an analysis of the information spreading delay in heterogeneous mobility dtns

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An Analysis of the Information Spreading Delay in Heterogeneous Mobility DTNs Andreea Picu Dr. T . Spyropoulos Theus Hossmann Computer Engineering and Networks Laboratory (TIK) Communication Systems Group (CSG) July 24, 2012

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Page 1: An Analysis of the Information Spreading Delay in Heterogeneous Mobility DTNs

7/22/2019 An Analysis of the Information Spreading Delay in Heterogeneous Mobility DTNs

http://slidepdf.com/reader/full/an-analysis-of-the-information-spreading-delay-in-heterogeneous-mobility-dtns 1/45

An Analysis of the Information Spreading Delay inHeterogeneous Mobility DTNs

Andreea Picu Dr. T. Spyropoulos Theus Hossmann

Computer Engineering and Networks Laboratory (TIK)Communication Systems Group (CSG)

July 24, 2012

Page 2: An Analysis of the Information Spreading Delay in Heterogeneous Mobility DTNs

7/22/2019 An Analysis of the Information Spreading Delay in Heterogeneous Mobility DTNs

http://slidepdf.com/reader/full/an-analysis-of-the-information-spreading-delay-in-heterogeneous-mobility-dtns 2/45

Outline

Motive & Goals

Our New Analysis

Empirical Resultsand Insights

Applications

Conclusion &Outlook

Outline

1

  Motivation & Goals2   Our New Analysis

Model and Delay Def.sDelay Derivation: The Gist

The Bounds3 Empirical Results and Insights

Bounds ValidationScaling with Network Size

4 Applications

5 Conclusion & Outlook

Picu, Spyropoulos, Hossmann   Information Spreading in DTNs   2 of 23

Page 3: An Analysis of the Information Spreading Delay in Heterogeneous Mobility DTNs

7/22/2019 An Analysis of the Information Spreading Delay in Heterogeneous Mobility DTNs

http://slidepdf.com/reader/full/an-analysis-of-the-information-spreading-delay-in-heterogeneous-mobility-dtns 3/45

Outline

Motive & Goals

Our New Analysis

Empirical Resultsand Insights

Applications

Conclusion &Outlook

Epidemic Information Spreading

Some node generates a message m...

Picu, Spyropoulos, Hossmann   Information Spreading in DTNs   3 of 23

Page 4: An Analysis of the Information Spreading Delay in Heterogeneous Mobility DTNs

7/22/2019 An Analysis of the Information Spreading Delay in Heterogeneous Mobility DTNs

http://slidepdf.com/reader/full/an-analysis-of-the-information-spreading-delay-in-heterogeneous-mobility-dtns 4/45

Outline

Motive & Goals

Our New Analysis

Empirical Resultsand Insights

Applications

Conclusion &Outlook

Epidemic Information Spreading

... “infected” nodes replicate m to every encountered node...

Picu, Spyropoulos, Hossmann   Information Spreading in DTNs   3 of 23

Page 5: An Analysis of the Information Spreading Delay in Heterogeneous Mobility DTNs

7/22/2019 An Analysis of the Information Spreading Delay in Heterogeneous Mobility DTNs

http://slidepdf.com/reader/full/an-analysis-of-the-information-spreading-delay-in-heterogeneous-mobility-dtns 5/45

Outline

Motive & Goals

Our New Analysis

Empirical Resultsand Insights

Applications

Conclusion &Outlook

Epidemic Information Spreading

... “infected” nodes replicate m to every encountered node...

Picu, Spyropoulos, Hossmann   Information Spreading in DTNs   3 of 23

Page 6: An Analysis of the Information Spreading Delay in Heterogeneous Mobility DTNs

7/22/2019 An Analysis of the Information Spreading Delay in Heterogeneous Mobility DTNs

http://slidepdf.com/reader/full/an-analysis-of-the-information-spreading-delay-in-heterogeneous-mobility-dtns 6/45

Outline

Motive & Goals

Our New Analysis

Empirical Resultsand Insights

Applications

Conclusion &Outlook

Epidemic Information Spreading

... until the whole network is “infected”.

