WSN unit 1 ppt

Wireless SensornetworksConcepts, Protocolls and Applications

Hon.-Prof. Dr. rer. nat. Peter Langendörferleader of the research group of sensor nets

telefon: 0335 5625 350fax: 0335 5625 671

e-mail: langendoerfer [ at ] ihp-microelectronics.comweb: www.tu-cottbus.de/systeme

Chapter 1Introduction, Applications and Challenges

Chair Systemswww.tu-cottbus.de/systeme

winter term 2010 – Wireless Sensor Networks Chapter 1 –

general information

• lecture dates– exercise each time after lecture (starts on demand)

• exam at the beginning of the vacations by exam or orally • certificate by proof of their participation in lecture

(list of participants: at least 5 participated)• documents for lecture and exercise on chair website• for rescheduling information or other announcements

will be publish on chair website and/or by email(please register in LEHVIS system)

• www.tu-cottbus.de/systeme



Literatur und Quellen

• Protocols and Architectures for Wireless Sensor NetworksProf. Holger Karl; Andreas Willig, Wiley, ISBN 0-470-09510-5

• Distributed Sensor NetworksS. Sitharama Iyengar and Richard. R. Brooks, Chapman & Hall/CRC, ISBN 1-58488-383-9

• Wireless Sensor Networks, Architectures and ProtocolsEdgar H. Callaway, Jr, Auerbach Publications ISBN 0-8493-1823-8

• Sensor Technology HandbookJohn S. Wilson, Newnes ISBN 0-7506-7729-5

• Ad Hoc Wireless NetworksMohamed Ilyas, CRC Press, ISBN 0-8493-1332-5

• Präsentationen aus dem WWRF• Folien des Kollegen Karl aus Paderborn



lecture overview

• Introduction, Applications and Challenges• Single Node Architectures • Physical Layer• MAC Protocols• LLC Protocols• Routing Protocols• Network Architectures• DSN Architectures• Power Management



infrastructure-based wireless networks

• Typical wireless network: Based on infrastructure– e.g., GSM, UMTS, …– base stations connected to a wired backbone network– mobile entities communicate wirelessly to these base stations– traffic between different mobile entities is relayed by base stations and

wired backbone– mobility is supported by switching from one base station to another– backbone infrastructure required for administrative tasks

IP backbone

ServerRouter

Gateways



infrastructure-based wireless networks (2)

• Which are the limits ?• What if …

– … no infrastructure is available ?• e.g., in disaster areas

– … it is too expensive/inconvenient to set up ?• e.g., in remote, large construction sites

– … there is no time to set it up ?• e.g., in military operations



possible applications forinfrastructure-free networks

• military networking: tanks, soldiers, …• finding out empty parking lots in a city, without asking a

server• search-and-rescue in an avalanche• personal area networking (watch, glasses, PDA, medical

appliance, …)

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• factory floor automation• disaster recovery

• car-to-car communication



sensor equipment

tiny 1cm³ Particleincludes sensors, battery,CPU, communication

source: www.teco.edu



sensor nodes

UC Berkeley: COTS Dust

UC Berkeley: COTS Dust UC Berkeley: Smart Dust

UCLA: WINSRockwell: WINS

JPL: Sensor Webs



Sensor Node

Processor Radio Frontend

Sensor Interface

Antenna



Sensorknoten

Processor Radio Frontend

Sensor Internface

Antenne

Power Mgmt.

Power Supply

Microcontroller Memory Hardware-Accelerator

Analogue Frontend

Baseband Base band

Sensor

Communication Interface

I/O



IHP Sensor nodes

Power Mgmt.

Power Supply

Microcontroller Speicher Hardware-Beschleuniger

Analoges Frontend

Baseband Basisband

Sensor

Kommunikationsschnittstelle

Ein-/Ausgabe

Memory250KB

SPI Baseband 868MHz

HW AccECC, AES

IPMS430

On board comm.

Power Mgmt.

Power Supply

Microcontroller Speicher Hardware-Beschleuniger

Analoges Frontend

Baseband Basisband

Sensor

Kommunikationsschnittstelle

Ein-/Ausgabe

Memory250KB

SPI Baseband 868MHz

HW AccECC, AES

IPMS430

On board comm.

