Position-based Routing inAd Hoc Networks

Brad StephensonA presentation submitted in partial fulfillment of the

requirements of the course ECSE 6962

Objectives

• Introduction to position-based routing

• Discuss location services

• Discuss specific routing algorithms– Greedy algorithm– Directional flooding algorithm– Hierarchical algorithm

• Comparison with topology-based algorithms

Review

• Topology-based routing– Uses information about the (virtual) links that

exist in a wireless network– Can be:

• Proactive• Reactive• Hybrid

Position-based Routing

• Additional information is used to make routing decisions, namely the physical location of the node

• Decisions made based on destination’s position and position of forwarding node’s neighbors

• Uses a location service to obtain the location of the destination node

Position-based Routing

• Does not require routing tables

• Traffic overhead may be small

• Supports delivery of packets to a geographical area, called geocasting [NI]

• Three broad categories:– Greedy forwarding– Restricted directional flooding– Hierarchical methods

Location Services

• Centralized location service– Mobile nodes register their position with the

location service– The service is contacted when a routing node

wishes to find a destination node– Similar to cellular network– Requires that position servers be well-known– Only works with a non-ad-hoc external service

Location Services

• Decentralized location services can be:– All-for-all– All-for-some– Some-for-all– Some-for-some

• See [MWH]

Decentralized Location Services

C

A

D

EB

G

F

ID Direction Distance Timestamp

Node A wants to send an update

DREAM [B]

Decentralized Location Services

C

A

D

EB

G

F

ID Direction Distance Timestamp

Node A wants to send an update

DREAM [B]

Decentralized Location Services

C

A

D

EB

G

F

DREAM [B]

ID Direction Distance Timestamp

Node A wants to send an update

Decentralized Location Services

C

A

D

EB

G

F

Spatial Resolution

DREAM [B]

ID Direction Distance Timestamp

Node A wants to send an update

Decentralized Location Services

C

A

D

E

G

F

DREAM [B]

B

Temporal Resolution

Decentralized Location Services

C

A L

E

G

S

Quorum-Based [MWH]

H

I

B

J

KD

1

2

3

The backbone must be set up using a non-positionbased ad hoc routing mechanism

• Location information for node A is stored in a virtual homezone

• The position of the homezone can be found by applying a well-known hash function to the node ID

Decentralized Location ServicesHomezone [MWH]

Decentralized Location ServicesHomezone [MWH]

C

A

D

E

B

G

FP

Taxonomy of Routing Algorithms [S02]

Key Assumptions

• Unit Disk Graph (UDG) model of physical layer

• Nodes are in two dimensional space

• Homogeneous nodes in the network

• What major limitations do these assumptions expose?

• Depends on the application

Key ideas inPosition-based Routing Algorithms [GSB]

• Loop-freedom• Distributed operation• Path strategy• Metrics• Memorization• Guaranteed delivery• Scalability• Robustness

Loop-freedom

• Should be inherently loop-free

• Avoids recovery strategies– timeout of old packets– memorizing packets that have been seen

before

Distributed operation

• Localized algorithms are preferred if performance matches global algorithms

• Decisions made based on local information

• Reduced overhead

• If using n-hop neighbors, can be classified as 2-localized, 3-localized, etc.

Path Strategy

• Single path

• Flooding

• Directional Flooding

• Multipath

Metrics

• Hop count

• Hop quality

• Power consumption

• Policy-based cost

• Expected hop count (accounts for retransmissions) [S02]

Memorization

• Better to avoid memorizing traffic because of queue size and changes in mobility

• Required for QoS-guaranteed paths

Guaranteed Delivery

• Delivery rate = # delivered / # sent

• Guaranteed delivery has delivery rate = 1

• To achieve this, we need a MAC protocol which provides retransmit or no collisions

Scalability

• Increase in overhead as number of nodes increases

• Sometimes a subjective measure

Robustness

• How does mobility affect the algorithm

• How accurately can we determine the position of the destination

Greedy Algorithms

• Loop free [SL]• Localized information• Single path strategy• Metric: Hop count• No memory• No guarantee of delivery• Scalable, O( sqrt(n) ) [MWH]• Somewhat robust

Greedy Packet Forwarding

4

S

2

3

5

1 (x, y) = (10, 3)

“Send to (10, 3)”

R

D

Greedy Packet Forwarding

4

S

2

5

1

Most Forward within R [TK]

R

3D

Greedy Packet Forwarding

4

S

2

5

1

Nearest with Forward Progress [MWR]

R

3D

Greedy Packet Forwarding

4

S

2

D

5

1

Compass Routing [MWR]

R

3

Greedy Algorithms

• Most forward within R– Get as far as you can within sender’s range

• Nearest with forward progress– Makes collisions less likely

• Compass Routing– Send to nearest neighbor that is directly

between sender and receiver

Greedy Routing Failure [MWH]

Local maximum

Recovery Algorithms

• Greedy Perimeter Stateless Routing Protocol (GPSR)

