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Wireless Sensor Networks SMART DUST from vision to products

Wireless Sensor Networks SMART DUST from vision to products. Kris Pister Prof. EECS, UC Berkeley Founder & CTO, Dust Networks. Wireless Sensor Networking. Decision Systems. Significant reduction in the cost of installing sensor networks Enables new class of services

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Wireless Sensor Networks SMART DUST from vision to products

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  1. Wireless Sensor NetworksSMART DUSTfrom vision to products Kris Pister Prof. EECS, UC Berkeley Founder & CTO, Dust Networks

  2. Wireless Sensor Networking Decision Systems • Significant reduction in the cost of installing sensor networks • Enables new class of services • Increases sensor deployment Monitoring Systems Control Systems Enterprise Applications Digital Sensors and Actuators Serial Devices Analog Sensors and Actuators Physical World

  3. Outline • History • Technology • Markets & Standards • Future

  4. Smart Dust History • 1992 Rand workshop • Future Technology Driven Revolutions in Military Operations • “Military Applications of MEMS”, K. Brendley, R. Steeb • 1994—1997? DARPA ISATs • 1995 coined “Smart Dust” • 1997 wrote Smart Dust proposal to DARPA/MTO • Goal: sensing and comm. from 1 cubic millimeter • 2002 Founded Dust Inc (now Dust Networks) • Jan 2003 – Dec 2004 on leave as CEO then CTO of Dust Networks

  5. Low Power Radio Projects Flashback: BSAC IAB Spring 2000 • LWIM (Bill Kaiser, UCLA) • 902-928MHz, 1mW goal • 1-1-1 SHARC (Tom Lee, Stanford) • 1 GHz, 1mW, 1mm2 goal • picoRadio (Rabaey/ Brodersen, BWRC, UCB) • 100uW, 0.1nJ/bit goal • …

  6. Lance Doherty, Jason Hill, Michael Scott, Robert Szewczyk,Alec Woo Flashback: BSAC IAB Spring 2001 Summary: • Use COTS to develop and deploy sensor networks • Research applications, security, and management of networks Recent results: • TinyOS released (30+ students at first short course) • Motes available from Crossbow (~$150) Future work: • Air-drop deployment of sensor network • Large-scale networks on campus Prof. Pister KSJP12 Off-the-shelf Macromote for Smart Dust and TinyOS Needle piercing pig skin

  7. UCB “COTS Dust” Macro Motes Services David Culler, UCB Networking TinyOS Rene 00 Mica 02 Dot 01 Demonstrate scale • Designed for experimentation • sensor boards • power boards NEST open exp. platform 128 KB code, 4 KB data 50 KB radio 512 KB Flash comm accelerators WeC 99 James McLurkin MS Small microcontroller - 8 kb code, 512 B data Simple, low-power radio - 10 kb EEPROM storage (32 KB) Simple sensors

  8. University Demos – Results of 100 man-years of research Motes dropped from UAV, detect vehicles, log and report direction and velocity Intel Developers Forum, live demo 800 motes, 8 level dynamic network, 50 temperature sensors for HVAC deployed in 3 hours. $100 vs. $800 per node. Seismic testing demo: real-time data acquisition, $200 vs. $5,000 per node vs.

  9. 800 node demo at Intel Developers Forum Self-configuring Self-healing Scalable Dynamic

  10. Seismic Structural Monitoring . Mote Infrastructure Goal: 100 sensors on three floors Traditional Infrastructure

  11. Energy Monitoring/Mgmt System • 50 nodes on 4th floor • 5 level ad hoc net • 30 sec sampling • 250K samples to database over 6 weeks

  12. 29 Palms Sensorweb Experiment Goals • Deploy a sensor network onto a road from an unmanned aerial vehicle (UAV) • Detect and track vehicles passing through the network • Transfer vehicle track information from the ground network to the UAV • Transfer vehicle track information from the UAV to an observer at the base camp.

