Introduction to Wireless Sensor Networks and its H/W Design Experiences

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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
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Outline

• Introduction to WSN
• Hardware and system architecture of WSN
• Case study ZebraNet
• Summary conclusions

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Introduction to WSN Why WSN?

• Personal institutional security
• National defense
• Radiology, medicine
• Chemical plants
• Toxic urban locations
• Agriculture
• Natural hazards
• Many others

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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

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Sensors in Unknown Terrain
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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
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EmbedSense Wireless SensorA 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

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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

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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

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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
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Processing subsystem - Illustration
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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

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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/write5ma 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
• EEPROM4KB-512KB, often used as program store

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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)

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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

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

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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

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Communication Subsystem
Startup time
Idle current
Energy per bit
Technology Data Rate Tx Current Energy per bit Idle Current Startup time
Mote 76.8 Kbps 10 mA 430 nJ/bit 7 mA Low
Bluetooth 1 Mbps 45 mA 149 nJ/bit 22 mA Medium
802.11 11 Mbps 300 mA 90 nJ/bit 160 mA High
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Design Principles

• Key to Low Duty Cycle Operation
• Sleep majority of the time
• Wakeup quickly start processing
• Active minimize work return to sleep
• WtotalRsleepWsleep RwakeWwake
  RactiveWactive
• W Power Dissipation
• R Ratio of the time period
• Dynamic Power Consumption
• Pdynamic Cswitched VDD2 fclk

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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

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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 gtgt many other sensor systems
• Long-running and autonomous
• Reliability and energy-efficiency are key

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Hardware Evolution
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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

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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

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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.

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Zebra show time
Solar Power with loosely rotated gt efficiency
dropped
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GPS Data for 1 Zebra Over 24 Hours
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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 Pdynamic Cswitched
VDD2 fclk
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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

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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

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• Thank you