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10/6/2008 1 GENERAL PRINCIPLES AND ARCHITECTURES FOR PUTTING SENSOR NODES TOGETHER TO FORM A MEANINGFUL NETWORK 1 Wireless Sensor Architecture FORM A MEANINGFUL NETWORK Mobile ad hoc networks… 2 Nodes talking to each other Nodes talking to “some” node in another network (Web server on the Internet, e.g.) Typically requires some connection to the fixed network Applications: Traditional data (http ftp or collaborative Applications: Traditional data (http, ftp, or collaborative apps) & multimedia (voice, video); i.e., humans in the loop Access Point Access Point Sources and sinks revisited… 3 Sources: Any entity that provides data/measurements Sinks: Nodes where information is required Belongs to the sensor network as such Is an external entity, e.g., a PDA, but directly connected to the WSN Main difference: comes and goes, often moves around, … Is part of an external network (e.g., internet), somehow connected to the WSN Source Sink Internet Sink Source Sink Source

Wireless Sensor Architecturecomp7860/08R-Fall/LectureNotes/00... · 2008. 10. 6. · 10/6/2008 1 GENERAL PRINCIPLES AND ARCHITECTURES FOR PUTTING SENSOR NODES TOGETHER TO FORM A MEANINGFUL

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Page 1: Wireless Sensor Architecturecomp7860/08R-Fall/LectureNotes/00... · 2008. 10. 6. · 10/6/2008 1 GENERAL PRINCIPLES AND ARCHITECTURES FOR PUTTING SENSOR NODES TOGETHER TO FORM A MEANINGFUL

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G E N E R A L P R I N C I P L E S A N D A R C H I T E C T U R E S F O R P U T T I N G S E N S O R N O D E S T O G E T H E R T O

F O R M A M E A N I N G F U L N E T W O R K

1

Wireless Sensor Architecture

F O R M A M E A N I N G F U L N E T W O R K

Mobile ad hoc networks…2

Nodes talking to each otherNodes talking to “some” node in another network (Web server on the Internet, e.g.)

Typically requires some connection to the fixed network

Applications: Traditional data (http ftp or collaborative Applications: Traditional data (http, ftp, or collaborative apps) & multimedia (voice, video); i.e., humans in the loop

Access PointAccess Point

Sources and sinks revisited…3

Sources: Any entity that provides data/measurementsSinks: Nodes where information is required

Belongs to the sensor network as suchIs an external entity, e.g., a PDA, but directly connected to the WSN

Main difference: comes and goes, often moves around, …Is part of an external network (e.g., internet), somehow connected to the WSN

Source

Sink InternetSink

Source

Sink

Source

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Single- versus multiple-hops…4

One common problem: limited range of wireless communicationEssentially due to limited transmission power, path loss, obstacles

Option: multi-hop networksSend packets to an intermediate nodeIntermediate node forwards packet to its destinationStore and forward multi hop networkStore-and-forward multi-hop network

Basic technique applies to both WSN and MANETNote: Store&forward multi-hopping NOT the only possible solution

E.g., collaborative networking, network codingDo not operate on a per-packet basis

SourceSink

Obstacle

Hopping in WSNs…5

Sources of mobility…6

Node mobilityA node participating as source/sink (or destination) or a relay node might move aroundDeliberately, self-propelled or by external force; targeted or at randomHappens in both WSN and MANET

Sink mobilitySink mobilityIn WSN, a sink that is not part of the WSN might moveMobile requester

Event mobility In WSN, event that is to be observed moves around (or extends, shrinks)Different WSN nodes become “responsible” for surveillance of such an event

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Sink mobility…7

Requestq

Movementdirection

Propagationof answers

Event mobility…8

Challenging goals: QoS…9

In MANET: Usual QoS interpretationThroughput/delay/jitterHigh perceived QoS for multimedia applications

In WSN, more complicatedEvent detection and/or reporting probabilityEvent classification errorDetection delayProbability of missing a periodic reportApproximation accuracy (e.g., when WSN constructs a temperature map)Tracking accuracy (e.g., difference between true and conjectured position of the pink elephant)

Related goal: robustnessNetwork should withstand failure of some nodes

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Challenging goals: Efficiency…10

Energy per correctly received bitCounting all the overheads, in intermediate nodes, etc.

Energy per reported (unique) eventAfter all, information is important, not payload bits!

Delay/energy tradeoffsDelay/energy tradeoffsNetwork lifetime

Time to first node failureNetwork half-life (how long until 50% of the nodes died?)Time to partitionTime to loss of coverageTime to failure of first event notification

Challenging goals: Scalability…11

Network should be operational regardless of number of nodes

At high efficiency

Typical node counts difficult to guessMANETs: 10s to 100s WSNs: 10s to 1000s, maybe more (possible?)

Requiring to scale to large node numbers has seriousconsequences for network architecture

Might not result in the most efficient solutions for small networks!Carefully consider the actual application needs before looking for many solutions!