Picu, Spyropoulos, Hossmann   Information Spreading in DTNs   3 of 23

Page 7: An Analysis of the Information Spreading Delay in Heterogeneous Mobility DTNs

7/22/2019 An Analysis of the Information Spreading Delay in Heterogeneous Mobility DTNs

http://slidepdf.com/reader/full/an-analysis-of-the-information-spreading-delay-in-heterogeneous-mobility-dtns 7/45

Outline

Motive & Goals

Our New Analysis

Empirical Resultsand Insights

Applications

Conclusion &Outlook

Epidemic Information Spreading

Simple

Robust

Works in any local information exchange context

Sometimes, the only option...

In DTNs:

broadcast routing / flooding

unicast routingdistributed estimationetc

Picu, Spyropoulos, Hossmann   Information Spreading in DTNs   4 of 23

Page 8: An Analysis of the Information Spreading Delay in Heterogeneous Mobility DTNs

7/22/2019 An Analysis of the Information Spreading Delay in Heterogeneous Mobility DTNs

http://slidepdf.com/reader/full/an-analysis-of-the-information-spreading-delay-in-heterogeneous-mobility-dtns 8/45

Outline

Motive & Goals

Our New Analysis

Empirical Resultsand Insights

Applications

Conclusion &Outlook

Common assumptions in existing analyses

1 Permanent network connectivitysynchronous operationability to communicate with all neighbors at will

2 Specific graph geometriescomplete, bipartite, Erdos-Renyi, regular etc.

3 Homogeneous communication rate  λ

Picu, Spyropoulos, Hossmann   Information Spreading in DTNs   5 of 23

Page 9: An Analysis of the Information Spreading Delay in Heterogeneous Mobility DTNs

7/22/2019 An Analysis of the Information Spreading Delay in Heterogeneous Mobility DTNs

http://slidepdf.com/reader/full/an-analysis-of-the-information-spreading-delay-in-heterogeneous-mobility-dtns 9/45

Outline

Motive & Goals

Our New Analysis

Empirical Resultsand Insights

Applications

Conclusion &Outlook

In the DTN context

All nodes are identical   ⇒   can be treated as group

Real DTN experiments   ⇒   heterogeneous mobility

Picu, Spyropoulos, Hossmann   Information Spreading in DTNs   6 of 23

Page 10: An Analysis of the Information Spreading Delay in Heterogeneous Mobility DTNs

7/22/2019 An Analysis of the Information Spreading Delay in Heterogeneous Mobility DTNs

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Outline

Motive & Goals

Our New Analysis

Empirical Resultsand Insights

Applications

Conclusion &Outlook

In the DTN context

All nodes are identical   ⇒   can be treated as group

Real DTN experiments   ⇒   heterogeneous mobility

Picu, Spyropoulos, Hossmann   Information Spreading in DTNs   6 of 23

Page 11: An Analysis of the Information Spreading Delay in Heterogeneous Mobility DTNs

7/22/2019 An Analysis of the Information Spreading Delay in Heterogeneous Mobility DTNs

http://slidepdf.com/reader/full/an-analysis-of-the-information-spreading-delay-in-heterogeneous-mobility-dtns 11/45

Outline

Motive & Goals

Our New Analysis

Model and Delay Def.s

Delay Derivation: The Gist

The Bounds

Empirical Results

and Insights

Applications

Conclusion &Outlook

What we do...

