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Decomposing Networks and Polya Urns with the Power of Choice Joint work with Christos Amanatidis, Richard Karp, Christos Papadimitriou, Martha Sideri Presented By: Henry Lin

Decomposing Networks and Polya Urns with the Power of Choice

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Decomposing Networks and Polya Urns with the Power of Choice. Presented By: Henry Lin. Joint work with Christos Amanatidis, Richard Karp, Christos Papadimitriou, Martha Sideri. Overview. Motivations Linked Decompositions Preferential Attachment Model Analysis of a Polya Urns Process - PowerPoint PPT Presentation

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Page 1: Decomposing Networks   and Polya Urns with the Power of Choice

Decomposing Networks and Polya Urns with the Power of Choice

Joint work with Christos Amanatidis, Richard Karp, Christos Papadimitriou, Martha Sideri

Presented By:

Henry Lin

Page 2: Decomposing Networks   and Polya Urns with the Power of Choice

Overview

Motivations

Linked Decompositions

Preferential Attachment Model

Analysis of a Polya Urns Process

Open Problems

Page 3: Decomposing Networks   and Polya Urns with the Power of Choice

Motivations

The Internet is large and growing rapidly– difficult to manage– routers cannot store too much data

Can we divide up the network into distinct regions that can be managed mostly independently and still route efficiently?

Page 4: Decomposing Networks   and Polya Urns with the Power of Choice

Linked Decomposition

Decompose into c connected components

Each node belongs to 1 or 2 components

Each component has size ~ a

Any two components intersect

Page 5: Decomposing Networks   and Polya Urns with the Power of Choice

Linked Decomposition Example

Decompose into c = 3 connected (small diameter) components

Each node belongs to 1 or 2 components

Each component has size ~ a = 6

Any two components intersect

Page 6: Decomposing Networks   and Polya Urns with the Power of Choice

Routing with Linked Decompositions

How to route to node v in your component(s)?

Store each node in your component(s)

uv

Page 7: Decomposing Networks   and Polya Urns with the Power of Choice

Routing with Linked Decompositions

How to route to node v in your component(s)?

Store each node in your component(s)

How to route to node v outside of component?

Store an intersection node in your component to reach v

u

v

w

Page 8: Decomposing Networks   and Polya Urns with the Power of Choice

Routing with Linked Decompositions

How to route to node v in your component(s)?

Store each node in your component(s)

How to route to node v outside of component?

Store an intersection node in your component to reach v

u

v

w

Requires O(a) storage per node

Requires O(n/a) storage per node

Page 9: Decomposing Networks   and Polya Urns with the Power of Choice

Linked Decompositions Desiderata

Recall: we can route with O(a+n/a) tables

Therefore, we want: size a ~ n and thus number of components c ~ n and diameter ~ log n

Can we do this?

Page 10: Decomposing Networks   and Polya Urns with the Power of Choice

Note: Routing with n tables can be achieved by other means

For example, by compact routing [AGMNT ‘04]

But a linked decomposition is much more than a routing scheme:– It breaks down a network into many largely

independent components, with no harm to routing capabilities

It is also very simple

Page 11: Decomposing Networks   and Polya Urns with the Power of Choice

What about the Internet?

Can we decompose into c ~ n components Each node belongs to 1 or 2 components Each component has diameter ~ log n Each component has size a ~ n Any pair of components intersect

Page 12: Decomposing Networks   and Polya Urns with the Power of Choice

Surprise!

