Wireless Sensor Networks Routing

Wireless Sensor NetworksRouting

Professor Jack Stankovic

University of Virginia2006

Single Hop NetworksSingle Hop Networks

Destination

Source

Diameter = 1

Any real applications?

Fixed DeploymentFixed DeploymentDiameter = 4

Comm.Range

Ad Hoc DeploymentNeighbor Discovery

Ad Hoc DeploymentNeighbor Discovery

ID Location1 x,y2 a,b3 c,d

1

23

Diameter = ?Data Structure

QuestionQuestion

• Suppose probability of a packet getting to next hop is 95%

• What is the probability of a packet making it across 10 hops?

(.95) ~= 60%10

Most WSNMost WSN

• Multi-hop• Ad hoc deployment

• Need “more interesting” routing protocols– Find routes on-demand– Energy issues– Irregular communication range– Interferences– Congestion– …

Outline – 9 Routing Algorithms

Outline – 9 Routing Algorithms

• GF (SGF; GPSR)• DSR (supports mobility) (MANET)• AODV (supports mobility) (MANET)• Directed Diffusion• SPEED (RT)• RAP (RT)• Critique: SPEED vs. RAP

• IGF (supports mobility, stateless)

Other Routing Algorithms(see text)

Other Routing Algorithms(see text)• Perimeter face routing

• Trajectory based routing• Cluster head routing• Minimum spanning trees• GEAR

– GF plus consider energy

• Rumor Routing

(total of 15 routing algorithms)

PrinciplesPrinciples

• Decentralized• Aggregate behavior• Minimize state information• Location based (not ID based -

usually)• Mobility (possible)• Integration of routing function with

“other” functions (e.g., data aggregation)

• Specialized patterns (N->1 base station)

Sensor Net RoutingSensor Net Routing

• End-to-end• Real-time• Collisions• Congestion• Power• Security• Mobility

Destination

Source

Assumption: Nodes know location (localization)

Last Mile

Base Station

Last Mile SemanticsLast Mile Semantics

• At least 1 - Any• At most 1• All

• Unicast – exactly which node by ID

s d

Geographic Forwarding (GF)

Geographic Forwarding (GF)

• GF always chooses a node that is closest to the destination.

• Every node knows its location.

GF – Information Required

GF – Information Required

• Node i (maintains routing table)– My location– List of neighbors and their locations

• Destination location• Find neighbor closest to destination

– How?

S

D

GFGF

• What if none in the correct direction– GF stops– Does not handle voids

– GPSR (goes around voids; can even go in opposite direction for awhile)

Voids and GPSRVoids and GPSR

Destination

Source

VOID

Left Hand Rule

Summary - GFSummary - GF

• Destination by geography/location not node ID

• Implications– Individual nodes are not important– Location is important– Route to area (all/any nodes in that

area)

• Many protocols extend basic GF– Example: GPSR, SGF, IGF, SIGF

MANET RoutingMANET Routing

• Mobile - nodes move • Ad hoc – no established

infrastructure or central administration

• DSR – dynamic source routing is a technique where the sender determines the complete sequence of nodes in the route

• AODV

Dynamic Source Routing (DSR)

Dynamic Source Routing (DSR)

• Route discovery (dynamic – on demand)

• Route reply

• Data delivery

• Route maintenance (in case Source, Destination, or router node moves out of range)

MANET: Dynamic Source Routing (DSR) – Route

Discovery

MANET: Dynamic Source Routing (DSR) – Route

Discovery

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Represents a node that has received Route RequestPacket (RREQ) for D from S

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Route Discovery in DSRRoute Discovery in DSR

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IK

Represents transmission of RREQ

Z

YBroadcast transmission

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[S]

[X,Y] Represents list of identifiers appended to RREQ

[S]

[S]


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[S,E]

[S,C]

[S,B]

[S,B]


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• Node C receives RREQ from G and H, but does not forward it again, because node C has already forwarded RREQ once

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[S,C,G]

[S,E,F]

QuestionQuestion

• How can a node know not to forward request again?

• Detect duplicate requests by keeping a list of– <initiator ID, request ID> for a time

period


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[S,C,G,K]

[S,E,F,J]


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• Node D does not forward RREQ, because node D is the intended target of the route discovery

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[S,E,F,J,M]

QuestionsQuestions

• Flooding– Cost (messages, energy, time)

• MANET networks => 20-30 nodes• WSN => 1000s of nodes

– WSN also have high density (lots of collisions; more wasted energy)

• Optimal Route found – Needed?

