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Deterministic Leader Election in Multi-Hop Beeping Networks Deterministic Leader Election in Multi-Hop Beeping Networks

Deterministic Leader Election in Multi-Hop Beeping Networks - PowerPoint Presentation

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Deterministic Leader Election in Multi-Hop Beeping Networks - PPT Presentation

What Algorithm to take Deterministic Heuristic Randomization Leader Election LeaderElection Leader Why deterministic leader election Why deterministic leader ID: 172387

1100 beep iteration beeping beep 1100 beeping iteration leader model deterministic election ids length listen 111 silence neighbor beeps

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Slide1

Deterministic Leader Election in Multi-Hop Beeping NetworksSlide2

What

Algorithm to take?

Deterministic

Heuristic

RandomizationSlide3

Leader

ElectionSlide4

LeaderElection

LeaderSlide5

Why

deterministic

leader election?Slide6

Why

deterministic

leader election?

Slide7

Single-Hop

from

[Willard, 1986] to

[

Clementi

et al., 2003]

(

depending

on

the

model)

Multi-Hopwith collision detection (deterministic):

[Kowalski & Pelc, 2009]without collision

detection (randomized

):

[

Czumaj

&

Rytter

, 2006]

[

Chlebus

et al.,

2012

]

(

deterministic

):

[

Chlebus

et al., 2012

]

[Kowalski & Pelc,

2009]

[

Vaya

, 2011]

 

Leader Election – Wireless Radio NetworksSlide8

Each

round: b

eep or listen

Listen: silence

or beep

(at least

one

neighbor

beeps

)

The Beeping ModelSlide9

Each

round: beep

or listenListen:

silence or

beep (at least

one

neighbor beeps

)

The Beeping Model

Beep

Listen

Listen

ListenSlide10

Each

round: beep

or listenListen:

silence or

beep (at least

one

neighbor beeps

)

The Beeping Model

Beep

Listens:

Silence

Listens:

Beep

Listens:

BeepSlide11

Each

round: beep

or listenListen:

silence or

beep (at least

one

neighbor beeps

)

The Beeping Model

Beep

Listen

Listen

BeepSlide12

Each

round: beep

or listenListen:

silence or

beep (at least

one

neighbor beeps

)

The Beeping Model

Beep

Listens:

Beep

Listens:

Beep

BeepSlide13

Randomized: [

Ghaffari

& Haeupler

, 2013]

 

Leader Election – in the Beeping ModelSlide14

Deterministic

& Uniform:

[this paper]

 

Deterministic Leader Election – in the Beeping Model

1110

1100

1010

1101Slide15

Deterministic Leader Election – in the Beeping Model

1

110

1

100

1

010

1

101Slide16

Deterministic Leader Election – in the Beeping Model

1

1

10

1

1

00

1

0

10

1

1

01Slide17

Deterministic Leader Election – in the Beeping Model

11

1

0

11

0

0

10

10

11

0

1Slide18

Deterministic Leader Election – in the Beeping Model

111

0

110

0

10

10

110

1

Slide19

Deterministic Leader Election – in the Beeping Model

1110

1100

1010

1101

1111

1111Slide20

Multi-Hop

Beeping

Model

110

Winner

Listening

Not sendingSlide21

But

what

about

Uniformity

?

I

know

nothing

(

I‘m

Jon Snow)Slide22

IDs

of

different length?

1100

111

10

1

11

10...01

 Slide23

IDs

of different length?

1100

111

10

1

11

10...01

 Slide24

IDs

of

different

length

?

1100

111

10

1

11

10...01

 Slide25

IDs

of

different

length

?

1100

1100

10

1

11

10...01

 Slide26

IDs

of

different

length

?

1100

1100

1100

1

11

10...01

 Slide27

IDs

of

different

length

?

1100

1100

1100

1100

10...01

 Slide28

IDs

of

different

length

?

1100

111

10

1

11

10...01

 

1. Iteration

done

1. Iteration

runningSlide29

IDs

of

different

length

?

1100

111

10

1

11

10...01

 

1. Iteration

done

1. Iteration

runningSlide30

IDs

of

different

length

?

1100

111

10

1

11

10...01

 

1. Iteration

done

1. Iteration

running

I

want

to

start

with

Iteration 2!

But I am still in

Iteration 1!Slide31

IDs

of

different

length

?

1100

111

10

1

11

10...01

 

1. Iteration

done

1. Iteration

running

Iteration

?

LISTEN

Iteration

?

LISTEN

Iteration

?

BEEP

 

Iteration

?

LISTEN

Iteration

?

BEEP

Iteration

?

LISTEN

 Slide32

Repeat

the

campaigning

process

times ->

But

how

big

is

?How do we stop?

 Quiescence?Slide33

Quiescence

?

Solution: Overlay Onion NetworkSlide34

Multi-Hop Leader

Election

in the Beeping Model

rounds

Deterministic

UniformQuiescent

Combinesa local campaigning algorithm

a technique to sequentially execute algorithms

an

overlay

onion

network

 ConclusionSlide35

Deterministic Leader Election in Multi-Hop Beeping Networks