Yes! Our experiments show that the actual Internet graph has a linked decomposition with these approximate parameters

Main point of this paper: A theoretical justification for this phenomenon

By analyzing a well-studied random model of the Internet

Page 13: Decomposing Networks   and Polya Urns with the Power of Choice

Preferential Attachment Model

PA(m) : Nodes arrive one at a time, each new node:– selects m nodes iid at random, proportional to degree– adds one edge to each of the m selected nodes

Page 14: Decomposing Networks   and Polya Urns with the Power of Choice

Preferential Attachment Model

PA(m) : Nodes arrive one at a time, each new node:– selects m nodes iid at random, proportional to degree– adds one edge to each of the m selected nodes

Page 15: Decomposing Networks   and Polya Urns with the Power of Choice

Preferential Attachment Model

PA(m) : Nodes arrive one at a time, each new node:– selects m nodes iid at random, proportional to degree– adds one edge to each of the m selected nodes

Page 16: Decomposing Networks   and Polya Urns with the Power of Choice

Preferential Attachment Model

PA(m) : Nodes arrive one at a time, each new node:– selects m nodes iid at random, proportional to degree– adds one edge to each of the m selected nodes

Page 17: Decomposing Networks   and Polya Urns with the Power of Choice

Preferential Attachment Model

PA(m) : Nodes arrive one at a time, each new node:– selects m nodes iid at random, proportional to degree– adds one edge to each of the m selected nodes

Page 18: Decomposing Networks   and Polya Urns with the Power of Choice

Preferential Attachment Model

PA(m) : Nodes arrive one at a time, each new node:– selects m nodes iid at random, proportional to degree– adds one edge to each of the m selected nodes

Page 19: Decomposing Networks   and Polya Urns with the Power of Choice

Preferential Attachment Model

PA(m) : Nodes arrive one at a time, each new node:– selects m nodes iid at random, proportional to degree– adds one edge to each of the m selected nodes

Page 20: Decomposing Networks   and Polya Urns with the Power of Choice

Preferential Attachment Model

PA(m) : Nodes arrive one at a time, each new node:– selects m nodes iid at random, proportional to degree– adds one edge to each of the m selected nodes

Page 21: Decomposing Networks   and Polya Urns with the Power of Choice

Linked Decomposition in PA(m)

Decompose graph into c connected components

Each vertex belongs to 1 or 2 components Each component has diameter d Each component has size about a Any two components intersect

Our Main Result: PA(m) graphs have linked decompositions whp with parameters above– (Note: m depends on ε)

= Θ(n1/2+ε)

= Θ(n1/2-ε)

= log n

Page 22: Decomposing Networks   and Polya Urns with the Power of Choice

Decomposing PA(m) graphs

For each node t є {1, ... ,n1/2-ε}, we assign node t to its own component

n1/2-ε1 …

Page 23: Decomposing Networks   and Polya Urns with the Power of Choice

Decomposing PA(m) graphs

1. For each node t є {n1/2-ε + 1, ... ,n/2}, we look at where the m edges of node t point, and assign node t to the component of lowest total degree

n1/2-ε1 … n1/2-ε+1

Page 24: Decomposing Networks   and Polya Urns with the Power of Choice

Decomposing PA(m) graphs

n1/2-ε1 … n1/2-ε+1 …

2. For each node t є {n1/2-ε + 1, ... ,n/2}, we look at where the m edges of node t point, and assign node t to the component of lowest total degree

Page 25: Decomposing Networks   and Polya Urns with the Power of Choice

Decomposing PA(m) graphs

n1/2-ε1 … n1/2-ε+1 … n/2

2. For each node t є {n1/2-ε + 1, ... ,n/2}, we look at where the m edges of node t point, and assign node t to the component of lowest total degree

Page 26: Decomposing Networks   and Polya Urns with the Power of Choice

Decomposing PA(m) graphs

3. For each node t є {n/2 + 1, ... ,n}, we look at the first two edges of node t, and assign each node t to two components of the endpoints

n1/2-ε1 … n1/2-ε+1 … n/2 n/2+1

Page 27: Decomposing Networks   and Polya Urns with the Power of Choice

Decomposing PA(m) graphs

3. For each node t є {n/2 + 1, ... ,n}, we look at the first two edges of node t, and assign each node t to two components of the endpoints

n1/2-ε1 … n1/2-ε+1 … n/2 n/2+1

Page 28: Decomposing Networks   and Polya Urns with the Power of Choice

Decomposing PA(m) graphs

3. For each node t є {n/2 + 1, ... ,n}, we look at the first two edges of node t, and assign each node t to two components of the endpoints

