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The “New Network Node” Algorithm. Brought to you by: Brian Wolf (Researcher) Harlan Russell (Advisor) Joe Hammond (Advisor Emeritus) Vivek Mehta (Graduate Student) Praveen Appani (Graduate Student). Outline. Mobile, Distributed, Wireless Networks Time Division Multiple Access

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Presentation Transcript
The “New Network Node” Algorithm

Brought to you by:

Brian Wolf (Researcher)

Joe Hammond (Advisor Emeritus)

Vivek Mehta (Graduate Student)

Praveen Appani (Graduate Student)

• Mobile, Distributed, Wireless Networks

• Time Division Multiple Access

• Algorithm for adding a New Node

• How well does this algorithm work?

• Conclusions

?

Mobile, Distributed, Wireless Network

• All network nodes are mobile

• No permanent network infrastructure

• No centralized control

• Variable terrain and propagation conditions

• Network topology can be irregular

Regular

Irregular

• Time is divided into fixed-length time slots

• In one time slot, a node may transmit or receive 1 message

• Collisions prevent a node from receiving a message

Collision Type 1:

two neighbors transmit

at the same time

Collision Type 2:

one node has two neighbors

transmit at the same time

(examples)

Fully Connected Network

Linear Network

2

1

3

1

5

3

2

4

5

4

Slot #

Slot #

3

5

1

2

4

3

5

1

2

4

R

3. New Node

3

1

5

2

4

• When a New Node powers up, it:

• Listens to network to find out who neighbors are

• Announces its presence by “shouting”

• Waits while neighbors quiet down their neighbors

• Exchanges transmission scheduling information

• Modifies schedule as needed to improve efficiency

• Goals for New Node Algorithm:

• Convergence - completion time

• 2) Success - new node knows all about neighbors

• - neighbors know all about new node

Tested by:

1) Randomly generated networks

2) Variable Density (avg. # of neighbors)

Soft failure: Node has all neighbors, but information about cycle size is wrong or 2 neighbors are not deferring

Hard failure: Node failed to detect all neighbors

• Algorithm takes longer to complete in dense networks

• Algorithm is more reliable in dense networks

• Chance of having undetected neighbors (hard failure) is small

• Complete success (no failures) is much harder to achieve for some network densities than others

• Finish the algorithm

• Test the algorithm more extensively

• Develop alternative algorithms

• Improve simulation software