outline wireless ad hoc & sensor networks...device • memory – stores data and programs often...

Wireless Ad Hoc & Sensor Networks (Wireless Sensor Networks - Part 1)

WS 2010/2011WS 2010/2011

Prof. Dr. Dieter HogrefeDr. Omar Alfandi

Outline• Introduction• Challenges in WSNs• Differences MANET vs. WSN• Basic Node Architecture

O ti S t f WSN• Operating Systems for WSNs• Famous Sensor nodes• Types of Source and sinks/• Types of Source and sinks/

Single-hop vs. Multi-hop/ Node mobility• WSN optimisation goalsWSN optimisation goals• WSN design principles• Summaryy

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What are WSNs?

• WSNs = Wireless Sensor Networks• Set of individual nodes that are able to interact with the

environment by sensing or controlling physical parameters

• Wireless communication enables the cooperation of the nodes to fulfil bigger tasks that single nodes could notF t Vi i A bi t I t lli• Future Vision: Ambient Intelligence– Many different devices gather and process information from

many different sources to control physical processes and to y p y pinteract with human users

– WSN is a crucial step towards Ambient Intelligence by providing the “last 100 meters” of pervasive controlthe last 100 meters of pervasive control

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Application Examples of WSNs

• Disaster relief operations– Wildfire detection– Sensor nodes with thermometers are

dropped from an air plane– Various temperature measurements areVarious temperature measurements are

collected to produce a temperature map

• Biodiversity Mapping– Gain an understanding about plants and animals

• Intelligent Buildings/Bridges– Measurements about temperature,

energy wastage– Monitoring of mechanical stress levelsMonitoring of mechanical stress levels

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Application Examples of WSNs

• Precision Agriculture– Precise irrigation and fertilising of fields– Temperature and brightness monitoring

• Medicine and health careP t ti d i t i– Postoperative and intensive care

– Long-term surveillance of patients

• Logistics• Logistics– Tracking of parcels during transportation– Inventory tracking in stores or warehousesy g

• …and a lot more – almost unlimited possibilitiesp

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Participants in a WSNsink

• Source– Sensor that senses data in its environment– Can be equipped with different sensors

• e.g. temperature, brightness, etc.– Reports the measurements to the sinkReports the measurements to the sink

• Sink (Base Station)– Interested in receiving data from the other sensor nodes

source

te ested ece g data o t e ot e se so odes– Can be either part of the WSN or an external device such as a

Laptop or PDAI l th i b t ti b t d di th– In general there is one base station, but depending on the application multiple base stations are possible

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Interaction Patterns between source and sink

• Event detection– If a certain event occurs, the sensor nodes report the

t t i t t d i kmeasurement to interested sinks

• Periodic measurementPeriodically reporting of events to interested sinks– Periodically reporting of events to interested sinks

• Function approximation and edge detection– Approximation of a function of space an/or time (e gApproximation of a function of space an/or time (e.g.

temperature map)– Edge Detection: Find edges or structures in such a function

• Tracking– Report the position of an observed intruder

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O ti S t f WSN• Operating Systems for WSNs• Famous Sensor nodes• Types of Source and sinks• Types of Source and sinks


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Challenges for WSNs – Characteristic requirements

• Type of Service– Not simply moving bits from one place

i th t k t thin the network to another– Rather: Provide meaningful information

and/or actions about a given task

“People want answers,not numbers”

(Steven Glaser UCg– Scoping of interactions, e.g.

• Geographic regionsTi I t l

(Steven Glaser, UC Berkeley)

• Time Intervals

• Quality of Service (QoS)Traditional QoS metrics do not apply– Traditional QoS metrics do not apply

– Adapted quality concepts such as• Reliable detection of events• Approximation quality of a temperature map

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• Fault tolerance– Be robust against node failures

( i t f i t f h i l d t ti t )(running out of energy, interferences, physical destruction etc.)

• LifetimeNormally the replacing of a node energy source is not possible– Normally the replacing of a node energy source is not possible

– The WSN should fulfil its task as long as possible energy-efficient operation

– Trade-off: Lifetime vs. QoS– BUT: What is the precise definition of Lifetime?

