energy aware

8/13/2019 Energy Aware

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Energy-aware Networks:

Reducing Power Consumption

by Switching Off

Network Elements

Luca Chiaraviglio

Marco Mellia

Fabio Neri

May 2008


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Motivations

Goals Solutions

Results

Technical issues Conclusions

Outline


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Introduction

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1. bush

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6. tibet

7. iraq8. india

9. macedonia

10. modern love


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Introduction

Italian Debt for Kyoto delay: 440.000.000 euro .Italy must pay a daily fine of 4.111.000 (47,6 per second) for the failure to

achieve the objectives of Kyoto Protocol from 2008.


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Introduction

ICT alone is responsible of a percentage which vary widely

from 2% to 10% of the world power consumption.


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Reduce the energy consumption of a network

Can be achieved by Reducing power consumption of devices

Routers: reduce cpu/memory/asics power consumption

Links: design more efficient modulation, low power tx

Reduce power consumption of the whole network

Efficient DESIGN of the network

Our Goal


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a physical network topology built by routers and links, inwhich links have a known capacity

the knowledge of the average amount of traffic

exchanged by any source/destination node pair

the power consumption of each link and node,

Problem Formulation

Given

the set of routers and links that must be powered on so that

the total power consumption is minimized

flow conservation and maximum link utilization constraints.

Find

Subject to


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Problem Formulation

yiis a router

xi jis a link with capacityci j

tsdis the traffic fromstod

fsdi jis the traffic fromstodon

link fromi toj

is the overprovisioning

constraint

P is the power

The problem isNP-complete!


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Algorithms

Node Heuristics

Link Heuristics

Least Flow

Random

Least Flow

Least Link

Random

Simpleheuristics!!


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,

Algorithms - II

1 2


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Topology

,

Core

Aggregation

Edge

10

30

120

5

3

2

Num

Nodes

Links

degree

Sources - Destinations

Tsd=U[0.5,1.5] Cij=min(floor(fij/),cijmin)


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Simulation Results

,

0,00%

5,00%

10,00%

15,00%

20,00%

25,00%

30,00%

LEAST_FLOW -

LEAST_FLOW

LEAST_LINK -

LEAST_FLOW

RANDOM -

LEAST_FLOW

RANDOM -

RANDOM

LEAST_FLOW -

RANDOM

LEAST_LINK -

RANDOM

L

Node Heuristic - Link Heuristic

Heuristics Comparison


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Simulation Results - II

,

0,00%

2,00%

4,00%

6,00%

8,00%

10,00%

12,00%

14,00%

LEAST_FLOW -

LEAST_FLOW

LEAST_LINK -

LEAST_FLOW

RANDOM -

LEAST_FLOW

RANDOM -

RANDOM

LEAST_FLOW -

RANDOM

LEAST_LINK -

RANDOM

N

Node Heuristic - Link Heuristic

Heuristics Comparison (2)


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Simulation Results - III

,

5,00%

10,00%

15,00%

20,00%

25,00%

30,00%

50 55 60 65 70 75 80 85 90 95 100

L

Percentage of links switched off versus

LEAST_FLOW - LEAST_FLOW

LEAST_LINK - LEAST_FLOW

RANDOM - LEAST_FLOW

LEAST_FLOW - RANDOM

LEAST_LINK - RANDOMRANDOM - RANDOM

0 100


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Simulation Results - IV

,

0,00%

2,00%

4,00%

6,00%

8,00%

10,00%

12,00%

14,00%

50 55 60 65 70 75 80 85 90 95 100

N

Percentage of nodes switched off versus

LEAST_FLOW - LEAST_FLOW

LEAST_LINK - LEAST_FLOW

RANDOM - LEAST_FLOW

LEAST_FLOW - RANDOM

LEAST_LINK - RANDOMRANDOM - RANDOM


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Parameter Impact - I

,

0,00%

5,00%

10,00%

15,00%

20,00%

25,00%

30,00%

35,00%

40,00%

45,00%

50,00%

6 10 15 20 25 30

L

x

Percentage variation of links switched offversus different values of x

x core

3x edge

12x aggregation


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Parameter Impact - II

,

0,00%

2,00%

4,00%

6,00%

8,00%

10,00%

12,00%

6 10 15 20 25 30

N

x

Percentage variation of nodes switched offversus different values of x


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Impact of traffic variation


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Traffic Variation

,

0

0,2

0,4

0,6

0,8

1

1,2

, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,

E[traffic]

Time

Traffic Variation


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,

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,

N

Time

Percentage Variation of Nodes Off

Traffic Variation


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,

0%

5%

10%

15%

20%

25%

30%

35%

, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,

L

Time

Percentage Variation of Links off

Traffic Variation


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Turning off network portions save energy

BUT

How to do this?

Device support

Standby mode? Idle mode?

Control plane impact

Centralized solution? Or distributed solution?

How to signal the device the power state?

How to control/reroute the traffic?

How to decide WHEN to enter idle mode?

Technical Issues


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Conclusions

- Minimization of the total power consumed by a network

- Connectivity and maximum link utilization contraints

- Simple Heuristics proposed for WAN scenario

- Possibility to turn off links and full nodes

Energy-aware

network design

-More efficient heuristics for nodes, e.g. minimize the number of

multiple paths

- Performance analysis on a real network

-Case study on operative networks

Next Steps

energy aware

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