1. 1 Introduction to Wireless Sensor Networks and its H/W Design Experiences Paper from: P. Zhang, C. Sadler, S. Lyon, and M. Martonosi, “ Hardware Design Experiences in ZebraNet, ” Proceedings of SenSys 2004, November 2004 Yueh-yi Wang 2005.11.17

2. 2 Outline  Introduction to WSN  Hardware and system architecture of WSN  Case study: ZebraNet  Summary & conclusions

3. 3 Introduction to WSN – Why WSN?  Personal & institutional security  National defense  Radiology, medicine  Chemical plants  Toxic urban locations  Agriculture  Natural hazards  Many others …

4. 4 Application of Sensors in - Environment Monitoring  Measuring pollutant concentration  Pass on information to monitoring station  Predict current location of pollutant contour based on various parameters  Take corrective action Pollutants monitored by sensors in the river bed Sensors report to the base monitoring station BS

5. 5 Sensors in Unknown Terrain

6. 6 Composition of a sensor(-actuator) node  Portable and self-sustained (power, communication, intelligence)  Capable of embedded complex data processing  Note: Power consumed in transmitting 1Kb data over 100m is equivalent to 30M Instructions on 10MIPS processor  Technology trends predict small memory footprint may not be a limitation in future sensor nodes  Equipped with multiple sensing, programmable computing and communication capability Sensing + CPU + Radio = Thousands of potential applications

7. 7 EmbedSense ™ Wireless Sensor A Wireless sensor and data acquisition system  Can be placed within implants on spining machinery and within composite materials  No batteries - big advantage  Uses an inductive link to receive power from external coil  Can be used in monitoring temperatures in Jet turbine engines  www.microstrain.com www.microstrain.com

8. 8 Different from traditional networks  Sensor networks are “data-centric” networks  Unique ID not effective in sensor networks large number of nodes imply large id, thus, data sent may be less than the address  Adjacent nodes may have similar data

9. 9 Hardware architecture of WSN- Parameters  Cost  Lifetime  Performance Speed (in ops/sec, in ops/joule) Comms range (in m, in joules/bit/m) Memory (size, latency)  Capable of concurrent operation  Reliability, security, size, packaging

10. 10 Hardware issue on WSN - A Generic Sensor Network Architecture PROCESSING SUB-SYSTEM COMMUNICATION SUB-SYSTEM SENSING SUB-SYSTEM POWER MGMT. SUB-SYSTEM ACTUATION SUB-SYSTEM SECURITY SUB-SYSTEM

11. 11 Processing subsystem - Illustration

12. 12 Processing subsystem- Microcontroller  von Neumann architecture (same address and data bus for I/D) typical 4 bit, 8 bit, 16 bit or 32 bit architectures speed 4 MHz-400MHz with 10-300 or more MIPS  operate at various power levels: fully active: 1 to 50 mW sleep (memory standby, interrupts active, clocks active, cpu off) sleep (memory retained, interrupts active, clocks active, cpu off) sleep (memory retained, interrupts active, clocks off, cpu off) 5uW latency of wakeup is an issue  fixed point / floating point operations  multiple processors may be used (potentially on same core) could be DSP, FPGA

13. 13 Processing subsystem- Memory  Considerations Speed, capacity, price, power consumption, memory protection  Types: SRAM: typical 0.5KB-64MB  Typical power consumption retained: ~100ua; read/write: ~10ma if separate chip retained: 2ua-100ua, read/write:~5ma if in core DRAM: high power consumption in retained mode Flash: 256KB-1GB or beyond  Typical power consumption retained: negligible; read/write: ~7/20ma erase operation is expensive  Large flashes are outside of core EEPROM:4KB-512KB, often used as program store

14. 14 Processing subsystem- Peripherals  Clock generators / Dividers  Hardware Timers  Peripheral interfaces (for sensors, actuators, I/O, power) (analog and digital) (multiple buses with bridges between them) SPI: Serial Peripheral Interface I2C UART: Serial communication General Purpose Input Output pins (GPIO)

15. 15 Processing subsystem- Peripherals (contd.)  Interrupts: Asynchronous breaks in program execution  Press of a button; expiration of a timer; completion of sensing data collection, of DMA transfer, of transmission event, … When interrupt occurs, processor transitions to the corresponding interrupt handler to service interrupt and then resumes execution Can have multiple priority levels Interrupts are enabled and disabled through registers for each peripheral