Ti til fi t d f il• Time until first node fails• 50% of nodes failed• Certain geographical area is not covered anymore Not uniquely defined!

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• Scalability– Architecture and protocols need to support a large amount of

sensors

• Wide range of densitiesNumber of nodes per unit area differs application dependent– Number of nodes per unit area differs application dependent

– Change over time due to node movement or node failures

• ProgrammabilityProgrammability– Increase the flexibility by enabling the re-programming of nodes

in the field to react to new situations

• Maintainability– Environment and WSN itself are changing self monitoring and adaptation of the system self-monitoring and adaptation of the system

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Challenges for WSNs – Required mechanisms

• Multihop wireless communication– To save energy limit radio range– Use intermediate nodes as relays

• Energy-efficient operationS i t ti d i ti– Sensing, computation and communication

• Auto-configurationFor a huge amount of sensors manual configuration is no option– For a huge amount of sensors manual configuration is no option

• Collaboration and in-network processing– Node collaborate to achieve a common goalNode collaborate to achieve a common goal– To improve efficiency the sensed data can be aggregated e.g. calculation of the average temperature

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Challenges for WSNs – Required mechanisms

• Data-centric networking– Focus on relevant data, not on the node which is providing it “R i l if t t d 30°C” e.g. “Raise an alarm if temperature exceeds 30°C”

– Nodes are characterised by the provided data (data-centric),not by the network address (address-centric)y ( )

• Locality– Do thing locally as far as possible, i.e. on the node itself or in

collaboration with its neighbours

• Exploit trade-offsM t ll t di t l– Mutually contradictory goals

– e.g. Energy vs. accuracy

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Why are WSNs different? – WSNs vs. MANETsWSN MANET

Applications and equipment

•Small sensor nodes with constrained hardware and

•Powerful nodes (laptop, PDA) with large batteriesq p

energy supply•In general, unattended operation

g•In general, more elaborate applications, e.g. VoIP, with human interaction

Application specific

•Infinite number of applications in terms of

•Although, a few scenarios not as many as in WSNs

devices, protocols, density etc.

Environment •Lot of environmental •More conventional human-Environment interaction

•Lot of environmental interactions•low data rates, but also data bursts new traffic patterns

•More conventional human-driven applications with well-understood traffic characteristicsbursts new traffic patterns characteristics

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Scale •Huge amount of sensor nodes more scalable solutions

•Significantly less nodes than in WSNs

required (e.g. Protocols without node identifiers)

Energy •Tighter requirements mostly •Energy constrained butEnergy Tighter requirements, mostly no recharge or replacement of batteries possible

Energy constrained, but often energy can be recharged

Self •Almost equal to MANETs but •One of the main features inSelf configurability

•Almost equal to MANETs, but different data traffic and energy trade-offs

•One of the main features in MANETs

D d bili I di id l d i i l E h d h ld b li blDependability and QoS

•Individual node is irrelevant as long as network is working•New QoS concepts necessary

•Each node should be reliable•QoS determined by applications such as VoIPjittjitter

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Data centric •Redundant deploymentmakes data centric protocols

•Data-centric protocols are more or less irrelevant for p

attractive MANETsSimplicity and resource

•OS and software must be simpler than on ‘normal’ PCs

•Slightly limited resources, but in general normal OS andresource

scarcenesssimpler than on normal PCs•Breaking of strict networklayers isolation to achieve simplicity

in general normal OS and applications can run on the nodes

simplicityMobility •Mostly stationary use, but

movement for certain applications possible e g

•One of the main features of MANETs caused by moving nodesapplications possible e.g.

tracking applications•Movement can be correlated e g sensors carried by a river

nodes•Movement can be correlated by moving groups

e.g. sensors carried by a river

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Basic Node Architecture

• Controller– processes all

l t d t Controller

Memory

Sensor(s)Communication relevant data

– capable of executing arbitrary code

Controller Sensor(s)