Tandem Node

First Tandem node, security flavour for BSI

FeuerWhere Node designed by IHP



sensors and local infrastructure

• location aware mall – Metro Future-Store– location aware shopping system– finds location of products

• ubiquitous mall – mobile communication + sensors/RFID

tagsSensor node• tiny 1cm³• sensors, • battery,• CPU, • communicationSource: www.teco.edu



telecom and internet world

• most modern cell phones combine features of former PDAs plus:– internet access– NFC– payment functionality



sensors and internet



applications

• bird observation on Great Duck Island– interest: breeding behavior: usage of burrows,

environment, breeding sites– nodes located in burrows and on surface– measurement: humidity, pressure, temperature,

ambient light (every minute)– infrared sensors detect presence of birds– ad-hoc clusters with dedicated node for long-range

communication



applications (2)

• ZebraNet– interest: behavior of individual animals, interactions,

human impact– hundreds of square kilometers, years of observation,

every 3 minutes– animals carry nodes with GPS and sensors (now

light, more coming)– data transferred whenever nodes come close

together– mobile base station (car or plane) collects data from

time to time• related: cattle herding using “virtual fences”



applications (3)

• disaster relief operations– drop sensor nodes from an aircraft over a

wildfire– each node measures temperature– derive a “temperature map”

• biodiversity mapping– use sensor nodes to observe wildlife

• intelligent buildings (or bridges)– reduce energy wastage by proper humidity,

ventilation, air conditioning (HVAC) control – needs measurements about room

occupancy, temperature, air flow, …



sensors and local infrastructure



Tunnel Monitoring



application (3)

• glacier monitoring– interest: monitor glacier dynamics to understand climate– nodes in drill holes measure pressure, temperature, tilt– base station on glacier uses differential GPS, transmits data via

GSM– major problem: radio communication through ice and water

• ocean water monitoring– interest: global, long-term coverage of ocean and climate– measure temperature, salinity, ocean profile continuously– nodes cycle to 2000m depth every ten days– data transmitted to satellite when on surface



application (4)

• vital sign monitoring– Interest: monitor vital signs of patients in hospital using WSN– Better accuracy and patient comfort compared to conventional

approaches– Components: patient identifier, medical sensors, display device,

setup pen– Staff uses setup pen to set up associations between body area

nodes• parts assembly

– Interest: assist assembly of do-it-yourself furniture– Parts and tools equipped with sensor nodes– Use force sensors (joints), gyroscope (screwdriver),

accelerometer (hammer)– Ad-hoc network detects activities, feedback via LEDs in furniture

parts



application (5)

• power monitoring– interest: save power in large office building– sensor node connected to each power outlet– transceiver nodes form multihop network to central unit, gateway

to internet

• other applications– grape monitoring: conditions which influence plant growth– cold chain management: monitor food temperature compliance– avalanche rescue: assist rescue of avalanche victims– military vehicle tracking: find and track e.g. tanks– self-healing mine field: Intact mines hop into a breach– sniper localization: locate snipers and bullet trajectories



application scenarios

• facility management– intrusion detection into industrial sites– control of leakages in chemical plants, …

• machine surveillance and preventive maintenance– embed sensing/control functions into places no cable has gone

before – e.g., tire pressure monitoring

• precision agriculture– bring out fertilizer/pesticides/irrigation only where needed

• medicine and health care– post-operative or intensive care



application scenarios (2)

• logistics– equip goods (parcels, containers) with a sensor node– track their whereabouts – total asset management– note: passive readout might suffice – compare RFIDs

• telematics– provide better traffic control by obtaining finer-grained

information about traffic conditions– intelligent roadside– cars as the sensor nodes



Application Areas

Industrial Automation Homeland Security

Telemedicine Context aware systems



Geographical setting and system req.

