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Wsn handbook

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narmada alaparthi

The document discusses wireless sensor networks and their components. It describes how sensor nodes are small, low-power devices that can sense environmental conditions like temperature, sound or vibration. They communicate wirelessly over short distances. The document outlines the hardware of sensor nodes, including their limited memory and processing. It also discusses the TinyOS operating system used for sensor networks and its component-based architecture.

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Wireless sensor networks Dr. Narmada Alaparthi
2 Wireless sensor networks A sensor node (mote)  8K RAM, 4Mhz processor  magnetism, heat, sound, vibration, infrared  wireless (radio broadcast) communication up to 100 feet  costs ~$10 (right now costs $200)
3 New Class of Computing year log(peoplepercomputer) streaming information to/from physical world Number Crunching Data Storage productivity interactive Mainframe Minicomputer Workstation PC Laptop PDA
4 Why use a WSN? • Ease of deployment  Wireless communication means no need for a communication infrastructure setup  Drop and play • Low-cost of deployment  Nodes are built using off-the-shelf cheap components • Fine grain monitoring  Feasible to deploy nodes densely for fine grain monitoring
5 Challenges in sensor networks • Energy constraint • Unreliable communication • Unreliable sensors • Ad hoc deployment • Large scale networks • Limited computation power • Distributed execution : Nodes are battery powered : Radio broadcast, limited bandwidth, bursty traffic : False positives : Pre-configuration inapplicable : Algorithms should scale well : Centralized algorithms inapplicable : Difficult to debug & get it right
6 Outline • Applications • Platforms (hw&sw) • WSN services (layers? what layers?) • Comparison with the Internet architecture
7 • Monitoring nesting behavior of birds  Great Ducks experiment • Detecting forest fires • Detecting chemical or biological attacks • Monitoring Redwood trees Ecology monitoring
8 Dense Self-Organized Multihop Network
9R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R 8 8.1 8.2 8.3 8.4 8.5 8.6 8.7 8.8 8.9 Temperature vs. Time Temperature(C) Humidity vs. Time 35 45 55 65 75 85 95 RelHumidity(%) 101 104 109 110 111 2003, unpublished Bottom Top 36m 34m 30m 20m 10m
10 Precision agriculture • Wireless sensor networks can be placed on farm lands to monitor temperature, humidity, fertilizer and pesticide levels • Pesticide and fertilizer can only be applied when and where required  Pesticide and fertilizer per one acre costs $20  Considering 100,000 acres savings of $2 million possible Vineyards BC
11 Equipment Health Monitoring in Semiconductor Fab Fab Equipment Mote + Vibration Sensors Ad Hoc Mote Network Intranet 802.11 Mesh Intranet isolation Root Node • Equipment failures in production fabs is very costly  Predict and perform preemptive maintenance • Typical fab has ~5,000 vibration sensors  Pumps, scrubbers, …  Electricians collect data by hand few times a year  Sample: 10’s kilohertz, high precision, few seconds
12 Put tripwires anywhere—in deserts, other areas where physical terrain does not constrain troop or vehicle movement—to detect, classify & track intruders Project ExScal: Concept of operation
13 Envisioned ExScal customer application Gas pipeline Border control Canopy precludes aerial techniques Rain forest – mountains – water environmental challenges Convoy protection IED Hide Site Detect anomalous activity along roadside
14 ExScal summary • Application has tight constraints of event detection scenarios: long life but still low latency, high accuracy over large perimeter area • Demonstrated in December 2004 in Florida • Deployment area: 1,260m x 288m • ~1000 XSMs, the largest WSN • ~200 XSSs, the largest 802.11b ad hoc network
15 Line in the sand project • Thick line allows detection & classification as intruders enter the protected region; also allows fine grain intruder localization • Grid of thin lines allows bounded uncertainty tracking Thick Entry Line A S S E T 1 km 250 m
16 ExScal sample scenarios Intruding person walks through thick line • (pir) detection, classification, and fine-grain localization Intruding vehicle enters perimeter and crosses thick line • (acoustic) detection, classification, and fine-grain localization Person/ATV traverses through the lines • coarse-grain tracking Management operations to control signal chains, change parameters, and programs dynamically; query status and execute commands
WSN Platforms: Hardware & Software
18 Types of sensor platforms 1. RFID equipped sensors 1. Smart-dust tags  typically act as data-collectors or “trip-wires”  limited processing and communications • Mote/Stargate-scale nodes • more flexible processing and communications 1. More powerful gateway nodes, potentially using wall power
19 Grain-sized nodes  Powered by inductive coupling to a transmission from a reader device to transmit a message back  Available commercially at very low prices × Computation power is severely limited × Can only trasmit stored unique id and variable × Hard to add any interesting sensing capability
20 Matchbox-sized nodes • Mica series, XSM node, Telos • 8-bit microprocessor, 4MHz CPU  ATMEGA 128, ATMEL 8535, or Motorola HCS08 • ~4Kb RAM  holds run-time state (values of the variables) of the program • ~128Kb programmable Flash memory  holds the application program  Downloaded via a programmer-board or wirelessly • Additional Flash memory storage space up to 512Kb.