Power Supply

Device

y

• Memory– stores data and programs often different types are used

Supply

• Communication– Device for sending and receiving data over a wireless channel

• Power Supply– Some form of batteries to provide energy; sometime recharging

by obtaining energy from the environment e g solar cellsby obtaining energy from the environment, e.g. solar cells

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Basic Node Architecture – Controller

• For the sensor nodes mostly microcontroller are used– general purpose processor, optimised for embedded

li ti l tiapplications, low power consumption

• ExamplesIntel StrongARM– Intel StrongARM

• High-end processor often used in PDAs– SA-1100 model: 32-bit RISC core, running @206MHz

– Texas Instruments MSP 430• Intended for usage in embedded applications

– 16-bit RISC core, up to 4 MHz, 2-10 kB RAM, several DACs, RT clock16 bit RISC core, up to 4 MHz, 2 10 kB RAM, several DACs, RT clock

– Atmel ATMega• ATMega 128L: Intended for usage in embedded applications

8 bit t ll l th MSP430 b t l– 8-bit controller, larger memory than MSP430, but slower

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Basic Node Architecture – Memory

• RAM (Random Access Memory)– To store intermediate sensor readings,

k t f f di tpackets for forwarding etc.– Is fast, but looses content if power supply

is interruptedp

• ROM (Read-Only Memory)– To store fix programs; not writeable

• EEPROM or Flash Memory– Enables overwriting of data– Can be used as intermediate storage if RAM is insufficient or if

the RAM’s power supply should be turned-off– BUT: long read/write access delays high energy requirementBUT: long read/write access delays, high energy requirement

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Basic Node Architecture – Communication

• Transceivers– Both a transmitter and a receiver are required in a sensor node– For practical purposes these two tasks are often

combined in one entity, the so called transceiver– Usually half-duplex operation is used because transmitting andUsually half duplex operation is used, because transmitting and

receiving at the same time is impractical in the wireless medium

• Transceiver States– Transmit– Receive

Idl (R d t i b t tl i i )– Idle (Ready to receive, but currently no receiving)• Some functions in the hardware can be turned-off to save energy

– Sleep (Significant parts of the receiver are switched off)p ( g p )• No receiving; Recovery time and start-up energy must be considered

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Basic Node Architecture – Communication

• Transceiver characteristics– Capabilities

• Interface: bit, byte or packet level?• Frequency range? (typically: 2.4 GHz, ISM band)• Multiple Channels? Data Rate? Range?p g

– Energy Characteristics• Power consumption for sending and receiving data?

Ti d ti t h b t t t ?• Time and energy consumption to change between states?• Transmission power control? Power Efficiency?

– Radio Performance• Modulation (ASK, PSK, …)? Noise figure (NF=SNRI/SNRO)?• Gain (signal amplification)? Receiver Sensitivity? Blocking

Perfomance? Out of band emissions? Carrier sense and RSSI?Perfomance? Out of band emissions? Carrier sense and RSSI? Frequency stability? Voltage range?

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Basic Node Architecture – Power Supply• Goal

– Provide as much energy as possible at smallest cost/ volume/ weight/ recharge timecost/ volume/ weight/ recharge time

• Options– Primary Batteries (not rechargeable)– Secondary Batteries (rechargeable)

• RequirementsC it (hi h t ll i ht ll l l i )– Capacity (high at small weight, small volume, low price)

– Capacity under load (withstand various usage patterns)– Self-discharge (if low long lifetime)g ( g )– Efficient recharging (at low current; no ‘memory effect’)– Relaxation (exploit the ‘self-recharging effect’)

Voltage stability (DC DC conversion)– Voltage stability (DC-DC conversion)

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Basic Node Architecture – Power SupplyPrimary Batteries

Chemistry Zinc-Air Lithium AlkalineE (J/ 3) 3780 2880 1200Energy (J/cm3) 3780 2880 1200

Secondary BatteriesSecondary BatteriesChemistry Lithium NiMHd NiCdEnergy (J/cm3) 1080 860 650

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Basic Node Architecture – Energy Scavenging