Demonstration side• 65 Ground water measurement

points• 12,6km² area• 250m to 2000m distance • Rural/forest area• No power supply

Requirements• Automatic measurement (min. once

a day)• Radio transmission• Local buffering of measurement

results• 10 year maintenance free operation• Temperature range -30°Cto +40°C• Protection against vandalism and

animals



Centralised server• GPRS/GSM connection

node• Local Internet-Server• Solar module

IQlevel System

Low Power Wireless Sensor Network• 868MHz Long Distance Radio• Ultra Low Power Micro controller• Low Duty Cycle Protocol• Crypto-based security• 10 years life time• Mesh-Network incl. adaptive

routingDigital probe

• Ultra Low Power Micro controller• Modular probe• Pressure-, ph-value-, sulphate- and

elect. conductivity measurements • Buffering of measurement results



Protecting First Responders

Vital parameters:• Body core temperature• Pulse• Blood oxygen saturation

Environmental data:• Remaining air in the breathing apparatus• Temperature inside protective clothing• Temperature at surface of protective clothing • Environmental temperature appr. 2 m above the head of fire

fighters• Relative humidity inside protective clothing• Relative humidity around the fire fighters• Explosive gas and/or explosive pyrolysis products



Data handling

• Buffering of all measurement data in the BAN

• In network processing (local evaluation)

• Timely transmission according a red-yellow-green model

– Red: acute life threatening situation, immediate data transmission (continuously)

– Yellow: situation might become life threatening in a short time scale, data transmission latest 10 sec. after measurement

– Green: no threat at all, transmission of data every 60 seconds as self-test



Harsh Environmental Conditions

• Temperature up to 1000°C• Saturated steam atmosphere• No sight due to smoke• Extremely noisy • Aggressive liquids and gas • Ionizing radiation• Blast e.g. after explosion


winter term 2010 – Wireless Sensor Networks Chapter 1 – 32

Protecting Critical Infrastructure (Drinking Water Pipeline)

Flow rate, pressure, quantity…



Measurement parameters

Location Distance to next substation

Parameter Unit

flow rate (m³/h) pressure, outlet (bar)

Waterworks Briesen ~1800 m

position of butterfly valve indicationpressure pipe A(1) (bar) pressure pipe N(2) (bar)

Briesen (protection on pipe bursts)

<~5800m

position of butterfly valve indicationflow rate (m³/h) quantity (m³)

pressure pipe A(1) (bar) pressure pipe N(2) (bar)

Jacobsdorf (protection on pipe bursts)

~4800m

position of butterfly valve indication

pressure pipe A(1) (bar) pressure pipe N(2) (bar)

Pilgram/Pagram (protection on pipe bursts)

~2500m

position of butterfly valve indicationflow rate (m³/h)

quantity intake from waterworks with negativ

back flow

(m³) Reservoir 0m

quantity intake from waterworks

(m³)

Measurements are done every 30 seconds



Pipe access points

34

• Power supply• Distance up to 6 km

• Spot to place additional hardware

• No power supply• Distance up to 3 km (usually

less)



SCADA Integration

WSAN



Intended System /software architecture

• MSP430 uC• Standard 868MHz radio (e.g. cc1100)

• + power amplifier + good antenna

• Tailored MAC & network stack • tinyOS

HWtinyOS

NetworkTransportRouting

ForwardingMAC

DCUUpdateservice

ServicesMIB/Identity

CiphersData storage

PROTIDS

Attestation

watchdog

Sensor

SensorcontrolNode Control

radio HWtinyOS

NetworkTransportRouting

ForwardingMAC

DCUUpdateservice

ServicesMIB/Identity

CiphersData storage

PROTIDS

Attestation

watchdog

Sensor

SensorcontrolNode Control

radio

Software Architecture



Lego like sensor node construction kit

What we would like to have

Secure Sensor Node for CIPSensor Node for Protection of First Responders/Environmental Monitoring



Construction Kit: Existing Components

• µC/Processors– Leon 2-3; MIPS; MSP430 derivate; 8051

• Radio Front Ends– UWB (802.15.4a), 868MHz (802.15.4 V2006); EN13757-3-4

• Hardware Accelerators/Power management– AES, ECC, TCP Checksum ; PowerSwitches

• Operating systems– tinyOS, Contiki, Reflex (BTU Cottbus); eCos

• Protocols– TCP, 802.15.4 Software (hardware under development); IHP-beaconing

• Middleware– tinyDSM (Event Definition; SQL like query language)



roles of participants in WSN

• sources of data: Measure data, report them “somewhere”– Typically equip with different kinds of actual sensors