  13. 8 packaged motes loaded on plane • Last 2 motes being dropped

  14. Smart Dust - Integration RECEIVER OPTICAL IN SENSORS ADC FSM 375 kbps 16 mm3 total circumscribed volume ~4.8 mm3 total displaced volume 8-bits PHOTO TRANSMITTER OPTICAL OUT 175 bps 1V 1-2V 3-8V 1V 1V 2V SOLAR POWER

  15. First sub-mW 900MHz radio Molnar, Lu, Lanzisera, Cook, Pister, CICC 2004 650mm Oscillator Divider Transmitter Receiver 875mm Inductor Chip

  16. UCB RF Mote on a Chip antenna uP SRAM Temp inductor Amp Radio ADC ~2 mm^2 ASIC crystal battery Optimistic! • CMOS ASIC • 8 bit microcontroller • Custom interface circuits • 4 External components ~$1

  17. Final UCB Hardware Results • 2 chips fabbed in 0.25um CMOS • “Mote on a chip” worked, missing radio RX (Jason Hill) • 900 MHz transceiver worked • Records set for low power CMOS • ADC (Mike Scott) • 8 bits, 100kS/s • 2uA@1V • Microprocessor (Brett Warneke) • 8 bits, 1MIP • 10uA@1V • 900 MHz radio (Al Molnar) • 20kbps, “bits in, bits out” • 0.4mA @ 3V

  18. Power Consumption • Sensing • Sensor Excitation • Sensor Interface • Amplifiers, filters, ADC • Data processing • Communication • PHY/MAC/NET Algorithms/computation • Encryption/security • Radio TX • Radio RX • Distributed Signal Processing • Time keeping • Leakage

  19. Radio Performance 25 20 15 IRX (mA) 10 5 100k Bit rate (bps) 300k 200k X cc2400 X cc2420 X Xemics cc1000 X X cc1000 X cc1000 Molnar (0.4mA) X X Otis (0.4mA)

  20. Power consumption versus data rate 1yr AA 2 weeks AA 1yr cr2032 Improved Hardware Software/algorithms 100M 802.11 a,b,g 1 M 802.15.4 Application Data Rate (bps) Cordless phones 10k 100 1 10m 100m 1m 10m 100m 1 10 Average Power consumption (W)

  21. Dust Networks • Incorporated July 2002 • Pister on leave Jan 2003  Dec 2004 • Series A Feb 2004 • Series B Jan 2005 • SmartMesh shipped Aug 2004

  22. Configure, don’t compile SmartMeshTM Console IP Network XML SmartMesh Manager Mote ~100 ft Reliability: 99.9%+ Power consumption: < 100uA average

  23. Energy Monitoring Pilot • Honeywell Service: monitor, analyze and reduce power consumption • Problem: ~$500/sensor wiring cost • Solution: Dust SmartMesh • Entire SmartMeshTM network installed in 3 hours (vs. 3-4 days) • 9 min/sensor

  24. Micro Network Interface Card Network Services Configurable Filter/Feedback Analog I/O Digital I/O Serial Port mNIC • No network software development • Variety of configurable data processing modules • Integrators develop applications, not mesh networking protocols • For compute-intensive applications, use an external processor/OS of your choice.

  25. Configurable Data Processing Network Services Configurable Filter/Feedback IP Network XML Analog I/O Digital I/O Serial Port SmartMesh Manager • Input Channel Configuration • Analog range, calibration • Sample rate • Input Filters • Accumulation • Min/mean/max • Theshhold • Control • Digital and Analog • Local & Network loops

  26. SAIC & Dust Networks Passive IR Passive IR and Camera 1.5 in MEMS and GPS 2.5 in 2.5 in

  27. Markets & Standards

  28. The Wireless World Size of market b/s (Sensor & Control Data) Sensors Kb/s (Voice) Decreasing Bandwidth Cellphones Wi-Fi Mb/s (Video) Hours Days Years Increasing Battery Life

  29. Sensor Networks Take Off! $8.1B market for Wireless Sensor Networks in 2007 Source: InStat/MDR 11/2003 (Wireless); Wireless Data Research Group 2003; InStat/MDR 7/2004 (Handsets)

  30. WDRG, 2003

  31. Sensor Networking Evolution Wireless Mesh • Very high reliability • $ Installation • Very Flexible Network • Long Reach Wired Networks • Very high reliability • $$$$ Installation • Inflexible Network Point-to-Point Wireless • Low reliability • $$ Installation • Flexible Network • Limited Reach

  32. Low Data Rate WPAN Applications (Zigbee) PERSONAL HEALTH CARE BUILDING AUTOMATION CONSUMER ELECTRONICS security HVAC AMR lighting control accesscontrol TV VCR DVD/CD remote PC & PERIPHERALS INDUSTRIAL CONTROL asset mgt process control environmental energy mgt mouse keyboard joystick RESIDENTIAL/ LIGHT COMMERCIAL CONTROL patient monitoring fitness monitoring security HVAC lighting control access control lawn & garden irrigation

