Routing Protocols for Sensor Networks

Routing Protocolsfor

Sensor Networks

AgendaAgendaGeneral PropertiesGeneral PropertiesArchitectures and RequirementsArchitectures and RequirementsRouting Protocols ClassificationRouting Protocols Classification10 Suggested Routing Protocols: 10 Suggested Routing Protocols:

LEACHLEACHPEGASISPEGASISTEENTEENAPTEENAPTEENSPIN SPIN

DDDDMCFMCFTTDDTTDDRWRWRRRR

AcknowledgementsAcknowledgementsE. Magistretti E. Magistretti (U. Bologna Italy)(U. Bologna Italy)J. Kulik J. Kulik (MIT; BBN Co.)(MIT; BBN Co.)R. R. Choudhury, P. Kyasanur & N. Vaidya R. R. Choudhury, P. Kyasanur & N. Vaidya (UIUC)(UIUC)P. Desai P. Desai (UFL)(UFL)D. Braginsky and D. Estrin D. Braginsky and D. Estrin (UCLA)(UCLA)S. Hazarika, W. Chen, Y. Gong & X. Liu S. Hazarika, W. Chen, Y. Gong & X. Liu (UMASS)(UMASS)T. Kwon & Mjnam T. Kwon & Mjnam (SNU Korea)(SNU Korea)R. Peterson & D. Rus R. Peterson & D. Rus (Dartmouth C.)(Dartmouth C.)H.C. Chung, K. Ghoshal & J. Krishna H.C. Chung, K. Ghoshal & J. Krishna (TAMU)(TAMU)C. TavoularisC. Tavoularis (Cornell ) (Cornell )G. Dong G. Dong (Virginia U.)(Virginia U.)

WSNWSN

Dartmouth College

ConceptsConcepts

Application:Application: Military Military

From UMASS

Environmental Environmental

From UMASS

Future Health Future Health

Circulatory Net




General Properties General Properties (1)(1)

Mainly for Information Collection Mainly for Information Collection Single OwnerSingle Owner Up to Hundreds of Thousands of Up to Hundreds of Thousands of

Nodes Nodes Disposable NodesDisposable Nodes Cheap NodesCheap Nodes Security ConcernsSecurity Concerns

General Properties General Properties (2)(2)

Bounded Bounded DirectedDirected Stream Stream (from/to (from/to Sink)Sink)

SomewhatSomewhat Limited Limited ComputationComputation CapabilityCapability

Limited Limited CommunicationCommunication Capability Capability Limited Limited PowerPower Resources Resources Node may Node may notnot have have Unique IDUnique ID Common case - Common case - StationaryStationary Nodes Nodes




General Architecture General Architecture (1)(1)

Sensor Unit Sensor Unit ADC – Analog Digital ConverterADC – Analog Digital Converter CPU – Central Processing Unit CPU – Central Processing Unit Power UnitPower Unit Communication UnitCommunication Unit

Sensor Network Node Main ComponentsSensor Network Node Main Components

General Architecture General Architecture (2)(2)

General Requirements General Requirements (1)(1)

Varying Network Size Varying Network Size Inexpensive Nodes EquipmentInexpensive Nodes Equipment Long Lifetime (Power) Long Lifetime (Power)

Load-BalancingLoad-Balancing Self-OrganizationSelf-Organization Re-tasking and Querying Capability Re-tasking and Querying Capability

General Requirements General Requirements (2)(2)

Sensible Data AggregationSensible Data Aggregation Consolidation of Redundant DataConsolidation of Redundant Data Application Awareness Application Awareness Tradeoff Tradeoff

CommunicationCommunication for for ComputationComputation Possible Mobility Possible Mobility




Protocol Classification Protocol Classification (1)(1)

ProactiveProactive – – First Compute all Routes;First Compute all Routes;Then RouteThen Route

ReactiveReactive – – Compute Routes On-DemandCompute Routes On-Demand

HybridHybrid – – First Compute all Routes;First Compute all Routes;Then Improve While RoutingThen Improve While Routing


DirectDirect – – Node and Sink Communicate Node and Sink Communicate DirectlyDirectly (Fast Drainage; Small Scale)(Fast Drainage; Small Scale)

FlatFlat (Equal) – (Equal) – Random Indirect Route Random Indirect Route (Fast Drainage Around Sink; Medium Scale)(Fast Drainage Around Sink; Medium Scale)

ClusteringClustering (Hierarchical) – (Hierarchical) – Route Thru Distinguished Nodes Route Thru Distinguished Nodes


Location AwareLocation Aware – – Nodes knows where they are Nodes knows where they are

