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Scattering Scatter Problem No Deterministic Solution Randomized Solution Related Problems and Self-Stabilization Conclusions Scatter Problem

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(1)

Scattering

1. 

Scatter Problem

2. 

No Deterministic Solution

3. 

Randomized Solution

4. 

Related Problems and Self-Stabilization

1.  Gathering Problem

2.  Pattern Formation Problems

5. 

Conclusions

Scatter Problem

(2)

Scatter Problem

Scatter Problem

 

Convergence

Regardless of the initial positions of the

matter clusters – mobile robots, entities, or agents -,

no two such things are eventually located at the same position.

 

Closure

Starting from a configuration where non two

matter clusters – mobile robots, entities, or agents -, are located at the same position,

no two such things are located at the same position thereafter.

(3)

Model

 

Autonomous

Weak robots

No central authority

Model

 

Autonomous

Weak robots

Move on the plane

Undistinguishable, same program No past

Observation of positions

Detect that more than one robot at a given position Common coordinate system

 

Mobile

 

Anonymous

 

Oblivious

 

No Explicit Communications

 

Multiplicity Detection

 

Localization Knowledge

(4)

Model

  Time Infinite sequence of time instants

  At each time instant t

  Each robot is either active or inactive

  Each active robot

  Observes

  Computes

  Moves

  At least one robot is activated

  Every robot is infinitely often activated (fairness)

Deterministic Scatter

Weak robots

(5)

Randomized Scatter

Compute the Voronoi Diagram If Random() = 0

then move arbitrarily in my cell

Randomized Scatter

Compute the Voronoi Diagram If Random() = 0

then move arbitrarily in my cell

(6)

Randomized Scatter

Compute the Voronoi Diagram If Random() = 0

then move arbitrarily in my cell

Randomized Scatter

Compute the Voronoi Diagram If Random() = 0

then move arbitrarily in my cell

(7)

Randomized Scatter

Compute the Voronoi Diagram If Random() = 0

then move arbitrarily in my cell

Randomized Scatter

Compute the Voronoi Diagram If Random() = 0

then move arbitrarily in my cell

(8)

Randomized Scatter

Compute the Voronoi Diagram If Random() = 0

then move arbitrarily in my cell

Randomized Scatter

Compute the Voronoi Diagram If Random() = 0

then move arbitrarily in my cell

(9)

Related Problems

 

Gathering Problem (GP)

Regardless of the initial positions on the plane of the mobile robots, make them gather at one point in a finite number of time instants.

[Ando et al. 99] [ Suzuki Yamashita 99] [Flocchini et al. 01]

[Cieliebak Prencipe 02] [Cieliebak et al. 03]

 

Pattern Formation Problem (PFP)

Regardless of the initial positions on the plane of the mobile robots, make them to form a desired pattern in a finite number of time instants.

For instance: regular n-gon (circle formation problem)

[ Suzuki Yamashita 99] [Flocchini et al. 99] [Flocchini et al. 01]

[Defago Konagaya 02] [Katreniak 05] [Dieudonné et al. 06]

[Dieudonné Petit 07]

Related Problems

 

Gathering Problem (GP)

 

Pattern Formation Problem (PFP)

 

Convergence: Starting from an arbitrary configuration, the robots eventually form a desirable configuration

 

Closure: Starting from a configuration where the robots are in the desirable configuration, they remain in a desirable configuration thereafter

Common Requirements for

specification:

(10)

Self-Stabilization

 

Convergence

Regardless of the initial state of the system, a self-stabilizing system is guaranteed to converge to the indented behavior in a finite number of time instants

 

Closure

If the system behaves according to its specifications, then it behaves according to its specification forever

Convergence phase

Expected behavior

closure with a probability equal to 1

Deterministic Probabilistic

Related Problems

 

Gathering Problem (GP)

 

Pattern Formation Problem (PFP)

 

Convergence and Closure

Common Requirements for specification:

 

In the initial configuration, no two robots are located at the same position

No Deterministic solution for GP or PFP is

« truly » self-stabilizing

(11)

Probabilistic Self-Stabilization

Combination of our scatter algorithm and any algorithm for the GP or PFP

… but unfortunately it does not work yet!

Randomized Scatter

Compute the Voronoi Diagram If Random() = 0

then move arbitrarily in my cell

How to make them quiescent?

(12)

Randomized Scatter

If there exists a position with more than one robot

then Compute the Voronoi Diagram If Random() = 0

then move arbitrarily in my cell

How to make them quiescent?

Termination detection of the scatter algorithm

Self-Stabilizing Gathering

If there exists at least two positions with more than one robot

then Scatter else Gather

(13)

Self-Stabilizing Gathering

If there exists at least two positions with more than one robot

then Scatter else Gather

Self-Stabilizing Gathering

If there exists at least two positions with more than one robot

then Scatter else Gather

(14)

Self-Stabilizing Pattern Formation

If there exists at least one position with more than one robot

then Scatter

else Pattern Formation

Self-Stabilizing Gathering

If there exists at least one position with more than one robot

then Scatter

else Pattern Formation

(15)

Self-Stabilizing Gathering

If there exists at least one position with more than one robot

then Scatter

else Pattern Formation

Conclusion

 

Scatter Problem

 

No Deterministic Solution

 

Randomized Solution

 

Randomized Self-Stabilizing Solutions

 

Gathering Problem

 

Pattern Formation Problems

 

Scatter in a weaker model (CORDA)

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