From Smart Dust to Reliable Networks

1. From Smart Dust to Reliable Networks Kris Pister Prof. EECS, UC Berkeley Founder & CTO, Dust Networks

2. Outline • Background • The Science Project • Market • The Hype • Technology • Challenges • Status • Applications • Open Research Problems

3. Grand Challenge A B C Reliably, at low power

4. Smart Dust Goalc. 1997

5. Smart Dust, 2002 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

6. 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 kbps EEPROM storage (32 KB) Simple sensors

7. 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.

8. Sensor Networks Take Off! Industry Analysts 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)

9. 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

10. $748,000,000 in ‘03 WDRG, 2003

11. Cost of Sensor Networks Mesh Networking Computing Power Installation, Connection and Commissioning Sensors $ Time

12. 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

14. Mesh Systems • Add: MoteIV, Arch Rock • Merged: • Chipcon/Figure8  TI/Chipcon • Integration Associates/CompXs

15. Dust Networks • Founded July 2002 • Angels, In-Q-Tel, ~$1.5M • 28 employees in Jan 04 • Series A Feb 2004 • Foundation • IVP • Series B Feb 2005 • Crescendo • Cargill

16. Network Architecture • Goals • High reliability • Low power consumption • No customer development of embedded software • Customer visibility into all aspects of network operation/status/health • Minimal/zero customer RF/networking expertise necessary • Challenges • 1W emitters in regulated but unlicensed RF bands • Extreme computation and communication resource constraints • MIPS, RAM, bps

17. What do OEMs and SIs want? ^ and scientists and and engineersand startups and grad students and…. • Reliability • Reliability • Reliability • Low installation and ownership costs • No wires; >5 year battery life • No network configuration • No network management • Typically “trivial” data flow • Regular data collection • 1 sample/minute…1 sample/day? • Event detection • Threshold and alarm

18. Reliability • Hardware • Temperature, humidity, shock • Aging • MTBF = 5 centuries • Software • Linux yes (manager/gateway) • TinyOS no (motes) • Networking • RF interference • RF variability

19. Goals • Networks must be • Reliable • count the 9s! • Scalable • thousands to tens of thousands of nodes • Low Power • Self forming, self healing • Zero wires • Flexible • Monitoring, maintenance, log file transfer, … • Battery only or powered infrastructure

20. Challenges • RF environments are dynamic • Time-varying multi-path • Time-varying interference • Sensor Networking is challenging • Traditional traffic models don’t apply • Internet, WiFi • Cell phones • Computational resources are limited

21. Implications of RF Challenges • “Transmit and forget” is unreliable • Lost packets • Single-path networks (trees) are very dangerous • Lost motes • Single-channel networks are fatal • Lost networks

22. RF Solutions • Temporal Diversity • Don’t quit until you get an acknowledgement • Spatial Diversity • Multiple paths from every mote • Frequency Diversity • Frequency hopping in addition to direct sequence spread spectrum

23. IEEE 802.15.4 & WiFi 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

24. 900 MHz cordless phone -50dBm Solid mote signal -20dBm

25. Zigbee 1.0 • Single channel networks are built into standard. This will be fatal for reliability. • Tree-based routing recommended by standard will likely not be adopted, especially given the single-channel radio. • No definition of duty cycling routers • Assumes powered routers, battery powered leaf nodes • No explicit prevention of router duty cycling – Zigbee 2.0?

26. 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

27. 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

28. Radio Reliability in a Crowded Spectrum • UWB? • Unclear potential for duty cycling • DSSS doesn’t cut it • Helpful, but only about 10dB • +20 dBm doesn’t cut it • Helpful, but expensive in batteries • 802.11 & cordless phones • Must frequency hop • Time synchronization required… …but you probably needed that anyway. • Lots of channels, lots of bandwidth, better scaling, …

29. Spatial effect of multipath Slide courtesy Sam Madden, MIT

30. Beware of static measurements and RF pathloss simulations • Site surveys need to be done over at least 24 hours • Simulation tool results need much more speckle Pictures from www.wirelessvalley.com

31. Distance vs. Received Signal Strength -40 -50 -60 RSSI [dBm] -70 -80 -90 -100 0 20 40 60 Distance [meters] 1/R2? 1/R4? Red dots are Friis at 900MHz, GT=GR=1

32. Frequency dependent fading and interference From: Werb et al., “Improved Quality of Service in IEEE 802.15.4 Networks”, Intl. Wkshp. On Wireless and Industrial Automation, San Francisco, March 7, 2005.

33. Path stability vs. Received Signal Strength

39. M Tu W Th F M Tu

40. Real RF links • Indoor propagation • not well modeled by Rk for any k • Attenuation ~ Free space (R2) + Uniform(0,30) dB + rand(t) * uniform(0,30) dB • Not symmetric, time varying • PER is not due to gaussian BER

41. Transmitter efficiency • Transmitter slope efficiency is typically 10—50% but… • Transmitter overhead is typically >10x the max output power, so… • Changing transmit power may be useful for interference reasons, but it has little effect on battery life Transmitter efficiency Pout [mW] 1 0 20 25 Pin [mW]

42. Energy per packet • Energy spent in turning on the transmitter and sending packet overhead (preamble, start symbol, headers and footers) typically exceeds the energy cost of the payload, often by 10x • The same is true for the receiver, but how do you know when to turn it on? Energy per packet Etx [uJ] 0 0 Lpayload [bits] 102…103

43. Network Types Why not use 802.11? Full Mesh Star Star-Mesh Powered mesh infrastructure Star-connected sensors No infrastructure Mesh-connected sensors X X

44. Time Diversity • Link-level acknowledgement • Keep trying until you get confirmation of success • Assume packet error rate, PER=20%=0.2 • Try N times • Overall failure probability is (PER)N • Overall success probability is 1- (PER)N

45. Path diversity • Assume overall reliability is 99% on each of k paths • Probability of success on at least one path is 1 - (1-0.99)k • k=2  99.99% • Path diversity allows smooth recovery from unexpected events • Alarms are generated in network and flow to manager • Manager takes appropriate action (e.g. add bandwidth, new parent, …)

46. Min_Parents = 2

47. Power-optimal communication A B A wakes up and listens B transmits B receives ACK A transmits ACK Worst case A/B clock skew • Assume all motes share a network-wide synchronized sense of time, accurate to ~1ms • For an optimally efficient network, mote A will only be awake when mote B needs to talk Expected packet start time

48. Packet transmission and acknowledgement Radio TX startup ACK RX Packet TX Radio TX/RX turnaround Mote Current Energy cost: 295 uC

49. Fundamental platform-specific energy requirements • Packet energy & packet rate determine power • (QTX + QRX )/ Tpacket • E.g. (300 uC + 200 uC) /10s = 50 uA

50. Idle listen (no packet exchanged) ACK RX Radio RX startup Mote Current Energy cost: 70 uC