Location-LessLocation-Less – – Nodes location is unimportant Nodes location is unimportant

Mobility AwareMobility Aware – – Nodes may move – Nodes may move –

Sources; Sinks; AllSources; Sinks; All


UnicastUnicast – – One-to-One Message Passing One-to-One Message Passing

MulticastMulticast (actually (actually Local Local BroadcastBroadcast) – ) – Node-to-Neighbors Message Node-to-Neighbors Message PassingPassing

BroadcastBroadcast – – Full-Mesh – Source to Everyone Full-Mesh – Source to Everyone


HistoricalHistorical Queries: Analysis of historical data Queries: Analysis of historical data“What was the watermark 2h ago in the southeast?”“What was the watermark 2h ago in the southeast?”

One-timeOne-time Queries: Queries: Snapshot viewSnapshot view“What is the watermark in the southeast?”“What is the watermark in the southeast?”

PersistentPersistent Queries: Queries: Monitoring over timeMonitoring over time“Report the watermark in the southeast for the next 4h”“Report the watermark in the southeast for the next 4h”

Query Models:Query Models:


AgendaAgendaGeneral PropertiesGeneral PropertiesArchitectures and RequirementsArchitectures and RequirementsRouting Protocols ClassificationRouting Protocols Classification10 Suggested Routing Protocols:10 Suggested Routing Protocols:



1 - LEACH 1 - LEACH – Discussed …– Discussed … Self-Organizing – Adaptive ClusteringSelf-Organizing – Adaptive Clustering Cluster-Heads elect themselves – Cluster-Heads elect themselves –

Now – Now – ““Random Round-RobinRandom Round-Robin”” Future – Power-Based ProbabilityFuture – Power-Based Probability

Nodes die in randomNodes die in random Stationary SinkStationary Sink Localized CoordinationLocalized Coordination Data FusionData Fusion

Low Energy Adaptive Clustering Low Energy Adaptive Clustering HierarchyHierarchy

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1 - LEACH 1 - LEACH (2)(2) ““Hot SpotHot Spot” Problem” Problem

(Nodes on a path from an event-congested area (Nodes on a path from an event-congested area to the sink may drain)to the sink may drain)

IInadequatenadequate for Time-Critical for Time-Critical ApplicationsApplications

Stationary Sink – Maybe Stationary Sink – Maybe UnpracticalUnpractical Basic Algorithm assumes any node Basic Algorithm assumes any node

can communicate with sink – can communicate with sink – limited limited scalescale


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1 - LEACH 1 - LEACH (3)(3) Works in Works in RoundsRounds, each with , each with

Set-Up (Short) and Steady-State Set-Up (Short) and Steady-State (Long)(Long)

Set-UpSet-Up Phase - subdivided: Phase - subdivided:– Advertisement Advertisement (I am a Cluster-Head)(I am a Cluster-Head)– Cluster Set-Up Cluster Set-Up (I am in your Cluster)(I am in your Cluster)– Schedule Creation Schedule Creation (This is your slot)(This is your slot)

Steady-StateSteady-State Phase: Phase:– Data TransmissionData Transmission using TDMA using TDMA


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1 - LEACH 1 - LEACH (4)(4) Everyone uses the same channelEveryone uses the same channel Different clusters use different CDMA Different clusters use different CDMA

codescodes Code chosen in randomCode chosen in random

Cluster-Head communicate with SinkCluster-Head communicate with Sink Can be extended to Hierarchical Can be extended to Hierarchical

Clustering Clustering


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1 - LEACH 1 - LEACH (5)(5)


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1 - LEACH 1 - LEACH (6)(6)


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2 - PEGASIS 2 - PEGASIS (1)(1) Token-Passing Chain-BasedToken-Passing Chain-Based Considered Near-Optimal (in a sense)Considered Near-Optimal (in a sense) Nodes die in randomNodes die in random Stationary Nodes and SinkStationary Nodes and Sink Every node have a global network Every node have a global network

mapmap Data FusionData Fusion Greedy chain constructionGreedy chain constructionProt

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Power-Efficient Gathering in Sensor Information Power-Efficient Gathering in Sensor Information SystemsSystems

2 - PEGASIS 2 - PEGASIS (2)(2)

Stationary NodesStationary Nodes Global InformationGlobal InformationLimited Scale:Limited Scale: Information travels many nodesInformation travels many nodes Assumes any node can Assumes any node can

communicate with sinkcommunicate with sinkMai

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2 - PEGASIS 2 - PEGASIS (3)(3) Greedy Algorithm Construct Chain –Greedy Algorithm Construct Chain –

Start at a node far from sink and Start at a node far from sink and gather everyone neighbor by neighborgather everyone neighbor by neighbor

