Wireless Sensor Networks Ad hoc and Sensor Networks Routing Protocols Joris Dobbelsteen Martijn van den Heuvel October 2008

Goals 

ID-centric routing 





Each node has unique identifier

Explain routing protocols 

Energy-efficiency vs robustness



Mobile nodes

NOT data-centric routing 

Look at chapter 12

October 2008

Joris Dobbelsteen, Martijn van den Heuvel

2

Overview 

Introduction



Protocol Classification



Unicast routing



Broadcast/Multicast routing



Geographic routing



Concluding remarks

October 2008

Joris Dobbelsteen, Martijn van den Heuvel

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Terms 









Forwarding Principle of receiving data and sending it again Routing Deciding how and where to forward Unicast Sending end-to-end (think Internet) Broadcast Sending to multiple parties (think TV) Multicast Send to multiple, but only interested, parties

October 2008

Joris Dobbelsteen, Martijn van den Heuvel

4

Basic Ideas 

Flooding 



Send a packet to all neighbours

Gossip 

Send a packet to a random selected neighbour

October 2008

Joris Dobbelsteen, Martijn van den Heuvel

5

Overview 

Introduction



Protocol Classification



Unicast routing



Broadcast/Multicast routing



Geographic routing



Concluding remarks

October 2008

Joris Dobbelsteen, Martijn van den Heuvel

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Protocol classification 

Proactive or table-driven protocol 



On-demand or reactive protocol 



Always keep routing data up-to-date

Route is only determined when needed

Hybrid protocols

October 2008

Joris Dobbelsteen, Martijn van den Heuvel

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Protocol Classification 

Distance Vector 



Based on Distributed Bellman-Ford

Link State 

Based on Dijkstra's Shortest Path

October 2008

Joris Dobbelsteen, Martijn van den Heuvel

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Distance Vector Routing 

Share routing table with neighbours



Vectors:



Periodic updates

October 2008

Joris Dobbelsteen, Martijn van den Heuvel

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DV – Distr. Bellman-Ford Initial Table

October 2008

Joris Dobbelsteen, Martijn van den Heuvel

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DV – Distr. Bellman-Ford Update from D to E:

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Joris Dobbelsteen, Martijn van den Heuvel

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DV – Distr. Bellman-Ford Update from B to A:

(Path to C not optimal yet!)

October 2008

Joris Dobbelsteen, Martijn van den Heuvel

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DV – Distr. Bellman-Ford After all updates:

October 2008

Joris Dobbelsteen, Martijn van den Heuvel

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Distance Vector Issues 

Looping: Send packet from A to C over B: B sends packet back ● No update from B to A ● A repeats send to B ●

Solutions: ● Introduce route time-outs ● Split horizon October 2008

Joris Dobbelsteen, Martijn van den Heuvel

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Distance Vector Issues 

Count to infinity:

Solution: Introduce max amount of hops October 2008

Joris Dobbelsteen, Martijn van den Heuvel

15

Link State Routing 

Identify neighbours



Identify link costs to neighbours



Flood neighbour info



Local Dijkstra's Shortest Path computation

October 2008

Joris Dobbelsteen, Martijn van den Heuvel

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Links State – Dijkstra

October 2008

Joris Dobbelsteen, Martijn van den Heuvel

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Link State Routing 

Solves count to infinity



Prevent looping: 

Periodically re-discover neighbours

October 2008

Joris Dobbelsteen, Martijn van den Heuvel

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Routing protocols Stateless Unicast

Stateful OLSR

Gossip

DSR AODV

Rumor routing

DSDV

TORA GeoTORA

Multicast/ Broadcast

GeRaF GPSR Flooding GEM ~ WSN

October 2008

Joris Dobbelsteen, Martijn van den Heuvel

BIP

~ MANET 19

Overview 

Introduction



Protocol Classification



Unicast routing Sending end-to-end



Broadcast/Multicast routing



Geographic routing



Concluding remarks

October 2008

Joris Dobbelsteen, Martijn van den Heuvel

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Unicast Routing 

Rumor routing



DSDV



OLSR



Dynamic Source Routing



AODV



TORA

October 2008

Joris Dobbelsteen, Martijn van den Heuvel

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Rumor routing 



Two agents 

Event source



Sink

Both perform a random walk until they intersect 

Path is established ?