21 Mica2 and Mica2Dot • ATmega128 CPU – Self-programming • Chipcon CC1000 – FSK – Manchester encoding – Tunable frequency • Low power consumption – 2 AA battery = 3V 1 inch
22 Basic Sensor Board • Light (Photo) • Temperature • Prototyping space for new hardware designs
23 Mica Sensor Board • Light (Photo) • Temperature • Acceleration – 2 axis – Resolution: ±2mg • Magnetometer – Resolution: 134µG • Microphone • Tone Detector • Sounder – 4.5kHz
24 Telos Platform • Low Power  Minimal port leakage  Hardware isolation and buffering • Robust  Hardware flash write protection  Integrated antenna (50m-125m)  Standard IDC connectors • Standards Based  USB  IEEE 802.15.4 (CC2420 radio) • High Performance  10kB RAM, 16-bit core, extensive double buffering  12-bit ADC and DAC (200ksamples/sec)  DMA transfers while CPU off
25 Brick-sized node: Stargate • Mini Linux computers communicating via 802.11 radios  Computationally powerful  High bandwidth  Requires more energy (AA infeasible) • Used as a gateway between the Internet and WSN
26 Stargate
27 Outline • Hardware  RFID, Spec  Mica2, XSM, Telos  Stargate • Software  TinyOS
28 TinyOS • most popular operating system for WSN  developed by UC Berkeley • features a component-based architecture  software is written in modular pieces called components  Each component denotes the interfaces that it provides  An interface declares a set of functions called commands that the interface provider implements and another set of functions called events that the interface user should be ready to handle • Easy to link components together by “wiring” their interfaces to form larger components  similar to using Lego blocks
29 TinyOS • provides a component library that includes network protocols, services, and sensor drivers • An application consists of  a component written by the application developer and  the library components that are used by the components in (1) • An application developer writes only the application component that describes the sensors used in the application, the middleware services configured with the appropriate parameters based on the needs of the application
30 Benefits of using TinyOS • Separation of concerns  TinyOS provides a proper networking stack for wireless communication that abstracts away the underlying problems and complexity of message transfer from the application developer  E.g., MAC layer • Concurrency control  TinyOS provides a scheduler that achieves efficient concurrency control  An interrupt-driven execution model is needed to achieve a quick response time for the events and capture the data  For example, a message transmission may take up to 100msec, and without an interrupt-driven approach the node would miss sensing and processing of interesting data in this period  Scheduler takes care of the intricacies of interrupt-driven execution and provides concurrency in a safe manner by scheduling the execution in small threads.