• Face-2 algorithm

• Other variants/combinations

• Based on traversal of planar graphs

• Returns to greedy mode when closer to destination than when it entered recovery

Recovery Algorithms

• Construct the planar subgraph [T]

• Forward the packet along interior face using the right hand rule

Recovery Algorithms[MWH]

Recovery Algorithms

4

S

2

D

5

1

3

Assume communication only occurs along the

edges of the planar graph

Scan begins at incoming edge

Recovery Algorithms

4

S

2

D

5

1

3

Assume communication only occurs along the

edges of the planar graph

Recovery complete! Revert back to greedy mode

Restricted Directional Flooding

• Not loop free• Localized operation• Path strategy: flooding/multipath• Metric: Hop count• Memory• No guarantee of delivery• Not scalable, O(n) [MWH]• Not robust

Restricted Directional Flooding

• DREAM and LAR

• Send packet to all neighbors “in the direction” of D

• How do we determine this direction?

Restricted Directional FloodingDREAM Expected Region [B]

Expected Region

D

R

S

q

Restricted Directional Flooding

• Needs a recovery mechanism if no neighbor is in the direction of the expected region

• None specified in DREAM proposal

• Area of future work

DREAM Expected Region [B]

Restricted Directional Flooding

• Uses the idea of restricted flooding toward the expected region for path discovery in non-position-based routing protocols [KV]

Location-Aided Routing [KV]

Hierarchical Routing

• Terminodes and Grid Routing

• Possibly reduces the complexity of information each node has to handle

• Improves scalability

• Can ad hoc networks also reap these benefits?

• Not without tradeoffs!

Hierarchical Routing

• Uses greedy approach for long-distance routing

• Uses non-position-based approach at the local level (proactive distance vector)

• Allows non-position-aware nodes to participate

• More tolerant of position inaccuracy

• More complex to implement

Grid Routing [MWH]

Topological vs. Positional

• Terminodes shown to improve packet delivery rates and overhead compared to reactive ad hoc routing [BGL]

• GPSR performs better than DSR in almost all criteria including overhead and delivery rate [Br]

• Both results are from simulations

Are there any applications?

• Vehicle-to-vehicle communication networks

• Geocasting can be useful for …– Tactical military information– Disaster response– Personalized Internet experience– Home security

(IMHO)

• Very little experimental work done, mostly simulation

• Assumptions limit the scope, practicality of results

• Solution: Need more engineering graduate students to conduct experiments

Future Work

• There is a plethora of ideas• Quantitative work must be performed• Investigate hashing in highly dynamic

networks• Probabilistic approach• Recovery strategies within constraints• Deeper hierarchies (3-tier, etc.)• What about anonymity?

Open Problems Remaining

• Mobility-caused loops

• Congestion considerations (replace hop count metric with e2e delay)

• Quality of Service considerations

• An excellent recent paper on using a non-UDG model is [SNK]

References• [B] Basagni, S., et al, A Distance Routing Effect Algoritm for

Mobility (DREAM). MOBICOM ’98.• [BGL] Blazevic, L., et al, Self Organized Terminode Routing.

IEEE Commun. Magazine, 2001.• [Br] Broch, J., et al, A Performance Comparison of Multi-hop

Wireless Ad Hoc Networking Routing Protocols. MOBICOM ’98.

• [GSB] Giordano, S., et al, Position Based Routing Algorithms for Ad Hoc Networks: A Taxonomy. www.site.uottawa.ca/~ivan/routing-survey.pdf

• [KV] Ko, Y.B. and Vaidya, N.H., Location-Aided Routing (LAR) in Mobile Ad Hoc Networks. ACM/Baltzer WINET J., vol. 6, no. 4, 2000.

• [MWH] Mauve, M., et al, A Survey on Position-Based Routing in Mobile Ad Hoc Networks. IEEE Network, November/December 2001.

References (cont.)• [NI] Navas, J.C. and Imielinski, T., Geographic Addressing and

Routing. MOBICOM ’97.• [S02] Stojmenovic, I., Position-Based Routing in Ad Hoc Networks.

IEEE Commun. Magazine, July 2002.• [SL] Stojmenovic, I. and Lin, X., Loop-free hybrid

single-path/flooding routing algorithms with guaranteed delivery for wireless networks. IEEE Trans. on Parallel and Distributed Systems, Oct. 2001

• [SNK] Stojmenovic, I., et al, Design Guidelines for Routing Protocols in Ad Hoc and Sensor Networks with a Realistic Physical Layer. IEEE Commun. Magazine, March 2005.

• [T] Toussaint, G. The Relative Neighborhood Graph of a Finite Planar Set. Pattern Recognition, vol. 12, no.4, 1980.

• [TK] Takagi, H. and Kleinrock, L., Optimal Transmission Ranges for Randomly Distributed Packet Radio Terminals. IEEE Trans. on Commun., 1984.