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6.829 Computer Networks Lecture 6: 6.829 Computer Networks Lecture 6:

6.829 Computer Networks Lecture 6: - PowerPoint Presentation

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6.829 Computer Networks Lecture 6: - PPT Presentation

Network Utility Maximization Mohammad Alizadeh Fall 2016 1 What Problem is TCP really solving 2 1 Mbs x 1 x 2 x 3 Maxmin rate allocation x 1 x 2 x 3 Maxmin ID: 931052

num log network utility log num utility network problem maximization tcp max maximize subject sx1 solving min link fairness

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Slide1

6.829Computer Networks

Lecture 6: Network Utility MaximizationMohammad AlizadehFall 2016

1

Slide2

What Problem is TCP really solving?

2

1 Mb/s

x

1

= ?

x

2

= ?

x

3

= ?

Max-min rate allocation?

x

1

x

2

x

3

Max-min

1/31/31/3TCP1/31/31/3

Assuming equal RTTs

Slide3

What Problem is TCP really solving?

3

1 Mb/s

x

1

= ?

x

2

= ?x3 = ?Max-min rate allocation?1 Mb/s

x

1

x

2

x

3

Max-min

1/2

1/2

1/2

TCP

~0.4

~0.6

~0.6

Slide4

What Problem is TCP

really solving?

4

1 Mb/s

x

1

= ?

x

2

= ?x3 = ?1 Mb/s

1 Mb/s

What is the difference between these links?

Slide5

What Problem is TCP really solving?

5

Slide6

Network Utility Maximization

6

TCP is solving

an optimization

problem!

Spurred a lot of research on analyzing and designing network protocols from the lens of optimization

>

5000 citations

Slide7

Outline for Rest of Lecture

Network Utility Maximization (NUM)Distributed Algorithm for NUMTCP’s NUM Problem

7

Slide8

Utility Function

The benefit derived from sending at rate x

We’ll assume U(.) is

increasing

&

concave

8

Good model for elastic flows

e

.g. file downloads

Slide9

Examples of Utility Functions

9

Slide10

Network Utility Maximization (NUM)

maximize log(x1) + log(x2) + log(x3)subject to: x

1 + x2 ≤ 1

x

1

+

x

3 ≤

1 10c1 = 1 Mb/sx1 x2 x3

c

2

= 1 Mb/s

Slide11

Network Utility Maximization (NUM)

maximize log(x1) + log(x2) + log(x3)subject to:

11

x

1

x

2

x

3

1 1 01 0 1c1 = 1 Mb/sx1 x2 x3

c

2

= 1 Mb/s

1

1

Slide12

NUM: General Case

12

maximize

subject to:

x

1

x

2

x

Nc1c2cL0 1 0 1 11 0 1 0 0

0

0 1 1 0N flowsL linksRLxN routing matrix

Slide13

NUM Example 1: Throughput Maximization

13maximize x1 + x2 + x

3subject to:

x

1

+ x

2

≤ 1

x1 + x3 ≤ 1 c1 = 1 Mb/sx1 x2 x3

c

2

= 1 Mb/s

x

1

=

0 Mb/s

x

2

=

1

Mb/s

x

3

=

1

Mb/s

Slide14

NUM Example 2: Proportional Fairness

14maximize log(x1) + log(x2

) + log(x3)subject to: x

1

+ x

2

≤ 1

x1 + x3 ≤ 1 c1 = 1 Mb/sx1 x2 x3

c

2

= 1 Mb/s

x

1

= 1/3

Mb/s

x

2

=

2/3

Mb/s

x

3

=

2/3

Mb/s

Slide15

NUM Example 3:“α-fairness”

15

c

1

= 1 Mb/s

x

1

x

2

x3

c

2

= 1 Mb/s

maximize

subject to: x

1

+ x

2

≤ 1

x

1

+

x

3

1

α ≥ 0 (a constant)

alpha

Objective

α = 0

Thrput

Maximization

α = 1

Proportional

Fairness

α

∞

Max-min Fairness

Slide16

Outline

The Network Utility Maximization (NUM) ProblemDistributed Algorithm for NUMTCP’s NUM Problem16

Slide17

Proportional Fairness Example

maximize log(x1) + log(x2) + log(x3)subject to: x1

+ x2 ≤ 1

x

1

+

x

3 ≤

1 17c1 = 1 Mb/sx1 x2 x3

c

2

= 1 Mb/s

Slide18

Distributed Algorithm

18

c

1

= 1 Mb/s

x

1

x

2

x3

c

2

= 1 Mb/s

p

l

= “congestion price” for link

l

price per

unit of bandwidth (

p

l

≥ 0)

q

i

= total price for source

i

Sum of prices on source

i’s

path

p

1

p

2

Slide19

The Source Problem

19

c

1

= 1 Mb/s

x

1

x

2

x3

c

2

= 1 Mb/s

Pick

rate x

i

to

maximize utility: log(x

i

) – q

i

x

i

p

1

p

2

x

i

= 1/q

i

This is done

independently

at each

source.

benefit

cost

Slide20

The Network Problem

20

c

1

= 1 Mb/s

x

1

x

2

x3

c

2

= 1 Mb/s

Adapt link prices periodically based on congestion

p

1

p

2

p

l

(t+1) = [

p

l

(

t) +

κ

(

y

l

(t) – c

l

) ]

+

total traffic at link

l

[.]

+

= max(., 0)

Slide21

The Network Problem

21

c

1

= 1 Mb/s

x

1

x

2

x3

c

2

= 1 Mb/s

Adapt link prices periodically based on congestion

p

1

p

2

p

l

(t+1) = [

p

l

(

t) +

κ

(

y

l

(t) – c

l

) ]

+

This is done

independently

at each

link.

Slide22

Putting it All Together

22

c

1

= 1 Mb/s

x

1

x

2

x3

c

2

= 1 Mb/s

Sources

p

1

p

2

x

1

(t) = 1 / (p

1

(t) + p

2

(t))

x

2

(

t) = 1 /

p

1

(t

)

x

3

(

t) = 1 /

p

2

(t

)

Links

p

1

(t+1) = [p

1

(t) +

κ

(y

1

(t) – c

1

)]

+

p

2

(

t+1) = [

p

2

(

t) +

κ

(

y2(t) – c2)]+

Slide23

Example

23

Slide24

Outline

The Network Utility Maximization (NUM) ProblemNUM Distributed AlgorithmTCP’s NUM Problem24

Slide25

TCP + PI

25

c

1

= 1 Mb/s

x

1

x

2

x3

c

2

= 1 Mb/s

Sources

p

1

p

2

Links

p

1

(t+1) = [p

1

(t) +

κ

(y

1

(t) – c

1

)]

+

p

2

(

t+1) = [

p

2

(

t) +

κ

(

y

2

(

t) –

c

2

)

]

+

x

1

(t) = 1 / RTT

1

x

2

(

t) = 1 /

RTT

2

x

3

(

t) = 1 / RTT3

Slide26

What is TCP’s Utility Function?

26

Slide27

27