All nodes are beautiful snowflakes

Heterogeneous communication rates  λi j

N -state Markov chain   ⇒   N -state Markov chain

Bounds for delay distribution

Dependency on contact graph properties

Picu, Spyropoulos, Hossmann   Information Spreading in DTNs   7 of 23

Page 12: An Analysis of the Information Spreading Delay in Heterogeneous Mobility DTNs

7/22/2019 An Analysis of the Information Spreading Delay in Heterogeneous Mobility DTNs

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Outline

Motive & Goals

Our New Analysis

Model and Delay Def.s

Delay Derivation: The Gist

The Bounds

Empirical Results

and Insights

Applications

Conclusion &Outlook

Heterogeneous Mobility

(i , j) meeting probability:   pci j  =   λ i j

∑  λ i j

Contact probability matrix:

Pc=

  pc

 

  pc

 pc       pcN ⋮ ⋮ ⋮

 pcN     

 pci j   estimated from pairwise intercontacts of  (i, j)

Picu, Spyropoulos, Hossmann   Information Spreading in DTNs   8 of 23

l d

Page 13: An Analysis of the Information Spreading Delay in Heterogeneous Mobility DTNs

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Outline

Motive & Goals

Our New Analysis

Model and Delay Def.s

Delay Derivation: The Gist

The Bounds

Empirical Results

and Insights

Applications

Conclusion &Outlook

Delays We Are Interested in

Total spreading delay:DSSS  = inf {n  >    ∶ S(T n)  = V }   (1)

Partial spreading delay:

DSSS(α)  = inf {n  >    ∶ S(T n)  =  α}   (2)

Transition delay:

Dα  = DSSS(α + ) − DSSS(α)   (3)

Picu, Spyropoulos, Hossmann   Information Spreading in DTNs   9 of 23

D l D i ti Th Gi t

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Outline

Motive & Goals

Our New Analysis

Model and Delay Def.s

Delay Derivation: The Gist

The Bounds

Empirical Results

and Insights

Applications

Conclusion &Outlook

Delay Derivation: The Gist

Picu, Spyropoulos, Hossmann   Information Spreading in DTNs   10 of 23

D l D i ti Th Gi t

Page 15: An Analysis of the Information Spreading Delay in Heterogeneous Mobility DTNs

7/22/2019 An Analysis of the Information Spreading Delay in Heterogeneous Mobility DTNs

http://slidepdf.com/reader/full/an-analysis-of-the-information-spreading-delay-in-heterogeneous-mobility-dtns 15/45

Outline

Motive & Goals

Our New Analysis

Model and Delay Def.s

Delay Derivation: The Gist

The Bounds

Empirical Resultsand Insights

Applications

Conclusion &Outlook

Delay Derivation: The Gist

Picu, Spyropoulos, Hossmann   Information Spreading in DTNs   10 of 23

D l D i ti Th Gi t

Page 16: An Analysis of the Information Spreading Delay in Heterogeneous Mobility DTNs

7/22/2019 An Analysis of the Information Spreading Delay in Heterogeneous Mobility DTNs

http://slidepdf.com/reader/full/an-analysis-of-the-information-spreading-delay-in-heterogeneous-mobility-dtns 16/45

Outline

Motive & Goals

Our New Analysis

Model and Delay Def.s

Delay Derivation: The Gist

The Bounds

Empirical Resultsand Insights

Applications

Conclusion &Outlook

Delay Derivation: The Gist

Picu, Spyropoulos, Hossmann   Information Spreading in DTNs   10 of 23

D l D i ti Th Gi t

Page 17: An Analysis of the Information Spreading Delay in Heterogeneous Mobility DTNs

7/22/2019 An Analysis of the Information Spreading Delay in Heterogeneous Mobility DTNs

http://slidepdf.com/reader/full/an-analysis-of-the-information-spreading-delay-in-heterogeneous-mobility-dtns 17/45

Outline

Motive & Goals

Our New Analysis

Model and Delay Def.s

Delay Derivation: The Gist

The Bounds

Empirical Resultsand Insights

Applications

Conclusion &Outlook

Delay Derivation: The Gist

Picu, Spyropoulos, Hossmann   Information Spreading in DTNs   10 of 23

Delay Derivation The Gist

Page 18: An Analysis of the Information Spreading Delay in Heterogeneous Mobility DTNs