Node Node ii (mod N) (mod N) is the leader in round is the leader in round ii Nodes passes token thru the chain to Nodes passes token thru the chain to

leader from both sidesleader from both sides Each node fuse its data with the restEach node fuse its data with the rest Leader transmit to sinkLeader transmit to sinkM

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SystemsSystems


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SystemsSystems



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Rounds Until DeathRounds Until Death

3 - TEEN 3 - TEEN (1)(1)

LEACH based ClusteringLEACH based Clustering Smart data transmission (Saves Smart data transmission (Saves

Power)Power) Nodes dynamic reconfiguration Nodes dynamic reconfiguration

abilityability Suits for Time-Critical applicationsSuits for Time-Critical applications

Threshold sensitive Energy Efficient Sensor Threshold sensitive Energy Efficient Sensor NetworkNetwork

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3 - TEEN 3 - TEEN (2)(2)

““Hot Spot” ProblemHot Spot” Problem Cluster-Heads need to listen Cluster-Heads need to listen

constantlyconstantly Wasted time-slotsWasted time-slots Can’t distinguish dead nodesCan’t distinguish dead nodes Other LEACH problems…Other LEACH problems…M

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NetworkNetwork

3 - TEEN 3 - TEEN (3)(3)

LEACH Proactive ClusteringLEACH Proactive Clustering Node transmit in Node transmit in timeslottimeslot only if only if

both:both:– Value greater then a Value greater then a Hard ThresholdHard Threshold

(H(HTT))– Value differs from last transmitted Value differs from last transmitted

value (value (SV SV ) by more then a ) by more then a Soft Soft ThresholdThreshold (S (STT))

After transmission After transmission SVSV is reset is reset

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Threshold sensitive Energy Efficient Sensor Threshold sensitive Energy Efficient Sensor NetworkNetwork

3 - TEEN 3 - TEEN (4)(4)

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NetworkNetwork

4 - APTEEN 4 - APTEEN (1)(1)

Improved (Adaptive - Hybrid) TEENImproved (Adaptive - Hybrid) TEEN All TEEN FeaturesAll TEEN Features More flexible More flexible logiclogic and and timeslotstimeslots Multi-type Queries:Multi-type Queries:

– Historical Historical (What was the temp. then?)(What was the temp. then?)– One-time One-time (What’s the temp. now?)(What’s the temp. now?)– Persistent Persistent (Tell me the temp for 2 hours)(Tell me the temp for 2 hours)

Can distinguish dead nodesCan distinguish dead nodes

Adaptive Periodic Threshold-sensitive Energy Efficient Sensor Adaptive Periodic Threshold-sensitive Energy Efficient Sensor NetworkNetwork

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LEACH problems…LEACH problems… Complex logicComplex logic

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4 - APTEEN 4 - APTEEN (3)(3) LEACH Proactive ClusteringLEACH Proactive Clustering Node transmit in Node transmit in timeslottimeslot only if both: only if both:

– Value greater then a Value greater then a Hard ThresholdHard Threshold (H(HTT))

– Value differs from last transmitted value Value differs from last transmitted value ((SV SV ) by more then a ) by more then a Soft ThresholdSoft Threshold (S (STT))

OrOr If did not transmit for a If did not transmit for a max timemax time (T (TC C ))OrOr if if queriedqueried by some sink by some sink

After transmission After transmission SVSV is reset is reset

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ssAdaptive Periodic Threshold-sensitive Energy Efficient Sensor Adaptive Periodic Threshold-sensitive Energy Efficient Sensor

NetworkNetwork

Power Consumption:Power Consumption: AAs could be expected – s could be expected –

APTEEN is better the LEACHAPTEEN is better the LEACHbut not as good as TEENbut not as good as TEEN

5 - SPIN 5 - SPIN (1)(1) Network-wideNetwork-wide Broadcast Broadcast Limited by Limited by

Negotiation Negotiation and using Local Communicationand using Local Communication Flooding problems Flooding problems solvedsolved::

Implosion – same data from many neighborsImplosion – same data from many neighborsDetection of overlapping regionsDetection of overlapping regionsExcessive resources consumption (Blindness)Excessive resources consumption (Blindness)

Needs only Needs only LocalizedLocalized Information Information Data FusionData Fusion Two main protocols SPIN-PP & SPIN-BCTwo main protocols SPIN-PP & SPIN-BC

Sensor Protocol for Information via Sensor Protocol for Information via NegotiationNegotiation

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5 - SPIN 5 - SPIN (2)(2) Broadcast Broadcast - - Limited ScaleLimited Scale – –

every node handles O(every node handles O(nn) messages) messages Data is updated throughout network Data is updated throughout network