31 Benefits of TinyOS • Modularity  TinyOS’s component model facilitates reuse and reconfigurability since software is written in small functional modules. Several middleware services are available as well-documented components  Over 500 research groups and companies are using TinyOS and numerous groups are actively contributing code to the public domain
32 RadioTimingSecDedEncode The Complete Application RadioCRCPacket UART UARTnoCRCPacket ADC phototemp AMStandard ClockC bitbytepacket SenseToRfm HW SW IntToRfm MicaHighSpeedRadioM RandomLFSRSPIByteFIFO SlavePin noCRCPacket Timer photo ChannelMon generic comm CRCfilter
33 TOS Execution Model • commands request action  ack/nack at every boundary  call command or post task • events notify occurrence  HW interrupt at lowest level  may signal events  call commands  post tasks • tasks provide logical concurrency  preempted by events RFM Radio byte Radio Packet bitbytepacket event-driven bit-pump event-driven byte-pump event-driven packet-pump message-event driven active message application comp encode/decode crc data processing
34 Event-Driven Sensor Access Pattern • clock event handler initiates data collection • sensor signals data ready event • data event handler calls output command • device sleeps or handles other activity while waiting • conservative send/ack at component boundary command result_t StdControl.start() { return call Timer.start(TIMER_REPEAT, 200); } event result_t Timer.fired() { return call sensor.getData(); } event result_t sensor.dataReady(uint16_t data) { display(data) return SUCCESS; } SENSE Timer Photo LED
35 Programming Syntax • TinyOS 2.0 is written in an extension of C, called nesC • Applications are too  just additional components composed with OS components • Provides syntax for TinyOS concurrency and storage model  commands, events, tasks  local frame variable • Compositional support  separation of definition and linkage  robustness through narrow interfaces and reuse  Interpositioning • Whole system analysis and optimization
WSN Services:
37 WSN services • MAC protocols (BMAC, SMAC, TMAC, etc.) • Topology control (GAF, SPAN, CEC, etc.) • Clustering (Leach, FLOC, etc.) • Time synchronization (Flooding time sync, reference broadcast) • Localization (cricket, range-free techniques...) • Routing (convergecast tree, geographic routing, hierarchical...) • Querying (DSIB, DQT, directed diffusion, etc.) • Tracking (Stalk, Trail, etc.) • Network reprogramming
Comparison to Internet architecture:
39 Compared to Internet • No clear layering; cross layer design is norm • No separation between edge vs core of the network  all nodes are both routers and hosts • End-to-end principle fails  unreliable channels, multihop latency • Ad hoc deployment  timesync, localization, topology control, clustering etc services needed • Routing needs are different...

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Wsn handbook

  • 1. Wireless sensor networks Dr. Narmada Alaparthi
  • 2. 2 Wireless sensor networks A sensor node (mote)  8K RAM, 4Mhz processor  magnetism, heat, sound, vibration, infrared  wireless (radio broadcast) communication up to 100 feet  costs ~$10 (right now costs $200)
  • 3. 3 New Class of Computing year log(peoplepercomputer) streaming information to/from physical world Number Crunching Data Storage productivity interactive Mainframe Minicomputer Workstation PC Laptop PDA
  • 4. 4 Why use a WSN? • Ease of deployment  Wireless communication means no need for a communication infrastructure setup  Drop and play • Low-cost of deployment  Nodes are built using off-the-shelf cheap components • Fine grain monitoring  Feasible to deploy nodes densely for fine grain monitoring
  • 5. 5 Challenges in sensor networks • Energy constraint • Unreliable communication • Unreliable sensors • Ad hoc deployment • Large scale networks • Limited computation power • Distributed execution : Nodes are battery powered : Radio broadcast, limited bandwidth, bursty traffic : False positives : Pre-configuration inapplicable : Algorithms should scale well : Centralized algorithms inapplicable : Difficult to debug & get it right