• sinks of data: Interested in receiving data from WSN – May be part of the WSN or external entity, PDA, gateway, …

• actuators: Control some device based on data, usually also a sink



design space

• deployment– random or installed at chosen spots– one-time or continuous– classes: random/manual; one-time/iterative

• mobility– motion by environment (e.g. wind, water)– motion because attached to mobile entities (e.g. zebras)– motion of automotive nodes– can be desired property or undesirable accident– motion has large impact on network algorithms– classes: immobile/partly/all; occasional/continuous;

active/passive



design space (2)

• cost, size, resources, energy– form factor depends on application (microscopic to shoebox)– cost from cents to hundreds of euro's– energy, computing, processing resources depend on size– classes: brick, matchbox, grain, dust

• heterogeneity– first approach: identical or indistinguishable nodes only– in practice: a variety of nodes can be very useful– bundle computational or communication resources (cluster

heads)– special capabilities only for some (e.g. GPS)– gateways to external networks (GSM, satellite, Internet)– heterogeneity has large effect on complexity of software– classes: homogeneous/heterogeneous



design space (3)

• communication modality– How do nodes communicate ?– most common: radio waves, usually sub-gigahertz bands– light beams or laser: smaller, more energy efficient (cf. Smart Dust)– RFID coupling, sound, ultrasound also useful– classes: radio, light, inductive, capacative, sound

• infrastructure– How to construct the communication network ?– infrastructure-based: sensors communicate via base stations only– ad-hoc: direct communication between nodes– infrastructure is costly to deploy, ad-hoc often preferred– ad-hoc allows routers, multihop, message forwarding– classes: infrastructure / ad-hoc



design space (4)

• network topology– important property:

diameter = max number of hops between any two nodes– single hop (d=1), infrastructure based (d=2), ad-hoc (d big)– topology affects QoS and software complexity– classes: single-hop / star / networked stars / tree / graph

• coverage– depends on range of attached sensors– sensors could cover only part of area of interest, or all, or

multiply– coverage influences observational accuracy, redundancy,

processing– classes: sparse / dense / redundant



design space (5)

• connectivity– Nodes always connected or only sometimes ?

Network sometimes partitioned ?– connectivity influences communication protocols and data gathering– classes: connected / intermittent / sporadic

• size– range: a few nodes to thousands of nodes

• lifetime– How long does the sensor network exist ?– range: some hours to several years

• other QoS requirements– real-time, robustness, tamper-resistance, eavesdropping resistance,– unobtrusiveness, stealth



Node Capabilities & Requirements

• Processing power : 8 or 16 bit µC• Memory : 16 to 256 kByte• Energy resources : typical small batteries

1000-5000 mAhenergy harvesting

• Active Time: 1-15 years• Cost : 1-100 $/node



real life connectivity

• figures show WSN deployed on a flat parking lot

• expected: simple, circular shape of “region of communication” –not realistic

• instead: – correlation between distance and

loss rate is weak; iso-loss-lines are not circular but irregular

– asymmetric links are relatively frequent (up to 15%)

– significant short-term PER variations even for stationary nodes



three regions of communication

• effective region: PER consistently 10%

• transitional region:anything in between,with large variation for nodes at same distance

• poor region: PER well beyond 90%



discussion and conclusions

• single hardware platform will not be sufficient to cover applications• avoid application-specific hardware by small set of platforms

– cover different parts of design space– modular approach (exchange components of node) could help

• software situation is even more complex– cover design space with set of protocols, algorithms, basic services– system designer is still faced by complexity of design space

• use middleware as in conventional systems ? No...– aspects of DS are hard to hide from developer (e.g. topology)– must expose characteristics to handle resource limitations – Middleware would introduce significant resource overheads

• unconventional approaches towards general abstractions under discussion, may be tis is even kind of middleware



… see you !

Thanks for your attention !

WSN unit 1 ppt

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