WSN unit 1 ppt

Wireless Sensornetworks Concepts, Protocolls and Applications Chapter 1 Introduction, Applications and Challenges

Hon.-Prof. Dr. rer. nat. Peter Langendörfer leader of the research group of sensor nets telefon: 0335 5625 350 fax: 0335 5625 671

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

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

winter term 2010 – Wireless Sensor Networks

Chapter 1 – Page 2

Chair Systems www.tu-cottbus.de/systeme

Literatur und Quellen • • • • • • •

Protocols and Architectures for Wireless Sensor Networks Prof. Holger Karl; Andreas Willig, Wiley, ISBN 0-470-09510-5 Distributed Sensor Networks S. Sitharama Iyengar and Richard. R. Brooks, Chapman & Hall/CRC, ISBN 1-58488-383-9 Wireless Sensor Networks, Architectures and Protocols Edgar H. Callaway, Jr, Auerbach Publications ISBN 0-8493-1823-8 Sensor Technology Handbook John S. Wilson, Newnes ISBN 0-7506-7729-5 Ad Hoc Wireless Networks Mohamed 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 Gateways

Server


IP backbone

Router Chapter 1 – Page 5


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 for infrastructure-free networks • factory floor automation

• disaster recovery

• car-to-car communication

ad

c ho

• 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, …) winter term 2010 – Wireless Sensor Networks



sensor equipment

tiny 1cm³ Particle includes sensors, battery, CPU, communication

source: www.teco.edu winter term 2010 – Wireless Sensor Networks



sensor nodes

UC Berkeley: COTS Dust UC Berkeley: COTS Dust

UC Berkeley: Smart Dust

Rockwell: WINS UCLA: WINS


JPL: Sensor Webs



Sensor Node Antenna Processor

Radio Frontend

Sensor Interface




Sensorknoten Antenne Processor

Radio Frontend

Sensor Internface

Power Mgmt.

Power Supply

Microcontroller

I/O

HardwareAccelerator

Memory

Baseband Base band

Analogue Frontend

Sensor Communication Interface




IHP Sensor nodes Tandem Node Power Mgmt.

Power Supply

Microcontroller

Speicher Memory 250KB

Ein-/Ausgabe

Basisband Baseband

IPMS430

SPI

HardwareHW Acc Beschleuniger ECC, AES

Baseband

Analoges

868MHz Frontend

Sensor Kommunikationsschnittstelle On board comm.

FeuerWhere Node designed by IHP


First Tandem node, security flavour for BSI



sensors and local infrastructure • location aware mall – Metro FutureStore – location aware shopping system – finds location of products

• ubiquitous mall – mobile communication + sensors/RFID tags Sensor node • tiny 1cm³ • sensors, • battery, • CPU, • communication Source: 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” winter term 2010 – Wireless Sensor Networks



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, … winter term 2010 – Wireless Sensor Networks



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 winter term 2010 – Wireless Sensor Networks



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 winter term 2010 – Wireless Sensor Networks



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 winter term 2010 – Wireless Sensor Networks



Application Areas

Homeland Security

Industrial Automation

Telemedicine winter term 2010 – Wireless Sensor Networks

Context aware systems Chapter 1 – Page 26


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 winter term 2010 – Wireless Sensor Networks



IQlevel System Centralised server • GPRS/GSM connection node • Local Internet-Server • Solar module 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 routing Digital probe • Ultra Low Power Micro controller • Modular probe • Pressure-, ph-value-, sulphate- and elect. conductivity measurements • Buffering of measurement results winter term 2010 – Wireless Sensor Networks



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 winter term 2010 – Wireless Sensor Networks



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




Protecting Critical Infrastructure (Drinking Water Pipeline)

Flow rate, pressure, quantity…




32

Measurement parameters Measurements are done every 30 seconds Location Waterworks Briesen

Distance to next substation ~1800 m

Briesen

<~5800m

(protection on pipe bursts)

Jacobsdorf (protection on pipe bursts)

~4800m

Pilgram/Pagram (protection on pipe bursts)

~2500m

Reservoir

0m


Parameter flow rate pressure, outlet position of butterfly valve pressure pipe A(1) pressure pipe N(2) position of butterfly valve flow rate quantity pressure pipe A(1) pressure pipe N(2) position of butterfly valve pressure pipe A(1) pressure pipe N(2) position of butterfly valve flow rate quantity intake from waterworks with negativ back flow quantity intake from waterworks


Unit (m³/h) (bar) indication (bar) (bar) indication (m³/h) (m³) (bar) (bar) indication (bar) (bar) indication (m³/h) (m³)

(m³)


Pipe access points • • •

• •

Spot to place additional hardware No power supply Distance up to 3 km (usually less)

Power supply Distance up to 6 km




34

SCADA Integration

WSAN




Intended System /software architecture • •

MSP430 uC Standard 868MHz radio (e.g. cc1100) • + power amplifier + good antenna

• •

Tailored MAC & network stack tinyOS

Software Architecture Sensor control

Node Control Transport Routing Forwarding MAC

Update service

Ciphers Data storage

radio


tinyOS HW

IDS Attestation

watchdog


Sensor

Network Services DCU PROT MIB/Identity


What we would like to have Lego like sensor node construction kit

Secure Sensor Node for CIP

Sensor 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 winter term 2010 – Wireless Sensor Networks



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 winter term 2010 – Wireless Sensor Networks



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 : • Memory : • Energy resources :

• Active Time: • Cost :


8 or 16 bit µC 16 to 256 kByte typical small batteries 1000-5000 mAh energy harvesting 1-15 years 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 winter term 2010 – Wireless Sensor Networks



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% winter term 2010 – Wireless Sensor Networks



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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