• Batteries can often not be recharged on the traditional way Therefore: Scavenging of energy from the environment

• Energy scavenging approaches– Photovoltaic (solar cells)

b t 10 W/ 2 d 15 W/ 2• between 10 µW/cm2 and 15 mW/cm2

– Temperature gradient• ~ 80 µW/cm2 @ 1V from 5K differenceµ @

– Vibration• between 0.1 and 10.000 µW/cm3

P i ti ( i l t i )– Pressure variation (piezo-electric)• ~ 330 µW/cm2 from the heel of a shoe

– Flow of air/liquidFlow of air/liquid• MEMS gas turbines no real results yet

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Operating Systems for WSNs• Usual Tasks of an Operating System (OS)

– Controlling and protecting the access to resources and managing their allocation to different userstheir allocation to different users

– Support for concurrent execution of several processes and communication between these processed

• Disadvantage of running a traditional OS on sensor nodes– Tasks are only partially required in embedded systems code is restricted code is restricted

– Microcontrollers do not have the required resources to run a full blown OS

– Special requirements such as energy-efficient execution, energy management etc. are not supported

– Efficient handling of multiple (asynchronous) external Sources is g p ( y )mostly not supported

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Operating Systems for WSNs – Concurrency

• Traditional concurrency approach: Processes/ Threads

Handle sensorprocess

Handle packetprocess

– Based on interrupts, context switching

• BUT: Process/ Thread approach• BUT: Process/ Thread approach is not suitable for WSNs– One process per protocol leads to p p p

too many context switches– Memory and execution overhead is

too big for available memorytoo big for available memory– Mostly only ‘little’ tasks so that

expensive context switching is not OS-mediatedjustifiable

OS mediatedprocess switching

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Operating Systems for WSNs – Concurrency

• Better approach for WSNs:event-based programming Sensor

eventRadio event

– Perform regular processingor be idle

– React to emerging events

Radio event handler

Sensor event handler

Idle/ Regular processingReact to emerging events

immediately when they happen– Basically: Interrupt handler– Normally two contexts

1. First context for time critical event-handlers event-handlers are simple and shortp the execution of an event-handler cannot be interrupted event-handlers are required to run to completion

2. Second context for processing normal codep g

performance improvement, memory and energy reduction30




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Famous sensor nodes

• Mica Mote– Family of sensor nodes, started in

th l t 1990the late 1990s– University of Berkeley, Cooperation with Intel

• EYES nodes• EYES nodes– Developed by Infineon– Sponsored by the EU-project “EYES”p y p j

• BTnodes– Developed at the ETH Zürich

• Scatterweb– Developed at the Computer Systems &

T l ti t th FU B liTelematics group at the FU Berlin

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Types of source and sink

• Sources– any entity that provides data/ measurements– typically a sensor node or an actuator node given feedback

• Sinksd h i f ti i i d– nodes where information is required

– Three sorts of sinks• sink is a sensor/ actuatorsink is a sensor/ actuator• sink is a device such as a PDA• sink is a gateway to another network such as the Internet

• Multiple Sources and/ or sinks are also possible– here: mostly one sink and multiple sources are considered

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Single-hop vs. multihop networks

• Common problem: Limited range of wireless communication– Due to limited transmission power, path loss, obstacles etc.

• Option: Multihop Networks– Send packets to intermediate node

I t di t d f d k t– Intermediate node forwards packetsin the direction of the destination

– Store-and-Forward multihop networkp– Basic technique that is used in

MANETs and WSNs

N tobstacle

• Note:– There are other techniques such as collaborative networking and

network coding which are not considered herenetwork coding which are not considered here

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Energy efficiency of multihop routing

• Intuitive approach– Attenuation of radio signals is at least quadratic in most

i tenvironments– It consumes less energy to use relays instead of direct

communication– Radiated energy required for distance d is reduced from

cdα to 2c(d/2)α (c some constant, path loss α > 2)