7/22/2019 An Analysis of the Information Spreading Delay in Heterogeneous Mobility DTNs

http://slidepdf.com/reader/full/an-analysis-of-the-information-spreading-delay-in-heterogeneous-mobility-dtns 18/45

Outline

Motive & Goals

Our New Analysis

Model and Delay Def.s

Delay Derivation: The Gist

The Bounds

Empirical Resultsand Insights

Applications

Conclusion &Outlook

Delay Derivation: The Gist

Picu, Spyropoulos, Hossmann   Information Spreading in DTNs   10 of 23

Delay Derivation The Gist

Page 19: An Analysis of the Information Spreading Delay in Heterogeneous Mobility DTNs

7/22/2019 An Analysis of the Information Spreading Delay in Heterogeneous Mobility DTNs

http://slidepdf.com/reader/full/an-analysis-of-the-information-spreading-delay-in-heterogeneous-mobility-dtns 19/45

Outline

Motive & Goals

Our New Analysis

Model and Delay Def.s

Delay Derivation: The Gist

The Bounds

Empirical Resultsand Insights

Applications

Conclusion &Outlook

Delay Derivation: The Gist

Picu, Spyropoulos, Hossmann   Information Spreading in DTNs   10 of 23

Delay Derivation: The Gist

Page 20: An Analysis of the Information Spreading Delay in Heterogeneous Mobility DTNs

7/22/2019 An Analysis of the Information Spreading Delay in Heterogeneous Mobility DTNs

http://slidepdf.com/reader/full/an-analysis-of-the-information-spreading-delay-in-heterogeneous-mobility-dtns 20/45

Outline

Motive & Goals

Our New Analysis

Model and Delay Def.s

Delay Derivation: The Gist

The Bounds

Empirical Resultsand Insights

Applications

Conclusion &Outlook

Delay Derivation: The Gist

Picu, Spyropoulos, Hossmann   Information Spreading in DTNs   10 of 23

Transition Delay

Page 21: An Analysis of the Information Spreading Delay in Heterogeneous Mobility DTNs

7/22/2019 An Analysis of the Information Spreading Delay in Heterogeneous Mobility DTNs

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Outline

Motive & Goals

Our New Analysis

Model and Delay Def.s

Delay Derivation: The Gist

The Bounds

Empirical Resultsand Insights

Applications

Conclusion &Outlook

Transition Delay

Picu, Spyropoulos, Hossmann   Information Spreading in DTNs   11 of 23

Transition Delay

Page 22: An Analysis of the Information Spreading Delay in Heterogeneous Mobility DTNs

7/22/2019 An Analysis of the Information Spreading Delay in Heterogeneous Mobility DTNs

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Outline

Motive & Goals

Our New Analysis

Model and Delay Def.s

Delay Derivation: The Gist

The Bounds

Empirical Resultsand Insights

Applications

Conclusion &Outlook

Transition Delay

Picu, Spyropoulos, Hossmann   Information Spreading in DTNs   11 of 23

Transition Delay

Page 23: An Analysis of the Information Spreading Delay in Heterogeneous Mobility DTNs

7/22/2019 An Analysis of the Information Spreading Delay in Heterogeneous Mobility DTNs

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Outline

Motive & Goals

Our New Analysis

Model and Delay Def.s

Delay Derivation: The Gist

The Bounds

Empirical Resultsand Insights

Applications

Conclusion &Outlook

Transition Delay

Picu, Spyropoulos, Hossmann   Information Spreading in DTNs   11 of 23

Transition Delay

Page 24: An Analysis of the Information Spreading Delay in Heterogeneous Mobility DTNs

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Outline

Motive & Goals

Our New Analysis

Model and Delay Def.s

Delay Derivation: The Gist

The Bounds

Empirical Resultsand Insights

Applications

Conclusion &Outlook

Transition Delay

Expected delay from state x  to state y :

