Wireless sensor networks

Murat Demirbas

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

(p

eo

ple

pe

r c

om

pu

ter)

streaming informationto/from physical world

Number CrunchingData Storage

productivityinteractive

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

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• Monitoring nesting behavior of birds

Great Ducks experiment

• Detecting forest fires

• Detecting chemical or biological attacks

• Monitoring Redwood trees

Ecology monitoring

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Dense Self-Organized Multihop Network

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Temperature vs. Time

Date

Tem

pera

ture

(C

)

Humidity vs. Time

35

45

55

65

75

85

95

Rel H

um

idit

y (

%)

101 104 109 110 111

2003, unpublished

Bottom Top

36m

34m

30m

20m

10m

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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

VineyardsBC

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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

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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

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Envisioned ExScal customer application

Gas pipeline

Border control

Canopy precludes aerial techniques

Rain forest – mountains – water

environmental challenges

Convoy protection

IEDHide SiteDetect anomalous activity

along roadside

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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

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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

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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

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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

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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

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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.

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Mica2 and Mica2Dot

• ATmega128 CPU– Self-programming

• Chipcon CC1000– FSK– Manchester encoding– Tunable frequency

• Low power consumption– 2 AA battery = 3V

1 inch

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Basic Sensor Board

• Light (Photo)• Temperature• Prototyping space for

new hardware designs

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Mica Sensor Board

• Light (Photo)• Temperature• Acceleration

– 2 axis– Resolution: ±2mg

• Magnetometer– Resolution: 134G

• Microphone• Tone Detector• Sounder

– 4.5kHz

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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

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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

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Stargate

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Outline

• Hardware

RFID, Spec Mica2, XSM, Telos Stargate

• Software

TinyOS

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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

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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

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Benefits of using TinyOS

• Separation of concerns

TinyOS provides a proper networking stack for wireless communicationthat 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.

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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

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RadioTimingSecDedEncode

The Complete Application

RadioCRCPacket

UART

UARTnoCRCPacket

ADC

phototemp

AMStandard

ClockC

bit

by

tep

ac

ke

t

SenseToRfm

HW

SW

IntToRfm

MicaHighSpeedRadioM

RandomLFSRSPIByteFIFO

SlavePin

noCRCPacket

Timer photo

ChannelMon

generic comm

CRCfilter

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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

bit

by

tep

ac

ke

t

event-driven bit-pump

event-driven byte-pump

event-driven packet-pump

message-event driven

active message

application comp

encode/decode

crc

data processing

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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

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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:

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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:

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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...