H thi h i i lifi d• However, this approach is over-simplified– Only radiated energy is considered,

but the actual consumed energy

Number one myth ofmulti-hopping: it saves energybut the actual consumed energy

(particularly of the relay nodes) is omitted– Great care should be taken when applying

lti h i ith th l f i i ffi i

(Min and Chandrakasan)

multi-hopping with the goal of improving energy efficiency

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Node Mobility• Node mobility

– Sensor nodes itself are mobileApplication dependent e g environmental– Application dependent, e.g. environmental control (static) vs. livestock surveillance (mobile)

– Deliberately, self-driven vs. driven by external force– Targeted vs. random movement

• Sink MobilityInformation sink that is not part of the WSN e g user with PDA– Information sink that is not part of the WSN, e.g. user with PDA

– Mobile requester• Event Mobilityy

– Cause of events or the object that should be tracked moves– Different sensors, which are in the range of the object/event, are

responsible for the surveillanceresponsible for the surveillance

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WSN Optimisation Goals

• Different scenarios, application types and network solutions Ch ll i ti Challenging questions:– How to optimise a network?

How to compare these solutions?– How to compare these solutions?– Which approach gives better support for my application?

• General answers appear impossible, but a few aspectsGeneral answers appear impossible, but a few aspects should be considered– Quality of Service– Energy Efficiency– Scalability

R b t– Robustness

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WSN Optimisation Goal – Quality of Service

• QoS in MANET– Low-level QoS:

• Throughput, delay, jitter, packet loss– High-level QoS

• Perceived QoS e.g. for multimedia applicationsPerceived QoS e.g. for multimedia applications

• QoS in WSNs is more complicated– Event detection/ reporting probabilityp g p y– Event classification error– Detection delay– Probability of missing a periodic report– Approximation accuracy

Tracking accuracy– Tracking accuracy

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WSN Optimisation Goal – Energy efficiency

• “Energy efficiency” covers several aspects– Energy per correctly received bit– Energy per reported (unique) event– Delay/energy trade-offs

Network lifetime– Network lifetime• Time to first node death• Network half-life• Time to partition• Time to loss of coverage• Time to failure of first event notificationTime to failure of first event notification

• The evaluation of these metrics needs clear assumptions– Node’s energy consumption, network load, radio channel behaviourgy p , ,

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WSN Optimisation Goal – Scalability

• Maintain performance characteristics regardless of the number of nodes

• Typical node numbers– MANETs: up to hundred nodes

WSN th d f d– WSNs: thousands of sensor nodes

• Information that have to be globally consistent should be minimised due to resource limitations e g limited memoryminimised due to resource limitations e.g. limited memory

• Scalability has direct consequences for the protocol designdesign– Often penalty in performance and/or complexity for small networks implement appropriate scalability support for your specific

application rather than trying to be as scalable as possible

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WSN Optimisation Goal – Robustness

• Robustness is directly related to QoS and scalability requirements

• WSNS should not fail just because – a limited number of nodes run out of energy

h i th i t– changes in the environment– interruption of radio links etc.

• Failures have to be compensated• Failures have to be compensated,e.g. by finding an alternative route, if a link breaks down

• Precise evaluation of robustness is difficultPrecise evaluation of robustness is difficult– depends mostly on failure models for nodes and communication

links in practise

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Design principles for WSNs

• The discussed optimisation goals does not provide any hints how they can be achieved by the network structure

• Some basic principles for designing network protocols– Distributed organisation

I t k i– In-network processing– Adaptive fidelity and accuracy– Data centricityData centricity– Exploitation of

• Location information• Activity patterns• Heterogeneity

– Component-based protocol stacks and cross-layer optimisationComponent based protocol stacks and cross layer optimisation

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Design principle – Distributed organisation

• WSN nodes should cooperatively organise the network using distributed algorithms and protocols lf i ti self-organisation

• Potential shortcomingsOft t li d h d l ti th t f– Often a centralised approach can produce solutions that perform better and use less energy, when taking all overheads into account

• Option: “limited centralised” solution– Elect nodes for local coordination/ control ti hi h creating a hierarchy