– unnecessary in many cases– unnecessary in many cases NetworkNetwork lifetime lifetime - not clear - not clear High High degreedegree nodes nodes = = High High powerpower

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5 - SPIN 5 - SPIN (3)(3)

SPIN-PPSPIN-PP (Point-to-Point Communication) (Point-to-Point Communication) Data is described by meta-data Data is described by meta-data ADVADV msg. msg. Node has data Node has data sends sends ADVADV to neighbors to neighbors If neighbor do not have data If neighbor do not have data sends sends REQREQ Node responds by sending the Node responds by sending the DATADATA This process continues around the This process continues around the

networknetwork Nodes may aggregate their data to Nodes may aggregate their data to ADVADV In a In a LossyLossy Network Network ADVADV may be repeated may be repeated

periodically and periodically and REQREQ if not answered if not answered

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5 - SPIN 5 - SPIN (4)(4)

SPIN-BCSPIN-BC (Local Broadcast (Local Broadcast Communication)Communication)

ADVADV and and DATADATA sending like sending like PPPP (but in (but in B.C.)B.C.)

Since only one Since only one REQREQ answer is needed, answer is needed, any node waits a random interval and any node waits a random interval and B.C. B.C. REQREQ only if none was received only if none was received yet. yet.

The rest – like The rest – like SPIN-PPSPIN-PP

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ADVNode with data

Node with data advertises to all its neighbors

5 - SPIN 5 - SPIN (5)(5)

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NegotiationNegotiation

SPIN-PPSPIN-PP

REQNode with data

Neighbor requests for data and it is sent

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NegotiationNegotiation5 - SPIN 5 - SPIN (5)(5)

SPIN-PPSPIN-PP

DATA Node with data

Node with data advertises to all its neighbors

5 - SPIN 5 - SPIN (5)(5)

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NegotiationNegotiation

SPIN-PPSPIN-PP

Node with dataADV

Receiving node sends ADV to neighbors

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SPIN-PPSPIN-PP

Node with data

Receiving neighbors requests for data.

REQ

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Already has data(or dead)

SPIN-PPSPIN-PP

Node with data

DATA

Receiving node sends ADV to neighbors

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SPIN-PPSPIN-PP

6 - DD 6 - DD (1)(1) Hybrid Data Centric Routing – Hybrid Data Centric Routing –

Looking for Named DataLooking for Named Data Query–Response ModelQuery–Response Model Performs Better than FloodingPerforms Better than Flooding Robust and Fault Tolerant (bypass Robust and Fault Tolerant (bypass

faults)faults) Localized Localized Interactions Data Fusion - Data Fusion - Application Specific

Filters

Directed DiffusionDirected DiffusionPr

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6 - DD 6 - DD (2)(2)

““Hot SpotHot Spot” Problem near sink” Problem near sink Periodic Periodic BroadcastsBroadcasts of “Interest” of “Interest”

Reduces Network LifetimeReduces Network Lifetime Trade-off: Energy Trade-off: Energy EfficiencyEfficiency vs. vs.

RobustnessRobustness and and ScalabilityScalability Complex Data Aggregation - Complex Data Aggregation -

may Lead to may Lead to Expensive NodeExpensive Node

Directed DiffusionDirected DiffusionM

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6 - DD 6 - DD (3)(3) A Query (A Query (InterestInterest) is Broadcasted by a ) is Broadcasted by a

node (sink)node (sink) Query Reaches Relevant Sensor Query Reaches Relevant Sensor

SourcesSources This Sets-Up This Sets-Up Exploratory GradientsExploratory Gradients Once Data is Available in a Source Once Data is Available in a Source

it is Sent Back via it is Sent Back via Reinforced PathReinforced Path Failing Links / Nodes are being Failing Links / Nodes are being

Gradually Gradually BypassedBypassed

Directed DiffusionDirected DiffusionM

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Sink

Interest = Interrogation

Gradient = Who is interested

CLASS_KEY IS INTEREST_CLASSLONGITUDE_KEY GE 10LONGITUDE_KEY LE 50LATITUDE_KEY GE 100LATITUDE_KEY LE 120SENSOR EQ MOVEMENTINTENSITY GE 0.6CONFIDENCE GE 0.7INTERVAL IS 10EXPIRE_TIME IS 100

6 - DD 6 - DD (4)(4)

Directed DiffusionDirected DiffusionIll

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2. subscribe (AttrVec, ApplCallback)1. subscribe (InterestAttrVec, Callback)