• Movement rates that can be supported?

Route Reply in DSRRoute Reply in DSR

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RREP [S,E,F,J,D]

Represents Route Reply (RREP)control message

Route ReplyRoute Reply

• Options for replying (routes need not be bi-directional)– Use reverse path (most common

choice)• Assumes symmetry in node-node

communication capability

– Look in node D cache and see if a route to the sender exists and use that route

– Find return route using route-discovery

Data Delivery in DSRData Delivery in DSR

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DATA [S,E,F,J,D]

Note: Packet header size grows with route length

DSRDSR

• Once path set up use it for “awhile”– During this period – no routing

overhead

• On movement of nodes– Re-establish path

• Note: nodes in MANET networks must be willing to act as routers as well as source/destination

DSR - Route MaintenanceDSR - Route Maintenance

• No periodic updates from neighbors as found in many routing solutions– Consumes too much energy

• Instead– Monitor route and inform sender of any

routing problems• Hop-by-hop ack – if a message M is not

ACKed after N attempts then the original sender is notified

Variations in Route Maintenance

Variations in Route Maintenance

• Use end-to-end ACKS instead

• Fix route from point of bad link instead of starting over

Summary - DSRSummary - DSR

• Designed for MANET networks• Sender determines the complete sequence of

nodes (only (dynamically) when needed)• No periodic routing table update messages, but

size of message increases as size of network grows (OK for small diameter networks)– Saves power

• Adapts (quickly?) to routing changes when hosts move

• Required little overhead when hosts do not move• Route lengths are close to optimal• Use same path over and over – nodes will die

fast?• Various optimizations have been developed

Ad Hoc On Demand Distance Vector (AODV)

Ad Hoc On Demand Distance Vector (AODV)

• Loop free routes• Repairs broken links• Does not require global periodic routing

advertisements• Nodes not in active paths neither maintain any

routing information nor exchange periodic routing tables

• Nodes discover routes when needed and then routing tables are used– Avoids path length problem of DSR (scales

better)

• Used for mobile networks

AODV – Route DiscoveryAODV – Route Discovery

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Represents a node that has received RREQ for D from S

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Route Requests in AODVRoute Requests in AODV

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Represents transmission of RREQ (hello messages) – only when necessaryKeep local routing tables

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S ->D ?

Route Requests in AODVRoute Requests in AODV

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IK

Represents links on Reverse Path Created as a packet moves toward destination

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S ->D ? E, C, B

Reverse Path Setup in AODV


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• Node C receives RREQ from G and H, but does not forward it again, because node C has already forwarded RREQ once

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• Node D does not forward RREQ, because node D is the intended target of the RREQ

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Forward Path Setup in AODV

Forward Path Setup in AODV

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Forward links are setup when RREP travels along the reverse path

Represents a link on the forward path

S->D FS->D E C

AODVAODV

• Nodes not along the path determined by the RREP will timeout (after about 3 sec) and will delete reverse pointers– Is this a general principle for WSN? For

mobile networks?

• Expiration time for the route table entry (updated after every message)

Route Table Entry DataRoute Table Entry Data

• Destination• Next hop• Number of hops• Sequence number for destination

• To avoid loops

• Active neighbors for this route– who will send me packets for this destination

(notify them of problem if my link to next hop breaks)

• Expiration time for the route table entry– to clean up the table

AODV Route Maintenance

2 choices

AODV Route Maintenance

2 choices• Periodic hello messages can be used to ensure symmetric links and to detect link failures– Principle?

• Upon detection of problem – restart discovery process with increased destination sequence number

DSR vs AODVDSR vs AODV

• DSR – all route information is stored in packet itself, bad for long routes– Dynamic– Set up route and then use for a long

time

• AODV – route information is in temporary routing tables – only on routes currently in existence– Dynamic– Set up route and then use for a long

time

Directed Diffusion Directed Diffusion

• Well known• One of first targeted for WSN• Routing and queries intimately tied

together– How many people do you observe in

area X?– Give me the temperature reading for

the next hour in area Y

– Diffuse the query into the sensor network• Query is persistent (until time t)• Must amortize cost of finding route over

data delivery (learn good routes)