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Joris Dobbelsteen, Martijn van den Heuvel

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Rumor routing 

Pro  





Simple On-demand, low protocol overhead Scales reasonably

October 2008

Con 

Risk of long paths



No guarenteed delivery



Not mobile



Tuned for infrequent events

Joris Dobbelsteen, Martijn van den Heuvel

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Unicast Routing 

Rumor routing



DSDV



OLSR



Dynamic Source Routing



AODV



TORA

October 2008

Joris Dobbelsteen, Martijn van den Heuvel

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DSDV 

Destination Sequence Distance Vector (DSDV) 

Based on distributed Bellman Ford



Route updates contain sequence number  

Detect updates Expires old routes

Prevent routing loops



Periodically send full route updates



On topology change, send incremental route updates



Unstable route updates are delayed

October 2008

Joris Dobbelsteen, Martijn van den Heuvel

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DSDV 

Pro



Con



High delivery rate



Complicated nodes



Short paths



High protocol overhead



Mobility





But not too much

Continuesly propagates updates 



October 2008

Network-wide

Does not scale

Joris Dobbelsteen, Martijn van den Heuvel

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Unicast Routing 

Rumor routing



DSDV



OLSR



Dynamic Source Routing



AODV



TORA

October 2008

Joris Dobbelsteen, Martijn van den Heuvel

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OLSR 

Optimized Link State Routing (OLSR) 

Based on Dijkstra's shortest path algorithm



Link-state 



Topology control  



Proactively maintains link state database

Use ”multipoint relays” (MPR) Allows efficient flooding

Send link state often to compensate for unreliability

October 2008

Joris Dobbelsteen, Martijn van den Heuvel

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OLSR 

Pro



Con



Widely used





Mobile









Not too much

Complicated nodes Continuesly propagates updates

Extensions for link quality Scales fairly good

October 2008

Joris Dobbelsteen, Martijn van den Heuvel

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Unicast Routing 

Rumor routing



DSDV



OLSR



Dynamic Source Routing



AODV



TORA

October 2008

Joris Dobbelsteen, Martijn van den Heuvel

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Dynamic Source Routing

4

5

3

5

[1

,2

[1,

,6

]

4,5 ]

2

6

[1,2,6]

7

]

5

3

6

7

Destination gives route reply 1

[1,2,3]

October 2008

7

6



1

4

4

[1,4

[1,2]

[1,2]

2]

Reactive → Discover by route requests [1] 1 1 3 2 2 [1,

[ 1]



4

2 5

Joris Dobbelsteen, Martijn van den Heuvel

6

3

7 31

Dynamic Source Routing 

Uses small ”route discovery”-packets



Source routing: sender specifies route



Extensions: 

Cache known routes



Learn from control messages send by other nodes



Try to repair lost route instead of re-discovery

October 2008

Joris Dobbelsteen, Martijn van den Heuvel

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Dynamic Source Routing 

Pro



Con



Simple



Flooding overhead



Reliably finds paths



Not mobile



Not scalable



Path only available at end-points

October 2008



Large packets

Joris Dobbelsteen, Martijn van den Heuvel

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Unicast Routing 

Rumor routing



DSDV



OLSR



Dynamic Source Routing



AODV



TORA

October 2008

Joris Dobbelsteen, Martijn van den Heuvel

34

AODV 

Ad hoc On demand Distance Vector 

Reactive protocol based on DSR



But routing tables instead of source routing



Add sequence numbers (as DSDV) 

Prevent count-to-infinity



Populate table using any received packet



Used in practice

October 2008

Joris Dobbelsteen, Martijn van den Heuvel

35

AODV 

Pro



Con



Used in practice



Complicated node



Reliably finds paths



Flooding overhead



Relative short paths



Mobile 

October 2008

Resolve stale caches

Joris Dobbelsteen, Martijn van den Heuvel

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Unicast Routing 

Rumor routing



DSDV



OLSR



Dynamic Source Routing



AODV



TORA

October 2008

Joris Dobbelsteen, Martijn van den Heuvel

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TORA 

Temporally-Ordered Routing Algorithm 

Maintain directed acyclic graph to specific destination  



Discovery using flooding (as DSR) Or proactive from destination

Work with heights 

Send packet to lower height router



When no outgoing edge, reconfigure



Can optimize routes

October 2008

Joris Dobbelsteen, Martijn van den Heuvel

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TORA Example Source

A

B E

D

C

A

F

C1

B E

D

1

F

Destination

Assign heights

DSR: find paths 3

A 2

D October 2008

0

B E

2

1

Joris Dobbelsteen, Martijn van den Heuvel

C F

1

0 39

TORA example 3

A 2

D

B E

2

1

C1 F

A 2

3

A 4

D

B E

D

0

No outgoing edge: increase height (+2)