InterestAttrVecCLASS_KEY EQ INTEREST_CLASSLONGITUDE_KEY IS 35LATITUDE_KEY IS 110SENSOR IS MOVEMENT

3. addFilter (FilAttrVec, FilterCallback)

FilterAttrVecCLASS_KEY EQ DATA_CLASSSENSOR EQ MOVEMENTINTENSITY GE 0.7

6 - DD 6 - DD (4)(4)


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Interests Setting up gradients

Source

Sink



6 - DD 6 - DD (4)(4)


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4. h = publish (SensedAttrVec)5. send (h, SensedAttrVec)

SensedAttrVecCLASS_KEY IS DATA_CLASSLONGITUDE_KEY IS 35LATITUDE_KEY IS 110SENSOR IS MOVEMENTINTENSITY IS 0.8CONFIDENCE IS 0.7

Low rate event

Sending data …6 - DD 6 - DD (4)(4)


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Low rate event

6. FilterCallback.recv (Message m1)

m2CLASS_KEY IS DATA_CLASSLONGITUDE_KEY IS 35LATITUDE_KEY IS 110SENSOR IS MOVEMENTINTENSITY IS 0.8CONFIDENCE IS 0.8

7. sendMessage (Message new)

m1a

m1b

m2

m2

6 - DD 6 - DD (4)(4)


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Low rate event

8. ApplCallback.recv (NRAttrVec)

6 - DD 6 - DD (4)(4)


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Sink

… and Reinforcing the best path

Low rate event Reinforcement = Increased interest

CLASS_KEY IS INTEREST_CLASSLONGITUDE_KEY GE 10LONGITUDE_KEY LE 50LATITUDE_KEY GE 100LATITUDE_KEY LE 120SENSOR EQ MOVEMENTINTENSITY GE 0.6CONFIDENCE GE 0.7INTERVAL IS 1EXPIRE_TIME IS 90

6 - DD 6 - DD (4)(4)


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Recoveringfrom node

failure

Source

Sink

Low rate event High rate event

Reinforcement

6 - DD 6 - DD (5)(5)


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Sink

Stable pathLow rate event

High rate event

6 - DD 6 - DD (5)(5)


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Recoveringfrom link failure

Source

Sink


Reinforcement

6 - DD 6 - DD (6)(6)


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Stable path

Source

Sink


Reinforcement

Use: “Interests set up gradients drawing down data”

6 - DD 6 - DD (6)(6)


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7 - MCF 7 - MCF (1)(1) Cost-FieldCost-Field min Cost from Node to Sink min Cost from Node to Sink

on Optimal Pathon Optimal Path Slop-Down the Cost-Fields to Get to Slop-Down the Cost-Fields to Get to

SinkSink Minimize Multiple Transmissions using Minimize Multiple Transmissions using

Back-OffBack-Off Algorithm Based on Algorithm Based on Node Node CostCost

LocalizedLocalized Communication Communication

Minimum Cost ForwardingMinimum Cost ForwardingPr

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7 - MCF 7 - MCF (2)(2)

High Time Complexity (due to High Time Complexity (due to back-off)back-off)

Many Sinks – Large Cost TablesMany Sinks – Large Cost Tables Cost Field Set-Up Time O(N)Cost Field Set-Up Time O(N) No Load-BalancingNo Load-Balancing

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Minimum Cost ForwardingMinimum Cost Forwarding

7 - MCF 7 - MCF (3)(3) Broadcast Broadcast ADVADV msg. and get Answers msg. and get Answers

from all Sinks from all Sinks Create Create Cost-FieldsCost-Fields Calculate Calculate Back-OffBack-Off Timer Proportional Timer Proportional

to Cost per each Sinkto Cost per each Sink Needed Information Sent thru Slop Needed Information Sent thru Slop If no ACK until If no ACK until TimerTimer Expires – Resend Expires – Resend

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Minimum Cost ForwardingMinimum Cost Forwarding

7 - MCF 7 - MCF (4)(4)

Minimum Cost ForwardingMinimum Cost ForwardingIll

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TimelineTimeline

A BC

7 - MCF 7 - MCF (5)(5)

Minimum Cost ForwardingMinimum Cost ForwardingIll

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S = 200 B = 120C = 90

A=150

Sink = 0

130100

110

50

6090

8 - TTDD 8 - TTDD (1)(1) Grid Grid Structure ClusteringStructure Clustering Stationary Location-AwareStationary Location-Aware Nodes Nodes Mission Aware – Infrequent ChangesMission Aware – Infrequent Changes Greedy Geographical Forwarding – Greedy Geographical Forwarding –