Directed DiffusionDirected Diffusion

• A Flexible Framework/Paradigm

• Allows many choices for various aspects of the “solution”

– Remind you of BMAC? (for MAC layer)– This is for routing

Directed Diffusion – Main Parts

Directed Diffusion – Main Parts

• Node (e.g., base station) requests data by sending an interest for named data– Data centric routing

• Data generated by sensors in response to query is sent in attribute-value pairs

• Data matching the interest is drawn towards the requester– Gradients

Directed DiffusionAttribute-Value Pairs

Directed DiffusionAttribute-Value Pairs

Type =mammal

Value =horse

Duration = 3-4 PM

PeriodicRate = Y

Area ={a,b;c,d}

5 attribute value pairs – cache request

Response might be from node A horse at 3:30 at location x1,y1

Directed Diffusion – Other Features

Directed Diffusion – Other Features

• Intermediate nodes can cache or transform data, e.g., performing data aggregation (application dependent)– Now combine routing, queries, and data

aggregation

• Biological metaphor (ants and chemical trails)

• Form of flooding

FloodingFlooding

• General Principle– When you don’t know where things are– When you need to inform entire

network of something• Disseminate code• Disseminate system parameters

– Optimize

FloodingFlooding

• Restricted Flood– Inform all nodes within “n” hops of a

node i

– How?• TTL (time to live field in packet header)

– Principle

• In n=3 the neighbors forward packet after decrementing counter to 2, same at the next hop; when counter = 0 stop

FloodingFlooding

• A wave propagates/diffuses through the network

• What can happen due to MAC layer collisions?– A node may miss the information

Flood Flood

Collision

Back to Directed DiffusionBack to Directed Diffusion

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(i) D sends interest for named data – attribute-value pairsincludes area of interest

(ii) Nodes record interest (S, B, C) (may perform data aggregation on return path)

(iii) B, C and Sactivate sensors

for event ofinterest

Yellow nodes have nointerest in data


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(i) Gradients set up for return path – to draw data to D(ii) Multiple paths are supported

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(i) Reinforce certain paths, e.g., those with lowest delay(ii) Negative reinforcement for unappealing routes

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After D received data

S might send 2 of3 messages to E and1 of 3 to C

Directed Diffusion – Routing Information per Node

Directed Diffusion – Routing Information per Node

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Each node maintains an interest cache Each entry in cache has a gradient field for each neighbor

Includes a duration field – after which this query terminates

Directed Diffusion (4 aspects) – Flexible Framework

Directed Diffusion (4 aspects) – Flexible Framework

• Interest Propagation– Flooding, constrained flooding, use previously

cached data

• Data Propagation– Reinforce single path, multiple paths with

different quality, with probabilistic forwarding

• Data Caching and Aggregation– Application semantics embedded

• Reinforcement– When, how many neighbors, negative

reinforcement

Directed Diffusion (DD)Directed Diffusion (DD)

• Loops prevented “outside” the basic localized DD algorithm (uses a message cache)

• Any node can apply reinforcement rules – enables local repair of failed or degraded paths

• Many local rules can be applied in context of DD paradigm

• Works for multiple sinks and multiple sources

Sensor Network RoutingSensor Network Routing

• Current routing solutions– Many classical solutions need routing tables

the size of the network– Most use single path to destination (DSR,

AODV,…)– Many use path finding beacons (DD) - bad for

real-time

• SPEED– local (neighbor) tables only– utilize multiple paths– no path set-up beacons needed– Real-time addressed

SPEED Protocol (7 Aspects)SPEED Protocol (7 Aspects)

• API (and last mile processing)• Neighbor Beacon Exchange• Delay Estimation Scheme• Neighborhood Feedback Loop (NFL)• Semi-Stateless Non-deterministic

Geographic Forwarding (SNGF)• Back-pressure Rerouting• Void Avoidance

SPEED ArchitectureSPEED Architecture

Last Mile Process

SNGFBackpressure

ReroutingNFL

Beacon Exchange

APIUniCast MultiCast AnyCast

MAC

Delay Estimation

Neighbor Table

QuestionQuestion

• Can we convert SPEED to a B-MAC philosophy?– Flexible, highly parameterized, …

API (Last Mile Processing)

API (Last Mile Processing)