October 2008

3

2

3

C F

1

0

Reconfigure heights B E

2

3

Joris Dobbelsteen, Martijn van den Heuvel

C F

1

0 40

TORA 

Pro 



Updates only to neighboors



Always loop-free



Scales reasonable



Reaches destination



Fault tolerance



Mobile

October 2008

Con 

Complicated node



Not optimal paths



No energy consideration

Joris Dobbelsteen, Martijn van den Heuvel

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Overview 

Introduction



Protocol Classification



Unicast routing Broadcast/Multicast routing 

Sending to multiple parties



Geographic routing



Concluding remarks

October 2008

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Broadcast/Multicast Routing Basic options 

Source-based tree: 



Shared, core-based trees: 



Construct a tree for every source

Use only a single tree for all sources

Mesh 

Improve redundancy

October 2008

Joris Dobbelsteen, Martijn van den Heuvel

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Optimizing Total Cost Make use of “wireless multicast advantage” Steiner tree

Shortest path tree Source

2

2

Destination 2

1

Destination 1

● ●

Source

2

2

Destination 2

1

Destination 1

Shortest Path: Minimize each single path Steiner tree: Minimize total network

Steiner Tree Problem is proven NP-hard! October 2008

Joris Dobbelsteen, Martijn van den Heuvel

44

Steiner Approximations 

Simple approximation  





Successively add using shortest path to some tree vertex Performs reasonably well in practice

Takahashi Matsuyama heuristic  



Randomly order vertices

Start with source node Add a destination node to the tree which has shortest path to an already added node

Wireless multicast advantage not exploited

October 2008

Joris Dobbelsteen, Martijn van den Heuvel

45

Broadcast Incremental Power 

Minimize total transmission power



Use a minimum-spanning-tree-type construction





Once a node transmits at a given power level, it becomes cheaper to reach additional neighbors From BIP to multicast incremental power (MIP): 

Start with broadcast tree



Prune unnecessary edges

October 2008

Joris Dobbelsteen, Martijn van den Heuvel

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BIP example Round 1:

Round 3:

A 5

S 3

D C

Round 2:

October 2008

Round 4:

D

3 B

7 2

C (1)

A

S (3)

B

9 D

1

3

S (1)

7

7

2

4

B

S (5) 10

C

A

3 B

7

1

A

3

S (3)

B

7

10 D

2

3 1

Round 5:

A

6

7 D

1 C

C (1) Joris Dobbelsteen, Martijn van den Heuvel

47

Broadcast Incremental Power 

Pro 

Power efficient



Cheap paths



Con 

Need underlying link state



Complex



Not mobile



High protocol overhead 

October 2008

Measure energy cost

Joris Dobbelsteen, Martijn van den Heuvel

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Overview 

Introduction



Protocol Classification



Unicast routing



Broadcast/Multicast routing



Geographic routing 



Use node location to aid routing

Concluding remarks

October 2008

Joris Dobbelsteen, Martijn van den Heuvel

49

Geographic routing 

ID based on geographic location 



Position-based routing 



Or mapping service

Use position to aid routing

Geocasting 

Send to any node in an area

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Basic geo-routing strategies 

Most forward within range 



Nearest node with (any) progress 



Node, within range, that is closest to destination

Minimize transmission power

Directional routing 

Closest to angle towards destination

October 2008

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GPSR 

Geometric Perimeter State Routing 



Uses greedy “most forward” strategy When stuck: 