  • 6. 6 Outline • Applications • Platforms (hw&sw) • WSN services (layers? what layers?) • Comparison with the Internet architecture
  • 7. 7 • Monitoring nesting behavior of birds  Great Ducks experiment • Detecting forest fires • Detecting chemical or biological attacks • Monitoring Redwood trees Ecology monitoring
  • 9. 9R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R 8 8.1 8.2 8.3 8.4 8.5 8.6 8.7 8.8 8.9 Temperature vs. Time Temperature(C) Humidity vs. Time 35 45 55 65 75 85 95 RelHumidity(%) 101 104 109 110 111 2003, unpublished Bottom Top 36m 34m 30m 20m 10m
  • 10. 10 Precision agriculture • Wireless sensor networks can be placed on farm lands to monitor temperature, humidity, fertilizer and pesticide levels • Pesticide and fertilizer can only be applied when and where required  Pesticide and fertilizer per one acre costs $20  Considering 100,000 acres savings of $2 million possible Vineyards BC
  • 11. 11 Equipment Health Monitoring in Semiconductor Fab Fab Equipment Mote + Vibration Sensors Ad Hoc Mote Network Intranet 802.11 Mesh Intranet isolation Root Node • Equipment failures in production fabs is very costly  Predict and perform preemptive maintenance • Typical fab has ~5,000 vibration sensors  Pumps, scrubbers, …  Electricians collect data by hand few times a year  Sample: 10’s kilohertz, high precision, few seconds
  • 12. 12 Put tripwires anywhere—in deserts, other areas where physical terrain does not constrain troop or vehicle movement—to detect, classify & track intruders Project ExScal: Concept of operation
  • 13. 13 Envisioned ExScal customer application Gas pipeline Border control Canopy precludes aerial techniques Rain forest – mountains – water environmental challenges Convoy protection IED Hide Site Detect anomalous activity along roadside
  • 14. 14 ExScal summary • Application has tight constraints of event detection scenarios: long life but still low latency, high accuracy over large perimeter area • Demonstrated in December 2004 in Florida • Deployment area: 1,260m x 288m • ~1000 XSMs, the largest WSN • ~200 XSSs, the largest 802.11b ad hoc network
  • 15. 15 Line in the sand project • Thick line allows detection & classification as intruders enter the protected region; also allows fine grain intruder localization • Grid of thin lines allows bounded uncertainty tracking Thick Entry Line A S S E T 1 km 250 m
  • 16. 16 ExScal sample scenarios Intruding person walks through thick line • (pir) detection, classification, and fine-grain localization Intruding vehicle enters perimeter and crosses thick line • (acoustic) detection, classification, and fine-grain localization Person/ATV traverses through the lines • coarse-grain tracking Management operations to control signal chains, change parameters, and programs dynamically; query status and execute commands
  • 18. 18 Types of sensor platforms 1. RFID equipped sensors 1. Smart-dust tags  typically act as data-collectors or “trip-wires”  limited processing and communications • Mote/Stargate-scale nodes • more flexible processing and communications 1. More powerful gateway nodes, potentially using wall power
  • 19. 19 Grain-sized nodes  Powered by inductive coupling to a transmission from a reader device to transmit a message back  Available commercially at very low prices × Computation power is severely limited × Can only trasmit stored unique id and variable × Hard to add any interesting sensing capability
  • 20. 20 Matchbox-sized nodes • Mica series, XSM node, Telos • 8-bit microprocessor, 4MHz CPU  ATMEGA 128, ATMEL 8535, or Motorola HCS08 • ~4Kb RAM  holds run-time state (values of the variables) of the program • ~128Kb programmable Flash memory  holds the application program  Downloaded via a programmer-board or wirelessly • Additional Flash memory storage space up to 512Kb.
