
• Reliability How to deal with 10K nodes with bad
  image
• ? Detection range by 6x (10m)
• New sensors to satisfy range/density/cost
  tradeoff
• ? Lifetime 8x (720hrs ? 1000hrs)
• Magnetometer Tstartup 40ms, Pss 18mW
• UWB Radar Tstartup 30s, Pss 45mW
• Optimistic lifetime 6000mWh / 63mW lt 100 hrs
• Must lower power
• Radio
• Fix anisotropic radiation and impedance mismatch

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Hardware Evolution
Telos Low-power CPU 802.15.4 Radio Easy to
use Sleep-Wakeup-Active
MICAz MICA2 - CC1000 802.15.4
Radio Sleep-Wakeup-Active
XSM2 XSM Improvements Bug Fixes
XSM MICA2 Improved RF Low-power sensing
Recoverability Passive Vigilance-Wakeup-Active
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Sensor Suite

• Passive infrared
• Long range (15m)
• Low power (10s of micro Watts)
• Wide FOV (360 degrees with 4 sensors)
• Gain 80dB
• Wakeup
• Microphone
• LPF fc 100Hz 10kHz
• HPF fc 20Hz 4.7kHz
• Gain 40dB 80dB (100-8300)
• Wakeup
• Magnetometer
• High power, long startup latency
• Gain 86dB (20,000)