Follow face using right-hand rule Switch to greedy when no longer needed

Requires planar graph

October 2008

Joris Dobbelsteen, Martijn van den Heuvel

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GPSR 

Pro



Con



Easy implementation



Long paths



Reaches destination



Not energy efficient



Scalable 



Mobile 



Known neighbours only Update location

Low protocol overhead

October 2008

Joris Dobbelsteen, Martijn van den Heuvel

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GeRaF 

Geometric Random Forwarding 

Handles nodes turning on and off



Basic idea  



Sender broadcasts packet Some receiver picks up and forward packet

Handling multiple forwarders 

October 2008

Larger forwarding probability when closer to destination

Joris Dobbelsteen, Martijn van den Heuvel

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GeRaF example

S Closer to destination Higher probability

D

October 2008

Joris Dobbelsteen, Martijn van den Heuvel

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GeRaF example

S

D

October 2008

Joris Dobbelsteen, Martijn van den Heuvel

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GeRaF 

Pro 



Scalable 





No state to maintain

Multiple paths 



Redundancy



Mobile



Relative short paths

October 2008

Con Probably reaches destination Multiple paths  

Protocol overhead Energy consuming

Joris Dobbelsteen, Martijn van den Heuvel

57

Graph Embedding (GEM) 

Constructs geographic structure 

Uses polar coordinates



Build spanning tree   

October 2008

Starting at central point (root) Distance = number of hops from root Angle = where in neighbourhood

Joris Dobbelsteen, Martijn van den Heuvel

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An g

le

GEM example

Di sta

nc e

Root October 2008

Joris Dobbelsteen, Martijn van den Heuvel

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Graph Embedding (GEM) 

Pro



Con



Reaches destination



Not mobile



Low protocol overhead



Difficult setup



Scalable



Short paths

October 2008



Determine angles

Joris Dobbelsteen, Martijn van den Heuvel

60

Geographic routing 

Position-based routing 



Use position to aid routing

Geocasting 

Send to any node in an area

October 2008

Joris Dobbelsteen, Martijn van den Heuvel

61

Location-Based Multicast 



Geocast: Flood within geographically restricted area Reach the “multicast zone” through “forwarding zone” 

Forwarding zone includes multicast zone and source



May make forwarding zone smaller with progress



Based on distance Multicast zone

S October 2008

Forwarding zone

Joris Dobbelsteen, Martijn van den Heuvel

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GeoTORA 

Based on TORA: 



Use TORA to reach any sink (anycast) 





Region of nodes are destination

Anycast: Reach one of the destinations

The sink floods the region Basically LBM, but with TORA for forwarding

October 2008

S

A T OR

Multicast zone

Forwarding zone

Joris Dobbelsteen, Martijn van den Heuvel

63

GeoTORA 

Pro 



Single protocol for unicast and multicast



Always loop-free



Scales reasonable



Reaches destination



Fault tolerance

October 2008

Con  



Complicated nodes No energy considerations No shortest paths

Joris Dobbelsteen, Martijn van den Heuvel

64

Trajectory-Based Forwarding 



Think of agent 

moving along trajectory



collection information

Describe trajectory 



Forward to next closest node

Theory only

October 2008

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65

Conclusion 

Pro-active protocols need considerable resources



Geo-routing scales better



Routing can 

Extend network lifetime



Optimize for energy consumption

Note: energy ≠ network lifetime 

'Best' routing protocol depends on application

October 2008

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66

References 











Holger Karl, Andreas Wilig; ”Protocols and Architectures for Wireless Sensor Networks”; Chap 11, John Wiley & sons Ltd; England, 2006; 0-470-09510-5 Andrew S. Tanenbaum; “Computernetwerken”; Chap 5.2, Pearson Education Benelux 4th edition 2nd reprint November 2005; 90-430-0698-X SECAN-LAB; “Interoperability Laboratory for Security in Ad-Hoc Networks”; 2006, University of Luxembourg; http://wiki.uni.lu/secan-lab/ James Newsome, Dawn Song; “GEM: Graph Embedding for Routing and Data-centric Storage in Sensor Networks Without Geographic Information”; ACM Conference Proceedings; November 2003 T. Clausen, P. Jacquet; “Optimized Link State Routing Protocol (OLSR)”; IETF RFC 3626 V. Park, S. Corson; “Temporally-Ordered Routing Algorithm (TORA) ”; version 1; work in progress Courtesy: Peter van der Stok and Holger Karl

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