 

 pxy 

 pxy  =   pcia  + pcib   + pc jc   + pckb

=   i∈Sα ;   j∉Sα

 pci j

=   cut volume of vertex set   Sα

=   ∂(Sα)

Expected transition delay:   E[Dα]   maxx , y 

 

 pxy   =

minSα

∂(Sα)

Picu, Spyropoulos, Hossmann   Information Spreading in DTNs   12 of 23

Transition Delay

Page 25: An Analysis of the Information Spreading Delay in Heterogeneous Mobility DTNs

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Outline

Motive & Goals

Our New Analysis

Model and Delay Def.s

Delay Derivation: The Gist

The Bounds

Empirical Resultsand Insights

Applications

Conclusion &Outlook

Transition Delay

Expected delay from state x  to state y :

 

 pxy 

 pxy  =   pcia  + pcib   + pc jc   + pckb

=   i∈Sα ;   j∉Sα

 pci j

=   cut volume of vertex set   Sα

=   ∂(Sα)

Expected transition delay:   E[Dα]   maxx , y 

 

 pxy   =

minSα

∂(Sα)

Picu, Spyropoulos, Hossmann   Information Spreading in DTNs   12 of 23

Transition Delay

Page 26: An Analysis of the Information Spreading Delay in Heterogeneous Mobility DTNs

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Outline

Motive & Goals

Our New Analysis

Model and Delay Def.s

Delay Derivation: The Gist

The Bounds

Empirical Resultsand Insights

Applications

Conclusion &Outlook

Transition Delay

Expected delay from state x  to state y :

 

 pxy 

 pxy  =   pcia  + pcib   + pc jc   + pckb

=   i∈Sα ;   j∉Sα

 pci j

=   cut volume of vertex set   Sα

=   ∂(Sα)

Expected transition delay:   E[Dα]   maxx , y 

 

 pxy   =

minSα

∂(Sα)

Picu, Spyropoulos, Hossmann   Information Spreading in DTNs   12 of 23

Transition Delay

Page 27: An Analysis of the Information Spreading Delay in Heterogeneous Mobility DTNs

7/22/2019 An Analysis of the Information Spreading Delay in Heterogeneous Mobility DTNs

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Outline

Motive & Goals

Our New Analysis

Model and Delay Def.s

Delay Derivation: The Gist

The Bounds

Empirical Resultsand Insights

Applications

Conclusion &Outlook

Transition Delay

Expected delay from state x  to state y :

 

 pxy 

 pxy  =   pcia  + pcib   + pc jc   + pckb

=   i∈Sα ;   j∉Sα

 pci j

=   cut volume of vertex set   Sα

=   ∂(Sα)

Expected transition delay:   E[Dα]   maxx , y 

 

 pxy   =

minSα

∂(Sα)

Picu, Spyropoulos, Hossmann   Information Spreading in DTNs   12 of 23

Transition Delay

Page 28: An Analysis of the Information Spreading Delay in Heterogeneous Mobility DTNs

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Outline

Motive & Goals

Our New Analysis

Model and Delay Def.s

Delay Derivation: The Gist

The Bounds

Empirical Resultsand Insights

Applications

Conclusion &Outlook

Transition Delay

Expected delay from state x  to state y :

 

 pxy 

 pxy  =   pcia  + pcib   + pc jc   + pckb

=   i∈Sα ;   j∉Sα

 pci j

=   cut volume of vertex set   Sα

=   ∂(Sα)

Expected transition delay:   E[Dα]   maxx , y 

 

 pxy   =

minSα

∂(Sα)

Picu, Spyropoulos, Hossmann   Information Spreading in DTNs   12 of 23

Total Delay Bound

Page 29: An Analysis of the Information Spreading Delay in Heterogeneous Mobility DTNs