Destination

Source

• AreaMulticast• AreaAnyCast• Unicast

PossibleINTERFERENCE

SPEEDSPEED

E2E Distance

j

FS

iD

Actual Speed

Speed to destination(Set Point )

E2E Delay is bound by E2E Distance/Speed SetPoint

USE VELOCITY

Nondeterministic Forwarding

Nondeterministic Forwarding

1(7,8)23 (4,7)33(3,4)75( 1,6)9

DelayPosition ID

100%(7,8)2RPPosition ID

RP: Relay probability

ComputeSpeed

Example 1:

7

29

3

Destination

s

Nondeterministic Forwarding Nondeterministic Forwarding

3(7,8)21 (4,7)36(3,4)72( 1,6)9

DelayPosition ID

50%(7,8)250%( 1,6)9

RPPosition ID

RP: Relay probability

ComputeSpeed

Example 2:

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Destination s

Nondeterministic Forwarding Nondeterministic Forwarding

2(7,8)25 (4,7)34(3,4)71( 1,6)9

DelayPosition ID

15%Drop

40% (4,7)345%(3,4)7

RPPosition ID

Drop ratio is computed according to the Neighborhood feedback control loop

ComputeSpeed

Example: Overload situation Example 3:

Back-pressure re-routingBack-pressure re-routing

• When all available forwarding nodes are congested, the sending node will drop packets, which will be perceived by previous nodes. Route changes.

Congestion Area

7M

DROP2(7,8)22 (4,7)32(3,4)71( 1,6)9

DelayPosition ID3

29

Void AvoidanceVoid Avoidance

• Only guarantees a greedy path (will not go backwards)

Void

EvaluationEvaluation

• 6 CBR flows on one side of terrain send to one base station on the other side of terrain

• Average number of hops (8-9)• 90% CI (within 2-10% of mean)• Miss ratio results – not shown here but

much better for SPEED • Under heavy congestion

– added flows in center of terrain

• Transient performance

8-9 hops

EvaluationEvaluation

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0 10 20 30 40 50 60 70 80 90 100

Rate (P/S)

Del

ay (

MS

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AODV

DSR

SPEED

E2E Delay Energy Consumption

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AODV

DSR

SPEED

GF

SPEED-S

SPEED-T

(Added Congestion)

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0 20 40 60 80 100 120 140 160 180 200

E2E

Del

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MS

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time(S)

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0 20 40 60 80 100 120 140 160 180 200

E2E

Del

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Figure A. E2E delay profile of DSR Figure B. E2E delay profile of AODV

Performance

PerformancePerformance

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E2E

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ay (M

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time(S)

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0 20 40 60 80 100 120 140 160 180 200E

2E D

elay

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Figure C. E2E delay profile of GF

Figure. D E2E delay profile of SPEED

Extensions?Extensions?

• Add power decision, i.e., choose next hop based on “most power” remaining

• Add reliable link decision, i.e., compute link quality and use it for choosing next hop

3(7,8)21 (4,7)36(3,4)72( 1,6)9

DelayPosition ID P LQ1.73.02.5

3.1

RAPRAP

• Goals– Minimize e2e deadline miss ratio– Provide high-level services APIs for

distributed micro-sensing applications (similar to DD and SPEED)

– Minimize communication and processing overhead

RAP ArchitectureRAP Architecture

Velocity Monotonic Scheduling

Prioritized MAC

Query/Event Service

Coordination Service

Location-Addressed Protocol

Sensing/Control Application

Query/Event Service APIs

Geographic Routing

BIG ISSUEBIG ISSUE

• What are the right interfaces for the protocol stack– MAC– Routing

• Internet has TCP/IP

• WSN needs Sensor Net Protocol (SP) equivalent!

QuestionsQuestions

• MAC – should MAC contain – Priorities? – Congestion information?– Acks/No Acks decisions?– Multi-frequencies information?