  33. Consumer vs Enterprise Class CONSUMER ELECTRONICS PC & PERIPHERALS INDUSTRIAL CONTROL RESIDENTIAL/ LIGHT COMMERCIAL CONTROL DUST NETWORKS DEFENSE BUILDING AUTOMATION PERSONAL HEALTH CARE • Consumer Class • Cost more important than reliability • Convenience driven • - Deployed in small area • - ‘Device’ driven Enterprise Class - Reliability more important than cost - Installation & mtce cost driven - Deployed in larger area - ‘System’ driven

  34. 802.15.4, Zigbee • Zigbee is an industry consortium created to apply 802.15.4 to commercial applications • “Toolkit” functionality of PHY and low-level MAC in 15.4 • Device/application profiles defined in Zigbee

  35. Network Types Full Mesh Star Star-Mesh Powered mesh infrastructure Star-connected sensors No infrastructure Mesh-connected sensors

  36. Cluster-tree Topology Clustered stars - for example, cluster nodes exist between rooms of a hotel and each room has a star network for control. Communications flow Full function device Reduced function device

  37. Techno-Rant • Reduced function devices are a non-starter for most applications • Tree-based routing is fatal • Cluster-tree combines both • Mesh != multi-hop • Mesh = path diversity • Fixed frequency is fatal • Wireless means no wires

  38. IEEE 802.15.4 PHY Overview Operating Frequency Bands Channel 0 Channels 1-10 2 MHz 868MHz / 915MHz PHY 868.3 MHz 902 MHz 928 MHz 2.4 GHz PHY Channels 11-26 5 MHz 2.4 GHz 2.4835 GHz Gutierrez

  39. IEEE 802.15.4 PHY Overview Operating Frequency Bands Channel 0 Channels 1-10 2 MHz 868MHz / 915MHz PHY 868.3 MHz 902 MHz 928 MHz 2.4 GHz PHY Channels 11-26 5 MHz 2.4 GHz 2.4835 GHz Gutierrez

  40. Interoperability • Consumer • Enterprise/OEM • Value of standards: • Speed adoption • Low cost components • Vendor to vendor interoperability? • System to system interoperability?

  41. So what should I use? • Networking Research • Crossbow and/or Moteiv + TinyOS • New Networking product • Buy chips and stacks, write software • 802.15.4 • Zigbee? • Home automation • Chipcon/Figure 8 • “Ember University”? • Application/Solution • Buy a reliable network, develop your product (not embedded software) • Dust Networks

  42. Important Players • Universities • TinyOS (UC Berkeley, UCLA, UW, Vanderbilt, …) • Network Theory • Startup Companies • Chipcon/Figure 8 • Crossbow • Dust Networks • Ember • Millennial Net • Major Corporate Research Groups • Intel • Microsoft • IT: Agilent, Cisco, HP, IBM, FranceTelecom, Nortel • Automation: GE, Honeywell, Johnson Controls, Siemens • Zigbee Alliance

  43. Future

  44. Receivers today and tomorrow Nguyen, Silicon Monolithic Integrated Circuits in RF Systems, 2001

  45. Differential Checkerboard Filter Input ports Input ports Output ports Output ports f0= 173 MHz BW = 110 kHz Ripple < 2dB Rejection = 12dB AIR Operation Footprint: 140 x 140 um [Sunil Bhave, Ph.D. Thesis, Sept 2004]

  46. Integrated Poly-SiGe MEMS/CMOS • Resonator Stacked on Amplifier • smaller area → lower cost • reduced interconnect parasitics • → improved performance • Resonator next to Amplifier • conventional layout Andrea E. Franke, et al, IEEE/ASME JMEMS, 12, 160-171 (2003). Source: R. Howe

  47. Nano Dust? • Nanotube sensors • Nanotube computation • Nanotube hydrogen storage • Nanomechanical filters for low-power RF

  48. Conclusion • Sensor networks are everywhere today • Installation is dominated by wiring costs • Wireless sensor networks are now • Reliable • Easy to integrate & install • Low cost • Projected to be a multi-billion $ industry • MEMS &Nano will reduce cost and improve capabilities moving forward

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