Design principles…12

Distributed organizationIn-network processing

AggregationDistributed source coding and distributed compressionDistributed and collaborative signal processingM bil d / t t kiMobile code/agent networking

Adaptive fidelityData centricity

Address data, not nodesImplementation options

Overlay networks and distributed hash tablesPublish/subscribeDatabases

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Design principles…213

Exploit:Location informationActivity patternsHeterogeneity

Component-based protocol stacks and cross-layer p p yoptimizationService interfacesGateway concepts

Distributed organization…14

Participants should cooperate in organizing the networkE.g., with respect to medium access, routing, …Centralistic approach as alternative usually not feasible—hinders scalability, robustness

Potential shortcomingsNot clear whether distributed or centralistic organization achieves better energy efficiency (when all “overheads” considered)

Option: “limited centralized” solutionElect nodes for local coordination/controlPerhaps rotate this function over time

In-network processing…15

MANETs are supposed to deliver bits from one end to the otherWSNs, however, are expected to provide information, not necessarily original bits

Additional optionspE.g., manipulate or process the data in the network

Main example: aggregation Apply composable aggregation functions to a converge cast tree in a network Typical functions: minimum, maximum, average, sum, … Not amenable functions: median

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In-network processing: Aggregation…16

Reduce number of transmitted bits/packets by applying an aggregation function in the network

1 1

1

31

1

6

1

11

1

1

In-network processing: Distributed…17

Depending on application, more sophisticated processing of data can take place within the network

Example edge detection: locally exchange raw data with neighboring nodes, compute edges, only communicate edge description to far away data sinksExample tracking/angle detection of signal source: Conceive of sensor nodes as a distributed microphone array use it to compute the angle of a nodes as a distributed microphone array, use it to compute the angle of a single source, only communicate this angle, not all the raw data

Exploit temporal and spatial correlationObserved signals might vary only slowly in time ! no need to transmit all data at full rate all the timeSignals of neighboring nodes are often quite similar ! only try to transmit differences (details a bit complicated, see later)

Seek other programming paradigms: mobile code, swarm intelligence

Adaptive fidelity…18

Adapt the effort with which data is exchanged to the currently required accuracy/fidelityExample: event detection

When there is no event, only very rarely send short “all is well” messagesWhen event occurs, increase rate of message exchanges

Example: temperatureWhen temperature is in acceptable range, only send temperature values at low resolutionWhen temperature becomes high, increase resolution and thus message length

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Data-centric networking…19

In typical networks (including ad hoc networks), network transactions are addressed to the identities of specific nodes

A “node-centric” or “address-centric” networking paradigm

In a redundantly deployed sensor networks, specific source y p y , pof an event, alarm, etc. might not be important

Redundancy: e.g., several nodes can observe the same area

Thus: focus networking transactions on the data directly instead of their senders and transmitters ! data-centric networking

Principal design change

Implementation options…20

Overlay networks & distributed hash tables (DHT)Hash table: content-addressable memoryRetrieve data from an unknown source, like in peer-to-peer networking—with efficient implementationSome disparities remain

Static key in DHT, dynamic changes in WSNDHTs typically ignore issues like hop count or distance between nodes when performing a lookup operation

Implementation options…221

Publish/subscribeDifferent interaction paradigmNodes can publish data, can subscribe to any particular kind of dataOnce data of a certain type has been published, it is delivered to all

b ibsubscribesSubscription and publication are decoupled in time; subscriber and published are agnostic of each other (decoupled in identity)

DatabasesMatches with the idea of using a data-centric organization of the networking protocols

Interested in certain aspects of data == formulating queries for a database

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Other design principles…22

Exploit location informationRequired anyways for many applications; can considerably increase performance

Exploit activity patternsWatch for “event shower” effect

Exploit heterogeneityBy construction: nodes of different types in the networkBy evolution: some nodes had to perform more tasks and have less energy left; some nodes received more solar energy than others; …

Cross-layer optimization of protocol stacks for WSNGoes against grain of standard networking; but promises big performance gainsAlso applicable to other networks like ad hoc; usually at least worthwhile to consider for most wireless networks

Service interfaces…23

The world’s all-purpose network interface: socketsGood for transmitting data from one sender to one receiverNot well matched to WSN needs (ok for ad hoc networks)

Expressibility requirementsSupport for simple request/response interactionsSupport for asynchronous event notificationDifferent ways for identifying addressee of data

By location, by observed values, implicitly by some other form of group membership, by some semantically meaningful form—“room 123”

Easy accessibility of in-network processing functionsFormulate complex events—events defined only by several nodes

Allow to specify accuracy & timeliness requirementsAccess node/network status information (e.g., battery level)Security, management functionality, …

Gateway concepts in WSNs…24

Necessary to the Internet for remote access to WSNsSame is true for ad hoc networks; additional complications due to mobility (change route to the gateway; use different gateways)WSN: Additionally bridge the gap between different interaction semantics (data vs. address-centric networking) in the gateway

d f diff di / lGateway needs support for different radios/protocols, …

Gatewaynode

Internet

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WSN to Internet communication…25

Example: Deliver an alarm message to an Internet hostIssues

Need to find a gateway (integrates routing & service discovery)Choose “best” gateway if several are availableHow to find Alice or Alice’s IP?

Ali ‘ d ktAlert Alice

Gatewaynodes

Alice‘s desktop

Alice‘s PDA

Alert Alice

Internet

Internet to WSN communication…26

Issues:How to find the right WSN to answer a need? How to translate from IP protocols to WSN protocols, semantics?

Remote requester

Gatewaynodes

Internet Gateway

WSN tunneling…27

Use the Internet to “tunnel” WSN packets between two remote WSNs

Gatewaynodes

Internet

Gateway

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Summary…28

Network architectures for ad hoc networks are—in principle—relatively straightforward and similar to standard networks

Mobility is compensated for by appropriate protocols, but interaction paradigms don’t change too much

WSNs, on the other hand, look quite different on many levels

Data-centric paradigm, the need and the possibility to manipulate data as it travels through the network opens new possibilities for protocol design

Next, we will look at how these ideas are realized by actual protocols