n1/2-ε1 … n1/2-ε+1 … n/2 n/2+1

Page 29: Decomposing Networks   and Polya Urns with the Power of Choice

Decomposing PA(m) graphs

3. For each node t є {n/2 + 1, ... ,n}, we look at the first two edges of node t, and assign each node t to two components of the endpoints

n1/2-ε1 … n1/2-ε+1 … n/2 n/2+1

Page 30: Decomposing Networks   and Polya Urns with the Power of Choice

Decomposing PA(m) graphs

3. For each node t є {n/2 + 1, ... ,n}, we look at the first two edges of node t, and assign each node t to two components of the endpoints

n1/2-ε1 … n1/2-ε+1 … n/2 n/2+1

Page 31: Decomposing Networks   and Polya Urns with the Power of Choice

Decomposing PA(m) graphs

3. For each node t є {n/2 + 1, ... ,n}, we look at the first two edges of node t, and assign each node t to two components of the endpoints

n1/2-ε1 … n1/2-ε+1 … n/2 n/2+1 n

Page 32: Decomposing Networks   and Polya Urns with the Power of Choice

Decomposing PA(m) graphs

Decompose graph into c=Θ(n1/2-ε) connected components

Each vertex belongs to 1 or 2 components Each component has diameter d=O(log n) Each component has size a=Θ(n1/2+ε) Any two components intersect

n1/2-ε1 … n1/2-ε+1 … n/2 n/2+1 n

Page 33: Decomposing Networks   and Polya Urns with the Power of Choice

Recall: Polya Urns Process

Process starts with:– N bins/urns and1 ball in each bin

At each step, pick a random bin with probability proportional to load– Add one ball to the selected bin

Bin loads become unbalanced whp

Page 34: Decomposing Networks   and Polya Urns with the Power of Choice

Polya Urns with the Power of Choice

Process P starts with:– N bins, O(N) balls– Each bin contains ≥ 1 ball

Pick m bins iid at random, with replacement, probability proportional to load– Add one ball to the least loaded of the m bins

Does this process balance bin loads?

Page 35: Decomposing Networks   and Polya Urns with the Power of Choice

Our Main Technical Result

Theorem: For any ε > 0, there exists an m, s.t. if we run P for Θ(N2+ε) steps, the loads of all bins differ by at most by a factor of (1±ε).

More complicated analysis shows the degree & size of components become balanced after Ω(c2+ε) = n nodes arrive in PA(m)

The main result follows

Page 36: Decomposing Networks   and Polya Urns with the Power of Choice

Polya Urns w/ Choice: Two Bins

Lt = fractional load of low bin at time t

Ht = fractional load of high bin at time t

Key insight: Pr[add ball to high bin] = (Ht )m

< Ht

Pr[add ball to low bin] = (1 - (1-Lt )m ) > Lt

Thus both bins obtain the same load, and stay roughly balanced whp (Azuma’s Inequality)

Can use Chernoff bounds to show fractional load of high bin decreases quickly

Page 37: Decomposing Networks   and Polya Urns with the Power of Choice

Very Rough Proof Sketch

Define a marker bin M Bins with less load than M are low bins

– Show fractional load of low bins increase

Bins with more load than M are high bins– Show fractional load of high bins decrease

Eventually every bin obtains the same load as bin M, and subsequently stays roughly balanced with bin M

Page 38: Decomposing Networks   and Polya Urns with the Power of Choice

Open Problems

Does Polya urns with m=2 choices balance after O(N2+ε) balls? Our proof for m=2 gives O(N3).– New proof being checked…

What are necessary and sufficient conditions for a linked decomposition to exist?

Show linked decomposition routing has limited congestion and is robust against failures?

Incentives for autonomous systems to form a linked decomposition?

Page 39: Decomposing Networks   and Polya Urns with the Power of Choice

Thanks!

Questions?