• Routing – should routing contain– Power issues– Data aggregation– Gradients– Link quality– Real-time

Query/Event APIQuery/Event API

• High-level abstraction for programming distributed micro-sensing applications

register_event {virusFound(0,0,100,100), // area to post eventquery { // query to be triggered

virus.count, // attributeperiod=1.5, deadline=5, // timing infobase=(100,100) // base

station location}

}


Prioritized MAC

Query/Event Service



Geographic Forwarding

VelocityVelocity

• Timing constraint: deadline• Location constraint: distance to

destination• Requested Velocity

– Embody both constraints– Reflect local urgency– Velocity = Distance/Deadline

• Velocity Monotonic Scheduling (VMS)– Priority = Requested Velocity


Prioritized MAC

Query/Event Service



Geographic Forwarding

ExampleExample

dis = 60 m; D = 2 sV = 30 m/sLOW Priority

dis = 90 m; D = 2 sV = 45 m/sHIGH Priority

A

B

D

C



• Dynamic VMS

– Fixed velocity on each hop

– V=dis(x0,y0,xd,yd)/D

– Adapt velocity at intermediate node

– Vi = dis(xi,yi,xd,yd)/Si

– Slack: Si = D - elapsedTime

• Static VMS

F(remaining distance)

Deadline Miss RatioDeadline Miss Ratio

Overall Deadline Miss Ratios with deadlines (5,10)

Deadline Miss Ratio: FCFS>DS>DVM,SVM

Why SVM better than DVM ??

Critique - SPEEDCritique - SPEED

• No prioritization: uniform speed may not be what applications want

• The uniform speed is not guaranteed (soft real-time)

• Need periodic beacon to maintain neighbor table (costs energy)

• Needs symmetric communication

• Extensions– Multiple speeds– Different importance for streams– Consider energy explicitly

Critique - RAPCritique - RAP

• An early paper to provide soft real-time in sensor network– Provides Real-Time communication

architecture– Provides VMS

• As in SPEED, only soft real-time, no admission control, no guarantee– Difficult to consider congestion, noise,

retries, lost packets, etc.

Real-time routing is very difficult because of congestion, failures, retries, etc.

Implicit Geographic Forwarding

Implicit Geographic Forwarding

• Tackle the rapid dynamics found in WSNs

• To deal with– Power Down Nodes (Sleep mode)– Node Mobility– Node Failure– Scale

• Lazy Binding (to the nth degree)• State Free – no routing tables

Lazy Binding ConceptLazy Binding Concept

Defer mapping network topologies into volatile states (e.g. route state) as late as this operation allows (last 50 microsec in IGF).

Binding Time: Network Creation Network Maintenance End-to-End Request Forwarding operation

Protocols: FIX DSDV, GPSR,SPEED DSR, AODV,DD IGF

FIX Proactive On-Demand Lazy-BindingRouting Category:

Lazier

IGF IGF

IGF is a combined Routing/MAC protocol

Eligible nodes - 60 degree cone (shift cone if necessary)

RTS - set timer based on distance and energy remaining

R

A

D

S30

30

N

Asleep

Moving Away

Summary of EvaluationSummary of Evaluation

• Ten times improvement in delivery ratio under high dynamics compared to best solutions

• Reduces end-to-end delay significantly• Reduces control overhead significantly

• Tested for– Static, mobile and power saving networks– Test in presence of voids, localization errors,

different densities, toggle and sleep percentages

Simulation EvaluationSimulation Evaluation

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0 4 8 12 16Node Moving Speed (m/s)

IGFGPSRDSRLAR

Packet Delivery Ratio Under High mobility

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

5 15 25 35 45 55 65 75 85 95

Toggle Period (Second)

IGF

GPSR

DSR

LAR

Packet Delivery Ratio Under Node State Transition

SummarySummary

Reverse Path

Neighbor Table

AODV DSR DD LAR

GF GPSR SPEED

IGF (none)

SummarySummary

• Routing with global tables not appropriate

• ID-based not as appropriate (more for MANET networks)

SummarySummary

• Geographic/Location based– Asymmetries – Symmetric Geographic

Forwarding (radio realities)– Voids– Fast dynamics– Real-time– Low cost– Integrate with power management,

data aggregation and security (secure IGF)

Summary/IdeasSummary/Ideas

• Neighbor discovery• Geographic location• Flooding (truncated)• Duration field (drop after delta t)• Eliminate duplicates• Biological metaphor – gradients• Velocity• Aggregate Behavior

Summary/IdeasSummary/Ideas

• Specialized traffic patterns• Optimize for power, congestion,

robustness• Integration of functionality• Tailorable via API• Unicast • Broadcast, Area Multicast, Anycast• Use link quality

Final QuestionsFinal Questions

• Congestion control– Is it needed?

• Interaction with a MAC protocol– Reliable message transmission needed?– How/where to support reliability

Wireless Sensor Networks Routing

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