– Perhaps rotate this function over time

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Design principle – In-network processing

• Nodes in the network are actively involved in taking decisions about how the network should operate BUT li it d t i f ti b t th t k it lf BUT: limited to information about the network itself

• This approach can be extended to information processingprocessing– arbitrary extensions providing any form of

data processing to improve the applicationp g p pp

• In-network processing techniques– Aggregation– Distributed source coding and distributed compression– Distributed and collaborative signal processing

M bil d / t b d t ki– Mobile code/ agent-based networking

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Design principle – In-network processing II

• Example: Aggregation– Application of composable aggregation

f ti t t tfunctions to a converge cast tree– Typical functions:

• Minimum, maximum, average, …

1.42

, , g ,– Information is aggregated into a

condensed form and then transmitted t ffi i

1.5

2 5

1

greater energy-efficiency 1.52

2.5

Example: AverageExample: Average

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Design principle – Adaptive fidelity

• Adapt the effort for exchanging data to the currently required accuracy/ fidelity save energy

• Example: event detection– When there is no event, only send rarely an “I am alive”-message

If t i th t f– If event occurs, increase the rate of messages

• Example: temperature monitoringWhen temperature is in an acceptable range only send– When temperature is in an acceptable range, only send temperature values at low resolution

– If temperature exceeds a certain threshold, increase the resolution

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Design principle – Data centric networking

• In typical networks, including MANETs, transactions are addressed to the identity of certain nodes– “node-centric” or “address-centric” networking paradigm

• However, in WSNs sensors are redundantly deployed, the specific source of an event is not important only thethe specific source of an event is not important – only the data itself is relevant

• Thus focus on the data of networking transactions• Thus, focus on the data of networking transactions, instead of the senders and receivers– “data-centric” networking paradigmg p g– Decoupling of identities and decoupling of time

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Design principle – Data centric networking II

• Implementation options for data-centric networking– Overlay networks and distributed hash tables (DHT)

• Data is stored in a table and is identified via a given key (hash)• DHT will provide one or multiple sources for the data associated

with the key efficient data source lookup• WSN challenges

– Static keys in DHT vs. dynamic requests in WSNs– DHT ignores distance/ hop count between nodes, i.e. adjacent g p , j

neighbours are defined on the basis of semantic information

– Publish/ Subscribe• Nodes can publish data; Nodes can subscribe for any kind of data• Nodes can publish data; Nodes can subscribe for any kind of data• If data is published, the data will be delivered to all subscribers

– Database• Querying the database for certain aspects, e.g. in SQL

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Design principle – Exploitation

• Exploitation of location information– Location of an event is a crucial information for many applications

d it th f l d il bland it therefore, already available– Exploit this information to simplify the design and operation of

communication protocols; improve energy efficiencyp ; p gy y

• Exploitation of activity patterns– Protocol Design should consider special activity patterns in WSNs

such as low activity and when an event occurs high activity, i.e. bursts of traffic

• Exploitation of heterogeneity• Exploitation of heterogeneity– By construction: different types of nodes in the network– By evolution: some nodes have higher workload, thus less energyy g , gy

52

Design principle – Cross-layer optimisation

• Normally the network layers are strictly separated– The functionality of each layer is implemented in a component– Certain interfaces are provided to enable communication between

the layers

• In WSNs sometimes these strict lines are passed• In WSNs sometimes these strict lines are passed (Contrary to the rules of standard networking!)– Big Performance gaing g– However, new problems occur

• Feedback loopsE d i f ti lit d f f th ti t• Endangering functionality and performance of the entire system

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Summary

• WSN have (almost) unlimited application space• There are a lot of special characteristics that have to be

considered for WSNs, which differ from common networks

• Although MANET and WSNs have a similar background there are several differencesTh d hit t ll th ti t• The node architecture as well as the operating system have to be specially adapted to the application area of the WSNthe WSN

• There are several optimisation goals and design principles that should be taken into account for p pdeveloping and implementing a WSN

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outline wireless ad hoc & sensor networks...device • memory – stores data and programs often...

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