  • 21. 21 Mica2 and Mica2Dot • ATmega128 CPU – Self-programming • Chipcon CC1000 – FSK – Manchester encoding – Tunable frequency • Low power consumption – 2 AA battery = 3V 1 inch
  • 22. 22 Basic Sensor Board • Light (Photo) • Temperature • Prototyping space for new hardware designs
  • 23. 23 Mica Sensor Board • Light (Photo) • Temperature • Acceleration – 2 axis – Resolution: ±2mg • Magnetometer – Resolution: 134µG • Microphone • Tone Detector • Sounder – 4.5kHz
  • 24. 24 Telos Platform • Low Power  Minimal port leakage  Hardware isolation and buffering • Robust  Hardware flash write protection  Integrated antenna (50m-125m)  Standard IDC connectors • Standards Based  USB  IEEE 802.15.4 (CC2420 radio) • High Performance  10kB RAM, 16-bit core, extensive double buffering  12-bit ADC and DAC (200ksamples/sec)  DMA transfers while CPU off
  • 25. 25 Brick-sized node: Stargate • Mini Linux computers communicating via 802.11 radios  Computationally powerful  High bandwidth  Requires more energy (AA infeasible) • Used as a gateway between the Internet and WSN
  • 27. 27 Outline • Hardware  RFID, Spec  Mica2, XSM, Telos  Stargate • Software  TinyOS
  • 28. 28 TinyOS • most popular operating system for WSN  developed by UC Berkeley • features a component-based architecture  software is written in modular pieces called components  Each component denotes the interfaces that it provides  An interface declares a set of functions called commands that the interface provider implements and another set of functions called events that the interface user should be ready to handle • Easy to link components together by “wiring” their interfaces to form larger components  similar to using Lego blocks
  • 29. 29 TinyOS • provides a component library that includes network protocols, services, and sensor drivers • An application consists of  a component written by the application developer and  the library components that are used by the components in (1) • An application developer writes only the application component that describes the sensors used in the application, the middleware services configured with the appropriate parameters based on the needs of the application
  • 30. 30 Benefits of using TinyOS • Separation of concerns  TinyOS provides a proper networking stack for wireless communication that abstracts away the underlying problems and complexity of message transfer from the application developer  E.g., MAC layer • Concurrency control  TinyOS provides a scheduler that achieves efficient concurrency control  An interrupt-driven execution model is needed to achieve a quick response time for the events and capture the data  For example, a message transmission may take up to 100msec, and without an interrupt-driven approach the node would miss sensing and processing of interesting data in this period  Scheduler takes care of the intricacies of interrupt-driven execution and provides concurrency in a safe manner by scheduling the execution in small threads.
  • 31. 31 Benefits of TinyOS • Modularity  TinyOS’s component model facilitates reuse and reconfigurability since software is written in small functional modules. Several middleware services are available as well-documented components  Over 500 research groups and companies are using TinyOS and numerous groups are actively contributing code to the public domain
  • 33. 33 TOS Execution Model • commands request action  ack/nack at every boundary  call command or post task • events notify occurrence  HW interrupt at lowest level  may signal events  call commands  post tasks • tasks provide logical concurrency  preempted by events RFM Radio byte Radio Packet bitbytepacket event-driven bit-pump event-driven byte-pump event-driven packet-pump message-event driven active message application comp encode/decode crc data processing
  • 34. 34 Event-Driven Sensor Access Pattern • clock event handler initiates data collection • sensor signals data ready event • data event handler calls output command • device sleeps or handles other activity while waiting • conservative send/ack at component boundary command result_t StdControl.start() { return call Timer.start(TIMER_REPEAT, 200); } event result_t Timer.fired() { return call sensor.getData(); } event result_t sensor.dataReady(uint16_t data) { display(data) return SUCCESS; } SENSE Timer Photo LED
  • 35. 35 Programming Syntax • TinyOS 2.0 is written in an extension of C, called nesC • Applications are too  just additional components composed with OS components • Provides syntax for TinyOS concurrency and storage model  commands, events, tasks  local frame variable • Compositional support  separation of definition and linkage  robustness through narrow interfaces and reuse  Interpositioning • Whole system analysis and optimization
  • 37. 37 WSN services • MAC protocols (BMAC, SMAC, TMAC, etc.) • Topology control (GAF, SPAN, CEC, etc.) • Clustering (Leach, FLOC, etc.) • Time synchronization (Flooding time sync, reference broadcast) • Localization (cricket, range-free techniques...) • Routing (convergecast tree, geographic routing, hierarchical...) • Querying (DSIB, DQT, directed diffusion, etc.) • Tracking (Stalk, Trail, etc.) • Network reprogramming
  • 39. 39 Compared to Internet • No clear layering; cross layer design is norm • No separation between edge vs core of the network  all nodes are both routers and hosts • End-to-end principle fails  unreliable channels, multihop latency • Ad hoc deployment  timesync, localization, topology control, clustering etc services needed • Routing needs are different...

Editor's Notes

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