1. April 27, 20051 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)

2. April 27, 20052 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

3. April 27, 20053 Evolution : Extreme Scale (“ExScal”) Scenarios 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 ExScal Focus Areas: Applications, Lifetime, and Scale

4. April 27, 20054 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

5. April 27, 20055 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?

6. April 27, 20056 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 –UIUC –University of Virginia –MITRE/NGC/others Why this mix? Easy classification: –Noise =  PIR   MAG   MIC –Civilian = PIR   MAG   MIC –Soldier = PIR  MAG  MIC –Vehicle = PIR  MAG  MIC

7. April 27, 20057 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?

8. April 27, 20058 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 –< 6WHr capacity –Average power < 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

9. April 27, 20059 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 T DC = 1.07 draws  7% of power budget –Radio needed to forward event detections and meet latency

10. April 27, 200510 Quality vs. Lifetime : Sensor Operation Low (<< P budget ) Medium (< P budget ) High (  P budget ) Short (<< T event ) Duty-cycle or Always-on Duty-cycle Medium (< T event ) Duty-cycle or Always-on ?? Long (  T event ) Always-on?Unsuitable Power Consumption (with respect to budget) Startup Latency (with respect to event duration)

11. April 27, 200511 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

12. April 27, 200512 Quality vs. Lifetime : Passive Infrared Sensor Quad PIR sensors –Power consumption: low –Startup latency: long –Operating mode: always-on –Sensor role: wakeup sensor

13. April 27, 200513 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

14. April 27, 200514 Quality vs. Lifetime : Magnetic Sensor Magnetometer –Power consumption: high –Startup latency: medium (LPF) –Operating mode: triggered

15. April 27, 200515 Quality vs. Lifetime : Passive Vigilance Trigger network includes hardware wakeup, passive infrared, microphone, magnetic, fusion, and radio, arranged hierarchically Nodes: sensing, computing, and communicating processes Edges:  False Alarm Rate Energy Usage HighLow High Energy-Quality Hierarchy 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…

16. April 27, 200516 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 H 0 & H 1 How to Optimize Energy-Quality? –Let x* = (x 1 *, x 2 *,..., x n *) be the n decision boundaries between H 0 & H 1. for n processes. Then, given a set of ROC curves, optimizing for energy-quality is a matter of minimizing the function f(x*) = E[power(x*)] subject to the power, probability of detection, and probability of false alarm constraints of the system.

17. April 27, 200517 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?

18. April 27, 200518 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

19. April 27, 200519 Engineering Considerations: Wireless Retasking No hardware protection Basic idea presented by Stajano and Anderson Once started –You can’t turn it off –You can only speed it up Our implementation:

20. April 27, 200520 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”

21. April 27, 200521 Engineering Considerations: Packaging

22. April 27, 200522 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

23. April 27, 200523 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

24. April 27, 200524 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

25. April 27, 200525 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. 

26. April 27, 200526 Discussion

27. April 27, 200527 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

28. April 27, 200528 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

29. April 27, 200529 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…

30. April 27, 200530 Quality vs. Lifetime : Duty-Cycling Sensors Acoustics: duty-cycling possible for “periodic snippets” Magnetic: duty-cycling impossible (Power avg, f s and T startup conflict) Infrared: duty-cycling impossible (T startup too big, but not needed)

31. April 27, 200531 Differing Energy Usage Patterns

32. April 27, 200532 Quality vs. Lifetime : Passive Vigilance 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… Trigger network includes hardware wakeup, passive infrared, microphone, magnetic, fusion, and radio, arranged hierarchically Nodes: sensing, computing, and communicating processes Edges:  False Alarm Rate Energy Usage HighLow High Energy-Quality Hierarchy

33. April 27, 200533 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 (> 30 days) –Latency: 10 – 30 seconds –Coverage: 10km^2 (could not meet given constraints) Supportability –Adaptive: Dynamic reconfiguration of thresholds, etc.

34. April 27, 200534 XSM RF Performance

35. April 27, 200535 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: T startup = 40ms, P ss = 18mW –UWB Radar: T startup = 30s, P ss = 45mW –Optimistic lifetime: 6000mWh / 63mW < 100 hrs –Must lower power Radio –Fix anisotropic radiation and impedance mismatch

36. April 27, 200536 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 XSM MICA2 + Improved RF + Low-power sensing + Recoverability Passive Vigilance-Wakeup-Active XSM2 XSM + Improvements + Bug Fixes

37. April 27, 200537 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)