16. 16 Processing subsystem- Timers Controls the mode (interval or one-shot) Starts and stops the timer Enables/disables the interrupts for this timer Holds value to compare against Holds the value that initializes the timer at startup

17. 17 Sensor Subsystem  Multiple types of sensors may be used: Environmental: pressure, gas composition, humidity, light… Motion or force: accelerometers, rotation, microphone, piezoresistive strain, position… Electromagnetic: magnetometers, antenna, cameras… Chemical/biochemical  Digital or analog output  MEMS enabling

18. 18 Power Management Subsystem  Voltage regulator typical ranges: 1.8V, 3.3V, 5V multiple voltages for various subsystem/power levels  Gauges for voltage or current battery monitor (allows software to adapt computation)  Control of subsystems wakeup/sleep  Control of platform clock rate, processor voltage

19. 19 Communication Subsystem IEEE 802.11 Bluetooth Mote Energy per bit Startup time Idle current Technology Data Rate Tx Current Energy per bit Idle Current Startup time Mote 76.8 Kbps 10 mA430 nJ/bit7 mALow Bluetooth1 Mbps45 mA149 nJ/bit22 mAMedium 802.1111 Mbps300 mA90 nJ/bit160 mAHigh

20. 20 Design Principles  Key to Low Duty Cycle Operation: Sleep – majority of the time Wakeup – quickly start processing Active – minimize work & return to sleep W total =R sleep *W sleep + R wake *W wake + R active *W active W: Power Dissipation R: Ratio of the time period Dynamic Power Consumption  P dynamic = C switched * V DD 2 * f clk

21. 21 Case Study: Hardware Design Experiences in ZebraNet  Biologists Wishlist Lightweight Detailed 24/7 archival position logs Mobile No fixed base station (no cellular service) Restricted human access to systems  ZebraNet: Wireless ad hoc network on zebras Intelligent tracking collars placed on sampled set of zebras Sensor network: data collected includes  GPS position info, temperature, … ➨ Energy-efficient ➨ GPS-enabled ➨ Wireless ➨ Peer-to-peer routing and data storage ➨ Plan 1 year of autonomous operation

22. 22 ZebraNet vs. Many Other Sensor Networks …  All nodes mobile: Even “ base station ” is mobile; intermittent drive-bys upload data  Large spatial extent 100s-1000s of sq. kilometers  “ Coarse-Grained ” nodes: Storage and processing capability >> many other sensor systems  Long-running and autonomous Reliability and energy-efficiency are key

23. 23

24. 24 Hardware Evolution

25. 25 Other Evolution  Change of -controller Main reason is the variable clock frequency. Lower power usage (switching clocks) TI MSP430F149 allows multiple clocks  32 KHz in sleep mode  8 MHz in normal mode  32 KHz clock consumes 0.05 mA more than sleep

26. 26 Important Features  Nodes obtain GPS reading every 8 minutes  GPS can sync to global clock  Nodes attempt to send information over radio every 2 hours  All data logged to onboard flash (local as well as received)  ~256 bytes per hour

27. 27 ZebraNet Protocols  Two peer-to-peer protocols evaluated here Flooding: Send to everyone found in peer discovery. History-Based: After peer discovery, choose at most one peer to send to per discovery period: the one with best past history of delivering data to base.

28. 28 Zebra show time Solar Power with loosely rotated => efficiency dropped

29. 29 GPS Data for 1 Zebra Over 24 Hours

30. 30 Power Consumption  Radio Tx consumes the most critical power.  The 2nd one is GPS.  Radio Rx takes the longest time while working.  Not much difference on u-C under 8MHz and 32KHz (odd?) Dynamic Power Consumption P dynamic = C switched * V DD 2 * f clk

31. 31 Summary and Conclusions  New design approach derived from the experience with resource constrained wireless sensor networks Active mode needs to run quickly to completion Wakeup time is crucial for low power operation  Wakeup time and sleep current set the minimal energy consumption for an application Sleep most of the time  Tradeoffs between complexity/robustness and low power radios  Careful integration of hardware and peripherals

32. 32 Summary and Conclusions  Hardware choice worked very well for sparse node- to-node communication  Simplicity of software environment dictated - controller choice  Details matter in WSN power management  Future work of ZebraNet

33. 33 Thank you