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Outline

Motive & Goals

Our New Analysis

Model and Delay Def.s

Delay Derivation: The Gist

The Bounds

Empirical Resultsand Insights

Applications

Conclusion &Outlook

y

Graph  α-conductance:   Φα  = minSα

  ∂(Sα)α ⋅

(N   − α

)

Graph conductance:   Φ  = minα

Φα

Key Inequality

minSα

(Sα) 

  Φα  ⋅ α

(N   − α

  Φ⋅ α

(N   − α

)

E

[DSSS

] =

N −

α=

E

[Dα

N −

α=

Φα   ⋅ α(N   − α)

N −

α=

Φ ⋅ α(N   − α)   = ln(N   − )

N Φ

Picu, Spyropoulos, Hossmann   Information Spreading in DTNs   13 of 23

Total Delay Bound

Page 30: An Analysis of the Information Spreading Delay in Heterogeneous Mobility DTNs

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Outline

Motive & Goals

Our New Analysis

Model and Delay Def.s

Delay Derivation: The Gist

The Bounds

Empirical Resultsand Insights

Applications

Conclusion &Outlook

y

Graph  α-conductance:   Φα  = minSα

  ∂(Sα)α ⋅

(N   − α

)

Graph conductance:   Φ  = minα

Φα

Key Inequality

minSα

(Sα) 

  Φα  ⋅ α

(N   − α

  Φ⋅ α

(N   − α

)

E

[DSSS

] =

N −

α=

E

[Dα

N −

α=

Φα   ⋅ α(N   − α)

N −

α=

Φ ⋅ α(N   − α)   = ln(N   − )

N Φ

Picu, Spyropoulos, Hossmann   Information Spreading in DTNs   13 of 23

Total Delay Bound

Page 31: An Analysis of the Information Spreading Delay in Heterogeneous Mobility DTNs

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Outline

Motive & Goals

Our New Analysis

Model and Delay Def.s

Delay Derivation: The Gist

The Bounds

Empirical Resultsand Insights

Applications

Conclusion &Outlook

y

Graph  α-conductance:   Φα  = minSα

  ∂(Sα)α ⋅

(N   − α

)

Graph conductance:   Φ  = minα

Φα

Key Inequality

minSα

(Sα)    Φ

α  ⋅ α

(N   − α

)    Φ ⋅ α

(N   − α

)

E

[DSSS

] =

N −

α=

E

[Dα

N −

α=

Φα   ⋅ α(N   − α)

N −

α=

Φ ⋅ α(N   − α)   = ln(N   − )

N Φ

Picu, Spyropoulos, Hossmann   Information Spreading in DTNs   13 of 23

Total Delay Bound

Page 32: An Analysis of the Information Spreading Delay in Heterogeneous Mobility DTNs

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Outline

Motive & Goals

Our New Analysis

Model and Delay Def.s

Delay Derivation: The Gist

The Bounds

Empirical Resultsand Insights

Applications

Conclusion &Outlook

y

Graph  α-conductance:   Φα  = minSα

  ∂(Sα)α ⋅

(N   − α

)

Graph conductance:   Φ  = minα

Φα

Key Inequality

minSα

(Sα)    Φ

α  ⋅ α

(N   − α

)    Φ ⋅ α

(N   − α

)

E

[DSSS

] =

N −

α=

E

[Dα

N −

α=

Φα   ⋅ α(N   − α)

N −

α=

Φ ⋅ α(N   − α)   = ln(N   − )

N Φ

Picu, Spyropoulos, Hossmann   Information Spreading in DTNs   13 of 23

What Just Happened?