Building GridBuilding Grid Localized CommunicationLocalized Communication

Two-Tier Data DisseminationTwo-Tier Data DisseminationPr

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8 - TTDD 8 - TTDD (2)(2)

No Mobile SensorsNo Mobile Sensors Requires Location InformationRequires Location Information Grid Nodes may DrainGrid Nodes may Drain

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Two-Tier Data DisseminationTwo-Tier Data Dissemination

8 - TTDD 8 - TTDD (3)(3) Grid Build using Greedy Algorithm and Grid Build using Greedy Algorithm and

Location AwernessLocation Awerness Node Floods Messages to Node Floods Messages to

Dissemination NodesDissemination Nodes Dissemination Nodes Forward to SinkDissemination Nodes Forward to Sink If a Node Fails – Grid is FixedIf a Node Fails – Grid is Fixed

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Two-Tier Data DisseminationTwo-Tier Data Dissemination

Source

Dissemination Node

Sink

Data Announcement

Query

Data

Immediate DisseminationNode

8 - TTDD 8 - TTDD (4)(4)

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TTDD BasicsTTDD Basics

Source

Dissemination Node

Sink

Data Announcement

Data



TrajectoryForwarding


8 - TTDD 8 - TTDD (5)(5)

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TTDD Mobile SinksTTDD Mobile Sinks

TTDD Multiple Mobile TTDD Multiple Mobile SinksSinks

Source

Dissemination Node

Data Announcement

Data Immediate DisseminationNode


8 - TTDD 8 - TTDD (6)(6)

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9 - RW 9 - RW (1)(1) Finding a Finding a Random Walk Random Walk over a over a GridGrid Multi-path Routing Multi-path Routing Load BalancingLoad Balancing Large Scale NetworksLarge Scale Networks Nodes Assumed to be Mostly StationaryNodes Assumed to be Mostly Stationary No Location Information NeededNo Location Information Needed Little State InformationLittle State Information LocalizedLocalized Communication Communication

Random WalksRandom WalksPr

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Different Routes Different Routes at Different at Different

TimesTimes

9 - RW 9 - RW (2)(2)

Topology may not be PracticalTopology may not be Practical(Nodes are Assumed to be Located (Nodes are Assumed to be Located at Cubic Grid Junctions)at Cubic Grid Junctions)

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Random WalksRandom Walks

9 - RW 9 - RW (3) - RSG(3) - RSG

RRegular egular SStatic tatic GGraphsraphs Find coordinates differences (Find coordinates differences (x, x, y) using y) using

Distributed Bellman Ford (local comm.)Distributed Bellman Ford (local comm.) For every node compute probability of For every node compute probability of

moving on X and Y moving on X and Y (By the diagonal to the destination)(By the diagonal to the destination)

On each node move to a adjacent one on X On each node move to a adjacent one on X or Y using that probability. Adjust near end.or Y using that probability. Adjust near end.

All Paths together draws a straight “Banana”All Paths together draws a straight “Banana”

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9 - RW 9 - RW (4) - ISG(4) - ISG

IIrregular rregular SStatic tatic GGraphs (Some dead nodes)raphs (Some dead nodes) Same as Same as RSGRSG but… but… If one adjacent node is missing – go to the If one adjacent node is missing – go to the

other (with p=1).other (with p=1). If both are missing – go to a neighbor If both are missing – go to a neighbor

whose B-F distance to the destination is whose B-F distance to the destination is strictly smaller than the current nodestrictly smaller than the current node(This will create a detour).(This will create a detour).

(Could optimize by not getting to that node…).(Could optimize by not getting to that node…).

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9 - RW 9 - RW (5) - DG(5) - DG

DDynamic ynamic GGraphs (Nodes may sleep and raphs (Nodes may sleep and wake)wake)

Same as Same as ISGISG but… but… When a node changes state: the one-hop When a node changes state: the one-hop

neighbors change B-F labels and possibly neighbors change B-F labels and possibly trigger further label (distances) changestrigger further label (distances) changes

Concerns:Concerns:– Delays in propagating updatesDelays in propagating updates– Sensitivity to inaccuracies in labelsSensitivity to inaccuracies in labels

