wireless sensor networks murat demirbas. 2 wireless sensor networks a sensor node (mote) 8k ram,...

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

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

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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2003, unpublished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

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

VineyardsBC

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

IEDHide SiteDetect 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

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Mica Sensor Board

• Light (Photo)• Temperature• Acceleration

– 2 axis– Resolution: ±2mg

• Magnetometer– Resolution: 134G

• 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 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.

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

bit

by

tep

ac

ke

t

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

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

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...