Page 33: An Analysis of the Information Spreading Delay in Heterogeneous Mobility DTNs

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Outline

Motive & Goals

Our New Analysis

Model and Delay Def.s

Delay Derivation: The Gist

The Bounds

Empirical Resultsand Insights

Applications

Conclusion &Outlook

pp

Exact delay formula based on cut volumes  ∂(Sα)st bound:replace all α−cut volumes with resp.  α−conductance Φα

nd bound:

replace all cut volumes with overall graph conductance Φ

Implications:

Bounds’ tightness depends on graph structure

No discernable communities ⇒ very tight bounds

Clear community structure ⇒ less tight bounds

Picu, Spyropoulos, Hossmann   Information Spreading in DTNs   14 of 23

Distribution Bound

Page 34: An Analysis of the Information Spreading Delay in Heterogeneous Mobility DTNs

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Outline

Motive & Goals

Our New Analysis

Model and Delay Def.s

Delay Derivation: The Gist

The Bounds

Empirical Resultsand Insights

Applications

Conclusion &Outlook

P[ DSSS  = k]  =N 

α=

wα pα( − pα)k−,i.e., sum of geometrics.

Picu, Spyropoulos, Hossmann   Information Spreading in DTNs   15 of 23

Distribution Bound

Page 35: An Analysis of the Information Spreading Delay in Heterogeneous Mobility DTNs

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Outline

Motive & Goals

Our New Analysis

Model and Delay Def.s

Delay Derivation: The Gist

The Bounds

Empirical Resultsand Insights

Applications

Conclusion &Outlook

P[ DSSS  = k]  =N 

α=

wα pα( − pα)k−,i.e., sum of geometrics.

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Distribution Bound

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Outline

Motive & Goals

Our New Analysis

Model and Delay Def.s

Delay Derivation: The Gist

The Bounds

Empirical Resultsand Insights

Applications

Conclusion &Outlook

P[ DSSS  = k]  =N 

α=

wα pα( − pα)k−,i.e., sum of geometrics.

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Distribution Bound

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Outline

Motive & Goals

Our New Analysis

Model and Delay Def.s

Delay Derivation: The Gist

The Bounds

Empirical Resultsand Insights

Applications

Conclusion &Outlook

P[ DSSS  = k]  =N 

α=

wα pα( − pα)k−,i.e., sum of geometrics.

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The NCP: Indicator of Community Structure

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Outline

Motive & Goals

Our New Analysis

Empirical Resultsand Insights

Bounds Validation

Scaling with Network Size

Applications

Conclusion &Outlook

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Expected Spreading Delays

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Outline

Motive & Goals

Our New Analysis

Empirical Resultsand Insights

Bounds Validation

Scaling with Network Size

Applications

Conclusion &Outlook

Expected spreading delays   Coefficients of variation

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Spreading Delay CCDFs

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Outline

Motive & Goals

Our New Analysis

Empirical Resultsand Insights

Bounds Validation

Scaling with Network Size

Applications

Conclusion &Outlook

Infocom MIT

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Spreading Delay CCDFs

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Outline

Motive & Goals

Our New Analysis

Empirical Resultsand Insights

Bounds Validation

Scaling with Network Size

Applications

Conclusion &Outlook

HCMM   SLAW and MIT

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Algorithms Based on Epidemic Spreading

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Outline

Motive & Goals

Our New Analysis

Empirical Resultsand Insights

Applications

Conclusion &Outlook

Randomized forwarding

Distributed estimation

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Conclusion

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Outline

Motive & Goals

Our New Analysis

Empirical Resultsand Insights

Applications

Conclusion &Outlook

New analysis for epidemic spreading in DTNs:

Much more generic mobility

Bounds for expected delay & delay distribution

Bound tightness linked to graph structure

Delay scaling behaviour linked to graph structure

Applies to algorithms based on epidemic spreading

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Outlook

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Outline

Motive & Goals

Our New Analysis

Empirical Resultsand Insights

Applications

Conclusion &Outlook

Further relax mobility assumptionsSemi-MarkovNo exponential assumption

Further explore the applications domain

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The End

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Outline

Motive & Goals

Our New Analysis

Empirical Resultsand Insights

Applications

Conclusion &Outlook

Thank you for your attention.

Please, ask questions.

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