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S

u4

u1vu3

u2

R

P3 P1

P4

P2

0 1 2 N-1…...0

1

2

N-1

...[3,2]

d e[3,

2]=2

9 - RW 9 - RW (6) - RSG(6) - RSG

Illus

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Illus

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ssRandom WalksRandom Walks

9 - RW 9 - RW (7) – RSG (7) – RSG vs.vs. ISG ISG

Illus

trat

ion

Illus

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1,7 1,3 0,0 0,1

1,4 2,3 2,3 2,1

4,12,20,01,1

7,13,11,11,1

0 1 20

1

2

3

31/2

11

1

1/22/3

1

1

1/3

1

1 1/2

1/2

1

1/2

1

1/2

1,20 1,10 1,4 1,1

1,10 2,6 3,3 4,1

10,16,23,31,4

20,110,14,11,1

1/2 2/3 3/4

1/22/3

3/4

1/31/2

1/3

1

1/4

1/3 1/2 1/3

2/3

1 1

1/42/3

1/2

1

0 1 20

1

2

11

1/2

3

3

ISG ISG


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RSG (DG Similar)RSG (DG Similar) ISGISG

A Random walk by flipping a fair coinA Random walk by flipping a fair coin

Load DistributionLoad Distribution - - NarrowNarrow


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RSG (DG Similar)RSG (DG Similar) ISGISG

A Random walk by RSG/ISG algorithmsA Random walk by RSG/ISG algorithms

Load Distribution Load Distribution -- Flat Flat

10 - RR 10 - RR (1)(1)

Observation: for many application Observation: for many application any arbitrary path will do – any arbitrary path will do – No Need for a Shortest PathNo Need for a Shortest Path

Nodes are Nodes are Densely DistributedDensely Distributed Bidirectional LinksBidirectional Links LocalizedLocalized Communication Communication StationaryStationary Nodes Nodes Meet Trails of Queries and EventsMeet Trails of Queries and Events

Rumor RoutingRumor RoutingPr

otoc

ol

Prot

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H

ighl

ight

sH

ighl

ight

s

10 - RR 10 - RR (2)(2)

Attractive only when the ratio Attractive only when the ratio between between eventsevents and and queriesqueries is is inside a threshold where it is not inside a threshold where it is not attractive to flood neither.attractive to flood neither.

Optimal parameters Optimal parameters depend depend heavily on topologyheavily on topology (but can be (but can be adaptively tuned)adaptively tuned)

Does Does notnot guarantee delivery guarantee delivery

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Rumor RoutingRumor Routing

10 - RR 10 - RR (3)(3) Movement on the net is done by several Movement on the net is done by several

agents, trying (randomly) to walk straight.agents, trying (randomly) to walk straight. Every node maintains lists of neighbors and Every node maintains lists of neighbors and

events (how to get to the reporting node).events (how to get to the reporting node). An agent coming from and event is updating An agent coming from and event is updating

nodes it visits.nodes it visits. An agent coming from a query is searching An agent coming from a query is searching

for ways to the reporting nodes.for ways to the reporting nodes. High probability the lines will intersect.High probability the lines will intersect.M

ain

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10 - RR 10 - RR (4)(4)

Rumor RoutingRumor RoutingIll

ustr

atio

nIll

ustr

atio

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Event 1Event 2

Knows Event 1

Knows Event 2 Knows Both EventAgent

10 - RR 10 - RR (5)(5)

Rumor RoutingRumor RoutingIll

ustr

atio

nIll

ustr

atio

nss

Event Source

Query Source

Very Very

Theoretical

Theoretical Execution

Execution




Done!!!

ConclusionsConclusionsWSNWSN will spread to many applications will spread to many applicationsProperties and Requirements are bothProperties and Requirements are both UniqueUnique and and DiversifiedDiversifiedRouting ProtocolRouting Protocol choice choice is and probably will continue to beis and probably will continue to be Application DrivenApplication DrivenMore More AnalysisAnalysis, , SimulationsSimulations and new and new IdeasIdeas are needed for every category are needed for every category

References References (1)(1)

Q. Jiang, D. Manivannan, Q. Jiang, D. Manivannan, Routing Protocols for Sensor Routing Protocols for Sensor NetworksNetworks, IEEE Consumer Communications and , IEEE Consumer Communications and Networking Conference (CCNC'04), 2004.Networking Conference (CCNC'04), 2004.

R. Jurdak, C. V. Lopes, P. Baldiy, R. Jurdak, C. V. Lopes, P. Baldiy, A Framework for Modeling A Framework for Modeling Sensor NetworksSensor Networks, 19th Annual ACM Conference on Object-, 19th Annual ACM Conference on Object-Oriented Programming, Systems, Languages, and Oriented Programming, Systems, Languages, and Applications (OOPSLA'04), 2004. Applications (OOPSLA'04), 2004.

W. Heinzelman, A. Chandrakasan, and H. Balakrishnan, W. Heinzelman, A. Chandrakasan, and H. Balakrishnan, Energy-Efficient Communication Protocol for Wireless Energy-Efficient Communication Protocol for Wireless Microsensor NetworksMicrosensor Networks, IEEE Proceedings of the IEEE , IEEE Proceedings of the IEEE International Conference on System Sciences, 2000.International Conference on System Sciences, 2000.

S. Lindsey, C. S. Raghavendra, S. Lindsey, C. S. Raghavendra, PEGASIS: Power Efficient PEGASIS: Power Efficient GAthering in Sensor Information SystemsGAthering in Sensor Information Systems, IEEE Aerospace , IEEE Aerospace Conference, 2002.Conference, 2002.


A. Manjeshwar and D. P. Agrawal,A. Manjeshwar and D. P. Agrawal, TEEN: A Protocol for TEEN: A Protocol for Enhanced Efficiency in Wireless Sensor NetworksEnhanced Efficiency in Wireless Sensor Networks, , Proceedings of the 1st International Workshop on Parallel Proceedings of the 1st International Workshop on Parallel and Distributed Computing Issues in Wireless Networks and and Distributed Computing Issues in Wireless Networks and Mobile Computing (with IPDPS'01), 2001.Mobile Computing (with IPDPS'01), 2001.

A. Manjeshwar and D. P. Agrawal, A. Manjeshwar and D. P. Agrawal, APTEEN: a hybrid APTEEN: a hybrid protocol for efficient routing and comprehensive protocol for efficient routing and comprehensive information retrieval in wireless sensor networksinformation retrieval in wireless sensor networks, , Proceedings of the International Parallel and Distributed Proceedings of the International Parallel and Distributed Processing Symposium (IPDPS'02), 2002.Processing Symposium (IPDPS'02), 2002.

J. Kulik, W. Heinzelman, and H. Balakrishnan, J. Kulik, W. Heinzelman, and H. Balakrishnan, Negotiation-Negotiation-Based Protocols for Disseminating Information in Wireless Based Protocols for Disseminating Information in Wireless Sensor NetworksSensor Networks, Wireless Networks, Vol. 8, pp. 169-185, , Wireless Networks, Vol. 8, pp. 169-185, 2002.2002.

C. Intanagonwiwat, R. Govindan, D. Estrin, J. S. Heidemann, C. Intanagonwiwat, R. Govindan, D. Estrin, J. S. Heidemann, and F. Silva, and F. Silva, Directed Diffusion for Wireless Sensor Directed Diffusion for Wireless Sensor NetworkingNetworking, IEEE/ACM Transactions on Networking, vol. 11, , IEEE/ACM Transactions on Networking, vol. 11, no. 1, pp. 2-16, 2003.no. 1, pp. 2-16, 2003.


F. Ye, A. Chen, S. Lu, L. Zhang, F. Ye, A. Chen, S. Lu, L. Zhang, A Scalable Solution to A Scalable Solution to Minimum Cost Forwarding in Large Sensor NetworksMinimum Cost Forwarding in Large Sensor Networks, , Proceedings of the 10th IEEE International Conference on Proceedings of the 10th IEEE International Conference on Computer Communications and Networks (ICCCN'01), Computer Communications and Networks (ICCCN'01), 2001.2001.

F. Ye, H. Luo, J. Cheng, S. Lu, and L. Zhang, F. Ye, H. Luo, J. Cheng, S. Lu, and L. Zhang, A Two-Tier Data A Two-Tier Data Dissemination Model for Large-scale Wireless Sensor Dissemination Model for Large-scale Wireless Sensor NetworksNetworks, ACM International Conference on Mobile , ACM International Conference on Mobile Computing and Networking (MOBICOM'02), 2002.Computing and Networking (MOBICOM'02), 2002.

S. D. Servetto, G. Barrenechea, S. D. Servetto, G. Barrenechea, Constrained Random Walks Constrained Random Walks on Random Graphs: Routing Algorithms for Large Scale on Random Graphs: Routing Algorithms for Large Scale Wireless Sensor NetworksWireless Sensor Networks, In the Proceedings of the 1st , In the Proceedings of the 1st ACM International Workshop on Wireless Sensor Networks ACM International Workshop on Wireless Sensor Networks and Applications (WSNA'02), 2002. and Applications (WSNA'02), 2002.

D. Braginsky, D. Estrin, D. Braginsky, D. Estrin, Rumor Routing Algorithm For Rumor Routing Algorithm For Sensor NetworksSensor Networks, In the Proceedings of the 1st ACM , In the Proceedings of the 1st ACM International Workshop on Wireless Sensor Networks and International Workshop on Wireless Sensor Networks and Applications (WSNA'02), 2002. Applications (WSNA'02), 2002.

KarlFriedrich Hieronymus Baron of Munchausen (1720-1797)

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Routing Protocols for Sensor Networks